September 6, 2023

Detailed analysis of the actual 2017 HEDIS clinical measure supplied by National Committee for Quality Assurance (NCQA)

In this exercise, we will perform a detailed analysis of the actual 2017 HEDIS clinical measure supplied by National Committee for Quality Assurance (NCQA). Our measure analysis will focus on diabetes care. In preparation for this exercise, please download and review the Comprehensive Diabetes Care (CDC) measure provided in the Unit 4 readings tab. Be sure to read through and understand the measure in its entirety. The major parts of the measure are as follows:

Summary of changes: updates for the current year (measures are typically updated annually).

Description: basic summary of the measure.

Eligible population: defines inclusion criteria.

Denominator: the number representing the total population.

Numerator: definition criteria for identification of patients for the measure.

Hybrid Specification: other criteria combinations for the measure (FYI – will not be utilized for this exercise).

We will utilize ICD, CPT, LOINC, and RxNORM codes as, and where applicable for the entire measure building exercise. For all parts, use an example output table in the following general format, but you can deviate as you see fit and to whatever matches your style for presenting data. Formatting is not important; your understanding of the measure building process and the meaning of clinical data codes are important.

Step 1. Define eligible population in a table format and label it Eligible Population Table. 10 points.

Locate Eligible Population section of the HEDIS measure on pp. 1 – 2. Select appropriate medical data vocabularies for each of the categories, find necessary codes, and provide a table in a format of or similar to the example table above. Do not worry about specific dates (just use “last year” or any time definition of your choice when needed) and financial/insurance measures such as Product Lines, Allowable Gap, and Benefit. In the real world, you will have access to this data from various systems and will be required to include every step and every data element, but we will disregard financial and time data for now, for academic purposes.

Step 2. Define the denominator in table format and label it Denominator Table. 10 points.

Apply the same strategy you employed to build eligible population under Step 1 to define the entire denominator. Denominator description is on page 4 of the measure specification. You already have eligible population defined from Step 1, so no need to repeat, and you can skip to the next section that describes HbA1c controls.

Step 3. Define the numerator in a table format and label it Numerator Table. 10 points.

We continue applying the same strategy to define the numerator. In this section:

a. LOINC would be your main vocabulary that also includes some of the value sets listed in the measure specification.

b. RxNorm may be necessary for drug definitions.

c. If you are unable to locate some of the value sets, such as CKD (chronic kidney disease), replace with codes pertaining to this disease or skip the value set. In real data analytics environment, you will not be allowed to skip, but you will also have access to a greater variety of tools to locate necessary codes.

d. Note that medical documentation codes will not delineate percentages, i.e. <7%, >9%; this is done by analysts on paper and implemented by software engineers programmatically. For our purposes, you can just specify percentages in the description – applicable codes will be the same no matter percentages. Or you can list all percentage descriptions on the same line within the same specification.

e. You can skip the Eye Exam section on Page 6: there is no easy way for you to locate relevant codes.

f. On page 7, use RxNORM search to locate codes for ACE Inhibitors.

g. We stop on page 8 and do not take on Hybrid Specification that concludes measure definition.

Follow the steps described in the NCQA measure for the numerator, accounting for the notes above.

Your output is tables representing Steps 1, 2, and 3. Again, feel free to use a different output format and/or more tables as necessary. The format of these assignment instructions is purposely ambiguous and does not provide you with line-by-line directions. Finer detail is not omitted. Instead, it represents academic and industry realities of the modern data science development times; there are no directions, out-of-the-box solutions, or specific one-ways of doing “things”. It’s on you to demonstrate your creative thinking to get through the sea of options or no options, to find a workable solution.

The ultimate output of your measure is a rule-based program that would be built upon foundations you have just laid out in this exercise. Were you a medical professional with an ability to create new ideas for measures and actually define these measures, you could find yourself working for either organizations like NCQA that define new measure standards or numerous technology or consultancy firms that either program standard measures and/or define custom ones.

APA requirements for this exercise are relaxed to reflect its technical nature, but please cite all references using APA style, as usual. You do not need to reference ICD-10, LOINC, CPT, or RxNorm databases that we know you will be using for this exercise. But please do reference any literature that you did utilize, as/if applicable.

See attached document for reading materials, guideline, and complete assignment.

Requirements: 3 days

Comprehensive Diabetes Care (CDC)

Summary of Changes to HEDIS 2017

Added an administrative method and new value set to identify negative eye exams in the year prior to the measurement year.

Added glycohemoglobin, glycated hemoglobin and glycosylated hemoglobin as acceptable HbA1c tests.

Clarified documentation requirements for a negative eye exam.

Replaced “Each of the 7 rates” with a “” for the “Measurement year” row in Table CDC-1/2/3.

Description

The percentage of members 18–75 years of age with diabetes (type 1 and type 2) who had each of the following:

* Additional exclusion criteria are required for this indicator that will result in a different eligible population from all other indicators. This indicator is only reported for the commercial and Medicaid product lines.

Eligible Population

Note: Members in hospice are excluded from the eligible population. If an organization reports this measure using the Hybrid method, and a member is found to be in hospice or using hospice services during medical record review, the member is removed from the sample and replaced by a member from the oversample. Refer to General Guideline 20: Members in Hospice.

Table CDC-A: Prescriptions to Identify Members With Diabetes

Note: Glucophage/metformin as a solo agent is not included because it is used to treat conditions other than diabetes; members with diabetes on these medications are identified through diagnosis codes only. NCQA will post a complete list of medications and NDC codes to www.ncqa.org by November 1, 2016

Administrative Specification

* The CPT Category II code (3045F) in this value set indicates most recent HbA1c (HbA1c) level 7.0%–9.0% and is not specific enough to denote numerator compliance for this indicator. For members with this code, the organization must use other sources (laboratory data, hybrid reporting method) to identify the actual value and determine if the HbA1c result was <8%. Because providers assign the Category II code after reviewing test results, the date of service for the Category II code may not match the date of service for the HbA1c test found in other sources; if dates differ, use the date of service when the test was performed. The date of service for the Category II code and the test result must follow the requirements outlined in General Guideline 36 (i.e., the dates of service for the code and the test result must be no more than seven days apart).

_____________

Table CDC-L: ACE Inhibitors/ARBs

Note: NCQA will post a comprehensive list of medications and NDC codes to www.ncqa.org by November 1, 2016.

_____________

Exclusions (optional)

Members who do not have a diagnosis of diabetes (Diabetes Value Set), in any setting, during the measurement year or the year prior to the measurement year and who had a diagnosis of gestational diabetes or steroid-induced diabetes (Diabetes Exclusions Value Set), in any setting, during the measurement year or the year prior to the measurement year.

Organizations that apply optional exclusions must exclude members from the denominator for all indicators. The denominator for all rates must be the same, with the exception of the HbA1c Control (<7.0%) for a Selected Population denominator.

If the member was included in the measure based on claim or encounter data, as described in the event/ diagnosis criteria, the optional exclusions do not apply because the member had a diagnosis of diabetes.

Hybrid Specification

Note: For Hybrid reporting, search the medical record for required exclusions and apply them before determining if the member has a numerator hit. Organizations are not required to search for required exclusions if a member has an administrative hit for the indicator, but must exclude these members if they are discovered during medical record review.

Exclusions (optional)

Refer to Administrative Specification for exclusion criteria. Identify members who did not have a diagnosis of diabetes, in any setting, during the measurement year or the year prior to the measurement year, and who had a diagnosis of gestational diabetes or steroid-induced diabetes, in any setting, during the measurement year or the year prior to the measurement year.

Note

Organizations may select a data collection method (Administrative vs. Hybrid) at the indicator level, but the method used for HbA1c testing and control rates must be consistent.

Blindness is not an exclusion for a diabetic eye exam because it is difficult to distinguish between individuals who are legally blind but require a retinal exam and those who are completely blind and therefore do not require an exam.

Hypertensive retinopathy is not handled differently from diabetic retinopathy when reporting the eye exam indicator; for example, an eye exam documented as positive for hypertensive retinopathy is counted as positive for diabetic retinopathy and an eye exam documented as negative for hypertensive retinopathy is counted as negative for diabetic retinopathy. The intent of the eye exam indicator is to ensure that members with evidence of any type of retinopathy have an eye exam annually, while members who remain free of retinopathy (i.e., the retinal exam was negative for retinopathy) are screened every other year.

If a combination of administrative, supplemental or hybrid data are used, the most recent result must be used, regardless of data source, for the indicators that require use of the most recent result.

If an organization chooses to apply the optional exclusions, members must be numerator negative for at least one indicator, with the exception of HbA1c Poor Control (>9%). Remove members from the eligible population who are numerator negative for any indicator (other than for HbA1c Poor Control [>9%]) and substitute members from the oversample. Do not exclude members who are numerator compliant for all indicators except HbA1c Poor Control (>9%), because a lower rate indicates better performance for this indicator.

Monitoring for Diabetic Nephropathy

Data Elements for Reporting

Organizations that submit HEDIS data to NCQA must provide the following data elements.

Table CDC-1/2/3: Data Elements for Comprehensive Diabetes Care

Logical Observation Identifiers Names and Codes (LOINC®)Users’ GuideVersion 2.67 PUBLISHED DECEMBER 2019 For LOINC Version 2.67loinc.org Download the free LOINC database, access learning resources, ask questions, request new LOINC terms, and participate in the LOINC community.search.loinc.org Perform searches on the LOINC database using advanced syntax capabilities.COPYRIGHT ©1995-2019 REGENSTRIEF INSTITUTE, INC. AND THE LOGICAL OBSERVATION IDENTIFIERS NAMES AND CODES (LOINC) COMMITTEE. ALL RIGHTS RESERVED.

iiTable of ContentsCopyright Notice and License ………………………………………………………………………………………………….ixNotice of Third Party Content and Copyright Terms ……………………………………………………………………………………………..xvRequired Attributions for Third Party Content not identified as such in the EXTERNAL_COPYRIGHT_NOTICE field: …………………………………………………………………………………………………………………………………………………………………xv1 Introduction ………………………………………………………………………………………………………………………………11.1 Acknowledgments ……………………………………………………………………………………………………………………………………………………21.2 What is not part of the name ………………………………………………………………………………………………………………………………….21.3 Scope of LOINC ………………………………………………………………………………………………………………………………………………………..32 Major Parts of a LOINC term …………………………………………………………………………………………………52.1 General naming conventions ………………………………………………………………………………………………………………………………….62.1.1 Abbreviations in names of Component (Analyte) ………………………………………………………………………………………………………….62.1.2 General naming rules for the Component (Analyte) ……………………………………………………………………………………………………..72.1.3 Punctuation in Analyte names …………………………………………………………………………………………………………………………………………82.1.4 Case insensitivity ………………………………………………………………………………………………………………………………………………………………92.1.5 Roman numerals vs. Arabic numerals ……………………………………………………………………………………………………………………………92.1.6 Exponents ……………………………………………………………………………………………………………………………………………………………………………92.1.7 Use of the slash (/) ……………………………………………………………………………………………………………………………………………………………..92.1.8 Use of curly braces {} in LOINC names ………………………………………………………………………………………………………………………..102.2 Component/Analyte (1st part) ……………………………………………………………………………………………………………………………….102.2.1 Analyte name (1st subpart) ……………………………………………………………………………………………………………………………………………102.2.2 Challenge test (2nd subpart) ………………………………………………………………………………………………………………………………………….122.2.3 Adjustments/corrections (3rd subpart) ……………………………………………………………………………………………………………………….172.2.4 Distinguishing multiple values for any test via the test name (4th subpart) ……………………………………………………….172.3 Kind of Property (also called kind of quantity) (2nd part) ………………………………………………………………………………..172.3.1 Quantitative Properties …………………………………………………………………………………………………………………………………………………..182.3.2 Qualitative Properties ……………………………………………………………………………………………………………………………………………………..202.3.3 More examples of LOINC Properties ……………………………………………………………………………………………………………………………202.4 Time Aspect (point or moment in time vs. time interval) (3rd part) ………………………………………………………………..252.4.1 Time Aspect Modifier ………………………………………………………………………………………………………………………………………………………272.5 System (sample) type (4th part) …………………………………………………………………………………………………………………………….272.5.1 Special issues related to XXX as a System …………………………………………………………………………………………………………………..292.5.2 Super System (2nd subpart) ……………………………………………………………………………………………………………………………………………302.6 Type of Scale (5th part) …………………………………………………………………………………………………………………………………………..302.6.1 Quantitative (Qn) ……………………………………………………………………………………………………………………………………………………………312.6.2 Ordinal (Ord) ……………………………………………………………………………………………………………………………………………………………………312.6.3 Quantitative/Ordinal (OrdQn) …………………………………………………………………………………………………………………………………….31

iii2.6.4 Nominal (Nom) ………………………………………………………………………………………………………………………………………………………………..322.6.5 Narrative (Nar) ………………………………………………………………………………………………………………………………………………………………..322.6.6 Multi ………………………………………………………………………………………………………………………………………………………………………………….322.6.7 Document (Doc) ………………………………………………………………………………………………………………………………………………………………322.7 Type of Method (6th part) ……………………………………………………………………………………………………………………………………..332.7.1 Methods for identifying nucleic acids …………………………………………………………………………………………………………………………342.7.2 Immune assays ………………………………………………………………………………………………………………………………………………………………..362.7.3 Immunoblot and Line blot Methods ……………………………………………………………………………………………………………………………..372.7.4 Coagulation ……………………………………………………………………………………………………………………………………………………………………..372.7.5 Stains …………………………………………………………………………………………………………………………………………………………………………………372.7.6 Substrates used to measure enzyme activity…………………………………………………………………………………………………………….372.7.7 “Detection limit” Methods ……………………………………………………………………………………………………………………………………………..382.7.8 “Confirm” Method outside of Drug/Tox ……………………………………………………………………………………………………………………….382.7.9 Special issues with Methods for clinical measures …………………………………………………………………………………………………….382.7.10 Imaging studies ……………………………………………………………………………………………………………………………………………………………..393 Special cases …………………………………………………………………………………………………………………………..403.1 Findings viewed as variables or as values ………………………………………………………………………………………………………….403.1.1 Value …………………………………………………………………………………………………………………………………………………………………………………403.1.2 Variable (multiple choice) approach …………………………………………………………………………………………………………………………..403.2 Blood bank ……………………………………………………………………………………………………………………………………………………………….413.2.1 Panel reporting ………………………………………………………………………………………………………………………………………………………………..413.2.2 Multiple answer reporting …………………………………………………………………………………………………………………………………………….423.3 Immunocompetence studies (flow cytometry) …………………………………………………………………………………………………423.3.1 Number of cells containing the marker ………………………………………………………………………………………………………………………423.3.2 Percent of cells containing the marker ……………………………………………………………………………………………………………………….423.3.3 Specifying the parent cell population ………………………………………………………………………………………………………………………….423.4 Microbiology ……………………………………………………………………………………………………………………………………………………………433.4.1 Microbiology cultures ……………………………………………………………………………………………………………………………………………………433.4.2 Properties for culture terms …………………………………………………………………………………………………………………………………………..463.4.3 Microorganism identification based on nucleic acid targets ………………………………………………………………………………….463.5 Antimicrobial susceptibilities ………………………………………………………………………………………………………………………………463.5.1 Susceptibility thresholds based on type of infection (“Breakpoints”) …………………………………………………………………..473.5.2 Genotypic resistance testing and predicted susceptibility …………………………………………………………………………………….473.6 Cell counts………………………………………………………………………………………………………………………………………………………………..483.7 Skin tests ………………………………………………………………………………………………………………………………………………………………….483.8 Toxicology – Drug of abuse screening and confirmation ………………………………………………………………………………….493.8.1 Toxicology drug groups ………………………………………………………………………………………………………………………………………………….493.8.2 Cutoffs ………………………………………………………………………………………………………………………………………………………………………………513.8.3 Reporting the Method used for screen and confirm …………………………………………………………………………………………………523.8.4 Individual drug/metabolite test results ………………………………………………………………………………………………………………………523.8.5 Naming issues ………………………………………………………………………………………………………………………………………………………………….533.8.6 Summary …………………………………………………………………………………………………………………………………………………………………………..53

iv3.9 Molecular genetics LOINC naming ……………………………………………………………………………………………………………………..543.9.1 Introduction …………………………………………………………………………………………………………………………………………………………………….543.9.2 Brief review of molecular genetics terminology ……………………………………………………………………………………………………….543.9.3 Background on molecular genetics testing methods ……………………………………………………………………………………………….553.9.4 General molecular genetics naming rules ………………………………………………………………………………………………………………….553.9.5 Infectious diseases ………………………………………………………………………………………………………………………………………………………….583.9.6 Genetic conditions ………………………………………………………………………………………………………………………………………………………….583.9.7 Identity testing ………………………………………………………………………………………………………………………………………………………………..633.9.8 Tumor related genetics ………………………………………………………………………………………………………………………………………………….643.10 HLA allele and antigen nomenclature ………………………………………………………………………………………………………………643.11 Allergy testing ……………………………………………………………………………………………………………………………………………………….653.11.1 Naming rules for allergens ………………………………………………………………………………………………………………………………………….664 Clinical observations and measures …………………………………………………………………………………..684.1 Introduction …………………………………………………………………………………………………………………………………………………………….684.2 Atomic versus molecular (pre-coordinated names) …………………………………………………………………………………………704.3 Radiology reports ……………………………………………………………………………………………………………………………………………………714.4 Tumor registry …………………………………………………………………………………………………………………………………………………………715 Claims attachments ………………………………………………………………………………………………………………726 LOINC Document Ontology ………………………………………………………………………………………………..736.1 Introduction to the use of LOINC document type codes ………………………………………………………………………………..736.2 Relationship to other standards …………………………………………………………………………………………………………………………..746.2.1 HL7 …………………………………………………………………………………………………………………………………………………………………………………….746.3 Elements of document type codes ………………………………………………………………………………………………………………………746.3.1 Kind of Document …………………………………………………………………………………………………………………………………………………………..746.3.2 Type of Service ………………………………………………………………………………………………………………………………………………………………..766.3.3 Setting ……………………………………………………………………………………………………………………………………………………………………………….806.3.4 Subject Matter Domain (SMD) …………………………………………………………………………………………………………………………………….816.3.5 Role ……………………………………………………………………………………………………………………………………………………………………………………866.4 Rules for creating clinical notes from multiple attributes ………………………………………………………………………………876.4.1 Exceptions to rules for creating clinical notes …………………………………………………………………………………………………………..896.5 Document Ontology content in the LOINC distribution …………………………………………………………………………………896.6 Future work ……………………………………………………………………………………………………………………………………………………………..906.7 Proposing new LOINC document terms …………………………………………………………………………………………………………….907 Panels (Batteries) …………………………………………………………………………………………………………………..917.1 Goals ………………………………………………………………………………………………………………………………………………………………………….917.2 Types of results found in panels …………………………………………………………………………………………………………………………..917.2.1 Primary measurements or observations ……………………………………………………………………………………………………………………927.2.2 Derived observations …………………………………………………………………………………………………………………………………………………….927.2.3 Ask at order entry (AOE) questions and other associated observations ……………………………………………………………..92

v7.2.4 Impressions, interpretations, and comments ……………………………………………………………………………………………………………927.3 LOINC rules for panel names ……………………………………………………………………………………………………………………………….927.3.1 Component ………………………………………………………………………………………………………………………………………………………………………..927.3.2 Property and Scale ……………………………………………………………………………………………………………………………………………………………937.3.3 Time Aspect and System …………………………………………………………………………………………………………………………………………………..937.3.4 Examples of LOINC Panel names …………………………………………………………………………………………………………………………………937.4 Representing conditionality …………………………………………………………………………………………………………………………………947.4.1 Lupus anticoagulant testing as an example of complex conditionality …………………………………………………………………957.5 Approach to creating and defining distinct panels in LOINC …………………………………………………………………………977.5.1 General approach ……………………………………………………………………………………………………………………………………………………………977.5.2 Preference for methodless panel definitions …………………………………………………………………………………………………………….987.5.3 Special cases where enumeration of child elements is not practical …………………………………………………………………….988 Evolving principles for naming collections ……………………………………………………………………….998.1 Goals and general approach ………………………………………………………………………………………………………………………………….998.2 Collections as orders and observations ……………………………………………………………………………………………………………..998.3 LOINC Scale for collections ………………………………………………………………………………………………………………………………..1009 Additional content in the LOINC distribution ………………………………………………………………..1019.1 Additional attributes of LOINC terms ……………………………………………………………………………………………………………..1019.1.1 Names …………………………………………………………………………………………………………………………………………………………………………….1019.1.2 Classes …………………………………………………………………………………………………………………………………………………………………………….1039.1.3 Categorizing LOINC terms as Order, Observation, or Both ………………………………………………………………………………..1049.1.4 Associated observations …………………………………………………………………………………………………………………………………………….1049.1.5 Ask-at-order-entry (AOE) …………………………………………………………………………………………………………………………………………..1059.1.6 Related names ………………………………………………………………………………………………………………………………………………………………1059.2 LOINC Answers (LA) and Answer Lists (LL) …………………………………………………………………………………………………….1059.2.1 Null flavors in LOINC Answer lists ……………………………………………………………………………………………………………………………1069.3 LOINC Parts and Part hierarchies …………………………………………………………………………………………………………………….1079.3.1 Part distribution …………………………………………………………………………………………………………………………………………………………..1079.4 Descriptions ………………………………………………………………………………………………………………………………………………………….1079.5 LOINC Table Core ………………………………………………………………………………………………………………………………………………..1089.6 LOINC Groups ………………………………………………………………………………………………………………………………………………………10810 Standardized assessment measures ……………………………………………………………………………..10910.1 Introduction ………………………………………………………………………………………………………………………………………………………..10910.2 LOINC representation ………………………………………………………………………………………………………………………………………10910.2.1 Naming rules and conventions for names of collection terms (e.g. a panel, survey instrument) ………………..10910.2.2 Attributes of the LOINC terms for individual questions or variables ……………………………………………………………..10910.2.3 Structured answer lists …………………………………………………………………………………………………………………………………………….11010.2.4 Attributes of items that vary depending on the parent collection …………………………………………………………………..11010.2.5 Choosing the “display text” for a question or variable ………………………………………………………………………………………..11010.2.6 Type of Method (6th part) for a question or variable …………………………………………………………………………………………..111

vi10.2.7 Time Aspect (3rd part) for a question or variable …………………………………………………………………………………………………11110.2.8 Form Information ………………………………………………………………………………………………………………………………………………………11210.3 Assessment content in the LOINC distribution …………………………………………………………………………………………..11210.4 In-progress updates through our collaboration with CMS on post acute care assessments ………………11211 Editorial policies and procedures …………………………………………………………………………………..11411.1 Concept orientation and LOINC name changes ………………………………………………………………………………………….11411.2 Classification of LOINC term status ………………………………………………………………………………………………………………11411.3 Concept persistence and term deprecation …………………………………………………………………………………………………11611.4 Publication of LOINC codes in advance of official releases……………………………………………………………………….11611.5 File versioning and naming ………………………………………………………………………………………………………………………………11612 Recommendations for best practices in using and mapping to LOINC …………………..11712.1 Business rules for users mapping their local panels to LOINC panels …………………………………………………….11712.1.1 Must contain all of the required elements ……………………………………………………………………………………………………………11712.1.2 No extra primary measurements ……………………………………………………………………………………………………………………………11712.1.3 Optional elements are optional ………………………………………………………………………………………………………………………………11712.1.4 Substitutions related to Method …………………………………………………………………………………………………………………………….11712.1.5 Substitutions for mass versus substance Properties ………………………………………………………………………………………….11812.1.6 No substitutions of quantitative for qualitative (and vice versa) ……………………………………………………………………..11812.1.7 Pay attention to reflex elements …………………………………………………………………………………………………………………………….11812.1.8 Special case of differential counts (including conventions for not reporting zero counts)………………………….11912.1.9 Panels with only narrative definitions of the elements they should contain ………………………………………………….11912.2 Examples of applying the business rules for users mapping their local panels to LOINC panels ……….11912.2.1 Comparison Panel: Varicella zoster virus IgG and IgM panel – Serum (LOINC: 45063-5) …………………………..11912.2.2 Comparison Panel: Creatine kinase panel – Serum or Plasma (LOINC: 24335-2) …………………………………………11912.2.3 Comparison Panel: Drugs of abuse 5 panel – Urine by Screen method (LOINC: 65750-2) …………………………12012.3 Querying LOINC and creating intensional value set definitions based on LOINC database structure ..12112.3.1 Canonical representation of LOINC as a FHIR CodeSystem …………………………………………………………………………….12212.4 The Code System for identifiers assigned by LOINC ………………………………………………………………………………….12212.5 LOINC term names in HL7 messages …………………………………………………………………………………………………………….12212.6 Updating to new versions of LOINC ………………………………………………………………………………………………………………12312.7 Using URIs to identify LOINC artifacts ………………………………………………………………………………………………………….12312.7.1 Using a URI to identify LOINC as a code system ………………………………………………………………………………………………….12312.7.2 Using a URI to identify LOINC concepts as resources in RDF …………………………………………………………………………..12312.7.3 Using a URI to identify LOINC concepts as a value set ………………………………………………………………………………………124Appendix A LOINC Database Structure …………………………………………………………………………….125Appendix B Classes ………………………………………………………………………………………………………………..130Appendix C Calculating Mod 10 check digits …………………………………………………………………….139Appendix D Procedure for Submitting Additions or Changes to LOINC ……………………..140

viiIntroduction …………………………………………………………………………………………………………………………………………………………………140Appendix E Examples for LOINC Property Matching ……………………………………………………..144Appendix F Example Acronyms used in LOINC ………………………………………………………………..149Appendix G LOINC Technical Briefs ……………………………………………………………………………………152D-Dimer Revisions in LOINC ……………………………………………………………………………………………………………………………………153Cockcroft-Gault formula for estimating creatinine clearance, Schwartz equation for Glomerular Filtration Rate and MDRD formulae …………………………………………………………………………………………………………………………………………156Inducible Clindamycin Resistance in Staphylococcus and Streptococcus ……………………………………………………….160KIR Gene Family………………………………………………………………………………………………………………………………………………………….161Oxygen Saturation and LOINC® …………………………………………………………………………………………………………………………….162Nomenclature of Salmonella Species, Subspecies, and Serovars ………………………………………………………………………164Segmented Neutrophils Versus Polymorphonuclear WBC ……………………………………………………………………………….166Vitamin D …………………………………………………………………………………………………………………………………………………………………….167Free Thyroxine Index Variants ……………………………………………………………………………………………………………………………….170Streptococcus pneumoniae serotype nomenclature …………………………………………………………………………………………..172Appendix H LOINC Committee ……………………………………………………………………………………………174Annex LOINC/RSNA Radiology Playbook User Guide………………………………………………………A11 Introduction ……………………………………………………………………………………………………………………………………………………………….A11.1 Codes and workflows ………………………………………………………………………………………………………………………………………………………..A22 Syntax …………………………………………………………………………………………………………………………………………………………………………A32.1 Operators …………………………………………………………………………………………………………………………………………………………………………….A32.2 Parallelism ……………………………………………………………………………………………………………………………………………………………………………A43 Modality ……………………………………………………………………………………………………………………………………………………………………….A43.1 Definitions …………………………………………………………………………………………………………………………………………………………………………..A43.2 Usage Notes ………………………………………………………………………………………………………………………………………………………………………..A43.3 Allowed Modality/Subtype Combinations ………………………………………………………………………………………………………………………A54 Anatomic Location ………………………………………………………………………………………………………………………………………………………A64.1 Definitions …………………………………………………………………………………………………………………………………………………………………………..A74.2 Syntax and Modeling Principles ………………………………………………………………………………………………………………………………………A85 View ……………………………………………………………………………………………………………………………………………………………………………A115.1 Definitions ………………………………………………………………………………………………………………………………………………………………………..A115.2 Syntax ………………………………………………………………………………………………………………………………………………………………………………..A116 Timing ………………………………………………………………………………………………………………………………………………………………………..A137 Maneuver …………………………………………………………………………………………………………………………………………………………………A137.1 Definitions ………………………………………………………………………………………………………………………………………………………………………..A137.2 Syntax ………………………………………………………………………………………………………………………………………………………………………………..A148 Pharmaceutical ……………………………………………………………………………………………………………………………………………………….A148.1 Definitions ………………………………………………………………………………………………………………………………………………………………………..A148.2 Syntax ………………………………………………………………………………………………………………………………………………………………………………..A15

viii8.3 Examples …………………………………………………………………………………………………………………………………………………………………………..A158.4 Specifying more than one pharmaceutical …………………………………………………………………………………………………………………A158.5 Usage Notes ……………………………………………………………………………………………………………………………………………………………………..A158.6 Issues …………………………………………………………………………………………………………………………………………………………………………………A169 Reason For Exam ………………………………………………………………………………………………………………………………………………………A179.1 Definitions ………………………………………………………………………………………………………………………………………………………………………..A179.2 Examples …………………………………………………………………………………………………………………………………………………………………………..A189.3 Notes ………………………………………………………………………………………………………………………………………………………………………………….A1810 Guidance …………………………………………………………………………………………………………………………………………………………………A1810.1 Definitions ………………………………………………………………………………………………………………………………………………………………………A1810.2 Usage Notes …………………………………………………………………………………………………………………………………………………………………..A1910.3 Examples …………………………………………………………………………………………………………………………………………………………………………A2111 Subject ……………………………………………………………………………………………………………………………………………………………………A2111.1 Definitions ………………………………………………………………………………………………………………………………………………………………………A21

ixCopyright Notice and License“LOINC” means the work of clinical nomenclature called Logical Observation Identifiers Names and Codes (LOINC) that provides a universal code system for identifying laboratory and clinical observations and related content.The LOINC® codes, LOINC® Table (regardless of format), LOINC® Table Core, and LOINC® Changes File (collectively, the “Group 1 Artifacts”), and the LOINC® Release Notes and LOINC® Users’ Guide (collectively, the “Group 1 Documents”), are copyright © 1995-2019, Regenstrief Institute, Inc. and the Logical Observation Identifiers Names and Codes (LOINC) Committee. All rights reserved.The RELMA® program, RELMA® database and associated search index files (subject to the copyright above with respect to the LOINC® codes and LOINC® Table included therein), RELMA® Community Mapping Feature Database (collectively, the “Group 2 Artifacts”), and the RELMA® Release Notes and RELMA® Users’ Manual (collectively, the “Group 2 Documents”), are copyright © 1995-2019, Regenstrief Institute, Inc. All rights reserved.The LOINC® Panels and Forms File, LOINC® Answer File, LOINC® Part File, LOINC® Group File, LOINC® Document Ontology File, LOINC® Document Ontology OWL File, LOINC® Hierarchies, LOINC® Linguistic Variants Files, LOINC/RSNA Radiology Playbook, LOINC/IEEE Medical Device Code Mapping Table, LOINC® Consumer Name File, and LOINC Change Snapshot File (collectively, the “Group 3 Artifacts” and all subject to the copyright above with respect to the LOINC® codes and LOINC® Table to the extent included therein), are copyright © 1995-2019, Regenstrief Institute, Inc. All rights reserved.LOINC® and RELMA® are registered United States trademarks of Regenstrief Institute, Inc.Permission is hereby granted in perpetuity, without payment of license fees or royalties, to use, copy, or distribute the Group 1 Artifacts, Group 1 Documents, Group 2 Artifacts, Group 2 Documents, and Group 3 Artifacts (collectively, the “Licensed Materials”) for any commercial or non-commercial purpose, subject to the following terms and conditions:1. To prevent the dilution of the purpose of the LOINC codes and LOINC Table of providing a definitive standard for identifying clinical information in electronic reports, users shall not use any of the Licensed Materials for the purpose of developing or promulgating a different standard for identifying patient observations, such as laboratory test results; other diagnostic service test results; clinical observations and measurements; reports produced by clinicians and diagnostic services about patients; panels, forms, and collections that define aggregations of these observations; and orders for these entities in electronic reports and messages.2. If the user elects to use the RELMA program, users receive the full RELMA database and associated search index files with the RELMA program, including the LOINC Table and other database tables comprising the RELMA database. In addition to its use with the RELMA program, users may use the LOINC Table by itself and may modify the LOINC Table as permitted herein. Users may not use or modify the other database tables from the RELMA database or the associated search index files except in conjunction with their authorized use of the RELMA program, unless prior written permission is granted by the Regenstrief Institute, Inc. To request written permission, please contact [email protected]. The RELMA program also provides access to certain internet-based content copyrighted by Regenstrief Institute, Inc. No additional permission to modify or distribute this internet-based content is granted through the user’s use of the RELMA program.

x3. The RELMA program also includes the RELMA Community Mappings feature and access to the RELMA Community Mappings feature database. The accuracy and completeness of the information in the RELMA Community Mappings feature is not verified by Regenstrief Institute, Inc. or the LOINC Committee. Access to the RELMA Community Mappings feature is enabled by a user authentication from the RELMA login screen. If a user wishes to opt out of the RELMA Community Mappings feature, they can simply use RELMA without logging in. a. By using the RELMA Community Mappings feature, users agree as follows: i. Users may not copy, distribute, or share access to the information provided by the RELMA Community Mappings feature. ii. Users accept the risk of using the information provided by the RELMA Community Mappings feature, recognize that such information is submitted by other users, and understand that neither Regenstrief Institute, Inc. nor the LOINC Committee are liable for the information provided by the RELMA Community Mappings feature. iii. Regenstrief Institute, Inc. may contact users regarding: 1. Use of the RELMA Community Mappings feature; 2. Submission requests for additional information; and 3. Any mapping submissions that the user makes to the RELMA Community Mappings feature database; iv. Others may contact user about submissions made to the RELMA Community Mappings feature database; v. User will make reasonable efforts to submit user’s mappings back to the RELMA Community Mappings feature database, which may contain the following information (as applicable): 1. Local battery/panel/test code 2. Local battery/panel/test name/description 3. Units of Measure 4. LOINC code to which it is mapped 5. Date of mapping 6. Language of test names 7. Version of LOINC used to do the mapping 8. Contact information; vi. If a user submits mappings on behalf of an organization, the user represents that the user has the authority to submit the mappings and to agree to these terms on behalf of user’s organization. vii. If a user submits mappings back to the RELMA Community Mappings feature database, then the user hereby grants, on behalf of themselves and the user’s organization, Regenstrief Institute, Inc. a non-exclusive license without payment or fees to submitted mappings in perpetuity for purposes related to LOINC, RELMA, and Regenstrief Institute Inc.’s mission, including, but not limited to: 1. Modifying the information;

xi 2. Making information publicly available; 3. Performing aggregate analysis; 4. Conducting and publishing research that does not identify user or user’s organization by name; 5. Developing and enhancing LOINC and associated software tools.4. Users shall not change the meaning of any of the LOINC codes. Users shall not change the name of, or any contents of, any fields in the Group 1 Artifacts. Users may add new fields to the LOINC Table and LOINC Table Core File to attach additional information to existing LOINC records. Users shall not change the content or structure of the Group 3 Artifacts, but may notify the Regenstrief Institute, Inc. of any potential inconsistencies or corrections needed by contacting [email protected]. Users shall not use the LOINC parts or LOINC part hierarchies in any manner except as they are presented in the Licensed Materials (and/or in other formats of distribution approved by Regenstrief Institute, Inc.) to organize or be constituents of LOINC terms. LOINC parts and LOINC part hierarchies shall neither be used as a “standalone” terminology nor apart from LOINC terms. User understands that LOINC parts and LOINC part hierarchies are subject to change, addition, modification, or deletion, and are not strictly managed under the same policies as LOINC terms.6. A user may delete records from the LOINC Table or LOINC Table Core to deal with the user’s local requirements. A user also may add new records to the LOINC Table and LOINC Table Core to deal with the users’ local requirements, provided that if new records are added, any new entry in the LOINC_NUM field of such new records must contain a leading alphabetic “X” so that the new codes and records cannot be confused with existing LOINC codes or new LOINC codes as they are defined in later releases. Records deleted or added by users to deal with local requirements are not reflected in the official LOINC Table and LOINC Table Core maintained by the Regenstrief Institute, Inc. Users must also make reasonable efforts to submit requests to LOINC for new records to cover observations that are not found in the LOINC Table (and LOINC Table Core) in order to minimize the need for X-codes.7. LOINC codes and other information from the LOINC Table (and LOINC Table Core) may be used in electronic messages for laboratory test results and clinical observations such as HL7 ORU messages, without the need to include this Copyright Notice and License or a reference thereto in the message (and without the need to include all fields required by Section 9 hereof). When the LOINC code (from the LOINC_NUM field) is included in the message, users are encouraged, but not required, to include the corresponding LOINC short name (from the SHORTNAME field), the LOINC long common name (from the LONG_COMMON_NAME field), or for laboratory terms, the LOINC Display name (from the DisplayName field) in the message if the message provides a place for a text name representation of the code.8. Users may make and distribute an unlimited number of copies of the Licensed Materials. Each copy thereof must include this Copyright Notice and License, and must include the appropriate version number of the Licensed Materials if the Licensed Materials have a version number, or the release date if the Licensed Materials do not have a version number. This Copyright Notice and License must appear on every printed copy of the LOINC Table (and LOINC Table Core). Where the Licensed Materials are distributed on a fixed storage medium (such as CD-ROM), a printed copy of this Copyright Notice and License must be included on or with the storage medium, and a text file containing this information also must be stored on the storage medium in a file called “license.txt”. Where the Licensed Materials are distributed via the Internet, this Copyright Notice and License must be accessible on the same Internet page from which the Licensed Materials are available for download. This Copyright Notice and License must appear verbatim on every electronic or printed copy of the RELMA Users’ Manual and the LOINC Users’ Guide. The RELMA Users’ Manual and the LOINC Users’ Guide may not be modified, nor may derivative works of the RELMA Users’ Manual or LOINC Users’ Guide be created, without the prior

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xviA. The LOINC Part File, LOINC/SNOMED CT Expression Association and Map Sets File, RELMA database and associated search index files include SNOMED Clinical Terms (SNOMED CT®) which is used by permission of the International Health Terminology Standards Development Organisation (IHTSDO) under license. All rights are reserved. SNOMED CT® was originally created by The College of American Pathologists. “SNOMED” and “SNOMED CT” are registered trademarks of the IHTSDO. Use of SNOMED CT content is subject to the terms and conditions set forth in the SNOMED CT Affiliate License Agreement. It is the responsibility of those implementing this product to ensure they are appropriately licensed and for more information on the license, including how to register as an Affiliate Licensee, please refer to http://www.snomed.org/snomed-ct/get-snomed-ct or [email protected]. Under the terms of the Affiliate License, use of SNOMED CT in countries that are not IHTSDO Members is subject to reporting and fee payment obligations. However, IHTSDO agrees to waive the requirements to report and pay fees for use of SNOMED CT content included in the LOINC Part Mapping and LOINC Term Associations for purposes that support or enable more effective use of LOINC.B. The LOINC Answer File, RELMA database and associated search index files include content from SNOMED Clinical Terms (SNOMED CT®) which is used by permission of the International Health Terminology Standards Development Organisation (IHTSDO) under license. All rights are reserved. SNOMED CT® was originally created by The College of American Pathologists. “SNOMED” and “SNOMED CT” are registered trademarks of the IHTSDO. Use of SNOMED CT content is subject to the terms and conditions set forth in the SNOMED CT Affiliate License Agreement. It is the responsibility of those implementing this product to ensure they are appropriately licensed and for more information on the license, including how to register as an Affiliate Licensee, please refer to http://www.snomed.org/snomed-ct/get-snomed-ct or [email protected]. This may incur a fee in SNOMED International non-Member countries.C. The LOINC Part File, LOINC Answer File, RELMA database and associated search index files includes content from the US Edition to SNOMED CT, which is developed and maintained by the U.S. National Library of Medicine and is available to authorized UMLS Metathesaurus Licensees from the UTS Downloads site at https://uts.nlm.nih.gov.D. The Unified Medical Language System (UMLS) from the U.S. National Library of Medicine (https://www.nlm.nih.gov/research/umls/) is the source of RxNorm® content and is available to authorized UMLS Metathesaurus Licensees. E. The LOINC/RSNA Radiology Playbook and the LOINC Part File contain content from RadLex® (http://www.radlex.org), copyright © 2005-2019, The Radiological Society of North America, Inc., available at no cost under the license at http://www.rsna.org/uploadedFiles/RSNA/Content/Informatics/RadLex_License_Agreement_and_Terms_of_Use_V2_Final.pdf.F. The LOINC/IEEE Medical Device Code Mapping Table contains content from IEEE (http://ieee.org), copyright © 2019 IEEE. G. This product includes all or a portion of the UCUM table, UCUM codes, and UCUM definitions or is derived from it, subject to a license from Regenstrief Institute, Inc. and The UCUM Organization. Your use of the UCUM table, UCUM codes, UCUM definitions also is subject to this license, a copy of which is available at http://unitsofmeasure.org. The current complete UCUM table, UCUM Specification are available for download at http://unitsofmeasure.org. The UCUM table and UCUM codes are copyright © 1995-2019, Regenstrief Institute, Inc. and the Unified Codes for Units of Measures (UCUM) Organization. All rights reserved. THE UCUM TABLE (IN ALL FORMATS), UCUM DEFINITIONS, AND SPECIFICATION ARE PROVIDED “AS IS.” ANY EXPRESS OR IMPLIED WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.

11 IntroductionLOINC provides a set of universal names and ID codes for identifying laboratory and clinical test results.1,2 LOINC facilitates the exchange and pooling of results, such as blood hemoglobin, serum potassium, or vital signs, for clinical care, outcomes management, and research. LOINC’s universal identifiers (names and codes) can be used in the context of order and observation exchanges between information systems that use syntax standards such as HL73, CEN TC251, ISO TC215, ASTM4, and DICOM. Specifically, the identifier can be used as the coded value for an observation in any other standard that uses the observation/observation value paradigm, whether messages, documents, application programming interface (API), etc. For example, LOINC codes are used widely in the OBX segment “Observation Identifier” field (OBX-3) of an ORU HL7 (HL7 version 2.x or ASTM 1238-9410) message that may be sent between a Clinical Laboratory Information Management Systems (LIMS) and Electronic Health Record Systems (EHR).5,6 In this way, LOINC codes provide “universal” identifiers that allow the exchange of clinical data between heterogeneous computing environments.If data producers use only their internal (and idiosyncratic) codes to identify the variables, then receiving medical information systems cannot fully “understand” the results they receive unless they either adopt the producer’s codes (which is impossible if information system receives results from multiple sources, or invest in the work to map each producer’s coding system to their internal code system.7 If medical information producers who wish to communicate with each other adopt LOINC codes to identify their results in data transmissions, this problem would disappear. The receiving system with LOINC codes in its master vocabulary file would be able to understand and properly file HL7 results messages that identified clinical observations via LOINC codes. Similarly, if test and observation codes were reported with the LOINC codes, government agencies would be able to pool results for tests from many sites for research management and public health purpose. LOINC terms should be of interest to many in the healthcare ecosystem, including hospitals, clinical laboratories, outpatient services, state health departments, governmental health care providers, health IT vendors, diagnostic testing vendors, third-party payers, and organizations responsible for quality assurance and utilization review.In the beginning, we used many sources as substrate that informed the creation of LOINC, including the Silver Book from the International Union of Pure and Applied Chemistry (IUPAC) and the International Federation of Clinical Chemistry (IFCC),8 textbooks of clinical pathology (e.g., Henry9 and Tietz10), the expertise and work of the LOINC members, and EUCLIDES. We also reviewed the master test files of eight sources (Indiana 1 Forrey AW, McDonald CJ, DeMoor G, Huff, SM, Leavelle D, Leland D, Fiers T, Charles L, Stalling F, Tullis A, et. al. The logical observation identifier names and codes (LOINC) database: A public use set of codes and names for electronic reporting of clinical laboratory results. Clinical Chemistry 1996;42:81-90. [PubMed: 8565239]2 McDonald CJ, Huff SM, Suico JG, Hill G, Leavelle D, Aller R, Forrey A, Mercer K, DeMoor G, Hook J, Williams W, Case J, Maloney P. LOINC, a universal standard for identifying laboratory observations: A 5-Year update. Clinical Chemistry 2003;49:624-633. [PubMed: 12651816]3 Health Level Seven. An application protocol for electronic data exchange in healthcare environments. Version 2.3. Ann Arbor, MI: Health Level Seven, Inc.; 1997.4 ASTM E1238-94. Standard Specification for Transferring Clinical Observations Between Independent Computer Systems. Philadelphia: American Society for Testing Materials; 1994.5 McDonald CJ, Tierney WM. Computer-stored medical records. Their future role in medical practice. JAMA. 1988 Jun 17;259(23):3433-40. Review. PubMed PMID: 3286915.6 Dick AS, Steen EB (editors). The computer-based patient record. Washington DC: National Academy Press; 1991.7 McDonald CJ, Park BH, Blevins L. Grocers, physicians, and electronic data processing. AMA Continuing Medical Education Newsletter 1983;1:5-8.8 International Union of Pure and Applied Chemistry/International Federation of Clinical Chemistry. The Silver Book: Compendium of terminology and nomenclature of properties in clinical laboratory sciences. Oxford: Blackwell Scientific Publishers; 1995.9 Henry JB. Clinical Diagnosis and Management by Laboratory Methods. Philadelphia:W.B. Saunders; 1994.10 Burtis CA, Ashwood ER (editors). Tietz Textbook of Clinical Chemistry, 2nd ed. Philadelphia:W.B. Saunders; 1994.

2University/Regenstrief, University of Utah, Association of Regional and University Pathologists (ARUP), Mayo Medical Laboratories, LDS Hospital in Salt Lake City, the Department of Veterans Affairs, Quest Diagnostics, and University of Washington). From the start, this was an empirical effort with the goal to provide codes that correspond to the concepts in real world laboratories’ and clinical departments’ master files.We aim to achieve a level of detail in the definition of a LOINC term that will map one-to-one to the separately reported observations on a clinical laboratory or other clinical system report. If a test has its own column on a clinical report, or has a reference range that is significantly different from other tests, or has a different clinical meaning than other related tests, it will usually be assigned a separate LOINC code and name. LOINC creates terms both for individual variables (reportable tests or clinical measurements) and collections of such variables. We create terms that represent two kinds of collections: Panels, where the child elements are enumerated, and Documents where the terms represent general information collections whose contents are not explicitly enumerated.The Regenstrief Institute maintains LOINC and makes it available in a number of file formats. LOINC and the related files (such as this document) are copyrighted to assure that multiple variants of the standard do not emerge. Having many variants would defeat the purpose of a universal identifier for test results. LOINC is made available at no cost worldwide under the license at http://loinc.org/license. The LOINC Table, supporting documentation and supplemental files, and the RELMA® mapping program are all made available by the Regenstrief Institute on the LOINC website (http://loinc.org). LOINC content and associated documentation has been translated into many languages in further support of adoption globally.111.1 AcknowledgmentsOver the years, LOINC has been supported financially by many organizations and individuals. We are thankful for all of their generous support, which we acknowledge on the LOINC website.This work was initiated by and is performed under the auspices of the Regenstrief Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of any of our individual or organizational supporters.We remain grateful to the late Dr. Henrik Olesen for his very helpful comments and insights about laboratory test coding. Dr. Olesen served as chair of the Commission on Nomenclature for Properties and Units (1989) and member of the joint IUPAC-IFCC Commission on Nomenclature, Properties and Units (1988-1997).1.2 What is not part of the nameLOINC terms are not intended to transmit all possible information about a test or observation. They are only intended to identify the test result or clinical observation. Other fields in the message can transmit the identity of the source laboratory and special details about the sample. For instance, the result code may identify a blood culture, but the message source code can be more specific and identify the sample as pump blood.The level of detail in the LOINC Fully Specified Name was intended to distinguish tests that are usually distinguished as separate test results within the master file of existing laboratory systems. Indeed, at the outset, we used the master files from seven U.S. laboratories to shape this effort, and requests from commercial labs and hospitals continue to shape the content of the LOINC effort. Therefore, certain parameters and descriptions 11 Vreeman DJ, Chiaravalloti MT, Hook J, McDonald CJ. Enabling international adoption of LOINC through translation. J Biomed Inform. 2012 Aug;45(4):667-73. doi: 10.1016/j.jbi.2012.01.005. Epub 2012 Jan 21. [PubMed: 22285984];

3pertaining to test performance are specifically excluded from the fully specified test name. These parameters will typically be reported in separate fields (attributes) of a test/observation report message, not as part of the observation name. Attributes that we explicitly exclude from the fully specified name are:• the instrument used in testing• fine details about the sample or the site of collection, such as “right antecubital fossa”• the priority of the testing, e.g., whether stat or routine• who verified the result• the size of the sample collected• the place of testing (e.g., home, bedside, clinical lab) In the case of laboratory tests, the name does include information that identifies the type of sample (or specimen). However, the “sample” part of the name is not meant to carry all possible information about the sample, but only enough to indicate significant differences in the result and to reflect current usage in test names. For example, laboratories usually define urine sodium, sweat sodium, and serum sodium as different tests because each of these has a different normal range. But laboratories do not define different tests to distinguish the concentration of arterial serum sodium from venous serum sodium, though the lab may report that the sample was venous or arterial in another part of the report. We are guided by the pragmatics of conventional usage. If laboratories define separate tests for the same measurements done on different specimens (this usually implies a well-defined normal range difference), we will define different “result-able” tests in our dictionary. If they do not, we will not.The extent to which we include methods as part of the name is also guided by pragmatics. We distinguish tests/observations by the type of method used to produce the results only if a given type of method has an important effect on the interpretation of the result. This is a complex subject and it is difficult to fully describe our rationale in this guide. Where laboratories do not tend to include the method in the name (e.g., most of chemistry) we do not include the method in the name. Where they tend to (e.g., in immunochemistry) we do. For some tests, this can be justified by the standardization of methods to produce “equivalent” results, and sometimes by the many variables (method, reagent) that one could never hope to represent fully in a single name. However, even when we do distinguish these cases, we distinguish by type of method, not the most detailed possible method distinction. (See Section 2.7 – Type of Method, for more details.)The College of American Pathologists produces statistical summaries of the results for measurements of standard samples broken down by laboratory and by instrument or procedure. (These are called CAP surveys.) We considered using this CAP survey data to decide empirically when test names should be distinguished by method, but decided this was not feasible because many of the apparent differences in method obtained with the standard samples were artifacts of the sample matrix and did not apply to serum specimens. In addition, the variation among laboratories was often of the same magnitude as the variation among methods within laboratories for the same method.We do not mean to underrate the importance of method differences. The result message will still include information about the normal range for that particular test, the source laboratory and, if the laboratory wishes, specific information about the method. However, such information is reported in separate fields in the HL7 message (e.g., OBX-17 can carry very detailed method information). It is not embedded in the name of the test.1.3 Scope of LOINC The current scope of the existing laboratory portion of the LOINC database includes all observations reported by clinical laboratories, including the specialty areas: chemistry, including therapeutic drug monitoring and

4toxicology; hematology; serology; blood bank; microbiology; cytology; surgical pathology; and fertility. A large number of terms used in veterinary medicine have also been included. In addition, the scope includes those non-test measurements that are commonly required to interpret test results and are usually included as part of the report with the laboratory observations. Examples include:• for cervical pap smears, the phase of menstrual cycle or use of estrogens• for arterial blood gases, inspired oxygen• for drug concentrations used in pharmacokinetics, the dose• for a blood bank, the number of units dispensedThe June 2000 release contained our first foray into order sets/batteries. Existing LOINC codes could always be used to order the specific tests observation, but prior to 2000 there was no mechanism to use LOINC codes to order a set of observations.The clinical portion of the LOINC database covers tests, measures, and other observations about a patient that can be made without removing a specimen from them. LOINC has codes for observations like vital signs, hemodynamics, intake/output, EKG, obstetric ultrasound, cardiac echo, urologic imaging, gastroendoscopic procedures, pulmonary ventilator management, radiology studies, clinical documents, selected survey instruments (e.g. Glasgow Coma Score, PHQ-9 depression scale, CMS-required patient assessment instruments), and other clinical observations.

52 Major Parts of a LOINC termA LOINC term is defined as the combination of the LOINC code and the Fully Specified Name (FSN).The LOINC code is a unique, permanent identifier. The LOINC code has no intrinsic structure except that the last character in the code is a mod 10-check digit. The algorithm to calculate this check digit is given in Appendix C. All of the structure associated with a single LOINC entity is stored in other fields in the LOINC database.The FSN is composed of five or six main Parts: the name of the Component or Analyte measured (e.g., glucose, propranolol), the Property observed (e.g., substance concentration, mass, volume), the Time Aspect of the measurement (e.g., is it over time or momentary), the type of System or sample (e.g., urine, serum), the Scale of measurement (e.g., qualitative vs. quantitative), and where relevant, the Method of the measurement (e.g., radioimmunoassay, immune blot).The FSN is the combination of the main Parts and the colon character, “:”, which acts as a separator:<Analyte/component>:<kind of property of observation or measurement>:<time aspect>:<system (sample)>:<scale>:<method>Note Each attribute of the LOINC Fully Specified Name other than the Method should be valued for every active LOINC term. In some cases, such as for panel terms, one or more attribute values may be a dash ( -), but none of the primary attributes should have null values other than the Method. We have not declared a file specification definition requiring a value for these name fields because they were null for some older, deprecated terms. In the rare case that a new term is released without an attribute value, that term will be deprecated and a new term will be created as a replacement. The first part of the name can be further divided up into three subparts, separated by carats (^). The first subpart can contain multiple levels of increasing taxonomic specification, separated by dots (.). The third and fourth parts of the name (Time Aspect and System) can also be modified by a second subpart, separated from the first by a carat. In the case of Time Aspect, the modifier can indicate that the observation is one selected on the basis of the named criterion (maximum, minimum, mean, etc.); in the case of System, the modifier identifies the origin of the specimen if not the patient (e.g., blood donor, fetus, and blood product unit). The hierarchical structure is outlined in Table 1, with references to the section numbers where each item is explained in detail.Table 1: Hierarchical Structure of Fully Specified Analyte NamesSubpart NameSectionComponent/Analyte2.2Name and modifier2.2.1Component/Analyte name2.2.1.1Component/Analyte subname2.2.1.2Component/Analyte sub-sub-name2.2.1.3Information about the Challenge (e.g., 1H post 100 gm PO challenge)2.2.2

6Adjustments/corrections2.2.3Kind of Property (mass concentration, mass)2.3Time Aspect (point or moment in time vs. time interval)2.4System/sample type (urine, serum)2.5“Super System” (patient, donor, blood product unit)2.5.2Type of Scale (nominal, ordinal, quantitative)2.6Method Type2.7We used Tietz,12 Henry,13 IUPAC,14 EUCLIDES,15 diagnostic microbiology textbooks, such as Mahon and Manuselis,16 the American Association of Blood Banking,17 and other sources as well as the expertise of the individuals or the committee to choose preferred names.Here are some examples of fully specified LOINC names:Sodium:SCnc:Pt:Ser/Plas:QnSodium:SCnc:Pt:Urine:QnSodium:SRat:24H:Urine:QnCreatinine renal clearance:VRat:24H:Ur+Ser/Plas:QnGlucose^2H post 100 g glucose PO:MCnc:Pt:Ser/Plas:QnGentamicin^trough:MCnc:Pt:Ser/Plas:QnABO group:Type:Pt:Bld^donor:NomBody temperature:Temp:8H^max:XXX:QnChief complaint:Find:Pt:^Patient:Nar:ReportedPhysical findings:Find:Pt:Abdomen:Nar:ObservedBinocular distance:Len:Pt:Head^fetus:Qn:US.measured2.1 General naming conventions2.1.1 Abbreviations in names of Component (Analyte)In general, abbreviations are not used in the Component. For example, we use “total”, “fraction”, “oxygen”, “Alpha”, and “Beta” rather than “tot”, “frac”, “O2”, “A-”, and “B-”. However, there are a few exceptions, such as the 12 Burtis CA, Ashwood ER, Burns DE (editors). Tietz Textbook of Clinical Chemistry, 5th ed. Philadelphia: W.B. Saunders; 2013.13 Henry JB. Clinical Diagnosis and Management by Laboratory Methods. Philadelphia:W.B. Saunders; 1994.14 International Union of Pure and Applied Chemistry/International Federation of Clinical Chemistry. The Silver Book: Compendium of terminology and nomenclature of properties in clinical laboratory sciences. Oxford: Blackwell Scientific Publishers; 1995.15 Euclides Foundation International. EUCLIDES Laboratory Investigation Codes. Available from Dr. Georges DeMoor, Euclides Foundation International nv, Excelsioriaan 4A, B-1930, Zaventern, Belgium. Phone: 32 2 720 90 60.16 Mahon CR, Manuselis G (editors). Textbook of Diagnostic Microbiology. Philadelphia:W.B. Saunders; 1995.17 Walker RH. American Association of Blood Banks Technical Manual. 11th ed. Bethesda, MD: Amer Assoc of Blood Banks, 1993.

7commonly used abbreviations shown in Table 2.Table 2: Example Component AbbreviationsAbbreviationFull NameAbAntibodyAgAntigenDNADeoxyribonucleic acidHIVHuman immunodeficiency virusHLAHuman histocompatibility complex derived antigensHTLV IHuman t-cell lymphotropic virus-IIg “X”Immunoglobulins (e.g., IgG for immunoglobulin G, IgM for immunoglobulin M)NOSNot otherwise specifiedRNARibonucleic acidrRNARibosomal ribonucleic acid2.1.2 General naming rules for the Component (Analyte)2.1.2.1 Place the identifier of the substance being measured first. This means “Hepatitis A antibodies (Ab)” not “Antibodies, Hepatitis A.”2.1.2.2 Use the generic name of a drug, not the brand name, when referring to drug concentrations and antimicrobial susceptibilities, e.g., Propranolol, not Inderal. We will usually include the brand or trade names in the related names (synonyms) field.2.1.2.3 Use full taxonomic name of an organism or virus name (not the disease) when describing a test that diagnoses that disease. Say “Rickettsia rickettsii Ab” not “Rocky Mountain spotted fever Ab”. Say “herpes simplex virus Ab” not “HSV Ab.” The disease name should be included as a synonym in the related name field.2.1.2.4 Species and groups of species: SP identifies a single species whose identity is not known. SPP identifies the set of species beneath a genus. We have a third case, however. In some tests, antibodies apply to different strains of species. In rickettsial diseases, the antibodies are then against groups of species, e.g., the spotted fever group or the typhus group. In this case we use Rickettsia spotted fever group and Rickettsia typhus group.2.1.2.5 When tests include the name of a bacterium (e.g., Neisseria gonorrhoeae DNA probe) for the formal LOINC name we use the full bacterial name from the International Journal of Systematic and Evolutionary Microbiology.18 When it includes the name of a virus (e.g., West Nile Virus IgM antibodies), we use the viral name as given by Index Virum.192.1.2.6 When the test measures an antigen to a specific species of organism but cross-reactivity is such that other organisms are identified, the name should be the principal organism that is targeted by the test.2.1.2.7 Avoid “direct” and “indirect” except as parts of synonym names. Avoid “conjugated” and 18 Euzéby JP. List of bacterial names with standing in nomenclature: a folder available on the internet. Int J Syst Bacteriol 1997;47:590-592. [PubMed: 9103655]. (List of prokaryotic names with standing in nomenclature. [Update 2008 May 2, cited 2008 June]. Available from: http://www.bacterio.net)19 Virus taxonomy: classification and nomenclature of viruses: Ninth Report of the International Committee on Taxonomy of Viruses. (2012) Ed: King, A.M.Q., Adams, M.J., Carstens, E.B. and Lefkowitz, E.J. San Diego: Elsevier Academic Press. Available from: https://talk.ictvonline.org/taxonomy/

8 “unconjugated” when a more precise term, such as “glucuronidated” or “albumin-bound” is available.2.1.2.8 Use “platelets”, not “thrombocytes.”2.1.2.9 Name vitamins by the chemical name. For example, use thiamine not Vitamin B1, The name containing “Vitamin” will be included as a synonym. This is the only reasonable approach because all vitamins have a chemical name but not all vitamins have a “numbered” vitamin name. One exception to this rule is that we will use the widely accepted vitamin name for nutrition intake terms.2.1.2.10 Always specify whether serology tests measure the antigen or antibody, using the abbreviation “Ab” for antibody and “Ag” for antigen. Remove the “anti” from “ANTI X Ab.” It is redundant and obscures the most significant word in the name. Thus, “anti-smooth muscle Ab” becomes “Smooth muscle Ab.” Common abbreviations or shortened names, e.g., ANA for anti-nuclear antibody, will be found in the related names field.2.1.2.11 VDRL will be named Reagin Ab because that is what it is. We will have to depend upon synonyms and aliases to equate our “standardized” names with the old names.2.1.2.12 Use the noun form of the target of the antibody, e.g., Myocardium Ab, not Myocardial Ab.2.1.2.13 Anion vs. acid: Always use the anionic name for chemicals, not the acid name, e.g., lactate, citrate, and urate, not lactic acid, citric acid, and uric acid. The acid form of the name will be included in the related names field of the database.2.1.2.14 Alcohols: Always use the single-word names for alcohols: methanol, not methyl alcohol; ethanol, not ethyl alcohol, and so on.2.1.2.15 Always spell out OH as Hydroxy, or as – ol, with no space or hyphen between Hydroxy and the next word.2.1.2.16 Greek letters, alpha, beta, gamma, etc., are always spelled out (e.g., alpha tocopherol, not A-tocopherol), with a space between the spelled out Greek letter and the rest of the chemical name2.1.2.17 Use pH, not log (H+).2.1.2.18 Whenever possible, the Component will contain the scientific names of allergens. Note: This is a convention implemented in January 2002.2.1.2.19 Avoid use of the word “total” in laboratory test names, except when denoting the denominator of a fraction. Thus it is Alkaline phosphatase, not Alkaline phosphatase.total, but Alkaline phosphatase. bone/Alkaline phosphatase.total.2.1.2.20 For drug metabolites, we will use the “nor” form rather than “desmethyl”, e.g., nordoxepin not desmethyldoxepin.2.1.2.21 Abbreviate units of time, such as Y for year, D for day, and W for week. This only applies to time as a unit of measure, e.g., in the past 7D, and not when year or day are used to refer to a date or general time construct, e.g., next year.2.1.3 Punctuation in Analyte namesA number of Analyte names include punctuation characters such as commas, for example, to identify the position of multiple alkyl groups in a carbon chain. We will avoid special characters, e.g., commas, dashes, and parentheses, except where they are included in the name specified by IUPAC, the Chemical Abstract Service

9(CAS) convention, or another international convention. So for example, commas will appear in multiple substitutions of alkyl chains per the CAS standard, dashes, asterisks and colons will appear in HLA allele names, colons will appear in the names of some microorganisms, and parentheses (i.e., round brackets) will appear in the names of red blood cell antigens.2.1.4 Case insensitivityAll names are case insensitive. Prior to December 2006, we used upper case in the database and our examples, but we then changed to mixed case for easier readability. In electronic messages senders and receivers can use upper, lower or mixed case. However, the meanings should not be sensitive to case conversions to avoid any possibility of confusion when the information is sent over networks that may apply case conversion. To identify parts of the few names that by international convention are case sensitive, such as red blood cell antigens, we use the word “little” in front of the letter that is lower case. We use a similar convention to indicate superscripts with the word SUPER. See examples in Table 3.Beginning in June 2019 with LOINC version 2.66, we adopted tall man lettering for drugs with similar names based on the list recommended by the Institute for Safe Medication Practices, which includes the list previously published by the U.S. Food and Drug Administration. Tall man lettering uses upper case letters to distinguish key parts of the drug name in order to help visually differentiate similar names, such as cycloSPORINE and cycloSERINE. This format is still case insensitive in that the meaning is the same regardless of the case; however, for senders and receivers that can support mixed case display, the tall man lettering helps draw attention to the discriminating parts of similar names.Table 3: Example Case Specifying ConventionsOur conventionsStandard mixed caseL little u super little aLualittle i-1 subtype i-1 Subtype2.1.5 Roman numerals vs. Arabic numeralsWhenever possible, numerals shall be represented in their Arabic form. However, when the conventional name uses Roman numerals, as is the case for clotting factors such as factor VIII, the LOINC primary name will use Roman numerals and we define a synonym containing Arabic numerals.2.1.6 ExponentsWe will use the phrase “exp” to indicate an exponent in the Component. According to the Unified Code for Units of Measure (UCUM), exponents are typically represented using an asterisk (*) or carat (^). However, asterisks and carats both already have defined meanings in LOINC. (As described later, asterisks are used in variables that report another specific part of the LOINC name, and carats are used as delimiters of subparts.) For this reason, we use “exp” to avoid ambiguity. For example, the concept “height raised to the power of 2.7” is represented as “height exp 2.7”.2.1.7 Use of the slash (/)In the Component, a slash (/) is used to distinguish between a numerator and a denominator (a.k.a. Divisor) for terms that represent fractions or ratios. For example, Basophils/100 leukocytes represents the fraction of basophils out of the parent population of 100 leukocytes, and Lecithin/Sphingomyelin represents the ratio of lecithin to sphingomyelin. In the System, a slash is used as a conjunction and means “or”. A common example is

10Ser/Plas, which means that either Serum or Plasma is a suitable specimen for measuring a particular analyte.2.1.8 Use of curly braces {} in LOINC namesIn Section 2.5 we describe the use of XXX in the System when the material is unknown or specified elsewhere in the HL7/ASTM message. In some domains, particularly clinical observations, we have adopted a newer style of notation with curly braces to indicate that the information is provided elsewhere.For example, LOINC term 32491-3 represents a deep tendon reflex observation where the anatomic location is not specified in the term name:Deep tendon reflex:Find:Pt:{Reflex location}:Ord:ObservedSuch terms could be used in post-coordinated expressions where the value of “reflex location” is communicated elsewhere. The curly braces notation has the advantage over using XXX in some cases because it allows a more precise indication of the set of possible entities to expect for that piece of information. In the reflex example above, saying {reflex location} narrows the expected set of possible values down to those anatomic regions where a muscle tendon reflex can be observed.We have made use of this notation primarily in the System and Method part of the name.2.2 Component/Analyte (1st part)The first main part consists of three subparts: (1) the principal name (e.g., the name of the Analyte or the measurement); (2) the Challenge or provocation, if relevant, including the time delay, substance of challenge, amount administered, and route of administration; and (3) any standardization or Adjustment.The three subparts of the first part follow this syntax:<[analyte].[subclass].[sub-subclass]> ^ <[time delay] post [amount] [substance] [route])> ^ <adjustment>In the above syntax, the carat (^) is a required delimiter and the “dot” (.) separates the Analyte name from its subspecies.This convention also implies that dots (.) and carats (^) cannot be a formal part of any of the words that are connected by these delimiters.These subparts are described in greater detail below, Sections 2.2.1 through 2.2.3.2.2.1 Analyte name (1st subpart)The first subpart names the Analyte, including any relevant sub-classifications, separated from the main Analyte name by dots.2.2.1.1 Analyte/subclassThe principal name (the first subpart) can be divided further by subclass (e.g., Calcium by itself is one Component, Calcium.ionized names another test that measures a subclass of calcium). Subclasses are separated by dots. Examples of common subclasses include: bound, free, and bioavailable; ionized and non-ionized;

11glycated; glucuronidated and non-glucuronidated; IgA, IgD, IgE, IgG, and IgM as modifiers indicating the subspecies of antibodies. Note that bioavailable is distinguished from free by including both free and partially bound moieties.If the antibody is from a particular subclass of antibodies, specify the type of immunoglobulin (IgM, IgG, IgA, or IgD), e.g., Hepatitis A virus Ab.IgG, Hepatitis A virus Ab.IgM. If more than one subclass of immunoglobulin is included in the measurement, all are listed in the subclass, e.g., Mumps virus Ab.IgG+IgM with a plus sign (+) to separate the subspecies. There should be no spaces between the plus sign and the words it connects.If two or more constituents are measured as one quantity, each constituent should be named in the Component separated by a plus sign, e.g., Cyclosporine+metabolites or Human papilloma virus 16+18+31+33+35+45+51+52+56 DNA.If multiple Analytes are measured separately, the Analytes are separated by an ampersand (&) surrounded by spaces. Two cases that use the ampersand convention are the names of panel terms and impression terms.The naming of panel terms is described more completely in Section 8, but here we describe its use of ampersand. The enumerated child elements of a panel are each measured individually, so we often use ampersand in the name of the parent term (the panel term), e.g., ABO & Rh group panel. This particular example of ABO & Rh group also illustrates how panel terms using ampersand are different than an observation term with ampersand. The ABO & Rh group panel is linked to two separate observation codes, one for ABO and another for Rh group, that each carries its own result. An ABO & Rh group observation term would carry a combined (but separately measured) result (e.g. A positive). Either term could be used in ordering, depending on the reporting approach.Note In general, we recommend using separate observation terms for results that are measured separately. Older LOINC terms for assays that produce individual results for two or three analytes were sometimes modeled in LOINC as a single term with multiple analytes separated by “&”. The Answer List associated with such terms would include answer values combining the results from multiple analytes. Moving forward, only assays that truly produce a single result will be modeled this way; otherwise, a panel will be created with individual child terms for each separate result. Impression terms may also use ampersand, for example, Hepatitis A virus Ab.IgM & total impression. In the case of the Hepatitis antibody impression, both the IgM antibody and the total impression are described separately.In some cases, panel or impression Components contain both a plus sign (+) and an ampersand (&), for example, Human papilloma virus 16 & 18 & 31+33+35+39+45+51+52+56+58+59+66+68 DNA impression. In this example, the HPV 16 and HPV 18 impressions are both described separately, as is the impression for the group HPV 31+33+35+39+45+51+52+56+58+59+66+68, which is measured as a single quantity.2.2.1.2 DivisorSome Analytes contain a Divisor, which represents the denominator of a result that is expressed as a fraction or ratio. The numerator does not have a separate name because by default the Analyte is the numerator for all terms. In Analytes that do have a Divisor, the numerator is separated from the Divisor by a slash (/). For example, in the Analyte Albumin/Protein.total, the numerator is Albumin and the Divisor is Protein.total, so that the overall Analyte represents albumin as a fraction of the total protein. Similarly, Albumin/Creatinine represents

12the ratio of albumin to creatinine. Note that in the former case, the Property would be a type of Fraction, since albumin is a type of protein (i.e., albumin represents a fraction of total protein), whereas in the latter, the Property would be a type of Ratio, because the amount of albumin is being compared to the amount of creatinine, but neither of them is a parent compound of the other.2.2.2 Challenge test (2nd subpart)The second subpart contains information necessary to interpret “challenge” (or loading or tolerance) tests. Variables that report the result of a measurement taken a certain amount of time post challenge (e.g., glucose after an oral glucose tolerance test) must be distinguished according to the challenge and the time post challenge. Thus, the Challenge subpart has a substructure that identifies the time interval or time difference and the challenge, using the following syntax, where the word “post” (or base line) is required.<time delay> “post” <challenge>where the challenge can be further characterized as<amount given> <substance/treatment given> <route given>An example of a Challenge that used all parts would be: Aldosterone^1H post 25 mg captopril POThe time difference follows the syntax: n<S|M|H|D|W> where n is a number (possibly a decimal); S denotes seconds; M denotes minutes; H denotes hours; D denotes days; and W denotes weeks. The time delay can be preceded by a ‘greater than’ (>) sign, e.g., >4H. Table 4 lists some possible values for time difference, but any time specification that follows the above syntax would be legal.In addition to specifying a time elapsed since challenge, the time delay slot can be used to name a clock time when the measurement was taken, e.g., Glucose^10 AM specimen, or to specify the ordering of specimens, e.g., ^1st specimen, ^2nd specimen. Use this syntax to indicate pre- and post-immunization specimens, acute and convalescent specimens, or a series of specimens for which no more detailed information is available.Table 4: Example Time Delay Post ChallengeBSBaseline (time just before the challenge)PEAKThe time post drug dose at which the highest drug level is reached (differs by drug)TROUGHThe time post drug dose at which the lowest drug level is reached (varies with drug)RANDOMTime from the challenge, or dose not specified (random)n minutes/hours/days/weeks/months/etc. after challenge begun:1M1 minute post challenge6H6 hours post challenge2M2 minutes post challenge7H7 hours post challenge3M3 minutes post challenge8H8 hours post challenge4M4 minutes post challenge8H SHIFT8 hours aligned on nursing shifts5M5 minutes post challenge12H12 hours post challenge6M6 minutes post challenge24H24 hours post challenge7M7 minutes post challenge2D2 days8M8 minutes post challenge3D3 days9M9 minutes post challenge4D4 days10M10 minutes post challenge5D5 days15M15 minutes post challenge6D6 days20M20 minutes post challenge7D7 days

13Table 4: Example Time Delay Post Challenge25M25 minutes post challenge1W1 week30M30 minutes post challenge10D10 days1H1 hour post challenge2W2 weeks1.5H1½ hour (90 min) post challenge3W3 weeks2H2 hours post challenge4W4 weeks2.5H2½hours post challenge1MO1 month (30 days) post challenge3H3 hours post challenge2MO2 months (60 days) post challenge4H4 hours post challenge3MO3 months (90 days) post challenge5H5 hours post challengeThe second subpart is also used to describe measurements taken at a specified point after the beginning of an ongoing treatment, such as peritoneal dialysis, e.g., Creatinine^12H post peritoneal dialysis. More generally, this syntax can be used to indicate that observations were recorded, e.g., ^post partum, ^postoperative, or ^post EDTA therapy.The syntax of the second subpart can be specified in various ways to indicate Challenges of greater or lesser specificity, corresponding to the amount of detail that the laboratory knows about the challenge specimen.Examples of the range of possibilities include:Table 5: Example Challenge SubpartsAnalyte“^”Time“Post”AmountSub/TreatRoute11-Deoxycortisol^8Hpost30 mg/kgMetyraponePOCorticotropin^45Mpostdose u/kgInsulinIVAscorbate^postdosePO11-Deoxycortisol^2nd specimenpostXXX challenge17-Hydroxyprogesterone^6HpostXXX challenge11-Deoxycortisol^postXXX challengeCalcium^12HpostCFstC peptide^postCFstWe denote the route of the challenge by HL7 Version 2.3 “abbreviations for medication routes” (Table 6). An oral route of administration would be denoted by PO,20 an intravenous route by IV.Table 6: Example Route Abbreviations for Challenge Part(from HL7 v.2.3, Chapter 4)Abbr.Challenge DescriptionAbbr.Challenge DescriptionAPApply ExternallyMMMucus MembraneBBuccalNSNasalDTDentalNGNasogastricEPEpiduralNPNasal ProngsETEndotrachial TubeNTNasotrachial Tube20 In the United States, PO (an abbreviation for per ora) is used to identify medications taken by mouth.

14GTTGastronomy TubeOPOphthalmicGUGU IrrigantOTOticIMRImmerse (Soak) Body PartOTHOther/MiscellaneousIAIntra-arterialPFPerfusionIBIntrabursalPOOralICIntracardiacPRRectalICNIntracervical (uterus)RMRebreather MaskIDIntradermalSDSoaked DressingIHInhalationSCSubcutaneousIHAIntrahepatic ArterySLSublingualIMIntramuscularTRHThyrotropin-releasing hormoneINIntranasalTPTopicalIOIntraocularTRATracheostomyIPIntraperitonealTDTransdermalISIntrasynovialTLTranslingualITIntrathecalURUrethralIUIntrauterineVGVaginalIVIntravenousVMVentimaskMTHMouth/ThroatWNDWoundExamples:Glucose^30M post 100 g glucose PO:MCnc:Pt:Ser/Plas:QnGentamicin^trough:MCnc:Pt:Ser/Plas:QnFor drug peak (obtained at a time presumed to reflect the highest concentration) and trough (obtained at a time presumed to reflect the lowest concentration) measures, the nature of the substance loaded is the same as the Analyte name, and need not be included.2.2.2.1 Reporting the baseline measure as part of a Challenge testThrough LOINC release 2.52, we have defined one baseline term for different Challenge batteries when the Challenge is given by the same dose and route. For example, we define one baseline serum glucose for the 100 gm oral glucose tolerance test regardless of the number of separate measurements defined in the battery:Glucose^pre 100 g glucose PO A laboratory could use this same test identifier to identify the baseline result of a two-hour glucose tolerance and a three-hour glucose tolerance, for example.However, the number and variety of challenge terms users have been requesting are growing rapidly. It now appears impractical to create a baseline term for every dose and route combination. Furthermore, baseline measurements are not affected by the subsequent challenge and could in principle be reported simply as the “unadorned” measurement with no named relation to a coming Challenge. Therefore, we have created generic baseline “pre challenge” terms, for example, Glucose^pre XXX challenge. For these terms, the specifics of the challenge would be reported elsewhere.

152.2.2.2 Physiologic challengesSome challenges are defined in terms of a physiologic stress, not a dose of a chemical substance. The LOINC names currently cover calorie fasts (no calorie intake), exercise, and fluid restrictions. These Challenges are denoted by codes given in Table 7.In the case of such Challenges, the syntax also includes the duration of the Challenge. For example:post <duration><physiologic challenge> Triglyceride^post 12H CFstTable 7: Example Nature of ChallengeTypeDescriptionCFstCalorie fast. No caloric intake (food) for the period specified in the time part of the term, e.g., POST 12H CFstExerciseExercise undertaken as challenge (can be quantified)FFstFluid “fast.” No fluid intake for the period specifiedThe naming structure is an exact analogous structure to that of chemical challenges. A test for glucose after 12 hours of an energy fast would be represented as:Glucose^post 12H CFst:MCnc:Pt:Ser/Plas:QnA test for osmolality after a 12-hour fluid restriction would be:Osmolality^post 12H FFst:Osmol:Pt:Urine:QnA test for triglyceride after 12-hour energy fast would be:Triglyceride^post 12H CFst:MCnc:Pt:Ser/Plas:QnTwo durations can appear in one specification, for example:Cortisol^1.5H post 0.05-0.15 U insulin/kg IV post 12H CFst:MCnc:Pt:Ser/Plas:QnOur rules for naming challenge tests work well only when there is a single intervention followed by a test for one or more Components over time. Complex challenge tests involving more than one intervention or complicated sampling techniques need a unique name, but the name may not provide a complete description of all of the test parameters.2.2.2.3 Reporting characteristics of challenge as separate observationsBecause we cannot anticipate every type of challenge and route of administration, and because some challenge tests have no usual dose, some challenge tests will not contain a dose. Challenge observations that do not include a specific dose in the name have the word “dose” where a numeric dose would otherwise appear. The general form is:<analyte>^<time> post dose <route>Examples:Glucose^1H post dose insulin IV:MCnc:Pt:Ser/Plas:Qn

16The actual dose might then be sent as a comment or as a separate “test” that carries the dose as its value. To accommodate laboratories that wish to transmit the relevant challenge dose as a separate observation, we also define separate test names (and codes) for reporting such doses. This dose could then be sent by the reporting service as a separate result in a separate OBX segment.The name of the observation that identifies the value of the dose would have the form:<drug or challenge substance>: <time> post dose <challenge substance>Examples:Glucose.PO:Mass:Pt:Dose:QnGentamicin:Mass:Pt:Dose:QnThus we distinguish a drug concentration from the drug dose by means of the System (sample), 4th part, of the test name (see Section 2.5). You can find the observations that carry the dose of drugs or challenges grouped in the class DRUGDOSE in the LOINC database. This approach has the advantages of parsimony and practicality. It also provides an observation ID for the piece of information that must be transmitted along with the request for the observation.Another example would be:Oxygen:PPres:Pt:BldA:QnOxygen inhaled:VRat:Pt:Inhl gas:Qn Example Units: liters/minute or milliliters/secondOxygen inhaled mechanism:Type:Pt:Dose:Nom Comment: to report kind of delivery mechanism, e.g. nasal cannulaAn analogous approach is used for reporting many kinds of associated variables when the variables are not conventionally embedded in the name. We take this approach in part because there are too many levels of the variables and it is not feasible to represent them all.2.2.2.4 Generic Challenge specificationsWe allow for a range of specificity regarding Challenges from fully specified to very generic.Some Challenges will be specified fully as described above, e.g., ^30M post 100 g glucose PO. We will also include: challenges without the amount specified, e.g., ^30M post dose glucose; those that specify a time elapsed but not a particular challenge, e.g., ^1H post XXX challenge; those that do not specify the exact time but provide ordering information, e.g., ^2nd specimen post XXX challenge; or even more generic, ^post XXX challenge. These latter variants are needed to accommodate challenges that do not fit any common protocol, or referrals to reference laboratories where the study protocol is not reported.2.2.2.5 Acute and convalescent, pre and post immunizationTo assess the efficacy of immunizations, antibody levels are measured before and after the immunization; similarly, evidence for acute infection is obtained by assessing acute and convalescent screens. Both of these cases are reported with the 1st specimen, 2nd specimen syntax, for example:

17Acute specimen, 1st specimen, pre-immunization specimen:Streptococcus pneumoniae Ab.IgG^1st specimen:ACnc:Pt:Ser:QnConvalescent specimen, 2nd specimen, post-immunization specimen:Streptococcus pneumoniae Ab.IgG^2nd specimen:ACnc:Pt:Ser:Qn2.2.3 Adjustments/corrections (3rd subpart)The third subpart of the data element contains calculations that adjust or correct some measured value. We use this subpart to distinguish corrected or adjusted values from the uncorrected measurement, e.g., corrected cell counts from the raw cell counts. Since these attributes are unique to each measurement, they will be short phrases of text rather than a controlled vocabulary to define the content of the third subpart. However when defined, such a test will have a unique LOINC code and the meaning will be fixed by the text in the third part.Examples:Calcium.ionized^^adjusted to pH 7.4:SCnc:Pt:Ser/Plas:Qn Leukocytes^^corrected for nucleated erythrocytes:NCnc:Pt:Bld:Qn2.2.4 Distinguishing multiple values for any test via the test name (4th subpart)HL7 messaging allows for multiple results for one observation. However, some systems cannot distinguish separate answers per observation, so they made the test names like organism 1, organism 2 or substance 1, substance 2 to report multiple organisms or substances identified in samples. We do not encourage this type of reporting because that distinction can more clearly be accomplished by using one test name (e.g., organism identified) and the HL7 sub ID to distinguish the multiple organisms/substances. However, we have created a few terms to accommodate systems that bind the distinction into their test names. The fourth subpart of the Component name will allow reporting of repeat observations taken at the same time and/or on the same specimen.Example:Bacteria identified^^^2:Prid:Pt:Stool:Nom:Culture2.3 Kind of Property (also called kind of quantity) (2nd part)The second part of the fully specified name distinguishes between different kinds of quantities relating to the same substance, e.g., the mass concentration versus the substance (molar) concentration of sodium in a urine sample, or the absolute eosinophil count versus the percent of the total white count that is made up of eosinophils. The type of Property (kind of quantity) is an IUPAC concept described in the Silver Book.21We include most of the relevant IUPAC quantitative Property types in LOINC. We also have a set of Properties, such as PrThr (Presence or Threshold), Type, Seq (nucleotide sequence), and Loc (geographic location), that are used in qualitative terms. More examples of Properties are given in Table 8. The complete set of active LOINC Properties is available in the LOINC Part File and can be identified because they contain a PartTypeName of PROPERTY.21 International Union of Pure and Applied Chemistry/International Federation of Clinical Chemistry. The Silver Book: Compendium of terminology and nomenclature of properties in clinical laboratory sciences. Oxford: Blackwell Scientific Publishers; 1995.

182.3.1 Quantitative Properties2.3.1.1 Main quantitative Property categoriesMass: Observations reported with mass (milligrams, grams, etc.) in the numerator of their units of measure have Properties that begin with the word mass: mass content, mass concentration, etc.Substance: Observations reported with moles or mill equivalents in the numerator of their units of measure have Properties that begin with the word substance.Catalytic activity: Observations that report enzymatic activity have Properties that begin with catalytic, e.g., catalytic concentration, catalytic content.Arbitrary: Results that report arbitrary units in the numerator of their units of measure have a Property that begins with arbitrary.Number: Counts are associated with Properties that begin with “number”, e.g., a white blood cell count reported as a number of WBCs divided by volume of blood, would have a Property of number concentration.2.3.1.2 Quantitative Property category subtypesEach of the above major Property categories has number of derivatives: concentration, content, ratio, fraction, and rate (see LOINC properties table (Table 8)).Concentrations: An amount divided by a volume. These have units such as mg/dL, or gm/L.Contents: An amount divided by a mass. These have units such as mg/gm sample or mg/total protein.Ratios: When a result is reported as one measure divided by another taken from the same System, the Property is a ratio. The ratio of the mass concentration of substance A divided by the mass concentration of creatinine in a urine sample, for instance, is a mass ratio (MRto). The numerator and denominator of a ratio must come from the same System. If the measures come from different specimens, e.g., PT patient/PT control or creatinine serum vs. creatinine urine, it is a relative ratio (RelRto). The ratio of times coming from an actual and normal control (as in some coagulation tests) will be relative time (RelTime), a ratio of mass concentrations coming from two different specimens will be relative mass concentration (RelMCnc), and a ratio of catalytic concentrations from different specimens will have the property of relative catalytic concentration (RelCCnc).Fractions: Fractions are ratios of a part over a whole: Creatine kinase.MB/Creatine kinase.total, if measured in grams, is a mass fraction (MFr). Fractions are usually reported as percent. In Canada and other countries, fractions are measured as pure decimal fraction. For instance, a 95% O2 saturation would be resulted as 0.95. For some Analytes, both styles of reporting are used in Canada, so we were asked to distinguish decimal fractions from pure fractions. Beginning with the June 2012 release, we now include terms that have .DF appended to the existing fraction properties. For example, some terms now have properties of MFr.DF, SFr.DF, VFr.DF, etc. Because of the confusion that occurs in countries that report results as both decimal fraction and percent, these properties were created to represent decimal fractions that are reported without units.Rates: A rate is a measure per a time period, e.g., mg/day would be a mass rate (MRat). Clearances have the Property of volume rate, but “Clearance” will be included in Analyte name to clarify meaning, for example:Sodium renal clearance:VRat:24H:Urine:QnSome measures do not fit the above schema. For instance, IUPAC describes an entitic quantity. This refers to measure per entity (e.g., cells, receptors, and molecules). Entitic quantities usually have units that include the

19name of some entity, e.g., red blood cells (“per 106 RBCs”).One must be careful when mapping measures of constituents of red blood cells to LOINC code because they can be expressed many ways, e.g., as an amount “per mass of hemoglobin”, “per liter of blood” or “per red blood cell”. The first is a mass content, the second a mass concentration, and the last is an entitic mass (mass per entity) — all different properties.The pharmaceutical industry has the need for laboratory terms that are not specific as to whether the test measures a substance (substance concentration or substance rate) or mass (mass concentration or mass rate). We have created terms with the properties of MSCnc or MSRat to represent these more general test observations. By default, both RELMA and the online search application (http://search.loinc.org) hide these terms from the search results, but they can be displayed by adjusting the search limit settings in these programs.Some tests report the name of an organism (or initially report the presence of any organism, and later identify the particular strain), toxic substance, antibody or antigen, as a test result. Use Prid (presence or identity) as the type of Property field for results of this sort.Examples:Bacteria identified:Prid:Pt:Isolate:Nom:Bacterial subtypingBarbiturates positive:Prid:Pt:Urine:Nom:ConfirmNote For order sets/panels, the Property field may be populated by a dash (-).2.3.1.2.1 Arbitrary Concentration (ACnc)ACnc means the number of arbitrary units in a volume (arbitrary concentration). We originally used ACnc as a “temporary” place-holder for observations with ordinal answers. We then transitioned to replacing ACnc with either Pr (for results simply based on whether the Analyte is present or not without being determined by a cut off value) or Threshold (for observations reported as “positive” or “negative” based on an internal threshold or cut off). As we updated existing terms with the new model, in many cases it was difficult to definitively know how results were determined. Therefore, as of release 2.56, we are using a single Property of PrThr to represent results based on either the presence or absence of an Analyte regardless of whether or not it is based on an internal cut off. This change was approved by the Laboratory LOINC Committee in June 2016.The display name will continue to say Presence. All of the existing terms with a Property of ACnc, Pr or Threshold and a Scale of Ord were updated to have the Property PrThr for the 2.56 release. A single term with Property ACnt and Scale Ord was also updated to have the Property PrThr. Examples:Clonazepam:PrThr:Pt:Ser/Plas:OrdHepatitis B virus surface Ag:PrThr:Pt:Ser/Plas:Ord:Confirm Burkholderia mallei:PrThr:Pt:XXX:Ord:Organism specific cultureVKORC1 gene.c.1173C>T:PrThr:Pt:Bld/Tiss:Ord:MolgenThe Property of Prid will continue to be used when the result is selected from a list of organisms, as described above.

202.3.2 Qualitative PropertiesQualitative Properties describe what is being measured for non-quantitative laboratory and clinical concepts. Such Properties describe a wide variety of results, such as whether or not an analyte is present, the specific type of analyte detected, a person’s address, telephone number, or e-mail address, or a clinical finding. Three of the most common qualitative Properties in LOINC are PrThr, Prid, and Type. These specific Properties are often confusing to LOINC users, so they are described in more detail in this section.2.3.2.1 PrThrThe Property PrThr stands for “Presence or Threshold”, meaning either a) the actual presence or absence of an analyte, or b) that the amount of analyte detected is over some predetermined threshold.2.3.2.2 PridPrid, which stands for “Presence or identity”, is used for assays that detect whether or not an analyte of a particular kind is present, and if it is, to identify the specific analyte. One example of an assay that would be represented by a LOINC term with Property Prid is a bacterial culture. When a culture is performed, it is not known in advance whether or not any bacteria will be present. Therefore, one possible result for a bacterial culture is “No growth”. But, if one or more types of bacteria are determined to be present, then the specific identity (e.g. Staphylococcus aureus) is determined and reported.2.3.2.3 TypeThe Property Type is used for assays that identify the specific analyte in cases when the baseline presence of the analyte is known. For example, if an isolate known to contain Streptococcus pneumoniae is further analyzed to determine the specific serotype, the serotype assay would have a Property of Type, not Prid, because the presence of the Streptococcus is already known. 2.3.3 More examples of LOINC PropertiesCorrect assignment of Property tends to be the most difficult task for new users of LOINC. Section 4 describes more information about Properties for clinical terms, and Appendix E provides more explanation and many detailed examples.Table 8: Example LOINC PropertiesEnzymatic ActivityCAct*Catalytic ActivityCCncCatalytic ConcentrationCRtoCatalytic RatioCCnt*Catalytic ContentCFr*Catalytic FractionCFr.DFDecimal Catalytic FractionCRatCatalytic RateRelCCncRelative Catalytic ConcentrationCSubCatalytic SubstanceEntitic

21EntCat*Entitic Catalytic ActivityEntLenEntitic LengthEntLogNumLogarithmic Entitic NumberEntMassEntitic MassEntNum*Entitic NumberEntVol*Entitic VolumeEntSubEntitic SubstanceEntSRtoEntitic Substance RatioMassMassMassArMassMass/AreaMCnc*Mass ConcentrationMCncSqMass Concentration SquaredMCntMass ContentMDiffMass DifferenceMFr*Mass FractionMFr.DFMass Decimal FractionMFrDiffMass Fraction DifferenceMRatMass RateMRtoMass RatioRelMCnc*Relative Mass ConcentrationRelMRatRelative Mass RateThrMCnc *Threshold Mass ConcentrationMCncDiffDifference in Mass ConcentrationMCPctDiffPercent Difference in Mass ConcentrationSubstance (Moles/Milliequivalents)RelSCnc*Relative Substance ConcentrationSub*Substance AmountSCnc*Substance ConcentrationSCncSqSubstance Concentration SquaredSRto*Substance RatioSCnt*Substance ContentSFr*Substance FractionSFr.DFDecimal Substance FractionSRat*Substance RateRelSRatRelative Substance RateThrSCncThreshold Substance ConcentrationSCncDiffDifference in Substance ConcentrationLsCncLog Substance ConcentrationCountsNum*NumberNaricNumber Aeric (number per area)NCnc*Number Concentration (count/vol)NCncRangeNumber Concentration (count/vol) RangeNCntNumber Content = Count/Mass

22NFr*Number FractionNRatNumber=Count/TimeNRtoNumber RatioLnRtoLog Number RatioLnCncLog Number ConcentrationVolumesVol*VolumeVCnt*Volume ContentVFr*Volume FractionVFr.DFVolume Decimal FractionVRat*Volume RateVRatCntVolume Rate ContentVRatRtoVolume Rate RatioVRto*Volume RatioRelVolRelative VolumeRelVRatRelative Volume RateArVolVolume/AreaArVRatVolume Rate/AreaVFrDiffDifference in Volume FractionVPctDiffPercent Volume DifferenceVRtoPctDiffPercent Volume Ratio DifferenceTimeClockTimeClock TimeTimeTime DurationTimeDifDifference in Time DurationTimeFrTime FractionTRtoTime RatioTQ2Timing Quantity 2RelTime*Relative TimeDateDateDateRangeDate RangeDtTmRangeDate and Time RangeTmMCncTime mass concentrationTmStpTime Stamp—Date and TimeTmStpRangeTime Stamp RangeTmSCncTime substance concentrationArbitraryACncArbitrary ConcentrationACntArbitrary ContentThrACncThreshold Arbitrary ConcentrationARatArbitrary RateLaCncLog Arbitrary ConcentrationRelACncRelative Arbitrary ConcentrationAFrArbitrary FractionOther properties

23AccelAccelerationAddrAddressAnatAnatomyAngleAngleAperAppearanceArb*ArbitraryAreaAreaArAreaArea/AreaAreaFrArea FractionAreaRtoArea RatioBibBibliographic CitationCircCircumferenceCircFrCircumference FractionClass*ClassColorRtoColor RatioCompliComplianceCompliRtoCompliance RatioCmplxComplexDescDescriptionDiamDiameterDosageDosageElpotElectrical Potential (Voltage)ElpotRatVoltage Rate (=Amperage)ElpotRtoElectrical Potential RatioEmailAddrE-mail AddressArEnrgEnergy/AreaEngCncEnergy ConcentrationEngCntEnergy ContentEngDiffEnergy DifferenceEngFrEnergy FractionEngRatPower = Energy/TimeRelEngRatRelative PowerEngRatFrEnergy Rate FractionEngRtoEnergy RatioEnrgEnergyEquEquationFcnFunctionFindFindingFldConductFluid ConductanceFldResistFluid ResistanceForceMechanical ForceFreqFrequencyGenoGenotypeHxHistoryImpImpression/interpretation of study

24IDIdentifierInstrctInstructionsInvLenInverse LengthInverse VIInverse Inspired VolumeLenLengthLenFrLength FractionLRatLength RateLenRtoLength RatioLogLenRtoLog Length RatioArLenLength/AreaLikelihoodLikelihoodLocLocationLogInvPctLog Inverse PercentLogRtoElpLog Ratio Electrical PotentialMoMMultiple of the MedianMorphMorphologyNumRangeNumber RangeODOptical DensityOsmol*OsmolalityOsmolarityOsmolarityPctDiffPercent DifferencePnPerson NamePrThrPresence or ThresholdPrctlPercentilePridPresence or IdentityPPres*Pressure (partial)PPresDiffDifference in Partial PressurePPresRtoPartial Pressure RatioPresPressurePresRatPressure RatePressDiffDifferencePresRtoPressure RatioQuintileQuintileRatioRatioRangeRangeRatDiffRate DifferenceRelFldResistRelative Fluid ResistanceRelRtoRelative RatioRelSoundIntRelative Sound IntensityResisResistanceArResisResistance/AreaSatFr*Saturation FractionScoreScoreScoreDiffScore DifferenceScoreRangeScore Range

25SeqNucleotide SequenceShapeShapeSuscSusceptibilityTemp*TemperatureTempDiffTemperature DifferenceTeleTelephone NumberTscoreT ScoreTscoreDiffT Score DifferenceTxtTextThreshold*ThresholdThreshNumThreshold NumberTitrDilution Factor (Titer)TypeTypeURIUniform Resource IdentifierVCFVariant Call FileVel*VelocityVelRatVelocity RateVelRto*Velocity RatioViscViscosityZscoreZ Score* = from IUPAC Silver Book212.4 Time Aspect (point or moment in time vs. time interval) (3rd part)One can either measure a Property at a moment (point) in time or measure it over a time interval and integrate, in the mathematical sense, over time. In the latter case, we aggregate a “series” of physiologic states into a single scalar value that reflects some “average” Property measured over the specified time interval. Intervals also have relevance for rate measurements such as excretion (substance rate or mass rate) or clearances (volume rates). The amount over an interval is often expressed as a mass rate (MRat, e.g., g/24h) or a substance rate (SRat, e.g., mol/24h). Interval measurements often apply to urine and stool (e.g., collection over 24 hours and calculation of a concentration, total amount, or clearance). They also apply to clinical measurements, such as urine outputs where we have shift totals and 24-hour totals. Event counts on physiologic monitors, such as the number of premature ventricular contractions (PVCs) over 24 hours on a Holter monitor, are also of this type, as are look back periods for survey instruments.The allowed values for non-point Time Aspect are defined as a syntax exactly like the syntax for the times in challenge tests, for example:<numeric value><S|M|H|W>The most common one is 24H. Table 9 gives some other examples. The complete set of active LOINC Time Aspects is available in the LOINC Part File and can be identified because they contain a PartTypeName of TIME.For urine collection, 24H is the “standard” integrated measure and these are almost always reported as mass rates (MRat), substance rates (SRat), or catalytic (CRat) rates. These would contrast with spot or random urine tests

26that are represented as point (Pt) measures in our nomenclature and usually reported as concentrations – MCnc, CCnc, or SCnc for mass, catalytic, and substance concentrations respectively. However, we can also report the average concentration on a 24-hour specimen – in this case the Time Aspect value would be 24H but the Property would be MCnc/SCnc/CCnc instead of MRat/SRat/CRat.The designation of 24H collection is maintained for tests that traditionally have reference ranges based on amount of substance of a Component cleared or excreted in 24 hours. However, a given specimen could have a 23-hour collection time and would still be called a 24H study. Depending upon the policies and procedures of the lab, they might extrapolate the reported value to what it would have been if the collection continued for the full 24 hours and report it as moles per day.We also allow indirect specifications of a time window. Stdy identifies the duration of the study (without specifying an exact time); Enctr identifies the Encounter (ER visit, hospital stay, etc.).Sample volumes reported for timed measurements are carried in other fields or as separate “test” results in other OBX segments.Table 9: Example Duration CategoriesAbbr.Duration DescriptionsPtTo identify measures at a point in time. This is a synonym for “spot” or “random” as applied to urine measurements.StdyDuration of the studyEnctrDuration of an encounter (hospital stay, visit).EpisodeEpisodeGt 1HGreater than 1 hourGe 1 HrGreater than or equal to 1 hourLt 1HLess than 1 hourProcedure durDuration of the procedure (surgery, etc.)RptPeriodReporting periodXXXNot specified; time will be reported in another part of the electronic message* (star)Life of the “unit”. Used for blood products.Abbr.DescriptionAbbr.DescriptionAbbr.Description1M1 minute9H9 hours100D100 days5M5 minutes10H10 hours180D180 days10M10 minutes12H12 hours1W1 week15M15 minutes18H18 hours2W2 weeks20M20 minutes24H24 hours3W3 weeks30M30 minutes48H48 hours4W4 weeks45M45 minutes72H72 hours1Mo1 month90M90 minutes1D1 day2Mo2 months1H1 hour2D2 days3Mo3 months2H2 hours3D3 days6Mo6 months2.5H2.5 hours4D4 days12Mo12 months3H3 hours5D5 days1Y1 year4H4 hours6D6 days2Y2 years5H5 hours7D7 days3Y3 years6H6 hours14D14 days10Y10 years7H7 hours30D30 daysLifetimeLifetime

278H8 hours90D90 days2.4.1 Time Aspect ModifierThe second and optional subpart of the Time component allows an indication of some sub-selection or integration of the measures taken over the defined period of time: 8H^max heart rate would be the highest heart rate observed over 8H (Shift). Min, max, first, last, mean are the other possible values for this subpart. When nothing is stored in this subpart, we assume a mean value over the time period in questions. Valid values for this subpart are listed in table below.Table 10: Time Aspect Modifier CodesTimeDescriptionminMinimum value over intervalmaxMaximum value over intervalfrstFirst value observed during an intervallastLast value observed during an intervalmeanMean of all of the values observed on the interval (This is the default selection.)2.5 System (sample) type (4th part)System (sample) type is the fourth part of the fully specified test name. It consists of two subparts; the first part names the System, the optional second part, delimited with a “^”, indicates the Super System source of the sample if it is not the patient, e.g., fetus, blood product unit, donor, etc.We define different tests for the combination of Component (Analyte) and type of System (sample) that are commonly reported. In practice, laboratories include a relatively small range of sample types in their test names. Chemical tests commonly distinguish between serum, urine, blood, and cerebrospinal fluid. Microbiology cultures tend to distinguish between greater numbers of sources.Example Systems are listed in Table 11. The complete set of active LOINC Systems is available in the LOINC Part File and can be identified because they contain a PartTypeName of SYSTEM.For many chemistry tests we have included in the LOINC database a test name for identifying miscellaneous types of body fluid (Body fld), to provide a way to distinguish tests that are performed on fluid types that are not explicitly represented in the database. We use XXX in the System to identify a material that is unknown or not specified — it could be solid or fluid, for example. XXX is also used in the System when the material is specified, but recorded elsewhere in the HL7/ASTM message. Yet, using XXX as a System can be problematic (see also Section 2.5.1 – Special issues related to XXX as a System below).When should we lump a variety of specimen types under the nonspecific Body fld and when we should give a body material its own unique name for a given Component? The decision depends upon the degree to which laboratories have reported the Component-System pair as a separate “result” and the degree to which the normal ranges for a given Component-System have been standardized. By this rule, we will always define different tests for serum and for urine, when a Component can be measured in both. We define sweat sodium as a distinct test because it is a standardized test used to diagnose cystic fibrosis. We did not define duodenal fluid sodium as a separate LOINC code because this measure has not been standardized. This does not mean that the specifics about the System would be ignored. It just means that this information would be recorded in another field of the message (the specimen field of the HL7 OBR segment), not in the name. Generally, we will specify the type of

28System to distinguish at least among blood, urine, cerebrospinal fluid, pleural fluid, synovial fluid, and peritoneal fluid.For many types of tests, the distinction between plasma and serum is irrelevant. When testing on serum or plasma is clinically equivalent, the System should be recorded as Ser/Plas, meaning “either Serum or Plasma”. Note that the use of a LOINC code with Ser/Plas as the System to report the result of a specific manufacturer’s assay does not imply that the given assay is approved for use with both serum and plasma specimens; it simply means that the results obtained from testing serum and plasma are clinically equivalent, independent of which assay was used. Sometimes the test can only be run on either plasma or serum; the Component will then be associated with either Ser or Plas in one observation. If the test can be run on either but the results are clinically different and standardized (a very rare circumstance), two separate tests will be defined in our file, one with a System Plas and one with a System Ser. The current LOINC database includes some Ser tests and some Plas tests that should really be Ser/Plas. As we determine that a Ser or Plas test really should have been designated Ser/Plas, we will change the designation.As with Ser and Plas, when testing on various specimens is clinically equivalent and the system for the existing test(s) includes only one or a few of those systems, we will review such tests upon request and update them as appropriate to include the additional system(s). One such example is toxicology testing, in which at least a subset of tests (e.g., confirmatory) can be run on instruments that accept either Ser, Plas or Bld as the specimen, so we may update existing Ser/Plas or Bld terms to have the System Ser/Plas/Bld as appropriate.If the test is run on a combination of specimens (such as a ratio of substance found in CSF and plasma), the sample types are joined with a “+”, for example: Plas+CSF, Ser+CSF, or Isolate+Ser.Details about the exact source and collection method (e.g., blood drawn from the right arm and maintained on ice) are not a proper part of the test name and are reported in other parts of the message. For example, the SPM specimen segment of an HL7 message can be used to convey detailed information regarding the type of specimen, where and how it was collected, who collected it, and some basic characteristics of the specimen. Earlier versions of HL7 used OBR-17 as a field to report specimen source.Table 11: Example Laboratory System/sample TypesAbbr.NameAbbr.NameAbbr.NameAbscessAbscessExhl gasExhaled gas (breath)SalivaSalivaAmnio fldAmniotic fluidFibroblastsFibroblastsSemenSeminal fluidAnalAnusFistulaFistulaSerSerumAspAspirateFoodFood sampleSkinSkinBil fldBile fluidGasGasSputumSputumBldABlood arterialGast fldGastric fluid/contentsSpttSputum – tracheal aspirateBldLBlood bagGenitalGenitalStoolStool = FecalBldCBlood capillaryGenital fldGenital fluidSweatSweat BldCoBlood – cordGenital locGenital lochiaSynv fldSynovial fluid (Joint fluid)BldMVBlood- mixed VenousGenital mucGenital mucusTearTears BldPBlood – peripheralHairHairThrtThroat BldVBlood venousInhl gasInhaled gasPlateletsThrombocyte (platelet)Bld.dotBlood filter paperIsolateIsolateTissTissue, unspecifiedBody fldBody fluid, unspIsolate.meningitisIsolate from patient with meningitisTigiTissue large intestine

29BoneBoneWBCLeukocytesTsmiTissue small intestineBrainBrainLineLineTracheaTracheaBronchialBronchialLiverLiverTubeTube, unspecifiedBurnBurnResp.lowerLower respiratoryUlcUlcerCalculusCalculus (=Stone)Lung tissLung tissueUrethraUrethra CnlCannulaBone marMarrow (bone)UrineUrineCTpCatheter tipMeconiumMeconiumUrine sedUrine sediment CSFCerebral spinal fluidMilkMilkUnk subUnknown substanceCvmCervical mucusNailNail VagVaginaCvxCervixNoseNose (nasal passage)Vitr fldVitreous FluidColColostrumNphNaspopharynxVomitusVomitusCnjtConjunctivaPenile vesselsPenile vesselsBldWhole bloodCrnCorneaPenisPenisWaterWaterDentinDentinPericard fldPericardial fluidWoundWoundDial fldDialysis fluidPeriton fldPeritoneal fluid /ascitesXXXSee Section 2.5.1DoseDose med or substanceDial fld prtPeritoneal dialysis fluidDrainDrainPlacentPlacentaDuod fldDuodenal fluidPlasPlasmaEarEarPlr fldPleural fluid (thoracentesis fld)EndometEndometriumPPPPlatelet poor plasmaEnvironmental SpecimenEnvironmental SpecimenPRPPlatelet rich plasmaRBCErythrocytesPusPusEyeEyeRBCCoRed Blood Cells CordThese abbreviations are used in the laboratory LOINC codes. Systems in clinical LOINC terms are spelled out in full and should be easily understood.2.5.1 Special issues related to XXX as a SystemIncreasingly we get requests, often from the public health context, for tests with XXX as the specimen. XXX is a valid LOINC specimen, and often needed in many cases. However, LOINC typically needs a term with a more specific specimen instead of, or in addition to the XXX. Recall that XXX can be used to represent any kind of specimen (insects, road kill, and ingested food) when the material is unknown or specified elsewhere in the HL7/ASTM message. LOINC already has some general specimen terms that are broad but more constrained than XXX. For example, we have Bld/tiss and Body fld, which represents fluid from all of the serosal cavities, (though this also deserves discussion). We can create more such general specimen terms if needed.Use of XXX for the specimen can create problems. Firstly, the reference ranges for measures on a continuous scale change with specimen differences, and most systems depend upon the test code to get to the reference ranges. So using the same code for very different specimens can break the range checking in many systems. Of course the XXX specimen type is most commonly requested for microbiology tests used to identify micro-organisms by culture, DNA/RNA or specific antigens. In this case the nature of the specimen might not change the clinical implication for some organisms; we suspect that anthrax found anywhere in the body has the same implication. But it does make a big difference for some organisms that are natural inhabitants of the skin or digestive system, but not of the blood.

30Thirdly, if there is no hint of the specimen in the test name, clinicians will have a more difficult time ordering common microbiology tests. They won’t be able to order urine culture and blood culture each with a single click, and laboratories will have a more difficult time managing these orders. This is especially true given the current state of many HL7 messages that only rarely use codes in the specimen field. (Granted, there is hope for the future.) Fourthly, and most importantly, there is the issue of approved use. Package inserts are very specific and limiting about the specimens for which the test kit is approved. We have had a recent request for a test with specimen of XXX whose package insert allowed its use only on Saliva. What do we do? Referral laboratories tend to define tests for class of specimens approved for use on the instruments/test kits they employ. We have received requests for terms with XXX, but the test is really only used for specimens from body parts that can “catch” STD.So, the bottom line is that we won’t accept requests for tests with XXX specimens without a narrative description of the most common specimen and some sense of the range of specimens for which it is used. We will likely argue for either adding a distinct code for the dominantly common specimen (e.g. Stool for Entamoeba histolytica) or the specimen prescribed by the package insert, or for entertaining a new specimen code broader than those now available but narrower than XXX to accommodate a particular need, e.g. sterile body fluid, or Genital/anal/throat (for STD specimens). This will, of course, take time and discussion.2.5.2 Super System (2nd subpart)The second subpart of the System identifies a “super-system” when the source of the specimen is someone or something other than the patient and the result needs to be distinguished from the patient’s results because they will be stored together in the patient’s record. Examples of Super Systems include a blood product unit (BPU), a bone marrow donor, or a fetus. The Super System is also used when the clinical finding (history, physical) is about someone other than the patient and needs to be distinguished from the patient’s findings, for example, a history of diseases in a family member recorded in the patient’s chart. When the Super System is not included in a name, “patient” is the assumed default value.Note We use the term “fetus” broadly to include embryo, placenta, and products of conception.For instance, an example of representing a coagulation study that uses measures on both patient and a control might be:Coagulation reptilase induced:Time:Pt:PPP:Qn:CoagCoagulation reptilase induced:Time:Pt:PPP^control:Qn:CoagBlood banks often report red blood cell antigens for the patient and for each blood product pack assigned to that patient. So we have:A Ag:PrThr:Pt:RBC:OrdA Ag:PrThr:Pt:RBC^BPU:Ord2.6 Type of Scale (5th part)The fifth data part of the test name specifies the Scale of the measure, and is a required part. The abbreviation of the type of Scale (previously called precision), given in Table 12, should be used in the fully specified name. Note that with the release of Version 1.0K, May 1998, we changed the codes for these from SQ to ORD and from QL

31to NOM to more accurately identify the meaning.Table 12: Type of ScaleScale TypeAbbr.DescriptionQuantitativeQnThe result of the test is a numeric value that relates to a continuous numeric scale. Reported either as an integer, a ratio, a real number, or a range. The test result value may optionally contain a relational operator from the set {<=, <, >, >=}. Valid values for a quantitative test are of the form “7”, “-7”, “7.4”, “-7.4”, “7.8912”, “0.125”, “<10”, “<10.15”, “>12000”, 1-10, 1:256OrdinalOrdOrdered categorical responses, e.g., 1+, 2+, 3+; positive, negative; reactive, indeterminate, nonreactive. (Previously named SQ)Quantitative or OrdinalOrdQnTest can be reported as either Ord or Qn, e.g., an antimicrobial susceptibility that can be reported as resistant, intermediate, susceptible or as the mm diameter of the inhibition zone. (Previously named SQN) We discourage the use of OrdQn in other circumstances.NominalNomNominal or categorical responses that do not have a natural ordering. (e.g., names of bacteria, reported as answers, categories of appearance that do not have a natural ordering, such as, yellow, clear, bloody. (Previously named QL)NarrativeNarText narrative, such as the description of a microscopic part of a surgical papule test.“Multi”MultiMany separate results structured as one text “glob”, and reported as one observation, with or without imbedded display formatting.DocumentDocA document that could be in many formats (XML, narrative, etc.)SetSetUsed for clinical attachments2.6.1 Quantitative (Qn)Identifies Scales that can be tied to some physical quantity through a linear equation. This means that if we have two reports for the same quantity one with a value of 5 and the other a value of 10 we know that the two are related in amount through the linear equation Y = aX +b. When the intercept, b, is non-zero, we have a difference scale. (Fahrenheit temperature is a difference scale.) When it is zero we have a ratio scale (Kelvin temperature is a ratio scale).22,23 A Qn value may be reported as a value for a “continuous” Scale, as is the case for serum sodium, or it may be reported from a series of discrete values, as is the case for titers, e.g., 1:16, 1:32.2.6.2 Ordinal (Ord)Some observations have values that are well ordered, e.g., “present, absent”, “1+, 2+, 3+”, or “negative, intermediate, positive”, but the values have no linear relationship to one another. We do not know that positive is two or three times as much as intermediate, we just know that positive is more than intermediate. These kinds of observations have an ordinal Scale (Ord). Tests with “yes/no” answers are always ordinal (Ord). Tests reported as negative when less than the detection level but as quantified values otherwise should be regarded as quantitative (Qn).2.6.3 Quantitative/Ordinal (OrdQn)Rarely, a result can be reported in either an ordinal or quantitative Scale. The principal example of this scale is a MIC, which can be reported as either resistant/intermediate/susceptible or by the MIC numeric value. The need for terms with OrdQn as Scale was further obviated by clarification from HL7 that results such as “POS” and “NEG” should go in the OBX-8 field for normalcy status. Thus, LOINC codes with Scale of Qn can be 22 Stevens SS. Measurement, statistics, and the schemapiric view. Like the faces of Janus, science looks two ways–toward schematics and empirics. Science 1968;161:849-856. [PubMed: 5667519].23 Tang YW, Procop GW, Persing DH. Molecular diagnostics of infectious diseases. Clin Chem 1997;11:2021-2038. [PubMed: 9365385].

32appropriately used in these cases even if the “values” coming back are coded interpretations of the true numeric result value.2.6.4 Nominal (Nom)Some observations take on values that have no relative order. Think of the numbers on football jerseys. These simply identify the players; they do not provide quantitative information or rank ordering of the players. We refer to these as nominal (Nom) in Scale. Blood culture results provide a good example. Possible values could be Escherichia coli (or a code for E. coli) or Staphylococcus aureus. Other examples are admission diagnoses and discharge diagnoses. Any test or measure that looks broadly at patient or specimen and reports the name of what it finds is a Nom Scale. The values of nominal scaled observations are assumed to be taken from a predefined list of codes or from a restricted vocabulary (e.g. a menu of choices). These observations would typically be sent in an HL7 message OBX segment with a Coded Element (CE) data type (in earlier HL7 versions) or its superseding Coded with No Exceptions (CNE) and Coded With Exceptions (CWE) variants (later HL7 versions). It is important to note that the CE and CWE data types allow values to be set as codes with their print text or just as their print text alone. These data types and the Nom Scale would not be used for running narrative.2.6.5 Narrative (Nar)Some observations are reported as free text narrative. The content is not drawn from a formal vocabulary or code system. A dictated present illness would be an example of a Scale of narrative (Nar). Many clinical LOINC codes will come in two versions: one for the nominal (coded) version and one for a narrative (free text) version.2.6.6 MultiWe strongly encourage all reporting to be at the most granular level of detail. That is, if three numbers were reported, they would each be reported under a unique LOINC code and transmitted in a separate HL7 OBX segment. Occasionally reporting systems are not able to comply with this dictum. For example, some chromatography instruments can identify chemicals from the entire spectrum of known chemicals (CAS identifies more than 10 million distinct chemicals), and we may not have specific LOINC codes for reporting out these details. We have designated the Scale of Multi to identify results that include many separately structured results as one text “glob” with or without embedded (display formatting). Some laboratories report all of the details of many multiple measure tests under such globs with test names that correspond to their order name. We strongly discourage such reporting. It defeats the very purpose of individual codes to tag content.Note Because the individual elements of an Order set/Panel often have different Scales, the Scale for the order set term may be populated by a dash (-).2.6.7 Document (Doc)The Scale of Doc represents a collection of information that is either structured or unstructured. Individual LOINC codes are assigned for different collections of information regardless of the format in which they are presented, meaning that the same LOINC code should be used to represent a given document type regardless of whether it is in PDF, text document, JPG, XML, or HTML formats. The difference between Doc and Nar is that Nar represents a single free text result, while Doc is used for collections of results reported together, which may include narrative results.

33Note “Narrative reporting” as required by regulatory agencies such as the Office of the National Coordinator for Health Information Technology in the U.S. may be fulfilled by using LOINC terms with Scale Doc and thus is not only tied to the LOINC Nar Scale. 2.7 Type of Method (6th part) The Method by which the test was performed is the sixth part of the test name. Methods need only be expressed as part of the name when they provide a distinction between tests that measure the same Component (Analyte) but which have different clinical significance or have a different clinical reference ranges. For instance, whole blood glucose tested with a test strip might be distinguished in the Method field.A non-exhaustive list of example Methods are listed in Table 13. The complete set of active LOINC Methods is available in the LOINC Part File and can be identified because they contain a PartTypeName of METHOD. Further, many Methods have descriptions that can be found on the Details Page for that Part. For example, see the details page for LP70657-9 RRR.Laboratories do not include the Method as part of the name for most common chemical and hematological tests. They often need the freedom to choose the instrument according to time of day, urgency of the request for service, availability of the instruments and so on, even though the instruments may employ different methods. The laboratories then adjust each of the “interchangeable” instruments to produce equivalent results even though the instruments may use different methods. Therefore, we do not want to distinguish too finely on the basis of methods. When a LOINC term does include a Method, it usually describes a type or class of method and does not make fine-grained distinctions except in special cases. Though Method is rarely significant for many chemical and hematological tests, it is often important to immunochemical/serology testing, because the sensitivity and specificity of some tests varies greatly with the Method. For this reason, you will commonly see Methods included in microbiology tests and coagulation tests within the LOINC database.This does not mean that detailed information about the Method is irrelevant, but that it is not always useful or practical to bind it to the test name. It is an essential element of the internal quality assurance of laboratories and there are fields for reporting other details about the Method in HL7 and CEN TC251 test result messages.Table 13: Laboratory Method Type AbbreviationsMethodAbbr.CommentAgglutinationAgglCell binding assay immunofluorescent assayCBA IFACell binding assays are performed using cells that are engineered to only express the antigen of interest, which increases their specificity compared to traditional immunofluorescent assays.Coagulation AssayCoagTo distinguish coagulation assays based on clotting methods that test function/activity from Immune methods that detect the presence of clotting factors and may or may not be functional assays.Complement-dependent CytotoxicityCDCComplement FixationComp fixCytology StainCyto stainThe staining method used for pap smears, fine needle aspirates and other cell stains.DNA Nucleic Acid ProbeProbeSee Section 2.7.1 for more information about probes.

34Chromogenic/Enzymatic AssayChromoTo distinguish coagulation assays based on chromogenic (enzymatic) activity.ImmunoassayIAEncompasses all immunoassays with a few exceptions, including Immune Blot and Immune Fluorescence, which were created based on historic usage.Flocculation AssayFlocHemagglutination InhibitionHAIHemagglutinationHAEncompasses direct and indirectImmune BlotIBApplies to techniques that include electrophoretic or chromatographic separation such that position (size) of the band is part of the assessmentImmune FluorescenceIFEncompasses DFA, IFA, FA. Usually applies to cells and smears examined microscopically so that both the “where” and the “what” can be assessed, but can also be used on fluids in a way similar to ELISA. Does not include Cell binding assays (see CBA IFA above).Latex AgglutinationLALeukocyte Histamine ReleaseLHRLine blotLine blotA membrane strip pre-coated with a specific set of antigens in parallel lines that are incubated with antibodies in order to detect the targets of interest.Minimum Inhibitory ConcentrationMICAntibiotic susceptibilitiesMinimum Lethal ConcentrationMLCAlso called MBC (minimum bactericidal concentration)Molecular GeneticsMolgenGeneral class of methods used to detect genetic attributes on a molecular basis including RFL, PCR and other methods.NeutralizationNeutRadioimmunoassayRIARapid Plasma ReaginRPRMicroscopic flocculation test, using cardiolipin-lecithin-cholesterol antigen with carbon particles.Serum Bacterial TiterSBTDetermines the serum dilution that is capable of killing microorganisms.Rapid Plasma ReaginRPRMicroscopic flocculation test, using cardiolipin-lecithin-cholesterol antigen with carbon particles.Vertical Auto ProfileVAPDeveloped by Atherotech, Inc.Visual CountVCVenereal Disease Research LaboratoryVDRLMicroscopic flocculation test2.7.1 Methods for identifying nucleic acidsWe distinguish Methods that detect nucleic acid based on two aspects of the assay: whether or not the target nucleic acid is amplified (copied), and how it is detected. We are still working on determining what the most important distinctions are in the variety of nucleic acid detection methods that are used, and may update our Methods to reflect these distinctions in the future. As of the 2.63 release, however, we use the following Methods:Probe-based detection without amplification (Probe)Definition: A hybridization probe is a typically a short nucleic acid segment that binds to a complementary nucleic acid sequence that is specific to the target of interest. The probe is typically attached to signaling molecule in such a way that a signal is only generated when the probe binds to the target nucleic acid. In LOINC, the Probe method is used for assays that do not include either a nucleic acid amplification or a signal enhancement step.Target amplification followed by probe-based detection (Probe.amp.tar)

35Definition: The Probe.amp.tar Method in LOINC is used for assays that include a nucleic acid amplification step, in which many copies of the nucleic acid sequence(s) of interest are made, followed by detection of the target nucleic acid of interest using a hybridization probe. Nucleic acid amplification can be done using different techniques such as polymerase chain reaction (PCR). The primary difference between the Probe.amp.tar and Non-probe.amp.tar Methods is the technique used for target nucleic acid detection. Note that for historical reasons, this Method also includes older techniques for identifying PCR target amplification products, such as gel separation and staining to identify the fragments based on their expected sizes.The Probe.amp.tar Method is represented as NAA+probe in the Short Name and NAA with probe detection in the Long Common Name.Signal amplification followed by probe-based detection (Probe.amp.sig)Definition: Probe with signal amplification is a lab method that uses a hybridization probe, which is a typically a short nucleic acid segment that binds to a complementary nucleic acid sequence that is specific to the target of interest, followed by a signal enhancement step, in which the signal that is generated when the probe binds to the target sequence is multiplied so that it is “brighter” and easier to detect. Signal amplification can be done using different techniques, including the branched-chain DNA (bDNA) method. In theory, signal amplification is more sensitive than a probe by itself because it generates a brighter signal per each copy of the target sequence that is present. In LOINC, the Probe.amp.sig method is assigned to codes for assays that do not include a nucleic acid amplification step.The Probe.amp.sig Method is represented as Probe+sig amp in the Short Name and Probe with signal amplification in the Long Common Name.Target amplification followed by non-probe based detection (Non-probe.amp.tar)Definition: The LOINC Non-probe.amp.tar method is used for assays that include a nucleic acid amplification step, in which many copies of the nucleic acid sequence(s) of interest are made, followed by detection of the target nucleic acid of interest using a method other than a hybridization probe, such as melt curve analysis or turbidity measurement. The primary difference between the Probe.amp.tar and Non-probe.amp.tar Methods is the technique used for target nucleic acid detection.The Non-probe.amp.tar Method is represented as NAA+non-probe in the Short Name and NAA with non-probe detection in the Long Common Name.Historical information: In LOINC version 2.54, we added a new Method for target amplification with melt curve analysis (Melt.amp.tar) to distinguish assays that use melt curves rather than probes for analyte detection. For version 2.56, we replaced Melt.amp.tar with a more encompassing non-probe based Method (Non-probe.amp.tar) that is used for PCR assays with non-probe based detection technology, including melt curve analysis, and which still distinguishes from probe-based assays (Probe.amp.tar). The Method for the terms originally created with the Melt.amp.tar Method was updated to Non-probe.amp.tar for the 2.56 release, and Melt.amp.tar is no longer in use. Examples of specific techniques and their corresponding MethodsThe tables below describe specific techniques that are included in each of the four Methods described above.Table 14a: Examples of methodologies that are included in the Probe Method

36DNA probeA fragment of labeled DNA, usually 100–1000 bases long, which can be used to detect the presence of nucleotide sequences that are complementary to the sequence in the probe.RNA probeA fragment of labeled RNA, usually 100–1000 bases long, which can be used to detect the presence of nucleotide sequences that are complementary to the sequence in the probe.Table 14b: Examples of methodologies that are included in the Probe.amp.tar MethodPolymerase chain reaction (PCR) with probe-based target detection (e.g., conventional PCR, real-time PCR) A technique that requires repeated cycles of heating and cooling to double the targeted nucleic acid sequence with each cycle. In conventional PCR, after the amplification is complete, the target is detected using a labeled probe; in real-time PCR, the target is detected using probes during the amplification process.PCR with target detection based on gel separation and staining of PCR productsPCR followed by gel separation and staining to identify the fragments based on their expected sizes. This older technique for identifying PCR amplification products is included in Probe.amp.tar for historical reasons.Transcription mediated amplification (TMA)An isothermal technique that uses RNA polymerase and reverse transcriptase enzymes to amplify the targeted nucleic acid sequence.Nucleic acid sequence based analysis (NASBA)An isothermal transcription-based amplification method specifically designed for the detection of RNA targets.Strand displacement amplification (SDA)An isothermal amplification technique that relies on a strand-displacing DNA polymerase.Hybridization protection assay (HPA)A chemiluminescent-based detection assay that uses specific oligonucleotide probes labeled with an acridinium ester (AE) enzyme that emits a chemiluminescent signal when the probe binds to the RNA target.Table 14c: Examples of methodologies that are included in the Probe.amp.sig MethodHybridization protection assay (HPA)See description above.Branched chain DNA (bDNA)Involves a series of hybridization reactions for the detection of a nucleic acid sequence. bDNA is commonly used for the diagnosis and monitoring of viral and bacterial infections.Hybrid captureInvolves nucleic acid hybridization and microplate chemiluminescent detection. A microplate is coated with tagged antibodies that bind nucleic acid hybrids, capturing the hybrid molecules to the microplate.Table 14d: Examples of methodologies that are included in the Non-probe.amp.tar MethodTarget amplification (e.g., using conventional PCR) with melt curve analysisAmplification of a targeted nucleic acid sequence using a technique such as conventional PCR, followed by target detection by melt-curve analysis. DNA-binding dyes, such as SYBR Green I, are used to produce a melt-curve profile. The profile is based on the total fluorescence generated from the DNA-binding dye as it binds to melting double-stranded DNA as temperature changes.Loop-mediated isothermal amplification (LAMP)An isothermal nucleic acid amplification technique that uses 4-6 primers recognizing 6-8 distinct regions of target DNA. Synthesis is initiated by a strand-displacing DNA polymerase and two of the primers form loop structures to facilitate subsequent rounds of amplification. Note The items in the first column of the above table are not meant to be used as Methods in LOINC terms.2.7.2 Immune assaysImmune assays in the LOINC world include a large swath of tests. We have historically lumped together immune

37assays that detect the linking of antigens and antibodies via special signaling mechanisms, such as EIA, ELISA, chemiluminescence and other similar tests that produce one measure (quantitative or qualitative) of the analyte of interest. We thought of this class of tests as “EIA-like” and in the absence of an existing short acronym to describe their constituents, we borrowed EIA to provide this meaning in the Short Name and used Immunoassay in the Long Common Name to signal that this method type was not limited to pure EIA tests. In LOINC version 2.56, we changed the name of the EIA Method to IA (and EIA.rapid to IA.rapid), in order to mitigate some of the confusion regarding the EIA name. The Long Common Name will continue to use Immunoassay as it always has, and the Short Name will use IA rather than EIA.Some immunologic tests have always had their own Method type and were never lumped in the category of EIA-Immune assays described above. Immune blot (IB) tests, immune diffusion and immune based flow cytometry (FC) tests have always had specific method names because they are different in that they usually yield multiple related observations.Immune fluorescence tests (IFA, DFA and ACIF) also have had their own Method type, namely IF, because they can provide information about the presence or amount of a target analyte AND its location (or pattern) on a smear, tissue slice or cell. Immunofluorescent cell binding assays, which use cells that are engineered to express a single antigen of interest, use the Method CBA IFA. LOINC has also assigned distinct method types to some other immunologic tests including VDRL, Latex fixation, and other kinds of agglutination tests because these were their historic names or they had specialized uses or limits.We classify peroxidase and all other non-IF immune stains of tissue under the Method category immune stain.2.7.3 Immunoblot and Line blot MethodsLOINC has two different Methods for Immunoblot (IB) and Line blot. IB is used in cellular and molecular biology to identify a specific protein in a complex mixture extracted from cells. Gel electrophoresis separates polypeptide chains (subunits) into bands according to their molecular weight. The bands are transferred onto a membrane and incubated with a primary and secondary antibody to visualize the target subunits. The Line blot Method is similar in that it utilizes membrane strips that are pre-coated with a specific set of antigens in parallel lines that are incubated with antibodies in order to detect the targets of interest. However, LOINC distinguishes the two Methods based on when the electrophoretic/chromatographic separation occurs. In IB, the separation occurs in the testing laboratory, whereas in Line blot, it occurs during the manufacturing step and not in the testing laboratory.2.7.4 CoagulationWe distinguish among three kinds of coagulation methods: those that measure the coagulation activity (Coag), those that measure the coagulation factor via enzyme rate (Chromo or enzymatic), and those that measure the amount of the coagulant protein, not its activity. The Method that measures the amount of protein was called Imm until the 2.58 release, for which it was renamed IA to be consistent across laboratory classes.2.7.5 StainsWe provide very detailed distinctions among various tissue stains, naming them in full. Stain methods that are modifications of a basic method are named using a <basic>.<modification> syntax, e.g.:Methenamine silver stain.Jones2.7.6 Substrates used to measure enzyme activity

38For tests that are measuring enzyme activity using various substrates, the name of the enzyme or enzyme group will be the Component and the substrate will be the Method:Mitochondrial respiratory chain enzymes: CCnt: Pt: Fibroblasts: Qn: 1-14C-glutamate substrate 2.7.7 “Detection limit” MethodsIn specific instances, including viral load testing, urine albumin measurement and certain hormones (e.g., thyrotropin), we have LOINC codes where the Method value is the detection limit for the test. These were primarily created based on industry requests to differentiate tests that have at least an order of magnitude (10x) difference in detection thresholds, because this detection limit information was deemed more important than the specific laboratory method that was used. For example, we have codes for urine albumin with the Method Detection limit <= 20 mg/L and Detection limit <= 1 mg/L, and we also have thyrotropin terms with Method Detection limit <= 0.05 mIU/L and Detection limit <= 0.005 mIU/L. In some cases, the detection limit values are not round numbers, e.g., Detection limit <= 3.47 pmol/L. This seemingly odd value of 3.47 pmol/L is the molar equivalent of 1.0 ng/dL.Based on discussion at the June 2018 Laboratory LOINC Committee meeting, LOINC terms that specify a detection limit in the Method are no longer recommended for use, except in a select number of use cases such as thyrotropin and urine albumin. In general, we will not create new terms with such Methods because the detection limit is not actually a Method but rather a measure of the sensitivity of the test. Instead, we recommend using a more generic code, such as a term with Probe.amp.tar as the Method for a viral load, and reporting the detection limit separately using LOINC 87706-8 Laboratory device Detection limit.2.7.8 “Confirm” Method outside of Drug/ToxIn a few special cases outside of Drug/Tox, we have codes with the Method Confirm. In each of these instances, the fact that the specific instance of the result is a confirmatory result is deemed more important than the specific laboratory method used to obtain the result. Two such cases include ABO & Rh group typing, and Hepatitis B virus surface antigen testing in pregnant women.2.7.9 Special issues with Methods for clinical measures2.7.9.1 Estimated versus measured valuesFor some kinds of clinical measures we distinguish the Method Reported from Estimated and Measured. For example, reported body weight is the stated weight from a patient or surrogate. Estimated body weight is estimated by an observer, and measured would be the body weight as measured on a scale.2.7.9.2 OximetryUse of oximetry as a Method can cause confusion. For details see the Oxygen Saturation Technical Brief at the end of this guide, but briefly, oximetry has several specific types, including pulse oximetry, co-oximetry and heme-oximetry. Unfortunately, at one time the word “oximetry” was used interchangeably with “pulse oximetry,” which created confusion in LOINC because we have one Method called oximetry and another called pulse oximetry. To avoid ambiguity, as of version 2.54 we deprecated most of the terms with oximetry as the Method, and moving forward we will continue to review the ones that are remaining and create new terms with the Method pulse oximetry as needed.

392.7.10 Imaging studiesWe distinguish among the major imaging modalities for most measures derived from such imaging studies (e.g., cardiac outputs from a MUGA scan, angiography, 2D Echo, Doppler, etc.).2.7.10.1 Methods that include imaging modality and calculationIn some cases, the Method includes two concepts: the imaging modality and the method of calculation for the specific measure. Through LOINC version 2.50 we used the pattern <imaging modality>.<calculation>, for example, US.2D.Teichholz. This format, however, does not clearly differentiate between the two distinct concepts being represented. This was further complicated by our convention of using a dot (.) to specify the submodality (e.g. 2D). Beginning in LOINC version 2.52, we separated the two concepts with a plus (+) rather than a dot (.), so that US.2D.Teichholz became US.2D+Calculated by Teichholz method. We have now updated all existing terms, and are using this format going forward.

403 Special cases3.1 Findings viewed as variables or as values For some complex tests there are two ways to organize the results into a report.3.1.1 Value Assume a set “X” is made up of five “results” that can have a scale of (absent, present) or (0, 1). These results could be reported as:Finding 1 = Present – or – 1Finding 2 = Absent – or – 0Finding 3 = Present – or – 1Finding 4 = Absent – or – 0Finding 5 = Absent – or – 0Each finding is then considered a binary variable. This is sometimes called a “panel” approach.3.1.2 Variable (multiple choice) approach The alternative would be to report this information as a single variable (or multiple-choice question) with many possible values:Variable X – Finding 1, Finding 3In this case the findings are the values of a variable called Variable X; only the positive findings are reported as values. Many laboratory tests, e.g., those that test for HLA antigens, red blood cell antigens, or screens for toxic substances, could in theory be presented either way. The microscopic part of the differential count and urinalysis could also be described either way. History and physical findings and (given a real stretch) even culture results could be structured in the panel or multiple choice/multiple answer format.A single lab may report red blood cell antigens in either way, as a binary panel or a multiple-choice result, depending upon the purpose of the test. The routine cross and type are reported out in the multiple choice pattern format (only positives from a modest fixed set of tested antigens are reported). But if the tests are being used to prove fatherhood, the results are usually reported as a binary panel.Blood cultures could in theory be regarded as panels:Test NameValueEscherichia coliabsentStaphylococcus aureuspresent

41DiphtheroidsabsentStreptococcus pneumoniaeabsentPseudomonas aeruginosapresentAlthough in practice such tests are almost always reported in the multiple choice/multiple answer format, as follows:Test NameValuesBlood cultureP. aeruginosa, S. aureusWe bring up these issues to explain why we use a somewhat different data format for some types of tests, and why we sometimes provide for both reporting methods (e.g., HLA blood cell antigen tests) in the LOINC database. When a binary scale is used, the Scale will be ordinal (Ord) and the kind of Property will usually be presence (PrThr, for results based on the presence/absence of an analyte regardless of whether an internal cut off value is used to determine the ordinal result). When the multiple-choice multiple-answer approach is used, the Scale will be nominal (Nom) and the type of Property will be presence or identification (Prid).3.2 Blood bankRed cell antigens will be named in accordance with the American Association of Blood Banking (AABB) naming standards.24 In addition to the antigen or antibody, a modifier would be included in the super-system (the second subfield of the System field), to indicate whether testing was performed on the patient, donor, or blood product. Unless explicitly stated, testing is assumed to have been on a material collected from a patient. Additional information about the person identified in the System, such as the donor’s name or relationship to patient, should be placed in other OBX or comment segments of the message.Blood bank reporting illustrates the need for a method of reporting by panel and by multiple-answer mechanism. The LOINC database provides observation names for both kinds of reporting.3.2.1 Panel reportingEach reportable antigen must have its own test, so that each element in a full set of binary tests could be reported as (negative, positive) or (0, 1).The fully specified names of A, AB, B, and O blood types (as observations) would be as follows:Measure of serum antibody against type A blood of donor:A Ab:PrThr:Pt:Ser/Plas^donor:OrdPresence of A antigen on donor’s red blood cells:A Ag:PrThr:Pt:RBC^donor:OrdPresence of A antigen on the blood cells in a pack of blood given to the patient:A Ag:PrThr:Pt:RBC^BPU:Ord24 Walker RH. American Association of Blood Banks Technical Manual. 11th ed. Bethesda, MD: American Association of Blood Banks, 1993.

423.2.2 Multiple answer reportingAll blood antibodies found (or not found) can also be reported in one result term:Antigens absent:Prid:Pt:BBL^BPU:Nom Antibodies identified:Prid:Pt:Ser/Plas:NomThe LOINC database provides other “observations” for reporting: the status of each blood pack (e.g., held, given, discarded), and for reporting that information when HIS and medical records systems want it; how much of each type of blood product was given at a moment in time; the type of each pack; any adverse reaction to that pack; and the pack number to accommodate laboratories that send this information as discrete observations.Blood product disposition:Type:Pt:^BPU:NomBlood product type:Type:Pt:^BPU:Nom3.3 Immunocompetence studies (flow cytometry)The CD (Cluster of Differentiation) markers in the LOINC database include all of the single markers and the most commonly reported combinations, e.g., CD11C+CD20C+. Most of these are measuring the number or percent of a population of cells that bear the specific marker(s) of interest, e.g., Cells.CDx. In other cases, the percent of a population of abnormal cells, such as blasts, is measured, for instance, Blasts.CD2 or Abnormal blood cells.CD5. LOINC Components for cells with single markers typically do not include a plus or minus sign after the marker because flow cytometry labs do not report single CD marker-negative results, so when the marker is reported, the plus is implied. In other words, the LOINC Component Cells.CD4 represents the presence of CD4, and we do not have a Cells.CD4- Component, because such a result is not reported. However, when multiple markers per cell are reported, the pluses and minuses are always included, for example: Cells.CD3-CD8-CD57+Two kinds of measures are of interest, as described below.3.3.1 Number of cells containing the markerThe “absolute” number of such cells per cubic millimeter is represented as number concentrations, for example:Cells.CD16C+CD56+:NCnc:Pt:Bld:Qn3.3.2 Percent of cells containing the markerPercent of cells containing the named marker per 100 cells of that type is represented as number fraction, for example:Cells.CD16C+CD56+/100 cells:NFr:Pt:Bld:Qn3.3.3 Specifying the parent cell populationHistorically, the most common cell marker tests were measuring the marker(s) on a population of lymphocytes, such as CD4+ and CD8+ counts, and the LOINC Divisor for the terms representing the number fraction was simply specified as 100 cells, where the fact that the 100 cells are lymphocytes was understood. Over the last several years, cell markers have become more common in the diagnosis and monitoring of a variety of immune

43deficiencies and hematologic malignancies, and for these tests, the parent cell population may be not necessarily be lymphocytes. In order to fully specify what is being measured, many newer LOINC terms include the cell marker(s) that define the parent population in the Divisor. So for example, the following term is used to report the percent of cells that do not express CD4 or CD8 out of a population of cells that express CD3 and T-cell receptor (TCR) alpha and beta:80699-2 CD4-CD8-/100 CD3+TCR alpha beta+ cells in BloodHowever, in some cases, the parent population may vary depending on the clinical context and/or the laboratory, so we also have newer terms that have 100 cells as the Divisor. For these, we recommend reporting the parent cell population using a separate LOINC term, 32760-1 Cell type in Unspecified specimen.3.4 Microbiology3.4.1 Microbiology culturesThe inherent complexity in reporting microbiology culture results presents unique challenges for the goal of standardized observation names.3.4.1.1 Result statusThe result status (Preliminary, Final) should not be reported as a separate observation or as part of the name. It should be reported in the Result Status field (OBR-25) of the HL7 OBR segment.3.4.1.2 SpecimenThe specimen type (Serum, Blood, Urine, etc.) will be indicated in the HL7 OBR segment with the Specimen Source field (OBR-15), but may also be represented in the name.Details of specimen collection will usually be noted as OBX segments or comment segments that accompany the culture result message. The observation identifier for the OBX segment will have the fully specified name of “Specimen collection description:Find:Pt:*:Nom” and the Observation Sub-ID field will be used to order or group sets of observations. That is, if the material was collected by swabbing a wound of the right upper arm, multiple OBX segments would be created, each with the name “Specimen collection description:Find:Pt:*:Nom” and the Observation Results fields of the OBX segments would contain respectively “Swab,” “Right,” “Arm,” and “Wound.” (The granularity of the actual terms used in the specimen description is at the discretion of the user. Thus, “Right Arm Wound” as the value of a single OBX segment could be used in place of the three codes described in the previous sentence.)3.4.1.3 Descriptive resultsDescriptions of measurement and culture growth will be noted as separate OBX segments that accompany the culture result message. The name of the observation identifier will provide the context of the observation. For instance, the name for a quantitative test of bacteria in a specimen would be:Colony count:Num:Pt:XXX:Qn:VCDescriptions of Gram stain findings will be noted as OBX segments that accompany the culture result message.

44The name of the observation identifier will be:Microscopic observation:Prid:Pt:XXX:Nom:Gram stainThe result values that could be reported with this test (which is a multiple-choice, multiple answer type or observation) might include one or more of the following:Epithelial cellsGram-positive cocci in chainsMany Gram-negative diplococci3.4.1.4 Culture resultsThe organisms identified in a culture will be sent as result values in OBX segments. LOINC provides codes to identify the observation, but not for identifying the names of organisms that would appear as result values (i.e. in OBX-5). SNOMED CT is an appropriate source for these organism concepts.While “Throat Culture” is the source of the culture inoculum, it is also a label that indicates what kind of media was inoculated and the other techniques used in the laboratory. So, it is a short hand for a kind of method and such will be recorded as the Method part of the name. Thus, “Throat Culture”, “Blood Culture”, and “Clostridium difficile Culture” all represent labels for how a culture was performed.The LOINC naming model for routine cultures is:Bacteria identified:Prid:Pt:<specimen>:Nom:CultureExample names include:Bacteria identified:Prid:Pt:Bld:Nom:CultureBacteria identified:Prid:Pt:Burn:Nom:CultureBacteria identified:Prid:Pt:Stool:Nom:CultureThe LOINC names for cultures are based on the expected observations they generate, e.g. “bacteria identified” or “virus identified”. For most routine cultures the users are looking for bacteria. However, in some cases a routine culture may also grow out some fungi like yeasts. Such observations can also be reported under the same test code. But, since the culture would not be optimized for growing out fungi we have a bacteria-focused name.It is worth emphasizing these culture terms are intended for use as both as orders and observations despite having a more result-oriented name. Furthermore, as a matter of good clinical practice, most laboratories perform susceptibility testing on any significant isolate on a reflex basis. So there is no need for codes that say “culture and sensitivity” because it is implied. Thus, an order for:17928-3 Bacteria identified in Blood by Aerobe culturewould likely trigger several workflow steps, including bottle blood culture, bacteria isolation, identification, and antimicrobial susceptibility testing.

45Note At the current time, a single code for a routine or organism-specific culture is recommended for reporting the results of the bottle culture, bacterial isolation, and identification. Historically, all of these steps have been included in the laboratory workflow under the “culture” umbrella, and individual results for each step have not been reported to or stored in the patient’s record. Susceptibility testing would be reported with separate susceptibility terms as described in Section 3.5. LOINC names for Methods of staining a sample/material directly (where many descriptive observations are possible) include:Microscopic observation:Prid:Pt:XXX:Nom:Gram stainMicroscopic observation:Prid:Pt:XXX:Nom:Dry mountMicroscopic observation:Prid:Pt:XXX:Nom:India ink preparationMicroscopic observation:Prid:Pt:XXX:Nom:Trichrome stainMicroscopic observation:Prid:Pt:XXX:Nom:Giemsa stainNames for results of staining procedures performed on organisms that are growing in culture will use Isolate as the System (sample type). For example:Fungus identified:Prid:Pt:Isolate:Nom:Fungal subtypingNames for organism-specific cultures:Brucella sp identified:Prid:Pt:Bld:Nom:Organism specific cultureBordetella pertussis:PrThr:Pt:Thrt:Ord:Organism specific cultureChlamydia sp identified:Prid:Pt:Gen:Nom:Organism specific cultureLegionella sp identified:Prid:Pt:Sputum:Nom:Organism specific cultureNote if a test applies to a specific species of organism, the Component should include the genus AND species (at least). If the measure applies to a series of species in the same family the string “sp” must be included. If it applies to as subgroup of the genus, then that subgroup should be named.Names for Method for general class of organism:Fungus identified:Prid:Pt:Wound:Nom:CultureBacteria identified:Prid:Pt:CSF:Nom:CultureAgain, the Result Value of these tests would be either organism names or other statements of culture outcome. The table below contains valid values of the culture result from the HL7 OBX segment:Table 15: Example Culture ResultsNo growthGram-positive cocci

46Small Gram negative rodEscherichia coliNormal floraCandida albicans3.4.2 Properties for culture termsPresence or Identity (Prid) as a Property should be used when the value of a test can identify one set of alternative infectious agents. If the culture is for herpes virus and the culture can have results of herpes virus 1, herpes virus 2, etc., then Prid is the right Property. If the culture is for herpes virus and the answer is positive/negative or yes/no, then the Property should be presence (PrThr) and the Scale ordinal (Ord).3.4.3 Microorganism identification based on nucleic acid targetsPCR-based testing for the presence of microorganisms is becoming more common. Early on, we received requests for and created codes with Components such as Acinetobacter baumannii DNA or Influenza virus RNA. More recently, we have received requests for tests that detect bacteria, viruses, and other pathogens based on a specific genetic target. Thus, LOINC now contains terms with more specific Components such as Clostridium difficile toxin A+B (tcdA+tcdB) genes and Zika virus envelope (E) gene.As genetic testing continues to evolve, distinguishing the specific analyte (i.e. the genetic target) will be important for understanding the differences between tests, interpreting the results, and guiding further testing. Therefore, we will continue to create new LOINC codes that specify the gene targets, and ask requesters of new LOINC codes to supply this information. This specificity is important for bacterial identification, but also for other pathogens.3.5 Antimicrobial susceptibilities The drug susceptibility tests are grouped together in the LOINC database under the Class ABXBACT. Various agencies, including the FDA and CLSI in the U.S. and EUCAST in Europe, publish guidelines for determining susceptibility of different organisms to different antimicrobials.In LOINC, antimicrobial susceptibility tests are named according to the generic name of the drug tested and the methodology used in testing, with Property of susceptibility (Susc), and with Scale of quantitative (Qn), ordinal (Ord), or OrdQn. Thus, appropriate names would be:Ampicillin:Susc:Pt:Isolate:OrdQn:MICAmpicillin:Susc:Pt:Isolate:OrdQn:Agar diffusionTicarcillin+Clavulanate:Susc:Pt:Isolate:Qn:MLCTable 16 lists Methods in drug-susceptibility tests.Table 16: Drug Susceptibility MethodsMethodDescriptionAgar diffusionBacterial sensitivity via agar diffusion (Kirby-Bauer)MICMinimum inhibitory concentration

47MLCMinimum lethal concentrationSBTSerum bactericidal titerGradient stripSusceptible by E-Test or gradient strip methodMethodless codes also exist for each antimicrobial agent.3.5.1 Susceptibility thresholds based on type of infection (“Breakpoints”)In most cases, susceptibility thresholds are the same for a given organism+antibiotic combination regardless of infection site or route of antibiotic administration. However, for some antibiotic+organism combinations, the threshold (“breakpoint”) varies based on route of administration and/or type of infection, including meningitis, pneumonia, and urinary tract infection. These are two independent parameters: there are cases where one antibiotic could have multiple different breakpoints depending on the combination of route and type of infection, and others where one antibiotic will have a single breakpoint regardless of route and type of infection. For example, depending on whether or not the patient has suspected meningitis there are two different breakpoints for parenteral penicillin. But, there is a single breakpoint for vancomycin. The susceptibility test itself is carried out exactly the same way regardless of the breakpoint. It is only for the final step of assigning a susceptibility result that the specific breakpoint becomes important. These data are published by the same agencies (FDA, CLSI, EUCAST) that publish the common susceptibility thresholds.Prior to the 2.58 LOINC release, we specified that the susceptibility threshold was based on a meningitis breakpoint in the Component, e.g., Cefepime.meningitis. However, the concept really identifies an antimicrobial susceptibility result for a patient with suspected meningitis rather than a susceptibility result for a meningitis form of the antibiotic. Therefore, as of LOINC 2.58, we moved “meningitis” from the Component to the System: Isolate.meningitis. In upcoming releases, we will also be adding codes with the Systems Isolate.pneumonia and Isolate.UTI.Note that Isolate.meningitis (or “.pneumonia”, “.UTI”) indicates that the particular susceptibility result being reported is for an antibiotic that has a meningitis breakpoint and that the patient is suspected to have meningitis. This does not necessarily mean that a particular patient has meningitis. For the same patient with suspected meningitis, the result for an antibiotic that does not have a published meningitis breakpoint will be reported using a code with Isolate as the System.3.5.2 Genotypic resistance testing and predicted susceptibilityGenotypic resistance testing is done to look for genes or gene mutations that confer resistance to a drug or class of drugs. The subtle difference between phenotypic susceptibility and genotypic resistance testing is that susceptibility testing is used to determine whether or not a particular organism’s growth is actually inhibited in the presence of an antimicrobial, while testing for resistance mechanisms or genes is used to determine whether or not such genes or mutations are present and to predict whether the organism will be inhibited in the presence of a particular antimicrobial.Various Methods are available to test for the genetic information (e.g., specific resistance genes or nucleotide alterations in native genes) that encodes resistance mechanisms, including Probe.amp.tar, Non-probe.amp.tar, and Sequencing. Until 2018, LOINC bacterial genotypic susceptibility testing terms used the specific Methods named above; however, as approved by the Laboratory LOINC Committee in June 2018, moving forward we are recommending using the Molgen Method for all bacterial molecular resistance testing to obviate the need to create different terms for different molecular Methods (Probe.amp.tar, Sequencing, etc.). New terms will be created with the Method Molgen, and terms that were previously created with a Method other than Molgen will be reviewed and either updated to Molgen if not duplicative or the Status will be changed to Discouraged.

48Historically, susceptibility testing was always phenotypic; it was always performed on an Isolate, which is a microorganism from a patient specimen that is grown and isolated on culture media. However, with new molecular techniques, genotypic testing can be performed directly on patient specimens without the pre-step of isolating the organism. Rather than create separate terms for every possible patient specimen that can be tested, the Laboratory LOINC Committee approved an approach in June 2018 to create single terms for each resistance gene or resistance-conferring mutation with the System Isolate/Specimen. These terms will represent assays that can be done using a traditional isolated colony or on a direct specimen. This approach does NOT imply that every manufacturer’s genotypic assay is approved for testing on an isolate or any type of specimen. Existing terms with Isolate or other specific specimens as the System will be reviewed and either updated to the same model if not duplicative or the Status will be changed to Discouraged. LOINC terms that represent the predicted susceptibility of an organism to a particular antimicrobial based on the presence or absence of resistance genes or resistance-conferring mutations in native genes will contain the drug name or class in the Component, Isolate/Specimen as the System, and Genotyping as the Method. This model was also approved by the Laboratory LOINC Committee in June 2018.3.6 Cell countsQuantitative counts of various entities and cells in blood, urine, CSF, and other body fluids may be performed and reported in one of three ways. Cell counts in blood are often reported as absolute counts per unit volume (Property number concentration, NCnc), or percent of a general cell type, e.g., percent eosinophils, (Property number fraction, NFr). Blood cells are usually reported in such a manner, via either a manual or automated count method. Counts on urine and other body fluids can also be done as direct counts and reported as NCnc or NFr. However, they are more often reported as the number of entities or cells per microscopic high power or low power field, e.g., 5-10 cells per high power field. These are really numbers per area (Property Naric). For example, the number of erythrocytes casts per low power field would be reported as:Erythrocyte casts:Naric:Pt:Urine sed:Qn:Microscopy.light.LPFNote that even though the values are reported as a range, the Scale is still quantitative (Qn), because the values can be related through a ratio. We use HPF or LPF to identify high power and low power fields respectively. Large entities (such as casts) are usually reported per low power fields, smaller entities per high power fields.One other way such entities are reported is as a pure ordinal, e.g., none, few, moderate, loaded. These would be specified as arbitrary concentration (ACnc) Properties with ordinal (Ord) Scale, for example:Erythrocytes:ACnc:Pt:Semen:Ord:Microscopy.light3.7 Skin tests These follow the pattern of a challenge test. For a TB skin test it would be:Tuberculosis reaction wheal^3D post 25 TU ID:Diam:Pt:Skin:QnWhere TU means tuberculin units, ID means intradermal, Diam indicates a measure of the diameter of the wheal and so on.

493.8 Toxicology – Drug of abuse screening and confirmationMany kinds of test methods are used in toxicology:Screening tests include HPLC, EIA, TLC, RIA, GC, and GCMS (rarely).Confirmation tests are GCMS, LCMS, GC, and HPLC.Table 17: Drug of Abuse MethodsAbbr.DescriptionHPLChigh pressure liquid chromatographyTLCthin layer chromatographyGCgas chromatographyEIAenzyme immunoassayRIARadioimmunoassayGCMSgas chromatography/mass spectrometryLCMSliquid chromatography/mass spectrometryMany laboratories use GCMS to signal that the test is a confirmation of a previous screening test, but other methods are also used to confirm, and a given method can be used to screen or to confirm a test. However, it is important that two different methods be used for screen and for confirm and that they both be applied with techniques appropriate to the mode (screen or confirm). So the LOINC committee has determined it is better to distinguish the screening from the confirming procedure by the use of the words screen or confirm, in the Method part of the name, rather than by naming a specific method. Hence LOINC will distinguish toxicology Method by Screen and Confirm but not by particular methods.Toxicology tests can also be performed on a group of drugs/substances or on individual drugs/metabolites/substances. We will develop LOINC names and codes for both categories: groups of analytes, e.g., “barbiturates”, and individual analytes, e.g., “phenobarbital.”Group test results are usually reported as ordinal (present /absent) but can also be reported as mass concentrations when the numerator is the total mass of the detectable substances in the group. Group tests at the screening level may also be followed by a confirmation at the group level or by confirms of the individual drug/substance tests at the confirmatory level. Individual drugs/substances may be reported as present/absent (Ord) or as mass (or substance) concentrations (Qn).When individual drugs/substances are reported ordinally, the reporting threshold (the threshold at which a test level is considered positive) may also be reported as a separate “result.” Thus we have separate LOINC codes to report the cutoff used for defining a positive or negative value.3.8.1 Toxicology drug groupsGeneral principles: for each “group” of drugs (amphetamines, benzodiazepines, opiates, etc.) we will define the following kinds of LOINC observations:3.8.1.1 Screen for a group of drugs/ toxic substancesTerms representing screening for the group as a whole:“X”:PrThr:Pt:Ord:{System}:Screen

50Example answers: present/absentFor example, Amphetamines:PrThr:Pt:Urine:Ord:Screen Answer: presentTerms to identify the set of drugs/substances screened for by the group test. Here the answer will be a list of discrete drug/substance names or codes:“X” tested for:Prid:Pt:{System}:Nom:Screen Example answers: individual drugs that this screening test could detect, from a fixed listFor example, Amphetamines tested for:Prid:Pt:Urine:Nom:Screen Answer: amphetamine, methamphetamine, dextroamphetamine, levoamphetamine, pseudoephedrine3.8.1.2 Identify the drugs or substances screened for (and perhaps other information) as narrativeTerms of this format carry answers that are reported as a “glob” of narrative text. When a screen is reported as negative, confirmatory testing is not performed. When a screening test is reported as positive, the result must be confirmed by an independent testing method.“X” tested for:Prid:Pt:{System}:Nar:Screen Example answers: individual drugs that this screening test could detect, reported as a “blob” of text or canned comment.For example, Amphetamines tested for:Prid:Pt:Urine:Nar:Screen Answer: The EMIT urine screen for amphetamines detects amphetamine, methamphetamine, dextroamphetamine, levoamphetamine as indications of methamphetamine abuse. It is also reactive with a component present in over-the-counter nasal decongestant inhalers, and a positive result must be confirmed by a quantitative method that rules out the non-abuse situation.3.8.1.3 Confirmatory testing for the presence of one or more members of the group represented as a single observation“X”:PrThr:Pt:{System}:Ord:Confirm Example answers: present/absentFor example, Amphetamines:PrThr:Pt:Urine:Ord:Confirm Answer: present3.8.1.4 List of the actual drug/substances confirmed“X” positive:Prid:Pt:{System}:Nom:Confirm Example answers: a list of analytes detected

51For example,Amphetamines positive:Prid:Pt:Urine:Nom:Confirm Answer: dextroamphetamine, methamphetamine3.8.1.5 Confirmatory testing reported as a set of observations (more common)More commonly, confirmatory testing is reported as a set of observations that each report the presence (or quantitative amount detected) of an analyte in the group.“X”:PrThr:Pt:{System}:Ord:Confirm Example answers: present/absentor“X”:MCnc:Pt:{System}:Qn:Confirm Example answers: a quantitative amountFor example,Amphetamine:PrThr:Pt:Urine:Ord:Confirm Dextroamphetamine:PrThr:Pt:Urine:Ord:Confirm Methamphetamine:PrThr:Pt:Urine:Ord:Confirm Levomethamphetamine:PrThr:Pt:Urine:Ord:Confirm Example answers: present/absent3.8.2 CutoffsThe cutoff levels for screens and confirms of a given substance or group of substances will usually differ. There are three ways to indicate specific cutoffs in LOINC.3.8.2.1 We provide separate LOINC terms for reporting the cutoff levels of a number of commonly abused substances and substance groups“X” cutoff:MCnc:Pt:Urine:Qn:Screen “X” cutoff:MCnc:Pt:Urine:Qn:ConfirmFor example, Amphetamines cutoff:MCnc:Pt:Urine:Qn:Screen Answer: 1000 ng/mlMethamphetamine cutoff:MCnc:Pt:Urine:Qn:Confirm Answer: 500 ng/ml3.8.2.2 Two general cutoff terms, one for screen and one for confirm, can be applied to any substance whether or not a pre-coordinated term exists“X” cutoff:MCnc:Pt:{System}:Qn:Screen “X” cutoff:MCnc:Pt:{System}:Qn:Confirm

523.8.2.3 For commonly used cutoffs, such as those mandated by regulatory agencies, we provide pre-coordinated terms for reporting a “present/absent” result with the cutoff specified in the Method field“X”:PrThr:Pt:{System}:Ord:Screen>“N” “X”:PrThr:Pt:{System}:Ord:Confirm>“N”For example,Amphetamines:PrThr:Pt:Urine:Ord:Screen>1000 ng/mL Answer: not detected3.8.3 Reporting the Method used for screen and confirmWe provide terms for reporting the Method used for screen and confirm tests:“X” screen method:Prid:Pt:{System}:Nom:* “X” confirm method:Prid:Pt:{System}:Nom:*These would normally be reported in conjunction with terms reporting levels and possibly cutoffs, as in the following example:Amphetamines:PrThr:Pt:Urine:Ord:Confirm Answer: positiveAmphetamines cutoff:MCnc:Pt:Urine:Qn:Screen Answer: 1000 ng/mlAmphetamines screen method:Prid:Pt:Urine:Nom:* Answer: EIAAmphetamines positive:Prid:Pt:Urine:Nom:Confirm Answer: amphetamine, methamphetamineAmphetamine cutoff:MCnc:Pt:Urine:Qn:Confirm Answer: 500 ng/mlMethamphetamine cutoff:MCnc:Pt:Urine:Qn:Confirm Answer: 500 ng/mlAmphetamines confirm method:Prid:Pt:Urine:Nom:* Answer: GC/MS3.8.4 Individual drug/metabolite test resultsIndividual substances are typically reported as screens (ordinal), confirms (ordinal) or confirms (quantitative – usually mass or substance concentrations), though some labs also report as screen (quantitative). Ordinal terms for reporting individual substances should always specify a Method of screen or confirm.Group test screens may be confirmed by group confirms (as described above) or by individual confirms (Either ordinal or quantitative-depending upon the laboratory’s preference)

533.8.4.1 Individual test screen (ordinal)Methamphetamine:PrThr:Pt:Urine:Ord:Screen Example answer: present3.8.4.2 Individual test screen (quantitative)Methadone:MCnc:Pt:Urine:Qn:Screen Example answer: 150 ng/ml3.8.4.3 Individual test confirm (ordinal)Methamphetamine:PrThr:Pt:Urine:Ord:Confirm Example answer: present3.8.4.4 Individual test confirm (quantitative)Methamphetamine:MCnc:Pt:Urine:Qn:Confirm Example answer: 250 ng/mlIndividual tests may also be reported as simple quantitative (without confirm or screen), as is the case for therapeutic drug level monitoring.3.8.4.5 Individual substance measured quantitatively; screen/confirm is not relevantDigoxin:MCnc:Pt:Ser/Plas:Qn Example answer: 1.2 ng/ml3.8.5 Naming issuesFor confirms, you would always be looking for specific analytes. For example, you would never look for tetrahydrocannabinol, but would look for delta-9-tetrahydrocannabinol, 11-hydroxycannabinol, etc.3.8.6 SummaryFor each “group” LOINC defines the following set of terms:“Analyte group”:PrThr:Pt:Urine:Ord:Screen “Analyte group”:PrThr:Pt:Urine:Ord:Confirm “Analyte group”:MCnc:Pt:Urine:Qn:Confirm “Analyte group” tested for:Prid:Pt:Urine:Nom:Screen “Analyte group” tested for:Prid:Pt:Urine:Nar:Screen “Analyte group” positive:Prid:Pt:Urine:Nom:Confirm “Analyte group” screen method:Prid:Pt:Urine:Nom:* “Analyte group” confirm method:Prid:Pt:Urine:Nom:*For each individual analyte LOINC now defines the following set of terms:Analyte:PrThr:Pt:Urine:Ord:Screen Analyte:PrThr:Pt:Urine:Ord:Confirm

54Analyte:MCnc:Pt:Urine:Qn:Confirm Analyte:MCnc:Pt:Urine:Qn Analyte cutoff:MCnc:Pt:Urine:Qn:Screen Analyte cutoff:MCnc:Pt:Urine:Qn:Confirm3.9 Molecular genetics LOINC naming3.9.1 IntroductionMolecular pathology testing can be used for many purposes. In infectious disease testing to identify organisms and mutations in organisms; in genetic analysis to identify mutations including substitutions, deletions/insertions, frame shifts and trinucleotide repeats; to identify specific chromosomal translocation and clonality in leukemia and lymphomas; to identify various tumor associated genes and gene deletions; in paternity testing to determine the probability that a person is the parent of a child; and in forensic testing to determine the probability that a criminal is associated with genetic material he/she left as evidence.25LOINC term names follow the recommendations and nomenclature of other standards. As molecular genetic testing expands, we are evolving our naming conventions. Existing terms are being reviewed for compatibility with current naming conventions. An overall description of LOINC’s approach to naming molecular genetics tests can be found in the Deckard et al26 paper.3.9.2 Brief review of molecular genetics terminologyFor clarity, here we provide a brief introduction to some key genetics terminology. DNA consists of a series of nucleotides, nucleotides encode amino acids, and a string of amino acids forms a protein. There are four types of nucleotides (adenine, guanine, cytosine and thymine), and a sequence of three nucleotides that codes for one amino acid is called a codon. Codons are numbered from the first codon participating in the protein (in humans the codon for Methionine) starting with codon number 1. Locus refers to a specific DNA (or RNA) codon or the corresponding amino acid produced by this codon.The string of DNA that codes for a protein is usually interrupted by DNA segments called introns, which do not contribute to the protein definition. The coding sequences of DNA between the introns are called exons. Linked together, the exons provide the instructions for creating the specific protein. Exons may be numbered e.g., exon 1, exon 2, etc. Exon numbers sometimes appear in the names of DNA mutations, but for a number of reasons, identifying codon locations relative to an exon is unreliable and we will try to avoid such nomenclature when possible in LOINC names.The term “mutation” is usually applied to a genetic variant that causes a functional change in the gene and results in disease. Genetic changes that occur during the life of the patient such as tumor mutation are called somatic and those that are inherited are referred to as germ line. The nature of the specimen and the testing usually distinguishes these two, so it is not necessary to include this distinction in the test names.Alleles refer to different forms of a gene and are distinguished at the phenotype level. The term allele is usually applied to a genetic variant that does not cause a disease.25 Antonarakis, SE, and the Nomenclature Working Group. Recommendations for a nomenclature system for human gene mutations. Human Mutation 1998;11:1-3. [PubMed: 9450896].26 Deckard J, McDonald CJ, Vreeman DJ. Supporting interoperability of genetic data with LOINC. J Am Med Inform Assoc. 2015 May;22(3):621-7. [PubMed: 25656513.]

553.9.3 Background on molecular genetics testing methodsThe main laboratory methods used are Southern Blot, which applies hybridization to selected DNA “chopped up” by restriction enzymes, Northern Blot, which applies hybridization to all cellular RNA (which comes naturally in smaller segments), and Restriction Fragment Length Polymorphism (RFLP). RFLP depends on the Variable Number of Tandem Repeats (VNTR), which are normal, but specific variants of each person’s DNA. Southern Blot may be combined with RFLP to target mutations whose exact gene molecular chemistry is not known. For completeness sake, we mention Western Blot, which applies an analogous blot method to protein analysis.In situ hybridization is a method that applies probes to intact tissue. The cellular patterns of the homologies can then be read microscopically. There are a variety of methods for detecting such in situ probes. One popular method is Fluorescent In-Situ Hybridization (FISH). This technique is analogous to an immune stain except that the molecular binding is based on DNA/RNA homologies instead of antigen-antibody binding.DNA chips provide a radical new way to identify DNA and RNA sequences. In the patented AFYMETRIX® technique, the nucleoside chains are grown using lithography-like methods. Target DNA is tagged with a detector and “washed” over the chip in steps. The locations of the tags on the chip identify the DNA (RNA) in the sample.Identity testing is used to identify relationships among people and has special complexity. In paternity testing, it can be helpful to have DNA from the child, the putative father and the mother when possible to distinguish the alleles that come from the father.Forensic testing has special requirements of stringency and often mixes blood antigen testing with RFLP testing. The results are usually reported as a probability.3.9.4 General molecular genetics naming rulesLOINC’s approach to naming tests makes use of established conventions. For naming genetic tests that target specific genetic variations, LOINC uses the Human Genome Organization (HUGO) Gene Nomenclature Committee’s (HGNC) terminology to name the gene(s) and Human Genome Variation Society’s (HGVS) syntax to name the variation(s) of interest.HGVS provides seven types of prefixes to identify the difference types of reference sequences used in naming gene defects as described in Table 18. As of LOINC release 2.66, LOINC has terms for the first four (p., c., g., m.).Table 18: Four types of nomenclatures for identifying the location of a genetic defectDesignationExplanationpProtein reference sequence based on amino acid (codon) counting.cCoding reference sequence based on a transcript that encodes a protein and therefore excludes introns. Since three nucleotides = one codon, these will produce numbers 3x as large as those based on the protein.gGenomic reference sequence based on counting from the first nucleotide in the DNA for the gene of interest, as it exists natively in the chromosome with introns included.mMitochondrial reference sequence based on counting from the first nucleotide in the full mitochondrial DNA sequence.nNon-coding reference sequence based on a transcript that does not encode a protein.oCircular genomic reference sequence, for example, for plasmids or certain viruses.rRNA reference sequence.The HGVS recommendations have evolved over time. In our early approach, we used the extant protein-based naming convention to get the following name for the commonest mutation causing cystic fibrosis:

56CFTR gene.p.F508del:PrThr:Pt:Bld/Tiss:Ord:MolgenFor clarity’s sake, HGVS now prefers the three letter amino acid abbreviations over the single letter amino acid abbreviations we used in the above example.We embrace the HGVS naming style for naming mutations at the amino acid level, but the world has not been consistently quick to adopt it. The old style, perhaps because of its brevity, persists. As we update existing codes to harmonize with current HGVS guidelines, we will make it easy for users to find our test names by including the old style as synonyms for the new style. Under the current HGVS rules, the above name would be:CFTR gene.p.Phe508del:PrThr:Pt:Bld/Tiss:Ord:MolgenWhere we still report variants at the amino acid level, we use the nomenclature for human gene mutations proposed by Beaudet27 in the Component or in the LOINC Answer when the mutation is reported as an answer. A list of single and three letter amino acid codes are given in Table 19.Table 19: List of single letter amino acid codesAmino Acid1-Letter Symbol3-Letter SymbolAlanineAAlaArginineRArgAsparagineNAsnAspartic acidDAspCysteineCCysGlutamic acidEGluGlutamineQGlnPyroglutamic acidpQpGluGlycineGGlyHistidineHHisHydroxyproline, 4(R)-L-OHypIsoleucineIIleLeucineLLeuLysineKLysMethionineMMetPhenylalanineFPheProlinePProSerineSSerThreonineTThrTryptophanWTrpTyrosineYTyrValineVValUnknownXHGVS has made other changes in naming style. Overall they now prefer describing the variant at the coding DNA level as nucleotide changes rather than at the protein level as amino acid changes. The above cystic fibrosis mutation would have the following coding DNA-based name:27 Beaudet AL, Tsui LC. A suggested nomenclature for designating mutations. Human Mutation 1993;2 (4) :245-248. [PubMed: 8401532].

57CFTR gene.c.1521_1523del:PrThr:Pt:Bld/Tiss:Ord:MolgenFor the nucleotide changes, they have adjusted the syntax for representing a change from one nucleotide string to another as # String1>String2 rather than String1 # String2, where # is an integer representing the nucleotide position of the variation.Another common cause of cystic fibrosis is a mutation that at the amino acid level would be named p.Gly551Asp with the new protein based naming convention, c.G1652A with the old DNA naming convention and c.1652G>A with the new coding DNA naming convention. (Realize, of course, that more than one nucleotide-level variation name can correspond to a single amino acid variation name.)If clear guidelines are not in place for a given variant when a LOINC code is created, the familiar or common variant name may be used. LOINC will resort to using the disease name only when the gene has no name and/or the genetic defect is not yet fully specified. We will include the genetic disease name in the RELATEDNAMES2 field of the database when the disease name is not part of the Component. This allows users to easily find the LOINC term by the disease name as well.3.9.4.1 Specimens in molecular geneticsBlood is the most common specimen for molecular pathology studies. Leukocytes, bone marrow, tumors, products of conception and forensic specimens also contain DNA and are important specimens. The System (specimen) used in the LOINC name for genetic testing will usually be Bld/Tiss since the distinction between these two specimens is rarely important to the result of a molecular pathology test. We have split this further to accommodate fetal specimens (Tiss^fetus). Other specimens include amniotic fluid, CVS, bone marrow, fixed tissue, and CSF.3.9.4.2 Methods in molecular geneticsIn general, we do not create separate variables for each kind of molecular genetics method (e.g., Southern Blot Northern Blot, PCR, restriction fragment length polymorphism (RFLP)) because the different methods do not provide significantly different results. Moreover, there are a plethora of minor method variants, and we would not be able to keep up with their proliferation. Therefore, instead we use a generic Method of Molgen (for molecular genetics method) to indicate that a result of the analysis is based on a molecular genetics method rather than some chemical or antigen method.However, when results for a given molecular pathology technique are significantly different, we will distinguish the method. Examples of specific molecular pathology Methods in LOINC include fluorescent in situ hybridization (FISH), sequencing, multiplex ligation probe amplification (MLPA), and microarray comparative genomic hybridization (arrCGH).3.9.4.3 Narrative and document-level reporting in molecular geneticsBulk narrative reports in molecular pathology are often used to provide results for mutation analyses, without reporting any discrete coded answers. We discourage the use of this approach because it is not useful for automated analyses. Since these kinds of results often include some structured elements, we will use the Property Find and Scale Doc beginning with version 2.54. The Scale of Doc represents a collection of information (e.g. results contained in a report) that are either structured or unstructured. To assist with structured reporting, we will attach to these terms specific associated observations that could be used to send data in a structured format. With this approach, labs will still have the flexibility to send text reports. However, we encourage them to also report key data as structured results using the associated observation variables so that it is more easily understood by computers. We plan to use this model for newly created terms for molecular pathology tests and

58are contemplating the best approach for transitioning existing terms to this format over time.3.9.4.4 Inferred phenotype and genotypeBeginning in version 2.66, we have LOINC terms for genotype and phenotype results that are derived from their respective phenotype or genotype analysis. For such concepts we include the word “inferred” in the Component. One example is a blood banking panel that is used to report whether or not an RBC antigen is expected to be present in a patient or donor sample based on molecular analysis of the corresponding gene, such as the presence of K Ag based on analysis of the KEL gene, for which the Component is K Ag inferred phenotype. The reverse example is an assay that reports the genotype for the APOL1 gene based on analysis of apolipoprotein L1 isoforms; for this term, the Component is APOL1 inferred genotype.3.9.5 Infectious diseasesFor information about molecular genetics in the field of infectious diseases, see Section 3.4.3 – Microorganism identification based on nucleic acid targets.3.9.6 Genetic conditions3.9.6.1 Diagnostic assays for mutation analysisWe currently have at least four different styles for mutation analyses in LOINC:1. Single mutation analysis: Diagnostic assays for the detection of a specific mutation or variant2. Targeted mutation analysis: Diagnostic assays for a fixed set of the most common or important mutations3. Known mutation analysis: Diagnostic assays for one or more mutations that have been previously identified in an affected family member4. Full gene mutation analysis: Diagnostic assays usually done by sequencing of the entire coding region of a gene3.9.6.1.1 Diagnostic assays for the detection of a specific mutation or variantWhen looking for one mutation, use LOINC’s single mutation style of gene name followed by the specification of the nomenclature (p, g, c, or m) and the mutation name. A dot will separate the gene name and the mutation identifier:<gene name> gene.<mutation nomenclature>.<mutation and its location>For example, Factor V Leiden mutation would be represented as F5 gene.p.R506Q. Where “F5” identifies the gene, “gene” is a fixed part, “p” identifies the kind of mutation nomenclature (protein) and “R506Q” indicates that the amino acid arginine (R) is replaced by glutamine (Q) (see Table 19) at codon #506.Some examples of fully specified LOINC names for tests of specific mutation are:F5 gene.p.R506Q:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonyms: Factor V Leiden, Factor V resistance, APC resistance gene

59HFE gene.p.C282Y:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonyms: HLA-H gene, hemochromatosis geneCFTR gene.p.F508 del:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonyms: Cystic Fibrosis Transmembrane RegulatorAs mentioned above, HGVS now recommends the three letter amino acid abbreviations over the single letter amino acid abbreviations. As existing codes are updated, we will add synonyms for the old style to make it easy for users to find our test names.One type of testing procedure identifies a single mutation using two DNA probes: one for the normal locus and the other for the abnormal locus. When only the normal probe reacts, the laboratory reports “no mutation” or “wild type”. When both the normal and mutation probes react, the laboratory reports “heterozygous”. When only the mutation probe reacts it reports “homozygous”. Consequently, such single mutation testing produces one of three ordinal “answers”:1. no mutation (wild type)2. heterozygous mutation (the mutation found in one gene)3. homozygous mutation (the mutation was found in both genes in the gene pair)Specific testing such as this is only possible when the molecular pathology of the gene is very well known and only one defect is being reported.Both document-level (Scale is Doc) and ordinal (Scale is Ord) codes are available in the LOINC database for single variant tests. In cases where more than one variant is tested, a nominal (Nom) Scale will be used. As mentioned above, we encourage the use of document-level codes for the order and overall result report, which can be used in conjunction with additional LOINC codes for reporting the discrete results.Results for specific mutations or variants may also be reported as two separate observations: one observation reports the kind of mutation (allele) found in the first chromosome and another for reporting the kind of mutation for the paired chromosome. In this case, the identity of the allele is reported in the answer. For example:APOE gene allele 1:Prid:Pt:Bld/Tiss:Nom:Molgen Answers: E2, E3, or E4APOE gene allele 2:Prid:Pt:Bld/Tiss:Nom:Molgen Answers: E2, E3, or E43.9.6.1.2 Targeted mutation analysisLOINC’s approach to represent gene mutation analysis for many genetic variations within one or more genes has had the following form:<gene or disease name> targeted gene mutation analysis:Find:Pt:Bld/Tiss:Doc:Molgen For example:CFTR gene mutation analysis:Find:Pt:Bld/Tiss:Doc:Molgen Synonyms: Cystic fibrosis transmembrane regulatorBRCA1 gene mutation analysis:Find:Pt:Bld/Tiss:Doc:Molgen Synonyms: breast cancer risk gene

60For each such targeted mutation analysis, we recommend reporting the mutations that were tested using an additional LOINC code, such as LOINC 36908-2 (Gene mutations tested for) or gene-specific companion LOINC observation codes with the words “mutations tested for”:<Gene or disease name> gene mutations tested for:Prid:Pt:Bld/Tiss:Nom:Molgen For example:CFTR gene mutations tested for:Prid:Pt:Bld/Tiss:Nom:Molgen Example answers: “Delta F508”, “G542X”, “R553X”, “W1282X”, “N1303K”, etc.The additional LOINC code is needed for reporting the mutation(s) that could have been found in a given analysis so that clinicians can know what was looked for when no abnormalities were found.The above gene mutation analysis terms could be used for ordering or reporting the results of a given targeted mutation analysis. Both document-level (Scale is Doc) and nominal (Scale is Nom) codes are available in the LOINC database. As mentioned above, we encourage the use of document-level codes for the order and overall result report, which can be used in conjunction with additional LOINC codes for reporting the discrete results. Nominal results for such an analyses could be: 1) no pathologic mutations found or 2) a list of individual mutations/variations found. When reporting discrete mutations as results, we propose using the HGVS nomenclature and including (in parentheses) the historic versions of the mutation names when such names exist.3.9.6.1.3 Known mutation analysisThe first two approaches are commonly called “targeted” mutation analyses, or looking for specific mutations within a given gene. Labs may offer testing for both targeted mutation analysis and analysis for known familial mutations. Known familial mutations are those previously identified within an affected family member. To distinguish these testing approaches, LOINC further defines testing for known familial mutations:<Gene name> gene mutation analysis limited to known familial mutations:Find:Pt:Bld/Tiss:Doc:Molgen For example:TNFRSF13B gene mutation analysis limited to known familial mutations:Find:Pt:Bld/Tiss:Doc:MolgenSince testing may involve more than one known mutation, especially for autosomal recessive conditions, LOINC uses the plural form of mutations in the Component. However, these terms also refer to testing for only one known familial mutation.3.9.6.1.4 Full gene mutation analysisTo describe mutation analysis by sequencing of the entire coding region of the gene, we use:TNFRSF13B gene full mutation analysis:Find:Pt:Bld/Tiss:Doc:SequencingHere, we include the Method of sequencing since this is a technique commonly used to identify mutations with the entire coding region of a gene.3.9.6.2 Diagnostic assays for large deletions and/or duplications

61Detection of larger (>50 bp) genomic duplications or deletions is done by various techniques, including multiplex ligation-dependent probe amplifications (MLPA) and array-based comparative genomic hybridization (arrCGH). MLPA and aarCGH techniques detect gene dosage. To describe testing for large deletions and/or duplications (insertions) within a gene, we use:LDLR gene deletion+duplication:Prid:Pt:Bld/Tiss:Nar:MLPAIn this case, we specify the Method of multiplex ligation-dependent probe amplification (MLPA). MLPA is a common technique used to detect gene dosage of genomic deletions and duplications (e.g. one or more entire exons) and determine gene copy number.3.9.6.3 Trinucleotide repeatsA number of diseases, most of which manifest as neurologic disorders are caused by excessive repeats of specific trinucleotides, and the age of onset of the disease is inversely proportional to the number of excess repeats. Examples of these disorders include:• Fragile X syndrome• Huntington disease• Spinocerebellar ataxia (SCA1)We name the Component of these terms by the gene when the gene is well defined or the disease, and the name of the trinucleotide that repeats plus the word repeats.<disease or gene name>.<trinucleotide> repeatsFor example, Huntington disease would be represented as follows:HTT gene.CAG repeatsExamples of some fully specified LOINC names are:FRAXE gene.CGG repeats:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonym: Fragile x syndromeHTT gene.CAG repeats:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonyms: Huntington Disease, It15, HD, Huntington ChoreaSpinocerebellar ataxia genes.CAG repeats:PrThr:Pt:Bld/Tiss:Ord:Molgen DMPK gene.CTG repeats:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonym: Myotonic DystrophyThese are usually reported “not expanded”, “indeterminate” or “expanded”, so the Scale is Ord.When the actual number of trinucleotide repeats is reported, the Property is entitic number (EntNum) and the Scale is quantitative (Qn), and separate results are reported for each allele. Examples include:HTT gene allele 1.CAG repeats:EntNum:Pt:Bld/Tiss:Qn:Molgen HTT gene allele 2.CAG repeats:EntNum:Pt:Bld/Tiss:Qn:MolgenDMPK gene allele 1.CTG repeats:EntNum:Pt:Bld/Tiss:Qn:Molgen DMPK gene allele 2.CTG repeats:EntNum:Pt:Bld/Tiss:Qn:Molgen

623.9.6.4 Hematopathology gene re-arrangementImmune cells have an innate genetic variability due to rearrangement. The unique rearrangement can be used to identify the development of a clone of one cell type as occurs in many lymph cell tumors (e.g., lymphoma). We use the following format to identify clonal excess.Immunoglobulin heavy chain gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Immunoglobulin kappa light chain gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Immunoglobulin lambda light chain gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen TCRB gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Synonym: T cell receptor beta chainTCRD gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Synonym: T cell receptor delta chainTCRG gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Synonym: T cell receptor gamma chainThese would be reported as “clonal” or “not clonal”.3.9.6.5 Chromosomal alterations: translocations, deletions, and inversionsLOINC nomenclature follows the International System for Human Cytogenetic Nomenclature (ISCN) guidelines when describing chromosomal alterations, including translocations, large deletions and inversions. Tests to detect fused genes or transcripts (RNA, cDNA) due to a chromosomal alteration are designated as follows:t(<Chromosome of breakpoint gene 1>;<Chromosome of breakpoint gene 2>)(<Location on chromosome 1>; <Location on chromosome 2)(<gene1>,<gene2>) fusion transcriptFor example:t(9;22)(q34.1;q11)(ABL1,BCR) fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: Philadelphia chromosome, BCR1, chronic myeloid leukemia, CMLt(14;18)(q32;q21.3)(IGH,BCL2) fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: Follicular B cell lymphoma, oncogene B-cell leukemia 2, CLL, chronic lymphatic leukemia, follicular lymphomat(15;17)(q24.1;q21.1)(PML,RARA) fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: RAR, promyelocytic leukemia, myelogenous, retinoic acid receptor, acute promyelocytic leukemia, APLFor chromosomal deletions and inversion,‘t’ above would be replace with ‘del’ or ‘inv’, respectively:del(1)(p32p32)(STIL,TAL1) fusion transcript:PrThr:Pt:Bld/Tiss:Ord:Molgen Synonyms: SCL/TAL1 interrupting locus, T-cell acute lymphoblastic leukemia, ALL, T-ALL, TAL-1 deletionsinv(16)(p13.1;q22.1)(MYH11,CBFB) fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: inversion 16, AML, Acute myeloid leukemiaIn some cases, testing may involve comparing the fused transcript to a control transcript and results may be reported as a number ratio (NRto), log number ratio (LnRto), or relative ratio (RelRto):t(9;22)(q34.1;q11)(ABL1,BCR) fusion transcript/control transcript:NRto:Pt:Bld/Tiss:Ord:Molgen

63t(9;22)(q34.1;q11)(ABL1,BCR) fusion transcript/control transcript:LnRto:Pt:Bld/Tiss:Ord:Molgent(9;22)(q34.1;q11)(ABL1,BCR) b3a2 fusion transcript/control transcript (International Scale):RelRto:Pt:Bld/Tiss:Ord:MolgenTo specify “major” or “minor” breakpoints, we use:t(9;22)(q34.1;q11)(ABL1,BCR) fusion transcript major break points:Arb:Pt:Bld/Tiss:Ord:Molgent(9;22)(q34.1;q11)(ABL1,BCR) fusion transcript minor break points:Arb:Pt:Bld/Tiss:Ord:MolgenTo specify specific breakpoints, we use:t(9;22)(q34.1;q11)(ABL1,BCR) b2a2+b3a2 fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: major breakpoints, p210, e13a2, e14a2t(15;17)(q24.1;q21.1)(PML,RARA) bcr1 fusion transcript:Arb:Pt:Bld/Tiss:Ord:Molgen Synonyms: breakpoint cluster region 1, long formTranslocation terms can also be expressed as a fraction of cells that have the rearrangement versus total cells of interest:Cells.t(9;22)(q34.1;q11)(ABL1,BCR)/Cells.total:NFr:Pt:Bld/Tiss:Qn:Molgen If specific partner genes are not known, we use the pattern:CCND1 gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Synonym: Lymphoma 1BCL2 gene rearrangements:Arb:Pt:Bld/Tiss:Ord:Molgen Synonym: Lymphoma 23.9.7 Identity testingThe identity testers usually look at 4 genetic loci (each locus is polymorphic enough that any one match has a 10% error of being incorrect). The loci are independent so if all 4 probes match (including all exclusions and inclusions) the probability of an erroneously match is .0001 (one out of 10,000). They may use more than four depending upon the degree of confidence required by the circumstances of the testing. The forensic community chooses from a set of about 20 probes.We propose two styles for reporting identity testing: atomic and pre-coordinated definitions.3.9.7.1 Atomic styleThis style uses a series of LOINC names to report the kind of index case, the kind of comparison case, the results of the identity testing, and all of the other separate components of the testing. It includes an observation for reporting the actual probes used, and another observation for reporting the population that the probes assume. The Method will be MOLGEN.IDENTITY.TESTING. For example:DNA probes used:Prid:Pt:Index case^comparison case:Nom:Molgen.identity.testing Population base:Prid:Pt:Probes:Nom:Molgen.identity.testing

64Relationship:Type:Pt:index case:Nom:Molgen.identity.testing Example Answers: child, victim, suspectRelationship:Type:Pt:^comparison case:Nom:Molgen.identity.testing Example Answers: mother, alleged mother, father, alleged father, evidence (external to victim)Confidence of relationship:likelihood:Pt:Index case^comparison case:QN:Molgen.identity.testing Comment: gives the statistical confidence in the conclusionConclusion:Imp:Pt:index case^comparison case:Nar:Molgen.identity.testing Comment: gives a summary statement of the conclusion about identity of relatedness3.9.7.2 Pre-coordinated definitions alternative Some of the above atomic terms (e.g., DNA probes used) could also be reported with the pre-coordinated results.Relationship:likelihood:child^alleged mother:Qn:Molgen.identity.testing Synonym: maternity testing Comment: gives the likelihood that the alleged mother is the mother of the index childRelationship:likelihood:child^alleged father:Qn:Molgen.identity.testing Synonym: paternity testing Comment: gives the likelihood that the alleged father is the father of the index childRelationship:likelihood:victim^suspect:Qn:Molgen.identity.testing Comment: gives the likelihood that the genetic material on the victim is that of the suspectRelationship:likelihood:suspect^victim:Qn:Molgen.identity.testing Comment: gives the likelihood that the genetic material on the suspect is that of the victimIdentity:likelihood:evidence^suspect:Qn:Molgen.identity.testing Comment: gives the likelihood that the genetic material on the evidence is that of the suspectIdentity:likelihood:evidence^victim:Qn:Molgen.identity.testing Comment: gives the likelihood that the genetic material on the evidence is that of the victim3.9.8 Tumor related geneticsUsing the models described in this section, LOINC has terms for many genetic tests relevant to cancer, including tests related to tumor suppressor genes (e.g. BRCA1, BRCA2, and p53), oncogenes (e.g. HER2), and more.3.10 HLA allele and antigen nomenclatureNaming conventions for HLA alleles and antigens are specified by the WHO Nomenclature Committee for Factors of the HLA System. Recommendations for both allele and antigen naming have evolved since the original HLA terms were represented in LOINC. For the LOINC 2.54 release (December 2015), we updated nearly all of the antigen and allele terms to reflect the WHO Nomenclature Committee’s latest recommendations. HLA allele and antigen naming conventions are briefly described below; for more details, see http://hla.alleles.org/.Allele names begin with the “HLA-” prefix and gene name, followed by an asterisk (e.g. “HLA-A* or HLA-DR*”)

65and up to four sets of numbers separated by colons. The first set of digits following the asterisk describes the allele type, which may correspond to the serological antigen number (e.g., “HLA-A*01 corresponds to the antigen HLA-A1). The second set of digits is the subtype number, which is assigned in the order in which the subtype was identified and sequenced. The third and fourth sets of digits describe the specific sequence variations of the subtype, if applicable.Antigen names also begin with the “HLA-“ prefix and specific gene, but antigen names are distinguished from allele names in that the gene name is not followed by an asterisk. For HLA-A, -B, -DQ and -DR, the antigen number immediately follows the gene name, and HLA-C, -D and -DP have a lower case w between the gene name and the antigen number (e.g., HLA-Cw3). The lower case w is used to distinguish the C antigens from complement factors and the D and DP antigens as being identified by cellular techniques rather than serological ones. Most antigen names have one set of digits (the antigen number) following the gene name, but in some cases, if an antigen originally identified as a single antigen was later recognized as being two distinct entities, the original, broader antigen number will follow the specific number in parentheses. For example, HLA-B38(16) and HLA-B39(16).3.11 Allergy testingThe allergy testing industry provides tests for more than 450 different allergens today. Most testing detects IgE antibodies against these allergens. For some allergens testing for IgG and IgA antibodies are available, as well.For LOINC terms that represent allergen testing, the Component is the allergen name plus the type of the antibody (mostly IgE). Most allergens relate to animals, plants or derivatives of such entities. In the past (prior to LOINC version 2.04), we used the common name, rather than the scientific name to identify the allergen. However, this approach led to some duplicate term definitions, because two different companies would name the same allergen differently. It also led to ambiguity because two different species of animal or plant would sometimes have the same common name. As of version 2.04, we corrected these problems. To help reduce the ambiguity we now use the Latin name of the species of the biologic entity that causes the allergy.Some background: First, most allergens can also be identified with a special 2-5 character code assigned by Pharmacia28 that most allergy testing companies reference in their catalog of testing. We used these codes to identify duplicate and ambiguous LOINC allergy test terms. These Pharmacia codes are also included in the related names field of the database. Second, allergen tests are often reported in two styles: a quantitative raw measure and an ordinal (0-6) severity rank (RAST class). LOINC defines separate terms for each of these reporting styles. For example, the two LOINC codes for reporting IgE antibodies to Japanese Millet are:Echinochloa crus-galli Ab.IgE:ACnc:Pt:Ser:QnEchinochloa crus-galli Ab.IgE.RAST class:ACnc:Pt:Ser:OrdThe RAST class is a categorization of the raw measurement based on specific allergy criteria. The specific IgE class result values (0, 1, 2, 3, 4, 5, or 6) are an ordered categorical response rather than a continuous numeric scale, therefore “RAST class” terms have an ordinal (ORD) Scale.Laboratories also test mixtures of allergens to produce one result. An example of how these tests are represented is shown for LOINC 23797-4:(Acer negundo+Quercus alba+Ulmus americana+Populus deltoides+Carya pecan) Ab.IgE:ACnc:Pt:Ser:Ord:Multidisk 28 ImmunoCAP Allergens [Internet]. Uppsala(Sweden): ImmunoCAP; c2006 [updated 2007 November 2; cited 2008 June]. Available from: http://www.phadia.com/en-GB/5/Products/ImmunoCAP-Allergens/

66Related name: tx2There may be more than one type of allergen for each plant. For instance, IgE antibodies can develop towards tree pollen and the fruit of the same tree. Similarly, antibodies exist for grain and for grain pollen. In these cases, the LOINC Component will contain the word POLLEN to distinguish the pollen allergen from the food allergen. For example, the LOINC term for corn (maize) IgE antibody would be:Zea mays Ab.IgE:ACnc:Pt:Ser:Qn Related names: f8; cultivated corn; maizeZea mays pollen Ab.IgE:ACnc:Pt:Ser:Qn Related names: g202: cultivated corn; maize3.11.1 Naming rules for allergensThe Component (Analyte) for an allergen consists of the name of the biologic organism that is the source of the allergen. The formal name will use the Latin taxonomic name e.g. Arachis hypogaea. The Long Common Name will use the common name of that entity, e.g., Peanut, if one exists. In the case of very well specified allergens, the Component will also indicate whether the allergen has a natural source or has been generated via recombinant method by adding the word, native or recombinant, respectively. Different antigens from the same species are distinguished by the addition of a sequence number that roughly reflects when in time they were identified. So you will see names that contain content like the following:• Arachis hypogaea recombinant 1• Arachis hypogaea recombinant 3• Arachis hypogaea native 1• Arachis hypogaea native 3However, as is true in other classes of LOINC, we sometimes embed synonyms within the allergen Analyte name to help users recognize the term by their naming rules. Using the LOINC-wide convention, synonyms are enclosed in parentheses and immediately follow the word or words which they represent. We insert standard acronym names used by most allergen manufacturers as synonyms. These begin with lower case “n” or “r” to distinguish native from recombinant allergens followed by the first 3 letters of the genus (in Latin), a space and the first letter of the species (in Latin). If the first 3 letters of the genus and the first letter of the species are not enough to distinguish between two allergens, the second letter of the species name is added (e.g., Prunus avium recombinant (rPru av) 1). Because the content in the parentheses represents the antigen acronym and not the Pharmacia code, the antigen sequence number is purposely placed after the closed parenthesis. Of course we also append Ab.IgE to the end of this entity name.Putting this all together formal and common name for the Component for the allergens listed above become:LOINC codeFormal name of componentLong common name of component58779-0 Arachis hypogaea recombinant (rAra h) 1 Ab.IgEPeanut recombinant (rAra h) 1 IgE Ab

6758777-4Arachis hypogaea recombinant (rAra h) 3 Ab.IgEPeanut recombinant (rAra h) 3 IgE Ab65769-2 Arachis hypogaea native (nAra h) 1 Ab.IgEPeanut native (nAra h) 1 IgE Ab65771-8 Arachis hypogaea native (nAra h) 3 Ab.IgEPeanut native (nAra h) 3 IgE Ab

684 Clinical observations and measures4.1 Introduction For most of the measures we include separate observations for summary data, e.g., shift and 24-hour urine output totals. We also provide varying degrees of pre-coordination for the observation, the body site at which it was obtained, and the method. For example, a cardiac output based on the Fick method is distinguished from a cardiac output computed from 2D cardiac echo data.Physiologic measures are often monitored continuously over time and the instrument reports summary “statistics” over that reporting period. For vital signs, these can include minimum, maximum, and mean value over a time period. For intake and output, the total is the summary statistic usually reported. When we address measures taken over time, we usually include 1-hour, 8-hour, 10-hour, 12-hour, and 24-hour intervals to cover the varying lengths of work shifts within and across institutions. The LOINC names of these correspond to the form of a 24-hour urine specimen. The times are recorded in the duration (third part) of the name.The parts of clinical measurement names are largely the same as for laboratory measures, with some subtle differences that are detailed below.• Parts 2, 3, 5 and 6 (type of Property, Time Aspect, Scale, and Method) correspond exactly in meaning between laboratory and clinical LOINC codes.• System: Part 4, body System, has the same general meaning for clinical and laboratory measures, but whereas in the case of laboratory tests the System usually identifies a fluid and a body compartment by implication (e.g., serum, cerebral spinal fluid), for clinical terms, the System is usually a body part (e.g., chest), organ (e.g., heart), or part of an organ (e.g., heart.ventricle). In some cases the System may be an instrument or device attached to the system (e.g., OB ultrasound imaging device).• Component: In the case of laboratory test observations, the Component (part 1) usually identifies some chemical moiety that is distributed in the System (Glucose, or HIV 1 Ab). In the case of clinical terms, the Component usually identifies a particular projection of a three- or four-dimensional space to a measure of a particular feature (e.g., QRS interval, Intrachamber.systolic) of a time changing measure (Heart.ventricle.left.outflow tract). In addition, the Component is used to distinguish the various ranges or inflections of a physiologic tracing, or to define precisely the section in three-dimensional space in which an area or range is being measured. The Component includes such things as the special kinds of length (e.g., circumference, diameter, or radius) when length is the Property, and the specific level and axis on which a measurement of a body part is taken, e.g., circumference taken at the nipple line. The Component should remove all ambiguity as to what projection or axis or specific sub-time frame is being measured. So if one is measuring the diameter of the kidney, the System would have to specify kidney.right (or kidney.left), and the Component would identify the axis and level at which the diameter was measured (e.g., cross-sectional at level of pelvis). For a measure of chest circumference the System is chest, the Component is circumference at nipple line, and the Property is length. Areas, lengths, and volumes of organs all have to be specified enough in the Component to distinguish a particular area or length that is being measured. When a measure changes over some cycle (e.g., inspiration, expiration, diastole, and systole), then that should also be specified in the Component. (Duration is used to identify the duration of an overall study.)

69For most clinical measurements, the Component is an attribute of a patient or an organ system within a patient. However, attributes of non-patient systems are also often of interest. For example, we might want to know the class of instrument used to obtain the measurement: i.e., the vendor model number or institutional inventory number of an endoscopy. Such identification numbers have a Property of ID. Infection control might want the latter reported in order to track nosocomial infections. When attributes of an instrument or device are being reported, the System is the name of the instrument. The same is true when we report characteristics of tubes used to move fluid in and out of body cavities. For example, we might want to report the size and type of a nasogastric tube.Table 20: Example subjects covered in clinical LOINCBlood pressure (systolic, diastolic, and mean)Body measurementsBody weight (and measures used to estimate ideal body weight)Cardiac ultrasoundCardiac output, resistance, stroke work, ejection, fraction, etc.Circumference of chest, thighs, legsCritical care measuresDentalElectrocardiographic measuresEmergency department case reports (CDC DEEDS)Gastroenterology endoscopyHeart rate (and character of the pulse wave)Intake and outputMajor headings in operative noteMajor headings in discharge summaryMajor headings of history and physicalObstetric ultrasound imagingOphthalmology measurementsPathology protocolsPulmonary ventilator managementRadiology reportsRespiratory rateStandardized survey instrumentsUrology ultrasound imagingTo accommodate the special dimensions of clinical observations we have introduced new options for the kind of Property. The new kinds of Property are what you might expect from the new kinds of dimensions being measured (e.g., resistance, voltage, work per beat). However, we have also introduced three important new properties:• Anat: Anatomic is a special case of Prid that identifies anatomic sites.• Imp: Impression is a diagnostic statement, always an interpretation or abstraction of some other observation (a series of test results, an image, or a total patient), and almost always generated by a professional. (We could also consider the EKG cart’s automated diagnoses as impressions.) Impressions are used in laboratory medicine as well as clinical medicine, so you will see them appearing there as well.• Find: Finding is an atomic clinical observation, not a summary statement as an impression. Physical

70review of systems and other such observations have a Property of Find. These may have a Scale of Nom for coded findings, Nar for findings reported in narrative text or Ord for ordinal findings.• Hx: Terms representing patient or family history concepts originally had Components that began with “History of” and were assigned the Find Property. As of LOINC version 2.56, these terms were updated to remove “History of” from the Component and change the Property to Hx, which is exactly what this Property represents.In clinical measures, super systems (the second subpart of the System component) may be required. For example, we distinguish head measures of a patient versus a fetus as follows:Circumference.occipital-frontal:Len:Pt:Head:Qn Diameter.biparietal:Len:Pt:Head^fetus:Qn4.2 Atomic versus molecular (pre-coordinated names)With clinical terms we almost always have two ways of reporting. Using the first, we can report an observation by reporting a number of atomic variables which together fully describe the observation. For example, we have the following atomic observations for circumference measures. These variables let us deal with all of the unique kinds of circumferences for which we have not yet defined a pre-coordinated term.Table 21: Examples of Pre-Coordinated NamesCodeDescriptionCircumference:Len:Pt:XXX:QnThe actual measure of some circumferenceCircumference site:Anat:Pt:*:NomIdentifies the body part measured(specifies the System)Circumference method:Type:Pt:XXX:Nom:*Identifies the measuring technique used to obtain the circumference(answers = tape measure, derived, imaging)We also provide pre-coordinated terms that combine some of the atomic variables into one LOINC code. For example, we have:8279-2 Circumference.at nipple line:Len:Pt:Chest:Qn and8293-3 Circumference^inspiration:Len:Pt:Chest:Qnwhich provide more specificity and permit the key components of the measure to be expressed as one variable as is the convention in many clinical systems. We call these pre-coordinated codes “molecular” variables.Within the LOINC database molecular variables will vary with respect to how many atomic components are aggregated. As is true in some laboratory areas, methods often are not included as part of a name, nor are they always reported. The most common molecular aggregation is between functional measure and a particular site of measurement (e.g., the many different intravascular sites for blood pressure measurements). But in some cases, the molecular variables represent combinations of specific measures and particular methods (e.g., the cardiac output measures). Please note that most molecular variables could also be accompanied by one or more atomic measures to provide special information about the measure, e.g., special circumstances of the measure, or the vendor model number or institutional inventory number of the measuring instrument.When we have a variable that really reports what would have been contained in the name in a fully pre-

71coordinated term, we will place an asterisk in the part that will be reported as a value. For example, a variable that is used to report the anatomic site as an atomic variable, would have an asterisk (*) in the System part of the name. The variable used to report the method of a particular measure would have an asterisk (*) in the Method part of the name.4.3 Radiology reportsAs of the December 2017 LOINC release, we have completed updating all of our radiology content according to the LOINC/RadLex Unified Model, which was developed through our collaboration with the Radiological Society of North America (RSNA).You can find information about the unified model at the end of this document, in the Annex – RadLex-LOINC Radiology Playbook User Guide.The following table provides a reference for how the attributes in the Unified Model correspond to the primary LOINC Parts.Table 22: Relationship of primary LOINC Parts to Radiology attributesPrimary PartRadiology AttributeComponent 1st part (Analyte)View GuidanceReason for ExamComponent 2nd part (Challenge)TimingManeuverPharmaceuticalSystemAnatomySubjectMethodModality4.4 Tumor registryIn collaboration with North American Association of Central Cancer Registries, Inc (NAACCR, Inc), we have developed a set of LOINC codes that can be used to communicate tumor registry variables from clinical institutions to tumor registries and among tumor registries. These LOINC terms map to the content of NAACCR data set, and include variables for such things as the hospital at which the tumor was first diagnosed, the primary anatomic site of the tumor, it size, its degree of spread at the time of diagnoses, and a host of other variables of interest to the tumor registries. The NAACCR data set and other cancer-related demographics are identified by the Class TUMRRGT.The NAACCR standards and an implementation guide for transmitting these LOINC tumor registry variables within HL7 messages are available from the NAACCR website (http://naaccr.org).

725 Claims attachmentsFor more information see HIPAA Attachments display in RELMA, the HIPAA Attachment section in RELMA Users’ Manual, the respective documents published by HL7 Attachments Working Group, and the Attachments section of the LOINC website (http://loinc.org/attachments).

736 LOINC Document OntologyThis section describes our approach to creating a set of document type codes. This work began as a collaboration between the LOINC committee and the HL7 document ontology task force, with initial contributions from Stan Huff, Pavla Frazier, Bob Dolin, and Clem McDonald. The background and initial development of the ontology was described by Frazier et al.29 Over time, we have continued to make many refinements to this ontology. In particular, we have received exceptional contributions from colleagues at Columbia University and the U.S. Department of Veterans Affairs.6.1 Introduction to the use of LOINC document type codesIn creating and maintaining document type codes, it is important to distinguish between the purpose of local document names and the names represented by the document type code. Document type codes are created to provide consistent semantics for the names of documents when they are shared or exchanged between independent facilities or enterprises. The names and codes that are used locally within an enterprise are entirely under the control of the local enterprise, and these names are valuable to the workflow and access of information within the enterprise. It is assumed that the exact local name for the document will be retained in the system that created the document, and that the local name can be sent along with the document type code when the document is sent to an external organization. The document type code should only express the meaning in a document name that can be shared between independent organizations.For example, it is appropriate to have local document names like “Dr. Smith’s Tuesday Pain Clinic Note” or “Albuquerque VA General Medicine Consult Note” for use within an enterprise. However, some parts of these very specific local names are not meaningful outside of the originating enterprise. Thus, proper document type codes would have names like “Outpatient Pain Clinic Note,” or “General Internal Medicine Consult Note.”Table 22: Example Clinical NotesPossible local termsDocument type codesDr. Smith’s Tuesday Pain Clinic NoteOutpatient Pain Clinic NoteAlbuquerque VA General Medicine Consult NoteGeneral Internal Medicine Consult NoteThe naming rules in this Document Ontology apply primarily to “clinical notes.” For purpose of this Users’ Guide, a clinical note is a clinical document (as defined by the HL7 CDA Standard), where clinical professionals and trainees produced the document either spontaneously (e.g., I write my admitting note) or in response to a request for consultation. “Clinical Notes” provides a better description of the process.“Clinical Notes” are to be distinguished from patient reports such as radiology reports, pathology reports, laboratory reports, cardiac catheterization reports, etc., that are generated in response to an order for a specific procedure. Names for most of these later concepts are accommodated well by the clinical LOINC naming structure, and many such codes already exist within the LOINC database.We must also emphasize that the names constructed in LOINC are based on the expected information content 29 Frazier P, Rossi-Mori A, Dolin RH, Alschuler L, Huff SM. The creation of an ontology of clinical document names. Stud Health Technol Inform. 2001;84(Pt1):94-8. [PubMed: 11604713].

74of the document, rather than the document format. This is to say that the same LOINC code would be used to represent a given document type regardless of whether it was in PDF, text document, JPG, XML, or HTML formats – if the information content contained by those documents were the same.6.2 Relationship to other standards6.2.1 HL7HL7 will use LOINC codes for clinical document codes, and will not develop an independent document code system for clinical documents. At its option, HL7 may choose to limit its domain to a subset of LOINC codes.The HL7 document type code domain will overlap with similar concepts found in HL7 V2.x (user defined table 0270 Document Types; user defined table 0496 Consent Types). Our approach to manage this overlap is:• Create a mapping from LOINC codes to HL7 V2.x document codes.• Continue to develop LOINC codes to meet the needs of the HL7 V3 domain that are not present in the V2.x tables.6.3 Elements of document type codesIn the following, synonymy or equivalent terms are designated by parenthesis. Document codes are defined by their component parts. The first list of axis values was published in 2003, and served as the basis for an initial set of LOINC codes.Through both empiric analysis and expert review, we have continued evaluating and refining this list. The following listing contains the current set of axis values for the elements of document type codes that have been vetted by the LOINC Committee. We are in the process of carefully harmonizing our existing Document terms with these new values.6.3.1 Kind of DocumentDescription: Characterizes the general structure of the document at a macro level. Document types are differentiated based on the need to define distinct document headers.Allowed Values:Part NumberPart NameLP173387-4Administrative noteLP173388-2 Against medical advice noteLP173389-0 AgreementLP412176-2 Controlled substance agreementLP173390-8 CertificateLP173391-6 Birth certificateLP173392-4 Death certificateLP173393-2 Evaluation of mental and physical incapacity certificate

75LP267921-7 Proof of encounter certificateLP173394-0 ConsentLP173395-7 Abortion consentLP173396-5 Anesthesia consentLP267939-9 Blood or blood product transfusion consentLP173397-3 Hysterectomy consentLP267417-6 Long-term opioid therapy for pain consentLP173398-1 Organ donation consentLP173399-9 Procedure consentLP173400-5 Release of information consentLP416139-6 Research study consentLP173401-3 Sterilization consentLP173402-1 Surgical operation consentLP173403-9 ContractLP193873-9 Driver licenseLP173404-7 Health insurance cardLP173405-4 Health insurance-related formLP173406-2 Health record cover sheetLP173407-0 Legal documentLP200113-1 Legal letterLP416137-0 Portable medical order formLP173408-8 Power of attorneyLP248740-5 Medical clearance noteLP181089-6 RequestLP181085-4 Prescription requestLP173409-6Advance directivesLP173410-4 Do not resuscitateLP173411-2 Rescinded do not resuscitateLP173412-0 Living willLP173413-8 Rescinded advance directiveLP200111-5ChecklistLP267279-0 Discharge checklistLP173414-6DiagramLP173415-3FlowsheetLP181112-6FormLP204180-6 Mandatory reporting formLP416138-8 Medical history screening formLP416137-0 Portable medical order formLP181116-7InstructionsLP181119-1 Action planLP173754-5 ADHD action planLP173755-2 Anaphylaxis action planLP173756-0 Asthma action planLP173757-8 Autism action planLP173758-6 Complex medical conditions action plan

76LP173759-4 Cystic fibrosis action planLP173765-1 Diabetes type I action planLP173766-9 Diabetes type II action planLP173760-2 Heart disease action planLP173761-0 Inflammatory bowel disease action planLP173762-8 Multiple sclerosis action planLP173763-6 Muscular dystrophy action planLP173764-4 Seizure disorder action planLP173118-3 Discharge instructionsLP173417-9LetterLP200113-1 Legal letterLP204161-6ListLP181534-1 Prescription listLP173418-7NoteLP173419-5 Adverse event noteLP173420-3 AlertLP181207-4OrderLP416137-0 Portable medical order formLP181204-1PrescriptionLP181529-1 Prescription for diagnostic or specialist careLP181530-9 Prescription for durable medical equipment attachmentLP181190-2 Prescription for eyewearLP181531-7 Prescription for medical equipment or productLP181532-5 Prescription for medicationLP181533-3 Prescription for rehabilitationLP181534-1 Prescription listLP181231-4Photographic imageLP173421-1ReportLP183503-4 Case reportLP183502-6 Registry reportFurther explanation of LOINC’s use of “Note” (i.e., a Clinical Note, also known as “Clinical Document”) versus “Report”: In LOINC, a Note is a document generated by a clinician as part of patient care and includes notes written at the initiative of “individual clinic and consulting clinicians.” In contrast, a Report is usually generated in response to an order, e.g., radiology, pathology, and cardiac catheterization reports. In general, we will not make two distinct LOINC codes for concepts that have all of the same attributes except that one is a Note and one is a Report. Requests for such pairs of codes (or a request for a note when a report term exists or vice versa) will be reviewed on a case by case basis. Clinical documents meet five criteria, as defined in CDA 1.0: wholeness, stewardship, authentication, persistence, and human readability.6.3.2 Type of ServiceDescription: Characterizes the kind of service or activity provided to/for the patient (or other subject of the service) as described in the note. Common subclasses of service would be evaluations, consultations, and

77summaries. The notion of time sequence, e.g., at the beginning (admission) or at the end (discharge), is subsumed in this axis.Allowed Values:Part NumberPart NameLP173107-6CommunicationLP173099-5ConferenceLP173109-2 Case conferenceLP173110-0ConsultationLP173111-8 Confirmatory consultationLP173100-1CounselingLP173113-4 Group counselingLP173112-6 Individual counselingLP173114-2Daily or end of shift signoutLP173115-9Diagnostic studyLP173116-7 Inhalation challenge testLP173117-5EducationLP173120-9 Discharge teachingLP173121-7 Preoperative teachingLP173122-5Evaluation and managementLP173129-0 CareLP310260-7 Care managementLP173130-8 Crisis intervention (psychosocial crisis intervention)LP263715-7 Suicide preventionLP173131-6 Disease stagingLP173132-4 Disability examinationLP173133-2 Social security administration compensation examinationLP173134-0 Compensation and pension examinationLP173135-7 VA C&P exam.acromegalyLP173136-5 VA C&P exam.aid and attendance &or houseboundLP173137-3 VA C&P exam.arrhythmiasLP173138-1 VA C&P exam.miscellaneous arteries &or veinsLP173139-9 VA C&P exam.audioLP173140-7 VA C&P exam.bonesLP173105-0 VA C&P exam.bones fractures &or bone diseaseLP173141-5 VA C&P exam.brain &or spinal cordLP173142-3 VA C&P exam.chronic fatigue syndromeLP173143-1 VA C&P exam.cold injury protocolLP173144-9 VA C&P exam.cranial nervesLP173145-6 VA C&P exam.Cushings syndromeLP173146-4 VA C&P exam.dental &or oralLP173147-2 VA C&P exam.diabetes mellitusLP173148-0 VA C&P exam.miscellaneous digestive conditionsLP173149-8 VA C&P exam.ear diseaseLP173150-6 VA C&P exam.mental health eating disorders

78LP173151-4 VA C&P exam.miscellaneous endocrine diseasesLP173152-2 VA C&P exam.epilepsy &or narcolepsyLP173153-0 VA C&P exam.esophagus &or hiatal herniaLP173168-8 VA C&P exam.extremity jointsLP173154-8 VA C&P exam.eyeLP173155-5 VA C&P exam.feetLP173156-3 VA C&P exam.fibromyalgiaLP173157-1 VA C&P exam.general medicalLP173158-9 VA C&P exam.genitourinaryLP173159-7 VA C&P exam.disability in gulf war veteransLP173160-5 VA C&P exam.gynecological conditions &or disorders of the breastLP173161-3 VA C&P exam.hand &or thumb &or fingersLP173162-1 VA C&P exam.heartLP173163-9 VA C&P exam.hemic disordersLP173164-7 VA C&P exam.HIV-related illnessLP173165-4 VA C&P exam.hypertensionLP173166-2 VA C&P exam.infectious &or immune &or nutritional disabilitiesLP173167-0 VA C&P exam.large &or small intestinesLP173168-8 VA C&P exam.extremity jointsLP173169-6 VA C&P exam.liver &or gall bladder &or pancreasLP173170-4 VA C&P exam.lymphatic disordersLP173171-2 VA C&P exam.general mental disordersLP173172-0 VA C&P exam.mouth &or lips &or tongueLP173173-8 VA C&P exam.multiple examLP173174-6 VA C&P exam.musclesLP173175-3 VA C&P exam.miscellaneous neurological disordersLP173176-1 VA C&P exam.nose &or sinus &or larynx &or pharynxLP173177-9 VA C&P exam.peripheral nervesLP173178-7 VA C&P exam.initial evaluation post-traumatic stress disorderLP173179-5 VA C&P exam.review evaluation post-traumatic stress disorderLP173180-3 VA C&P exam.prisoner of war protocolLP173181-1 VA C&P exam.pulmonary tuberculosis &or mycobacterial diseasesLP173182-9 VA C&P exam.rectum &or anusLP173183-7 VA C&P exam.residuals of amputationsLP173184-5 VA C&P exam.miscellaneous respiratory diseasesLP173185-2 VA C&P exam.obstructive &or restrictive &or interstitial respiratory diseasesLP173186-0 VA C&P exam.scarsLP173187-8 VA C&P exam.sense of smell &or tasteLP173188-6 VA C&P exam.skin diseases other than scarsLP173106-8 VA C&P exam.social &or industrial surveyLP173189-4 VA C&P exam.spineLP173190-2 VA C&P exam.stomach &or duodenum &or peritoneal adhesionsLP173191-0 VA C&P exam.thyroid &or parathyroid diseasesLP173124-1 EvaluationLP173123-3 Annual evaluation

79LP173125-8 Functional status assessmentLP173204-1 Initial evaluationLP173205-8 Admission evaluationLP173200-9 Admission history and physicalLP173126-6 Readiness for military duty assessmentLP270301-7 ReevaluationLP173127-4 Risk assessment and screeningLP173128-2 Fall risk assessmentLP204157-4 Safety issue assessmentLP173192-8 Evaluation and management of a specific problemLP173193-6 Evaluation and management of anticoagulationLP173194-4 Evaluation and management of hyperlipidemiaLP173195-1 Evaluation and management of hypertensionLP267443-2 Evaluation and management of radiation exposureLP173197-7 Evaluation and management of smoking cessationLP208913-6 Evaluation and management of workers compensationLP269262-4 Fluid managementLP173198-5 History and physicalLP173199-3 Annual history and physicalLP173200-9 Admission history and physicalLP173202-5 Labor and delivery admission history and physicalLP173201-7 Comprehensive history and physicalLP173203-3 Targeted history and physicalLP204160-8 Medical equipment or productLP173206-6 PlanLP173209-0 Plan of careLP173213-2 ProgressLP173211-6 RestraintLP173214-0 Surgical operationLP173215-7 Postoperative evaluation and managementLP173216-5 Preoperative evaluation and managementLP173103-5 SummaryLP173218-1 Antepartum summaryLP173221-5 Discharge summaryLP222264-6 Immunization summaryLP173223-1 Labor and delivery summaryLP173222-3 Maternal discharge summaryLP175732-9 Population summaryLP173225-6 Summary of deathLP200117-2 Summary of encountersLP173224-9 Summary of episodeLP173226-4 Transfer summaryLP189614-3 Weight management summaryLP173227-2 Transplant candidate evaluationLP173228-0 Transplant donor evaluation

80LP173229-8 Well child visitLP173230-6Exercise testingLP263510-2ImmunizationLP204160-8Medical equipment or productLP173231-4Medication managementLP207306-4 Medication administrationLP266264-3 Parenteral therapyLP173232-2 Medication reconciliationLP203673-1NotificationLP203034-6 Admission notificationLP203035-3 Discharge notificationLP204130-1 Visit notificationLP173233-0OutreachLP173234-8ProcedureLP267418-4 Cardiopulmonary resuscitationLP269244-2 Conscious sedation procedureLP410764-7 Emergency procedureLP411573-1 Mechanical circulatory supportLP173235-5 Interventional procedureLP173236-3 Pathology procedureLP173237-1 AutopsyLP173238-9ReferralLP173240-5RespiteLP173104-3SupervisoryLP173242-1Triage6.3.3 SettingDescription: Setting is a modest extension of CMS’s coarse definition of settings, which have well-defined meanings. Setting is not equivalent to location, which typically has more locally defined meanings and is reported in other parts of the message. Setting would be limited to one of the following categories (with some future extensions possible).Most clinical report names would include a setting (at least at the top level) to avoid confusion between important classes of reports. For example, The Admission H&P is usually taken to be the Hospital Admission H&P, but it could be confused with the nursing home H&P if not distinguished by the setting. Setting is not a required component of the name.Allowed Values:Part NumberPart NameLP173041-7AmbulanceLP173042-5Birthing centerLP173043-3Emergency departmentLP173065-6HospitalLP173045-8Intensive care unit

81LP173046-6Long term care facilityLP173047-4 Custodial care facilityLP173048-2 Nursing facilityLP173049-0 Skilled nursing facilityLP173050-8 Unskilled nursing facilityLP222061-6Observation unitLP173051-6OutpatientLP266261-9 Adult day care centerLP173052-4 Ambulatory surgical centerLP173053-2 OfficeLP173054-0 Outpatient hospitalLP173055-7 Urgent care centerLP173056-5Patient’s homeLP220237-4PharmacyLP248736-3Recovery roomLP173057-3Rehabilitation hospitalLP173058-1TelehealthLP248737-1TeleimagingLP173059-9Telephone encounter6.3.4 Subject Matter Domain (SMD)Description: Characterizes the subject matter domain of a note.Allowed Values:Part NumberPart NameLP263512-8Addiction medicineLP172912-0 Addiction psychiatryLP172915-3Aerospace medicineLP345051-9AllergyLP172918-7AnesthesiologyLP172981-5 Pain medicineLP248728-0 Sleep medicineLP172919-5AudiologyLP172923-7Chiropractic medicineLP172933-6Critical care medicineLP172934-4DentistryLP172935-1DermatologyLP172924-5 Clinical and laboratory dermatological immunologyLP172936-9 DermatopathologyLP172987-2 Pediatric dermatologyLP172940-1Emergency medicine

82LP172957-5 Medical toxicologyLP172988-0 Pediatric emergency medicineLP173027-6 Sports medicineLP183499-5 TraumaLP173035-9 Undersea and hyperbaric medicineLP172942-7EthicsLP176905-0Exercise physiologyLP172943-5Family medicineLP172913-8 Adolescent medicineLP172947-6 Geriatric medicineLP248728-0 Sleep medicineLP173027-6 Sports medicineLP172894-0Forensic medicineLP172944-3 Forensic psychiatryLP172946-8General medicineLP345043-6ImmunologyLP172925-2 Clinical and laboratory immunologyLP342846-5Integrative medicineLP172911-2 AcupunctureLP172952-6Internal medicineLP172913-8 Adolescent medicineLP172921-1 Cardiovascular diseaseLP172927-8 Clinical cardiac electrophysiologyLP269425-7 Heart failureLP172953-4 Interventional cardiologyLP269424-0 Transplant cardiologyLP172941-9 EndocrinologyLP172938-5 DiabetologyLP173032-6 ThyroidologyLP172945-0 GastroenterologyLP172950-0 HepatologyLP172947-6 Geriatric medicineLP175685-9 HematologyLP172951-8 Infectious diseaseLP183500-0 HIVLP175686-7 Medical oncologyLP172962-5 NephrologyLP263511-0 DialysisLP173015-1 Pulmonary diseaseLP173023-5 RheumatologyLP248728-0 Sleep medicineLP173027-6 Sports medicineLP342846-5Integrative medicineLP172911-2 AcupunctureLP172956-7Medical genetics

83LP172926-0 Clinical biochemical geneticsLP172928-6 Clinical cytogeneticsLP172929-4 Clinical geneticsLP172930-2 Clinical molecular geneticsLP172959-1 Molecular genetic pathologyLP268361-5 PharmacogenomicsLP172958-3Mental healthLP345044-4 Eating disordersLP173011-0 PsychiatryLP172912-0 Addiction psychiatryLP172922-9 Child and adolescent psychiatryLP172944-3 Forensic psychiatryLP172948-4 Geriatric psychiatryLP173013-6 Psychosomatic medicineLP173012-8 PsychologyLP248501-1 Child and adolescent psychologyLP248729-8 NeuropsychologyLP172960-9Multi-specialty programLP345048-5 Aerodigestive medicineLP263714-0 Brain injuryLP345049-3 Cleft and CraniofacialLP345044-4 Eating disordersLP265794-0 PolytraumaLP172963-3Neurological surgeryLP345042-8 Spinal surgeryLP172964-1NeurologyLP263714-0 Brain injuryLP172931-0 Clinical neurophysiologyLP248726-4 EpilepsyLP172965-8 Neurology neurodevelopmental disabilitiesLP172898-1 Neurology w special qualifications in child neuroLP172981-5 Pain medicineLP248728-0 Sleep medicineLP173038-3 Vascular neurologyLP172968-2Nuclear medicineLP172899-9Nutrition and dieteticsLP345044-4 Eating disordersLP269243-4Obesity medicineLP172971-6Obstetrics and gynecologyLP221284-5 GynecologyLP202989-2 Gynecologic oncologyLP172955-9 Maternal and fetal medicineLP221283-7 ObstetricsLP173020-1 Reproductive endocrinology and infertilityLP172973-2Occupational therapy

84LP172901-3OncologyLP202989-2 Gynecologic oncologyLP175686-7 Medical oncologyLP172991-4 Pediatric hematology-oncologyLP173016-9 Radiation oncologyLP207940-0 Surgical oncologyLP172974-0OphthalmologyLP172975-7 OptometryLP172902-1Oral and maxillofacial surgeryLP172978-1Orthopaedic surgeryLP172977-3 Orthopedic sports medicineLP345042-8 Spinal surgeryLP173029-2 Surgery of the handLP172979-9Orthotics prostheticsLP172980-7OtolaryngologyLP172967-4 NeurotologyLP172994-8 Pediatric otolaryngologyLP173007-8 Plastic surgery within the head and neckLP248728-0 Sleep medicineLP172982-3Palliative careLP172983-1Pastoral careLP172984-9PathologyLP208907-8 Anatomic pathologyLP172936-9 DermatopathologyLP208906-0 Clinical pathologyLP172920-3 Blood banking and transfusion medicineLP208902-9 Chemical pathologyLP172959-1 Molecular genetic pathologyLP208903-7 Medical microbiology – pathologyLP241974-7 Toxicologic pathologyLP173002-9PediatricsLP172913-8 Adolescent medicineLP345048-5 Aerodigestive medicineLP172922-9 Child and adolescent psychiatryLP248501-1 Child and adolescent psychologyLP172937-7 Developmental-behavioral pediatricsLP172950-0 HepatologyLP172957-5 Medical toxicologyLP172961-7 Neonatal perinatal medicineLP192135-4 Birth defectsLP172985-6 Pediatric cardiologyLP172986-4 Pediatric critical care medicineLP172987-2 Pediatric dermatologyLP172989-8 Pediatric endocrinologyLP172988-0 Pediatric emergency medicine

85LP172990-6 Pediatric gastroenterologyLP173000-3 Pediatric transplant hepatologyLP172991-4 Pediatric hematology-oncologyLP172992-2 Pediatric infectious diseasesLP172993-0 Pediatric nephrologyLP172994-8 Pediatric otolaryngologyLP172995-5 Pediatric pulmonologyLP172996-3 Pediatric radiologyLP172997-1 Pediatric rehabilitation medicineLP172998-9 Pediatric rheumatologyLP172999-7 Pediatric surgeryLP248728-0 Sleep medicineLP173027-6 Sports medicineLP173003-7PharmacologyLP220238-2 Clinical pharmacologyLP268361-5 PharmacogenomicsLP173004-5Physical medicine and rehabilitationLP263714-0 Brain injuryLP172954-2 KinesiotherapyLP172981-5 Pain medicineLP172997-1 Pediatric rehabilitation medicineLP265794-0 PolytraumaLP173026-8 Spinal cord injury medicineLP173040-9 Vocational rehabilitationLP173005-2Physical therapyLP173006-0Plastic surgeryLP268363-1 Burn managementLP173007-8 Plastic surgery within the head and neckLP173029-2 Surgery of the handLP173008-6PodiatryLP173009-4Preventive medicineLP172957-5 Medical toxicologyLP172972-4 Occupational medicineLP173035-9 Undersea and hyperbaric medicineLP173010-2Primary careLP173014-4Public healthLP204156-6 Community health careLP267441-6 Environmental healthLP173018-5Radiology LP172939-3 Diagnostic radiologyLP172896-5 Interventional radiologyLP172969-0 Nuclear radiologyLP172996-3 Pediatric radiologyLP173016-9 Radiation oncologyLP173017-7 Radiological physics

86LP173037-5 Vascular and interventional radiologyLP173019-3Recreational therapyLP173021-9ResearchLP173022-7Respiratory therapyLP173025-0Speech-language pathologyLP173028-4SurgeryLP248500-3 Bariatric surgeryLP268363-1 Burn managementLP172932-8 Colon and rectal surgeryLP172999-7 Pediatric surgeryLP265794-0 PolytraumaLP173029-2 Surgery of the handLP173030-0 Surgical critical careLP207940-0 Surgical oncologyLP173031-8 Thoracic and cardiac surgeryLP207300-7 Cardiac surgeryLP173033-4 Transplant surgeryLP183499-5 TraumaLP265794-0 PolytraumaLP173039-1 Vascular surgeryLP269976-9ThromboembolismLP173034-2Tumor boardLP173036-7UrologyLP173001-1 Pediatric urologyLP248732-2Womens HealthLP185997-6Wound care managementLP268363-1 Burn managementLP412351-1 Wound, Ostomy, and Continence Care6.3.5 RoleDescription: Characterizes the training or professional level of the author or the party responsible for the content in the document. The role category is a high-level classification that does not get as detailed as specialty or subspecialty so as to avoid potential overlap with the subject matter domain axis.Allowed Values:Part NumberPart NameLP173066-4AssistantLP269965-2AttendingLP173067-2Case managerLP173068-0ClerkLP269966-0ConsultantLP173069-8CounselorLP264605-9Device

87LP269967-8FellowLP412180-4Healthcare navigatorLP173071-4HygienistLP173072-2InterdisciplinaryLP173073-0 TeamLP203036-1 Rapid response teamLP269968-6InternLP173074-8Medical assistantLP221282-9MidwifeLP173079-7 Nurse midwifeLP173075-5NurseLP173076-3 CRNALP173077-1 Certified nursing assistantLP173078-9 Clinical nurse specialistLP173079-7 Nurse midwifeLP173080-5 Nurse practitionerLP173081-3 Licensed practical nurseLP173082-1 Registered nurseLP173083-9PatientLP181523-4PharmacistLP173084-7Physician*LP269965-2 AttendingLP269966-0 ConsultantLP269967-8 FellowLP269968-6 InternLP269969-4 ResidentLP173090-4Physician assistantLP269969-4ResidentLP269801-9Social workerLP173091-2StudentLP173092-0 Medical studentLP173093-8 Nursing studentLP173094-6TechnicianLP173095-3TherapistNote * Physician subsumes medical physicians and osteopathic physicians.6.4 Rules for creating clinical notes from multiple attributes

88Names for required clinical notes would be constructed by picking entries from the Kind of Document axis and at least one of the other four axes (see exceptions below in Section 7.4.1). The LOINC committee will create LOINC codes for all required combinations (not all possible combinations).The original Document Ontology terms were created only for the document type of “note” and with the general naming pattern:<Subject Matter Domain> : <Training / Professional Level>: <Setting>: <Type> : NoteAs we have revised and refined the elemental axes in the Document Ontology, simple names would be constructed and ordered as follows:Table 23. Document Ontology LOINC Naming RulesComponentPropertyTimeSystemScaleMethodClass<Type of Service> <Kind of Document>FindPt<Setting>Doc<SMD>.<Role>DOC.ONTOLOGYIn general, combinations from within an axis are allowed in a term name where they make sense (typically, SMD and Service), but are disallowed where they do not (typically, Role and Setting). Combinations will be represented with a plus (+), so as to distinguish from elements containing “and” or “&”. Where a particular element is not defined for a given term and leaves a LOINC axis blank, the LOINC name will include the {} naming convention. For example, if a Setting is not designated, the System will be {Setting}. Where neither the SMD nor Role is specified, {Role} is used in the Method (as of LOINC version 2.54).LOINC codes for clinical notes designed according to this model and are assigned a Class of DOC.ONTOLOGY. The Class name was changed in LOINC version 2.50 from DOC.CLINRPT to DOC.ONTOLOGY, a more representative name for all types of documents (not just clinical reports) included in the LOINC Document Ontology.Example LOINC codes in the Document Ontology include:Table 24. Example Document Ontology LOINC CodesComponentPropertyTimeSystemScaleMethodClassGroup counseling noteFindPtHospitalDoc{Role}DOC.ONTOLOGYNoteFindPtOutpatientDoc{Role}DOC.ONTOLOGYAdmission evaluation noteFindPt{Setting}DocGeneral medicineDOC.ONTOLOGYHistory and physical noteFindPt{Setting}Doc{Role}DOC.ONTOLOGYFor every clinical note term we create with a designated Setting, SMD, and/or Role, we will also create a general “roll-up” term where the Setting, SMD and Role are not specified, i.e. they are defined as {Setting} and {Role}. The LOINC Committee has agreed not to create a general document code in some cases, including:1. The Component contains only one axis value, either a Type of Service or Kind of Document. Such a generic code (absent the other attributes) would violate the current policy to include the Kind of Document plus at least one other axis value.2. The general type of clinical document is not likely to ever exist.Example LOINC codes that do not have a general clinical note term include:Table 25. LOINC Code Exceptions to Creating a General Clinical Document Code

89ComponentPropertyTimeSystemScaleMethodClassAnesthesia consentFindPt{Setting}DocPatientDOC.ONTOLOGYOrgan donation consentFindPt{Setting}DocPatientDOC.ONTOLOGYHealth insurance cardFindPt{Setting}DocPatientDOC.ONTOLOGYTriage+Care noteFindPtEmergency departmentDocNurseDOC.ONTOLOGYPrescription requestFindPtPharmacyDocPharmacistDOC.ONTOLOGY6.4.1 Exceptions to rules for creating clinical notesAs noted above, the current policy for creating clinical notes is to include the Kind of Document plus at least one other axis value. The LOINC Committee has agreed to make exceptions to the Document Ontology rules for cases where only Kind of Document is commonly designated (e.g. Driver license).Example LOINC codes that are approved exceptions containing only a Kind of Document:Table 26. LOINC Codes with only a Kind of DocumentComponentPropertyTimeSystemScaleMethodClassAdministrative noteFindPt{Setting}Doc{Role}DOC.ONTOLOGYAsthma action planFindPt{Setting}Doc{Role}DOC.ONTOLOGYBirth certificateFindPt{Setting}Doc{Role}DOC.ONTOLOGYCase reportFindPt{Setting}Doc{Role}DOC.ONTOLOGYDeath certificateFindPt{Setting}Doc{Role}DOC.ONTOLOGYDo not resuscitateFindPt{Setting}Doc{Role}DOC.ONTOLOGYDriver licenseFindPt{Setting}Doc{Role}DOC.ONTOLOGYPhotographic imageFindPt{Setting}Doc{Role}DOC.ONTOLOGYPrescription listFindPt{Setting}Doc{Role}DOC.ONTOLOGYThe LOINC Committee also recognizes the need for terms with only a general Kind of Document (e.g. Letter, Note, Report) designated. We have agreed to create such terms, however, they will have a status of “discouraged” to caution users. If these general terms are used, we strongly recommend that they are used in a post-coordinated manner in conjunction with one of the LOINC terms included in the LOINC Document Ontology associated observations panel (LOINC: 80582-0) to carry the relevant attribute specifications.6.5 Document Ontology content in the LOINC distributionBeginning with LOINC version 2.44 (June 2013), a delimited text file containing the relationships between clinical document terms (i.e. those within the Class of DOC.ONTOLOGY) and their associated ontology axis values is available as a separate download from http://loinc.org. The document ontology axis values have been assigned LOINC Part identifiers and classified according to their document ontology axis. This file defines the relationships between a given LOINC term and its ontology axis values through these fields: LoincNumber, PartNumber, PartTypeName, PartSequenceOrder, PartName. These fields are largely self-explanatory, but of note is that the PartTypeName corresponds to the Document Ontology axis, and the PartSequenceOrder is relevant for terms that combine axis values from within an axis (see Section 7.4).

906.6 Future workWe continue active development and refinement of the Kind of Document axis. As we continue this work, we intend to develop equally specific definitive documents for other kinds of health care associated documents.6.7 Proposing new LOINC document termsNew LOINC document type codes can be proposed using the process described in Appendix D. In general, new term proposals that contain allowed combinations of existing axis values will be made expeditiously by Regenstrief staff. Requests for document titles containing new axis values to be added to the ontology will be reviewed by the LOINC committee, and thus their final modeling may take a bit longer.In LOINC, a Note is a document generated by a clinician as part of patient care and includes notes written at the initiative of “individual clinic and consulting clinicians.” In contrast, a Report is usually generated in response to an order, e.g., radiology, pathology, and cardiac catheterization reports. In general, we will not make two distinct LOINC codes for concepts that have all of the same attributes except that one is a Note and one is a Report. Requests for such pairs of codes (or a request for a note when a report term exists or vice versa) will be reviewed on a case by case basis.

917 Panels (Batteries)Beginning with version 1.0, the LOINC database was expanded to include order sets/panels. We use the word “panel” to mean collector terms that contain links to an enumerated set of discrete child elements. Across domains, this generic concept of a collection might be called a battery, form, data set, etc. The same general panel structure in LOINC is used to represent all of these kinds of collections.7.1 GoalsOur work in creating panels was stimulated by many requests for a standard set of test order codes from medical information system vendors who want to install their systems with a usable starter set of standard codes for common orders. They also want standard codes to ease the cross communications among merging hospitals.LOINC codes have been defined for most individual laboratory observations and for many clinical observations, and claims attachments. The same LOINC codes can be used to order individual laboratory and clinical observations, as well as to report the result. For example, a LOINC code for Blood Hemoglobin (LOINC: 718-7) could be used as easily to order the test as to report its result. In HL7 messages, the field where the code is used indicates its role as an order (e.g. OBR-4) or a result observation (OBX-3). Similarly, pre-existing LOINC codes could also be used to order more complex observations. The LOINC code used to order Urinary Creatinine Clearance (LOINC: 2164-2) actually implies an order for two distinct measures (serum creatinine and 24-hour urine creatinine) that are used to calculate the creatinine clearance.However, the existing single value LOINC codes could not be used to order many laboratory and clinical procedures that are ordered as a single-named test (battery), such as CBC, urine dipsticks, blood differential count, and LDH isoenzymes. Similarly physicians order blood pressure measures and expect to get (at least) the diastolic blood pressure and the systolic blood pressure. Though these are separate observations, for practical purposes one is never measured without the other.Initially, we created LOINC codes for the common “fixed” packages of observations. By fixed, we mean that certain kinds of measures will always be part of the battery, and the production of that particular set of measurements is tightly bound to the procedure, instruments that produce the values, or by a government mandate (e.g., LOINC: 24325-3: Hepatic function HCFA 2000 panel).Over time, we have evolved our approach to building panels of other observation collections. (For information on using the ORDER_OBS field of the LOINC database to help find panels that could be used as orders, see Section 10.3.)7.2 Types of results found in panelsTo understand the rules about how LOINC creates panels and how to map your local panels to LOINC panels, it is important to distinguish among several kinds of “results”.

927.2.1 Primary measurements or observationsThese observations report key measured results, and may indicate the presence/absence or amount of a substance or organism in the sample. For example, in an electrolytes panel, measured amounts of sodium, potassium, chloride, and bicarbonate would be the primary measures.7.2.2 Derived observationsThese observations are derived from mathematical or logical operations on the primary measurements. For example, in an electrolytes panel, the anion gap is a derived measure that is calculated by subtracting the concentrations of chloride and bicarbonate (anions) from the concentrations of sodium and potassium (cations).7.2.3 Ask at order entry (AOE) questions and other associated observationsThese observations are obtained from the requester as part of the test order and are generally delivered back to the requester as part of the result package. For example, the concentration of inspired oxygen is always an AOE question for blood gas measurements. Similarly, the date of last menstrual period is an AOE question for pap smears.Other kinds of observations are operationally treated in a similar manner although they may not be “questions” in the literal sense. For example, the volume and times (start, stop, duration) of urine collection are often sent along with the order and back again with the results. We call these “associated observations” and consider them like AOEs for the purpose of this discussion.7.2.4 Impressions, interpretations, and commentsLOINC defines an impression/interpretation as a summary statement about multiple observations. This kind of summary observation is often included in collections of results sent back to the requester. (Such summary observation terms in LOINC have the Property of Imp, for impression, in their name).As an aside, we note that decisions about test results being outside of normal range are best reported with the Interpretation Code (commonly referred to as the “Abnormal flag”) field of the HL7 OBX structure and not as a separate interpretation observation.7.3 LOINC rules for panel namesWe use most of the same general LOINC naming rules for panels as we do for individual observations. Here we describe some of the key unique features of panel names.7.3.1 ComponentIf a government authority recognizes the panel or order set, we will name such panels with the year that the recognition took effect. For example, LOINC includes the “Comprehensive metabolic 2000 panel”.For panels consisting of more than three constituent tests, the Component name will be a concatenation of:1. A name (e.g., Hemogram, Differential count, Vital Signs) to convey the content of the panel2. The word “Panel” included to unambiguously identify that this LOINC term refers to a panel or battery

93In the case that a well-defined panel exists but has no conventional name or the panel consists of three or less constituents, we will include each of the distinct measured entities separated by ampersand (&) in the Component. We may also use a more efficient syntax that implies a repeat of the first part of the name, e.g., Chlamydia Ab IgM & IgG Panel.In general, LOINC creates different codes for panels that contain reflex testing versus those that do not. Such panels will include reflex in the Component name, and the general approach is to name the base panel and the kind of test(s) or test panel done as a reflex in the panel name. The reflex test(s) can be a single test, a group of tests, or a test panel.7.3.2 Property and ScaleBecause the Property typically varies across the elements of a panel, the Property (i.e. the second part of the LOINC name) for the panel term may be populated by a dash (-). Likewise, the Scale (5th part of the LOINC name) will be populated by a dash (-) if the panel elements contain different scales.7.3.3 Time Aspect and SystemBecause these parts of the LOINC name are typically consistent across the primary measures of a panel, the Time Aspect and System of a panel name are usually specified with the same conventions that apply to observation terms.7.3.4 Examples of LOINC Panel namesThe following are a few examples of LOINC Panels (Order Set Names):Table 27: Examples of LOINC Panel Names (Order Set Names)LOINC_NUMLOINC Fully Specified NameDescription24358-4Hemogram WO platelets panel:-:Pt:Bld:QnHCT & HGB & WBC & RBC & Indices24359-2Hemogram WO platelets & W manual differential panel :-:Pt:Bld:QnHemogram & Differential Count24317-0Hemogram & platelets WO differential panel:-:Pt:Bld:QnHCT & HGB & WBC & RBC & Indices & Platelets24338-6Gas panel:-:Pt:Bld:QnpH & PO2 & PCO2 on blood without specifying whether arterial, venous, or other source. The report would usually include an observation about the inspired O2 sent along with the report. It may include a variety of other patient characteristics sent by the requester and a variety of computed variables.24336-0Gas panel:-:Pt:BldA: QnpH & PO2 & PCO2 on arterial blood. The report would usually include an observation about the inspired O2 sent along with the report. It may include a variety of other patient characteristics sent by the requester and a variety of computed variables.24339-4Gas panel:-:Pt:BldV:QnpH & PO2 & PCO2 on venous blood. The report would usually include an observation about the inspired O2 sent along with the report. It may include a variety of other patient characteristics sent by the requester and a variety of computed variables.29274-8Vital signs measurement:Find:Pt:^Patient^MultiDiastolic Blood Pressure & Systolic Blood Pressure & Pulse Rate & Respiratory Rate

9424357-6Urinalysis macro (dipstick) panel:-:Pt:Urine:-Urinalysis dipstick results. Usually includes Glucose, Bilirubin, estimate of leukocytes, estimate of RBCs, estimate of bacteria, Ph, Specific gravity. But we do not make distinctions about the exact set of measures on the dipstick. The ordering clinician will not necessarily know what particular dipstick is being used and is not able or interested in making those distinctions.29576-6Bacterial susceptibility panel:-:Pt:Isolate:OrdQnWould include susceptibility results for the antibiotics relevant to the isolates and the kind of culture.7.4 Representing conditionalityWithin the LOINC panel structure, we can set an attribute for each element of the panel that denotes whether or not it should be present (conditionality) in the panel when resulted. The primary measures are always required, but the other elements of the panel may have different kinds of conditionality.The conditionality attribute is visible on the details pages for panel terms under the column “R/O/C” and stored in the ObservationRequiredInPanel field of the LOINC panels and forms file (available for download from the LOINC website).Through version 2.48 of the LOINC database, the conditionality choices were limited to R (Required), O (Optional) and C (Conditional). Examples of simple order sets with terms that are either R or O:Table 28: Example Order Sets24358-4Hemogram WO platelets panel-PtBldQnR/O/C26464-8LeukocytesNCncPtBldQnR26453-1ErythrocytesNCncPtBldQnR718-7HemoglobinMCncPtBldQnR20570-8HematocritVFrPtBldQnR30428-7Mean corpuscular volumeEntVolPtRBCQnR28539-5Erythrocyte mean corpuscular hemoglobinEntMassPtRBCQnR28540-3Erythrocyte mean hemoglobin concentrationMCncPtRBCQnR30384-2Erythrocyte distribution widthEntVolPtRBCQnO30385-9Erythrocyte distribution widthRatioPtRBCQnO24326-1Electrolytes 1998 panel-PtSer/PlasQnR/O/C2951-2SodiumSCncPtSer/PlasQnR2823-3PotassiumSCncPtSer/PlasQnR2075-0ChlorideSCncPtSer/PlasQnR2028-9Carbon dioxideSCncPtSer/PlasQnR33037-3Anion gapSCncPtSer/PlasQnOStarting with version 2.50 (December 2014), we expanded the choices beyond R, O and C to include R-a (Required with alternative), Rflx (Reflex) and Rflx-a (Reflex with alternative). The expanded choices better accommodate reflex tests, cases in which more than one test could be used to fulfill a given requirement of the panel, and focus the use of C (which had previously been used as a “catch-all” for many types).Table 29 describes the expanded set of conditionality choices.

95Table 29: Options for Term Conditionality within PanelsCodeMeaningDiscussion /DefinitionRRequiredMeans this test must be included.R-aRequired with alternativesMeans required but has alternatives. The alternatives will usually be paired, and both will be marked with the R-a code. Results for at least one member of the pair must be included in the panel to satisfy the required condition, but both may be included. The C, conditional, had been used to deal with these cases in the past.The rule for pairing up of the alternatives for a given purpose will be described in a narrative usually in the panel description because the same rule will apply to many pairings in the panel. For example, the LA panel includes lots of coagulation measures and almost all can be reported as an actual time and/or as the ratio of patient time to the normal time. Measures of the same clotting function that differ only by how they are reported would be considered paired alternatives in this panel. More specific pairing rules may also be asserted in the “condition for inclusion” field associated with each item in the panel.CConditionalMeans that the required status of a given variable depends on other factors. This was too much of a waste basket category, which is why we added some new categories to specify what had usually been lumped as conditional.OOptionalMeans the variable may be included or not, but whether it is included or not has no bearing on the whether a given set of result represents the given panel. Simple calculations derived from other reported measurements and ask at order entry questions are almost always optional.RflxReflexMeans this test will be included in the panel only if it satisfies a reflex condition based on other results in the panel. Such cases had also been lumped under the conditional code in the past. In general, we will not define specific rules for reflexing except in very general terms.Rflx-aReflex with alternativesMeans that that the test is a reflex but that another test in the panel can serve as an alternate and either or both of these reflex tests can be reported. But if the reflex condition is met, at least one of the alternative pairs must be included. As in the case of R-a, what tests pair up as alternatives will be defined in a narrative in the panel description of the condition for inclusion field. If more than one measure can serve as a primary measurement, then both of them will be required with alternatives (R-a), and the criteria is that at least one of them must be present. An example would be the absolute count of neutrophils versus the percentage of total white count of neutrophils in a differential blood count – if one is absent the other must be present (of course they are both often reported).The criteria or explanation for when the tests with R-a, Rflx and Rflx-a should be included in the results for a particular panel can be seen on the comprehensive details page available within RELMA and the online LOINC search application (search.loinc.org).Note that the conditionality assigned to a term is panel-specific. In other words, a given test may be required in one context and optional in another, which is why both the conditionality and criterion for inclusion only appear in the panel details and not in the individual term details.We should acknowledge that LOINC includes many panels without the required status having been marked and that the conditional status has not been employed everywhere that it could have been, and that many terms marked as conditional under the previous model probably would be better categorized as required with alternatives, reflex, or reflex with alternative. (We still have LOINC development work to do.)7.4.1 Lupus anticoagulant testing as an example of complex conditionalityHere we describe lupus anticoagulant testing as a prototype to illustrate the use of conditionality. At the core of lupus anticoagulant testing is a three step process using a given coagulation measure, such as dRVVT. The first is a screening to determine whether a clotting abnormality exists. The second is a mixing study, in which the patient specimen is mixed with pooled normal plasma (PNP) and the same test (e.g. dRVVT) is rerun. This second test is used to evaluate whether the clotting problem is due to a clotting factor deficiency, such as occurs

96in Hemophilia. The third is yet another repeat of the same test (e.g. dRVVT) mixed with excess phospholipid – also called the confirmatory test. Lupus anticoagulant is declared present if the addition of excess phospholipid normalizes the result. There are a number of variations in lupus anticoagulant testing algorithms across laboratories. Some labs do the confirm test second and the mixing study third (if needed). The International Society of Thrombosis and Haemostasis (ISTH) recommends using two clotting tests: dRVVT and aPTT-LA (lupus sensitive), each reflexing to confirm and/or mixing study. However, at least two labs use three screening tests, adding PT to the dRVVT and aPTT-LA, reflex to mixing and confirm studies from these, and add further reflex testing, including thrombin time and from that a reflex to reptilase time. There are also variations in how the results are reported, e.g. as actual clotting times and/or as ratios of the actual time to the time of normal. And some labs define the kind of phospholipid they use for the confirm study, i.e., hexagonal or platelet derived phospholipid.The lupus anticoagulant panel for three screening tests shown below illustrates a number of issues related to conditionality described above. The three screening tests (dRVVT, aPTT and PT) are all required but can either be reported as the actual result or actual/normal, therefore all six terms are assigned the conditionality R-a. The mixing and confirmatory tests as well as thrombin time and reptilase time are only run if any of the screening tests are out of range and when run, can also be report as actual or actual/normal; therefore, all of these terms are assigned Rflx-a. The dRVVT and aPTT percent correction and screen to confirm ratio may not be reported by all laboratories and therefore have an O status. Finally, the overall interpretation must be reported and so is assigned R.Figure 1. Details page for three screening test lupus anticoagulant panel

977.5 Approach to creating and defining distinct panels in LOINC7.5.1 General approachThe defining characteristics of a LOINC panel term include the enumerated set of child elements and the conditionality of those elements. Thus, users must pay close attention to the full panel structure in order to know whether it is an appropriate representation of their local panel.When LOINC defines a panel, it will include all of its primary measurements/observations (flagged as required), and will also include commonly reported derived observations (flagged as optional). When laboratories report an interpretation across many observations in a panel, such as the differential count or a serum electrophoresis, the LOINC panel will include an interpretation term specific to that panel (flagged as optional). Likewise, the panel will also contain commonly included AOE variables and other associated observations (flagged as optional).LOINC will not define distinct panels for different collections that vary only on the optional elements (whether or not there is an interpretation, an additional derived calculation, variables sent along with the request, etc.). As a corollary, users can match their local panels to LOINC panels whether or not their reported results include those optional elements.During the several years prior to the LOINC 2.56 release, the number of requests for panel terms steadily increased. At the same time, newer laboratory methods have led to the creation of lab kits that could be customized by the end-user in terms of the individual tests that were run. For example, if a kit includes ten different assays, one hospital might implement six while another hospital might implement all ten of the assays. In addition, each version of the kit could potentially have different combinations of tests. Many of our requests were for panels that differed only slightly from existing panels, likely in part due to differences in the aforementioned kit implementation. Going forward, it now appears impractical to create a unique panel for every hospital, laboratory, and test kit. Therefore, at the June 2016 meeting, the Laboratory LOINC Committee agreed upon the following business rules for new panel requests:7.5.1.1 Panels for test kitsWe will make generic panels for groups of tests that are not specific to a particular manufacturer or test kit but that are method- and system-specific. Such panels will not have conditionality or cardinality specified. As test kits evolve over time, additional children may be added, but none will be removed except in limited circumstances. Examples of such panels are:79381-0 Gastrointestinal pathogens panel – Stool by Probe and target amplification method82180-1 Meningitis+Encephalitis pathogens DNA and RNA panel – Cerebral spinal fluid by Target amplification with non-probe based detection7.5.1.2 Panels for individual laboratories and/or hospitalsIn general, we will not create new panels for every hospital and laboratory, based on their unique combination of elements. However, we likely will make panels when many hospitals and/or labs use the exact same set of elements.

987.5.1.3 Fully specified panelsWe will make panels with conditionality and cardinality details in cases where a specific guideline or standard of care exists, such as the lupus anticoagulant screening panel examples above.7.5.2 Preference for methodless panel definitionsIn most cases, LOINC will not make up different panel terms for the same set of tests done by different methods. Because of the possible mixtures of methods within a panel, representing these distinctions would cause an explosion of the distinct panel, which would (usually) be a burden on the ordering provider. Further, in a given setting the ordering provider can only order the methods that are provided by his usual producer. Implied in the order is “Give me the battery produced by your usual methods”. Thus, as a general approach we tend to create panels with child elements that are methodless.In special circumstances though, we do create panels of method-specific observations. For example, we have different panels for screen and confirm methods. In such cases, the method specification is the defining characteristic of the panel.7.5.3 Special cases where enumeration of child elements is not practicalThere are special cases where LOINC may define a panel term by a narrative definition because it is not practical to fully enumerate all of the possible child elements and their conditionality. For example, public health, veterinary medicine, and other laboratories that are not charging Medicare or Medicaid for the tests they perform are not bound by the rules that penalize labs for performing and charging for tests that the practitioner did not explicitly order. This makes creating order panels a little easier.In the case of public health, the tests performed by a laboratory in response to a request may be chosen from a list of many possible tests, based on information provided by the requester, and the laboratory’s judgment. For example, CDC’s “Campylobacter, Helicobacter and related organisms identification and subtyping” (CDC-10127) order can include tests that identify the phenotype, the genotype, Penner serotype, PFGE, or AST, and might use multiple test procedures for each of these.

998 Evolving principles for naming collections8.1 Goals and general approachWe are in the process of evolving our model for naming collections in LOINC. Our goals in refining this model are to:• Create names that are consistent across different subject domains within LOINC• Make it easy to create a list of all codes that could be used as document type in CDA• Make it easy to create a list of all codes that could be used as section headings in CDA• Avoid proliferating namesTo this end, we are developing rules for how the naming of collections will apply to both laboratory collections (CBC, CHEM7) coded and structured clinical collections (Vital Signs), documents (Admit History and Physical Exam), Apgar scores, Braden Scale, Pain scales, etc. There will be two categories of names for collections:• Names for panels with enumerated discrete contents, and• Names for general collections of information.Using the existing panel mechanisms, the LOINC database will record the association between LOINC collections and individual observations where these associations are known. For example, LOINC already records the expected contents for CBC, Liver Enzymes, etc. It will also include definitions for Vital Signs, Cardiac Catheterization, Braden Scale, surveys, etc. We will create a single LOINC code for any general collection of information where the information content of the collection is the same, regardless of whether the content is a text document, a scanned image of text, or a sound file of the same information.Since collections are named by their real or anticipated contents, the same LOINC code could be used as either a document type or as a section type.8.2 Collections as orders and observationsThe same LOINC code will be used for ordering a procedure, naming the document produced as the description of the procedure, or naming the structured and coded set of observations from the procedure.For panels, the same code for CBC would be used as the ordered item in an order record or message, and as the panel identifier in the OBR segment of a result record or message. The same pattern would be followed for laboratory procedures and clinical procedures.For general collections, the same code would be used as the ordered item in an order record or message, and as the result identifier in a result message. For example, the general collection name could be used in a result

100message as the identifier of a document type, as a section label, as the universal identifier in an OBR segment, or as the identifier in an OBX segment depending on the circumstances. The same pattern would be followed for radiology procedures and clinical procedures.We are not taking away the flexibility of having the ordered code be different from the result code. For example, it is often desirable for the order code to be less specific and more abstract than the result code. LOINC would contain codes for something like “Exercise EKG” with the expectation that the result could come back as “AHA Protocol Stress EKG Result”. The point is that, when appropriate, we would use the same LOINC code in the contexts of orders and results. We would NOT make LOINC codes that meant “CBC Order” and “CBC Result”. Rather, we would use the same LOINC code for CBC in both orders and results.Current practice would also continue where a “pure” procedure is ordered and discrete results would be returned. For example, Urine Microscopic Exam could be ordered and discreet values for cell types, casts, amorphous material, etc. would be returned.8.3 LOINC Scale for collectionsWhere the Scale for individual elements in a panel vary, the name of the panel term itself will be a dash (-). The Scale for general information collections will be Doc, short for document, which is used in the most general sense of a text document, image, scanned text image, etc. We are in the process of reviewing our current use of Nar (narrative) or Nom (nominal) for general information collections in some portions of the LOINC database and migrating towards broader use of Doc. We have already made such changes in some areas, for example Radiology and Molecular Pathology.

1019 Additional content in the LOINC distribution9.1 Additional attributes of LOINC terms9.1.1 NamesIn addition to the Fully Specified Name (FSN), which is the 5 or 6 major Parts of a LOINC term concatenated together using the colon character as a separator, each LOINC term has several different names that have been added as LOINC has evolved. Each of these was created for a different purpose and presently, they are generated programmatically with manual curation in special cases. We began with the Short Name and Long Common Name in 2002 and 2009, respectively.Even after creating the Long Common Name, we continued to receive periodic requests from users to produce “prettier” display names for use in user interfaces, etc. While systematically created LOINC Long Common Names can be guaranteed to be unique (except for truly duplicate concepts), they are sometimes not the most user-friendly. This is also true for our automatically-generated LOINC Short Names. However, mostly what users wished for were names that leave out some of the defining attributes of the term (e.g. Property, Scale, and “default” specimens in the System) because they are unfamiliar to clinicians. This is problematic across all of LOINC because it would create ambiguous and duplicate names. For such reasons, we have always expected that users would link their own local preferred names to LOINC terms for use in reports and displays. Within a given local system context it may be possible to resolve the ambiguities created by names that omit these attributes. For example, if the user display always shows the reported units of measure, then having the Property in the display name may not be necessary.However, we continued to think about how we could create a more “friendly” name and with the input of the LOINC Community, we developed the Consumer Name and Display Name as described below. We welcome feedback from anyone that has implemented or plans to implement these names.9.1.1.1 Short NamesIn August 2002 we added the Short Name, which is a short, mixed case name for the LOINC concept. All laboratory and clinical LOINC terms have a Short Name. (Many survey LOINC terms do NOT have a Short Name). Our goal was to produce names no longer than 40 characters in order to fit within the space allocated by most laboratory reporting systems. In contrast to the LOINC FSN, case is significant in the LOINC Short Name. When possible, we have used common acronyms and common names rather than the more formal name rules of the FSN. For example, we used the English names of allergens in the short names rather than the formal Latin species names (in part because they were shorter). We have used all upper case to represent acronyms, and mixed case in organism names as specified in naming conventions (e.g., genus is capitalized, species is not). For virus names we used the acronym assigned by Index Virum, where available.The LOINC Short Names are subject to change and should not be used as identifying keys in any database.

1029.1.1.2 Long Common NamesIn 2009, after collecting and reviewing display names from several sources, we began releasing the Long Common Name. These names are also created by an algorithmic process and are checked for uniqueness. Most abbreviations and acronyms that are used in the LOINC FSN have been fully spelled out in English. For allergens, the common English names are used instead of the more formal Latin species names. For coagulation, the more commonly used phrases, such as “Prothrombin time”, have been used.We started creating Long Common Names first for laboratory terms, but are now producing them for all terms. The text strings for the long common names are subject to change over time as we continue to refine the algorithmic process and collect feedback from users. In particular, many of the Long Common Names for clinical terms have not had as intense focus as the laboratory terms have, so we expect these to be refined over time. In LOINC release 2.54, many of the echocardiography and ophthalmology were updated based on input from DICOM and the National Eye Institute, respectively. Through the LOINC 2.65 release, every LOINC Long Common Name was unique. This was true even for deprecated duplicate terms, some of which had additional periods appended to their names in order to make them unique. However, the LOINC Committee recommended that concepts that are truly duplicate (i.e., have the exact same values for each of their major Parts) should have the same Long Common Name, and we have implemented this change starting with the LOINC 2.66 release.9.1.1.3 Display NameBeginning with LOINC version 2.64, we began publishing Display Names, which were developed as a prototype for a more “clinician-friendly” set of names compared to the current LOINC Short Name, Long Common Name, and Fully Specified Name. They are created algorithmically from the manually crafted display text for each Part and are generally more concise than the Long Common Name. Currently only LOINC Laboratory terms have Display Names, though we may add Display Names for Clinical terms in the future. In general, Display Names are unique for a given concept; however, in the case of truly duplicate concepts (i.e., have the exact same values for each of their major Parts), the Display Name will be the same. Unlike the Short Name and Long Common Name, the Display Name does not include an indicator that a term is deprecated.Some of the high-level rules used to create the Display Names include:• Components are shortened where possible using common abbreviations and conventions such as including only the first letter of the genus when a Component includes both the genus and species;• Systems Ser/Plas and ^Patient are implied, and all other Systems are included in parentheses; • Exception: for terms with the Property Susc, the System is implied• For Timing Pt is implied and all other Timing values are specified;• If the Scale is Qn, the Property value is included and Scale is not; • Exception 1 – for the Properties ACnc and Likelihood, the Property is left off and Scale is included • Exception 2 – when the Component contains words that make the Property redundant, the Property is left off• If the Scale is not Qn, the Scale is included instead of the Property; • Exception 1 – in a few cases (e.g., ID, Imp) where the Property conveys specific information about what result to expect, the Property is included • Exception 2 – Nom is implied

1039.1.1.4 Consumer NameThe Consumer Name was originally hand-crafted for a very small subset of LOINC terms. At its inception, these names were labeled as “experimental”. In 2019 we undertook a concerted effort to develop a more comprehensive set of consumer-friendly names, primarily based on the increasing availability of consumer-facing health and wellness apps that take advantage of existing LOINC codes for the underlying data.Consumer Names are created based on manually crafted consumer name text for each Part. In contrast to the other names, this text may represent a more general concept for the defining Part. These names do not represent each of the defining Parts of a given term, are not unique, and do not include an indicator that a term is deprecated.Consumer Names are intended for downstream display only and are not intended to be used at any point in the clinical workflow, or for the purpose of mapping local terms to LOINC.Some of the high-level rules used to create the Consumer Names include:• The specimen is placed at the end of the name and is prefixed by a comma;• Almost all intravascular specimens are labeled Blood, with a few exceptions such as Dried Blood Spot;• Property, Scale, and Method values are mostly excluded. This results in many duplicate Consumer Names and is based on the assumption that the result value and/or the units of measure will provide context for the name;• Abbreviations are not used except in select cases, such as HIV; however, some abbreviations are included in parentheses for education purposes.The current collection of Consumer Names have a “pre production” maturity level and we welcome user feedback about them. Until they reach production status, we plan to release them in a separate file rather than in the existing Consumer_Name field in the LOINC table.9.1.2 ClassesWe assign each LOINC term to a general category called a Class. These categories are relatively broad and are intended to make it easier to sort and browse the database. They are not intended to be binding definitional characteristics of the term, and we may refine them over time. A more detailed listing of the Classes is presented in Appendix B. Throughout this document many of the naming conventions and approaches are described in reference to a Class of terms. Here we provide a bit of explanation about some of the laboratory term Classes.The Class of Microbiology includes all tests used to identify microorganisms and evidence for infection by specific organisms as well as cultures direct microscopic exams that identify organisms or prove evidence for present or past infection with specific organisms. Microbiology includes tests for antibodies, antigens, DNA and RNA. The Serology Class does not include measures antibodies or antigens related to microorganisms. Molecular pathology Class does not include RNA or DNA based tests for infectious organisms. (They are all included in Microbiology.)The Class Blood bank includes all blood bank testing including ABO-Rh testing. Allergy Class includes testing for antibodies to allergens (cat dander, trees, etc.). Serology includes rheumatological, and autoantibodies, and antigen measures not covered by these two classes. Hematology/cell counts exclude coagulation studies that are found in a separate Class. Measures of complement activity are included within Hematology, not Chemistry. Chemistry does not include challenge tests such as Glucose tolerance, ACTH stimulation, etc.; these are in a separate category called Challenge tests.

1049.1.3 Categorizing LOINC terms as Order, Observation, or BothLOINC terms can be matched to local test codes that fulfill different roles. For example, a LOINC code can be used to place an order, to report discrete observations, or in some cases a LOINC term can serve in both ways.The purpose of the ORDER_OBS field in the LOINC database is to provide users with an idea of the intended use of the term by categorizing it as an order only, observation only, or both. A fourth category, Subset, is used for terms that are subsets of a panel but do not represent a collection of items that is known to be orderable. Our categorization of a term in this way is not a normative or binding resolution. That is, it is not a definitional attribute of the term. Rather, it represents Regenstrief’s best approximation of how the term is used. (If you feel a term should be categorized a different way, please let us know.)In HL7 messages, the place in the message where the LOINC code is used will indicate what role the LOINC term is fulfilling. If it is in OBX-3, it is being used as an observation. If it is in OBR-4, it is an order.Examples of each category include:Order Only34531-4 Blood type and Crossmatch panel – BloodThis term represents an order for a type and cross that would never carry an answer (i.e., result value). Panel terms typically fall in the Order only category.Observation Only 51890-2 Factor VIII units given [#]This term is a discrete observation that would carry a result of the number of units given to the patient, but would never be placed as an order for ‘Factor VIII Units given’.Both882-1 ABO and Rh group [Type] in BloodThis term could be used to place an order as well as report the result of the test (e.g., A Positive).9.1.4 Associated observationsIn the LOINC Table, a LOINC term can be linked to one or more optional “associated observations” in the AssociatedObservation field. Associated observations are additional variables that may be reported along with the primary observation. Within LOINC, we can link primary observation terms to other single LOINC terms or panels containing a set of terms.There are three main use cases for linking LOINC terms to other associated observations:1. Reporting information related to the primary result that otherwise might be reported using a comment field, such as the volume of urine in a 24-hour urine collection or specimen weight;2. Including key data in a structured, computable format when sending an otherwise unstructured text report or document;3. Identifying the sections and entries from HL7 Clinical Document Architecture (CDA) implementation guides that can be reported with certain LOINC document codes.

105Associated observations can be used in conjunction with lab results that are typically sent in an unstructured format, such as genetic testing results. We encourage laboratories to report as much data as they can using the discrete variable LOINC codes so that the data are more directly computable. For example, associated observations linked to a BRCA1 gene targeted mutation analysis may include concepts such as gene identifiers, the reason for genetic testing, genetic sequence variation that was found, genomic reference sequence, and specific version of the coding system that was used to report the results. At the same time, laboratories can still retain the flexibility of sending text reports that can be formatted for readability.Many LOINC document codes can be used with one or more related HL7 CDA implementation guides (IG). To facilitate identifying which sections (and sometimes entry level codes) may be used with a particular document code, we are working to link a panel of associated observations for each IG.9.1.5 Ask-at-order-entry (AOE)Ask-at-order-entry (AOE) observations in LOINC are observations obtained from the requester as part of the test order and generally delivered back to the requester as part of the result package. For example, the concentration of inspired oxygen is always an AOE question for blood gas measurements as well as the date of last menstrual period for pap smears.Within LOINC, we can connect AOE observations to the primary test using a similar structure as described for associated observations. The linkage between the primary observation and AOE observations is stored in the AskAtOrderEntry field of the LOINC Table. We have not implemented AOE observations extensively yet but have the mechanism in place, and we are working with multiple organizations to target specific domains, including infectious diseases and other public health domains such as lead testing.9.1.6 Related namesThe LOINC database includes a field (RELATEDNAMES2) for related names associated with LOINC terms. We provide these associations as a service to LOINC users to help them find the concepts they are searching for. We often colloquially use the word “synonym” when referring to related names, however, most of the terms in the RELATEDNAMES2 field are not true synonyms. Values in this field may include common names, abbreviations, previous nomenclature, common misspellings, allergen codes, and associated diseases. This information is intended to help users locate relevant concepts, but it may also result in “false-positive” search results due to overlap in the related names associated with different concepts. For example, one of the related names for Influenza is Flu, so searching for Flu will return LOINC codes relevant to Influenza. However, Flu is also associated with Fluid, so the same search for Flu will also return LOINC codes with the System of Body fluid, Amniotic fluid, etc.9.2 LOINC Answers (LA) and Answer Lists (LL)Across many domains, the meaning of a particular observation can be best understood in the context of the set of possible answers (result values). For example, the questions/items in standardized assessment instruments often have highly specialized, fixed answer lists. In many contexts, it is the answer list that most completely defines the meaning of the concept represented by the question. Additionally, because many of the answer choices are highly specialized, few are represented by existing codes in reference terminologies. For these reasons, we have created a structured representation of answer lists in LOINC.We identify the binding of LOINC observation codes to answer lists as “normative”, “preferred”, or “example”.Normative lists are those specifically defined by a validated instrument or other authoritative source.

106When using LOINC codes bound to normative answer lists, only answers in the specified set are allowed as result values. Examples of sources for Normative answer lists are PROMIS or the Clinical Pharmacogenetics Implementation Consortium (CPIC).Preferred lists contain a set of answers that users are strongly encouraged to use. They represent a recommended set, however, in contrast to a Normative list, alternate result values may be used if necessary. Preferred lists may come from a variety of sources, including professional organizations (e.g., American Physical Therapy Association), device manufacturers, and government (e.g., Centers for Diseases Control and Prevention, National Eye Institute).Example lists are meant to be illustrative of possible result values. Users can also think of them as a starter set to which they may add or subtract depending on their use case. Many of the Example answer lists are in the lab domain, where different labs may report similar results in a variety of ways, such as “Positive”, “Present”, “Detected”, “Abnormal” or “Out of range” but for which we have a single Example answer list.Starting in the version 2.61 release, we have created a mechanism by which a single LOINC term may be linked to multiple answer lists with different binding strengths defined in the context of a given panel. For example, if two different survey instruments have the exact same question with two different answer lists, rather than making two different codes with different Methods, we now have the ability, within the context of a panel, to attach a different answer list to the same question. We will only use this mechanism when the meaning of the observation is the same across panels. If the observations represent different questions, we will make different codes. We will apply this format to new terms moving forward and plan to update existing terms over time.Not all answer lists are fully enumerated within LOINC. For example, some questions may have their answers drawn from a large terminology such as ICD-9-CM or CPT and we do not reproduce those lists within the LOINC structure. Answer lists that are not enumerated within LOINC are flagged to indicate that they are externally defined. We record the answer list OID (whether assigned by Regenstrief or another organization) and optionally a URL pointing to the external system.Individual answers are assigned a non-semantic identifier with a “LA” prefix and a mod-10 check digit (see Appendix C). The answer codes LOINC assigns are unique by lexical string (ignoring capitalization), and by intention do not distinguish between strings that may have different meanings depending on their contextual use.LOINC answer lists are also assigned a non-semantic identifier with a “LL” prefix and a mod-10 check digit (see Appendix C). LOINC answer lists are available for viewing in the RELMA program and on details pages. There are details pages for each LOINC answer list, and the answer list also appear as a section of the details pages for LOINC terms they are associated with.Beginning with LOINC version 2.61, answer lists (and answers) are also available in the Answer artifact, which is a separate download from the LOINC website. This file includes two tables: one includes all of the Answer lists (including information about each list as well as the answer strings it contains) that are associated with LOINC terms in the current release, and the second contains links between all of the LOINC terms that have answer lists and those lists. Please see the AnswerFile_Readme.txt document included in the AnswerFile for more information.9.2.1 Null flavors in LOINC Answer listsIt is often necessary to indicate that a valid result value is not present. For example, a question on a questionnaire might have a set of response choices and then one choice at the end like “unknown”, “not applicable”, “not available”, etc. In HL7 standards, these kinds of response values are called null flavors (see https://www.hl7.org/fhir/v3/NullFlavor/index.html).

107There are two techniques for communicating a null flavor. In version 3 messaging, there is a dedicated nullFlavor attribute that is available for every observation, so these choices are not part of the actual answer list. In version 2 messaging and FHIR, the convention includes the specific allowed null flavors within the choices of the answer set. We can see advantages to both approaches.Within LOINC, we do not want to make different answer lists that vary only by the inclusion or exclusion of certain null flavors. This is true even for Normative answer lists. Thus, our policy is to add specific null flavors as entries in the answer list where we are aware of their relevance. But, any LOINC answer list (including Normative lists) can be extended or limited by null flavors without violating the intended conformance that is specified through the binding. So, if a Normative answer list included an “unknown” answer choice, LOINC would not create a separate code for the same observation with “not available” in the answer list instead of “unknown”. From the perspective of conformance to the LOINC meaning, users are also free to make such substitutions, insertions, or exclusions of null flavor(s) in the answer list.9.3 LOINC Parts and Part hierarchiesIn order to support several key aspects of development, Regenstrief has created LOINC parts, which are a coded representation of a value for a dimension used to specify a LOINC term. LOINC parts support the translation of LOINC terms into other languages, easy linking of synonyms across many terms, the creation of hierarchies to group related LOINC terms, and several other functions.Individual LOINC parts are assigned a non-semantic identifier with a LP prefix and a mod-10 check digit. The intended use of the LOINC parts and LOINC part hierarchies are to organize or be constituents of LOINC terms. As described in the LOINC license, they are not intended for use as a “standalone” terminology nor apart from LOINC terms.Furthermore, LOINC parts and LOINC part hierarchies are not strictly managed under the same policies (e.g. concept orientation, concept permanence) as are LOINC terms.9.3.1 Part distributionBeginning with LOINC version 2.61, we are releasing a Part artifact as a separate download from the LOINC website. This file includes three tables: one includes all of the Parts associated with all of the LOINC terms in the current release, the second contains links between LOINC terms and their parts, and the third has mappings between a subset of Parts and related codes from external standard terminologies such as SNOMED CT. Please see the PartFile_Readme.txt document included in the PartFile for more information.9.4 DescriptionsLOINC contains two types of descriptions, one at the Part level and one at the term level. Descriptions are attached to parts when the information is specific to the part, such as Component or Method, and they are attached to the term when the information applies to the term as a whole and not to any individual part of the term. For example, the Component part Glucose is associated with a description for the carbohydrate glucose, while the following term description describes the Peritoneal Equilibration Test, which applies to the combination of Glucose, Overnight dwell and Peritoneal dialysis fluid:79264-8 Glucose [Moles/volume] in Peritoneal dialysis fluid –overnight dwell

108A Peritoneal Equilibration Test (PET) is used to assess transport properties of the peritoneal membrane in patients undergoing peritoneal dialysis. Patients arrive at the dialysis unit in the morning with their overnight dwell fluid still in the abdomen. The overnight fluid is completely drained and sampled for testing. In the classic PET, 2000 ml of a 2.27% glucose solution is instilled and peritoneal dialysis is begun. Ten ml samples are drawn at time 0, 2, and 4 hours to measure creatinine, urea, and glucose. The PET assesses the rate of solute equilibration between peritoneal capillary blood and dialysate based on the ratio of the solute concentrations in dialysate and plasma (D/P). PET results are used to adjust various aspects of a patient’s peritoneal dialysis regimen, including dwell time, number of exchanges, and dialysis volume and composition. [PubMed: 7474677]9.5 LOINC Table CoreBeginning with LOINC version 2.61, we are providing an artifact called LoincTableCore that is available as a separate download from the LOINC website. The purpose of this core table is to provide essential LOINC content in a format that is more stable over the long-run. The core table contains all of the LOINC terms that are in the complete table (i.e., the same number of rows), but a subset of the fields (i.e., different number of columns). The fields included in the core table are ones that are both crucial for defining each LOINC term and whose structure is not likely to change in the short-term. We are providing this format in order to make it easier for implementers to update to the latest LOINC release without having to make changes to their database structure. However, depending on their use case, some implementers may still need to refer to the complete LOINC table in order to find all of the relevant information.9.6 LOINC GroupsBeginning with LOINC version 2.61, we are providing an artifact called Groups that is available as a separate download from the LOINC website. The goal of the LOINC groups project is to create a flexible, extensible, and computable mechanism for rolling up groups of LOINC codes for various purposes. Representative use cases include aggregating data for displaying on a flowsheet within an EHR system, retrieving data for quality measure reporting, and collecting data for research. This is a work in progress and the contents of the file and the groupings MUST be validated by users prior to implementation in any aspect of clinical care. Please see the GroupFile_Readme.txt document contained in the GroupFile for more information.

10910 Standardized assessment measures10.1 IntroductionThe LOINC committee approved inclusion of standardized assessment measures (e.g., survey instruments) with version 1.0p. Representing the observations in these assessments within LOINC required a modest extension of the System axis to include aggregate units of analysis, such as ^family, and storage of additional attributes within the LOINC database. Bakken30 provides a detailed description of the methodology for inclusion and evaluation into LOINC and the extensions to the LOINC axes.The initial corpus of material represented in LOINC came from standardized nursing assessment instruments. We have since expanded the content to cover standardized assessment instruments in many other domains. As we have added content, we have iteratively refined our modeling. Vreeman et al have published a summary of our approach and its evolution.3110.2 LOINC representationThe overall organization of the survey instruments and other collections are represented in LOINC using a nested panel structure consistent with the existing model for laboratory panels. LOINC terms are created for the individual questions/items within an instrument, as well as for the panels/groups of terms representing the hierarchical nature of the instrument. We recognize that standardized assessments have psychometric properties that are essential to their interpretation, and so the data model includes elements such as the actual question text and allow answer options as attributes of the LOINC observation term.10.2.1 Naming rules and conventions for names of collection terms (e.g. a panel, sur-vey instrument)LOINC creates terms for the collection as described in the section on Order Panels (batteries). Typically, the Property and Scale attributes are a hyphen (-), because the child elements (questions) vary in these axes. We create different panel terms for different versions of the same instrument where there are meaningful changes (e.g. different questions asked, different answer choices, etc). Some assessment instruments of the same version have different “forms” for various purposes that contain unique collections of items. For example, the OASIS-C has five unique forms that represent different subsets of questions that are used at various times: Start of Care, Resumption of Care, Follow-up, Transfer to a Facility, and Discharge from Agency. LOINC creates different panel terms for each of these forms.10.2.2 Attributes of the LOINC terms for individual questions or variables30 Bakken S, et al. Evaluation of Clinical LOINC (Logical Identifiers, Names, and Codes) for Terminology Model for Standardized Assessment of Measures. JAMIA 7:2000; 529-538. [PubMed: 11062226]31 Vreeman DJ, McDonald CJ, Huff SM. LOINC® – A Universal Catalog of Individual Clinical Observations and Uniform Representation of Enumerated Collections. Int J Funct Inform Personal Med. 2010;3(4):273-291. Epub 2011 May 23. [PubMed: 22899966]

110The LOINC table contains fields that store additional attributes relevant to many terms for individual questions or variables. Examples include the fields that store the exact question text, external copyright notice, example units, and the HL7 field where the content should be delivered (if Null, presume OBX).In order to accommodate inclusion of instruments that are copyrighted by a third party, we have added an external copyright field to the LOINC Table (EXTERNAL_COPYRIGHT_NOTICE). This field stores the specified terms of use, and additionally, these terms are visually highlighted in the RELMA program when they appear in search results. We have only included content in this manner that is consistent with LOINC’s overall aim, so the content allows free use and distribution for clinical, administrative, and research purposes either with permission or under applicable terms of use.LOINC does not usually create terms for information that has a designated field in an HL7 message. But, in order to create complete sets of items for some instruments we have created LOINC terms for items such as patient first name. To identify this content, we added an HL7 Field Sub ID to the LOINC table and indicate the corresponding HL7 place (e.g. PID-5.2).10.2.3 Structured answer listsThe questions/items in standardized assessment instruments often have highly specialized, fixed answer lists. As described in Section 9.2, we have created a structured representation of the answer lists for the questions in assessment instruments represented in LOINC.10.2.4 Attributes of items that vary depending on the parent collectionSome important attributes of a LOINC term for a question or variable may vary when that concept is used in different assessments or on different forms of the same assessment. For example, “measured body weight” is a variable of many different assessments. In the context of each instrument, that same concept could have different local codes, help text, validation rules, or associated branching logic. We therefore store these attributes at the level of the instance of the item in a particular panel.10.2.5 Choosing the “display text” for a question or variableAs discussed in the previous sections, we have three fields that can capture the exact display of the question/item on the form in question. (For some instruments, it can be difficult to determine what exactly is the question text.) The Component of a LOINC term represents the thing or attribute being measured, and is the default for capturing the item text. However, there are several reasons why the Component may not be the exact item text. The most important ones include: our LOINC naming conventions do not permit certain characters (e.g. “/” or “?”) because of our internal “Part” parsing rules, that some aspects of the question are modeled in other parts of the formal LOINC name, or that there is some important aspect to the “thing being measured” (e.g. a lookback period of the last 7 days) that is not represented explicitly on the form for that particular item.In general, for purposes of displaying the item text as it appears on the instrument, one can follow this rule:1. DISPLAY_NAME_FOR_FORM in the FORM_DATA table (RELMA) or FORMS table (CSV file export) [if populated]. This field provides an override display that is linked to the instance of the LOINC question code in a particular form. It allows for the same clinical concept to have slight presentation variances on different forms where those variances have no change in the concept meaning and accommodates instances where the LOINC naming conventions require some difference between the item and the LOINC Component. For example, an item might have the form label of “Body Mass Index (BMI)” but the LOINC Component would simply be Body mass index. We have also used the DISPLAY_NAME_FOR_FORM field in cases where minor edits in question text (e.g. referring to the subject as “patient” versus “resident”) vary by form but do not have a significant change in question meaning.

111 If the question or variable is from a survey:2. SURVEY_QUEST_TEXT in the LOINC table [if populated]. This field is populated when the variable/item is asked as a question. In some cases, the variable has both a question and a label. In these cases, the SURVEY_QUEST_TEXT field is populated with both, in the pattern of [Label].[Question text]. For example, for item J0300 on the MDS version 3 we have “Pain Presence. Ask resident: ‘Have you had pain or hurting at any time in the last 7 days?’”3. COMPONENT in the LOINC table. This is the default display. Else:4. SHORTNAME in the LOINC table. This field contains a short display name (target is 40 characters or less).5. COMPONENT in the LOINC table. This is the default display.In addition to these fields, some LOINC codes used in survey instruments may have other LOINC name fields such as a Long Common Name and Consumer Name. These additional names may be useful in some contexts for these items, but we will still use the above rule to capture the item’s representation in the instrument. Some of the original survey instruments modeled in LOINC may not follow this rule exactly, in part due to the fact that we did not have the full survey representation model as we do presently. Ongoing work includes reviewing where modifications may be needed.10.2.6 Type of Method (6th part) for a question or variableFor variables linked to a defined answer list that come from an external source, it has become our policy to enter the initial source as the Method. For example, variables first entered for the Minimum Data Set (MDS) will have a Method of MDS. This does not mean that the term cannot be used in any other contexts, such as other panels or surveys. As long as the defining context of use is understood, the variable can be used in other contexts where the term is exactly the same, including the answer lists, as the original term.10.2.7 Time Aspect (3rd part) for a question or variableBeginning with the June 2015 LOINC release, the Time Aspect for survey questions that include a lookback period specify that lookback period as the Time rather than using Pt. This change was approved by the LOINC Clinical Committee at the February 2015 Clinical LOINC meeting and will apply to all new terms moving forward.At the August 2015 Clinical LOINC meeting, further naming conventions were approved. These conventions include:• Using the exact timing given in a validated survey question as the Time Aspect value (i.e., for questions with a 7-day lookback period, using 7D for Time Aspect rather than 1W)• Adding Lifetime as a possible Time Aspect value• For questions with a lookback range, using the longer end of the range for Time Aspect (e.g., if the question asks “In the last 2-6 months…”, the Time Aspect value will be 6Mo).As of LOINC version 2.54, nearly all of the existing survey instrument terms that include a lookback period have an updated Time Aspect part, and we will continue to make these changes moving forward for any terms that were not updated for the 2.54 release.

11210.2.8 Form InformationAssessment instruments often contain additional text either preceding or following an item to guide users in completing the form or provide additional context about the item. LOINC uses two fields, form CodingInstructions and Context, to represent this information.When the text gives details about completing the form, for example, “Enter 88 if patient does not answer or is unable to respond”, that text is represented as form CodingInstructions.When the text provides additional explanation or description, it is typically represented as Context. For example, along with an item recoding the number of stage 2 pressure ulcers a patient has, the form may display a clinical explanation of what a stage 2 ulcer is: “Stage 2: Partial thickness loss of dermis presenting as a shallow open ulcer with a red or pink wound bed, without slough. May also present as an intact or open/ruptured blister.” Such text is represented as Context.These form-specific attributes are displayed on the LOINC details pages and are present in the LOINC Panels and Forms File.10.3 Assessment content in the LOINC distributionBeginning with LOINC version 2.26 (January 2009), an export of panels and forms content has been available as a separate download in the LOINC release called the LOINC Panels and Forms File. This package contains the full assessment content, including:1. The hierarchical structure (parent/child relationships) and panel-specific attributes2. An extract of the main LOINC Table for all of the terms in the set3. The structured answer list for each LOINC variable term in the setThis content is available for download from the LOINC website. Please see the PanelsAndFormsReadMe.txt file in the LOINC Panels and Forms File for more details. All of the assessment content is also included within the RELMA program. 10.4 In-progress updates through our collaboration with CMS on post acute care assessmentsThrough a collaboration with Centers for Medicare and Medicaid Services (CMS), we are updating the current LOINC representation of CMS Long-term Post Acute Care (LTPAC) assessments and creating new LOINC representations for CMS PAC assessments not currently represented in LOINC. The work includes the Nursing Home Minimum Data Set (MDS), Long-term Care Hospital CARE Data Set (LCDS), In-Patient Rehabilitation Facility Patient Assessment Instrument (IRF-PAI), and the Home Health Outcome and Assessment Information Set (OASIS).Our work on this content began in August 2016, and starting with LOINC version 2.63 (December 2017), new and updated content represents current versions of all four CMS LTPAC assessments. As we continue to collaborate with CMS, we plan to release the LOINC representation for each new version of these assessments prior to its CMS final publication date so that the LOINC content will be available for implementation at the time of final publication.

113In undertaking this work, the LOINC Committee agreed to adopt a unified Method of CMS Assessment across all instruments, rather than having a Method specific to the assessment instrument that was first modeled in LOINC. This change encourages and facilitates re-use of assessment variables across instruments where appropriate.We have also enhanced the RELMA program with links to the CMS assessment item codes that are searchable as “Related Codes”. For example, searching “RelatedCodes: BB0700” in RELMA will return the LOINC term that represents the CMS assessment item “Expression of ideas and wants”.

11411 Editorial policies and procedures11.1 Concept orientation and LOINC name changesLOINC is a concept-based terminology, which means that it provides a way of naming classes of things that exist in the real world. Each concept (term) is given an identifier and a fully-specified name. Other attributes, including other names such as a Short Name and Long Common Name, are also provided in the LOINC database. The concept is anchored by the LOINC code, not by the particular strings in the formal name we happen to use to explain the code. It is certainly not possible to convey all of the subtleties that exist in the world with formal machinery alone, which is why we are also working very hard to include narrative text descriptions with each term that further elaborate and explain the concept.In a complex, organic terminology like LOINC, name changes and modifications are unavoidable for many reasons. Since its inception, LOINC has maintained a set of editorial policies that guide our adherence to this concept-oriented ideal even as the terminology evolves over time. An over-arching policy is that we can change the name (i.e. the human-readable representation of the concept) in any way that does not change the meaning of the concept. In other words, a modification is allowable and valid if it is still an unambiguous reference to a class of things in the real world.For example, two different numbering systems have been used to identify the serotypes of Streptococcus pneumoniae, which are important in gauging the coverage of polyvalent pneumonia vaccines. The U.S. system uses only numbers while the Danish system includes numbers and letters. For a period of time, LOINC term names were split and used a mixture of the Danish and U.S. identifiers. Subsequently, we converted the few Danish serotype identifiers to their corresponding U.S. serotype identifiers. Even more recently, when we found out that the Danish nomenclature is, in fact, the one that is commonly used both internationally as well as in the U.S., and that the numbers assigned to serogroups and serotypes identified over the last several years made our existing terms ambiguous and confusing, we did a thorough review of our existing terms. As described in more detail in the Streptococcus pneumoniae serotype nomenclature technical brief, we deprecated all of the terms that were ambiguous and mapped them to new terms. In addition, we updated the names for the ones ones that were not ambiguous, because this was not a fundamental change to the underlying concept, but rather just the particular labels used to express it.Not all situations are crystal clear, so our general policy is to seek as much input as is feasible, and often, such cases are brought for discussion to the LOINC Committee.11.2 Classification of LOINC term statusLOINC development follows best practices for terminology system development by never reusing or deleting codes. If a LOINC term is identified as erroneous or a duplicate of a previous term it is flagged as deprecated in the database, but the record is not removed. Changes in concept status are made very judiciously.Prior to the LOINC version 2.31 release (June 2010), we identified such deprecated terms by populating the STATUS field of the database with DEL and wherever possible identified superseding concepts in the MAP_TO field of the LOINC Table. Active (non-deprecated) records had no value (null) in the STATUS field. Based on new use

115cases and input from the LOINC community, LOINC 2.31 implemented an expansion to that classification. The presently supported values for term Status, with the definition and implications for use, are:StatusDescriptionACTIVEConcept is active. Use at will.TRIALConcept is experimental in nature. Use with caution as the concept and associated attributes may change.DISCOURAGEDConcept is not recommended for current use. New mappings to this concept are discouraged; although existing mappings may continue to be valid in context. Wherever possible, the superseding concept is indicated in the MAP_TO field of the MapTo Table (see Appendix A, Table 31b) and should be used instead.DEPRECATEDConcept is deprecated. Concept should not be used, but it is retained in LOINC for historical purposes. Wherever possible, the superseding concept is indicated in the MAP_TO field of the MapTo Table (see Appendix A, Table 31b) and should be used both for new mappings and updating existing implementations.Furthermore, LOINC 2.31 added two new fields:STATUS_REASONClassification of the reason for concept status. This field will be Null for ACTIVE concepts, and optionally populated for terms in other statuses where the reason is clear. DEPRECATED or DISCOURAGED terms may take values of: AMBIGUOUS, DUPLICATE, or ERRONEOUS.STATUS_TEXTExplanation of concept status in narrative text. This field will be Null for ACTIVE concepts, and optionally populated for terms in other statuses.Our initial implementation of these new concept status values in LOINC 2.31 populated the STATUS field with ACTIVE or DEPRECATED based on their existing status and have identified a limited set of terms that have been designated DISCOURAGED or TRIAL.The principal reason identifying terms as DISCOURAGED is where we have strong inclinations that a particular term is no longer valid given current practice. For example, we have flagged as DISCOURAGED several lutropin terms with Properties consistent with mass or molar units because all lutropin sources that we could reach report concentrations in international units (IU) per volume and the drug lutropin is prescribed in terms of international units per volume. To avoid confusion on the part of mappers, the DISCOURAGED Status steers them away from these terms to the more likely candidates.The principal reason for identifying terms as TRIAL is a very constrained circumstance, such as when the source of the term is still equivocating. This has been illustrated in our work to create a LOINC representation of federally-required patient assessment instruments. Here, the item meaning is defined in the context of use within that instrument. We have been fortunate to work with assessment developers in the early stages of instrument development. This is advantageous because it enables the codes to be included in data specifications and documents as they are developed, but we are in the position of creating codes and names for data elements whose attributes are still in flux. As the instrument evolves, the specific representation of the item (question) or answer options on the form may change. Ultimately, the representation will be settled by an authoritative body (such as CMS) and they are intended for use in one context – the official release of the instrument. Identifying these terms as TRIAL allows us to include them in the public distribution while clearly flagging their “pending” status. Once the final concept representation has been determined, terms initially labeled TRIAL would be reclassified as ACTIVE (or perhaps in rare circumstances DEPRECATED or even rarer DISCOURAGED).In LOINC 2.42, the MAP_TO field of the LOINC Table was removed and replaced with a separate MapTo table. The original MAP_TO field was created to store a single replacement LOINC term number for when a LOINC was deprecated. We later learned that there were times when there was more than one possible replacement term, depending on certain conditions. To address this problem we created a new MapTo table that was first released with version 2.34. The original MAP_TO field was retained for a few releases, but was removed from the LOINC Table in version 2.42. See Appendix A, Table 31b for information about the MapTo table.In rare cases, we have had to “undeprecate” DEPRECATED terms when upon further, very careful review, we discovered that the concepts are, in fact, valid. Such terms will revert back to a STATUS of ACTIVE but can be

116identified by the value UNDEL in the Chng_Type field. We have chosen to undeprecate the codes in such rare cases (instead of making new terms) because DEPRECATED terms continue to be included in the LOINC database, and some users may continue to use such concepts or have historical data associated with those codes. If we were to create new codes for the same concept, different users could potentially use different codes to identify the exact same data.11.3 Concept persistence and term deprecationLOINC codes are never reused or deleted, and the concept meaning is persistent over time despite the fact that there may be modifications to the name (as described above). If we discover that a LOINC term’s meaning is a duplicate of another existing term or it is somehow erroneous, it will be given a Status of DEPRECATED but not removed from the database.In the past, when we encountered duplicate terms (i.e. terms that had different names but meant the same thing), our general policy was to deprecate the newest term. Many times, this convention worked well because the older term was more likely to have been incorporated into user’s systems through mappings, etc. However, this was not always the case. Sometimes, the new term had the clearer, more recognizable label and thus it was most likely the most mapped-to term. Therefore, our current policy is to make the change to require (in our estimation) the least amount of re-mapping for existing users.Our general policy is not to make any edits to a term once it is DEPRECATED. However, in rare cases we may update one or more names of DEPRECATED terms in order for them to correctly represent the original meaning of the term. For example, in LOINC 2.66, the Long Common Name for 26693-2, which has the Component Streptococcus pneumoniae 12f Ab, was updated from Deprecated Streptococcus pneumoniae 12 Ab [Mass/volume] in Serum to Deprecated Streptococcus pneumoniae 12f Ab [Mass/volume] in Serum.11.4 Publication of LOINC codes in advance of official releasesSupported by the LOINC Committee, Regenstrief has had a long-standing policy of returning new LOINC codes to those who made the request (i.e. the submitter) as soon as the LOINC term passes our internal QA processes rather than waiting for the next official release. The LOINC Committee has also approved Regenstrief’s publication of the new codes on the LOINC website after they pass internal QA but in advance of the next official release. It is understood that providing these codes back to the requestor and listing them on the LOINC website is done for informational purposes only, with the additional caveat that the concept could change prior to inclusion in a public release. The public should not be expected to have adopted such “pre-released” LOINC codes until they appear in a formal release. Yet, such an approach is valuable because it facilitates the inclusion of new codes in implementation guides and other documents and systems that have their own, often lengthy, development cycles.11.5 File versioning and namingBeginning with the June 2018 LOINC release, we implemented a policy on versioning and naming of LOINC release artifacts that was approved by the LOINC Committee. This policy includes approaches to version numbers, major versus minor (or patch) changes, and content versus file structure changes. See the LOINC Versioning page on our website for details.

11712 Recommendations for best practices in using and mapping to LOINC12.1 Business rules for users mapping their local panels to LOINC panelsThrough discussion with the ACLA, the S&I Framework aLOINC Order Code Initiative, and others, the LOINC Committee has vetted a set of business rules to help LOINC users understand how to compare their panels to a LOINC panel. These rules help clarify what variation is allowed within the LOINC panel definition that still constitutes a “match” for their panel. In these rules, we use “element” to mean a child LOINC that is a member of the panel definition.12.1.1 Must contain all of the required elementsTo establish equivalence (e.g. for mapping), a user panel must contain all of the required elements of a LOINC panel. Some of the other business rules define allowable substitutions, but the general rule is that all required elements must be present in the user panel.12.1.2 No extra primary measurementsA user panel cannot be considered equivalent to a LOINC panel term if it contains additional primary measured tests that are not part of the LOINC panel definition.12.1.3 Optional elements are optionalA user panel can be considered equivalent to a LOINC panel term whether or not it contains the elements marked as optional in the LOINC panel definition.12.1.4 Substitutions related to MethodPanel elements that do not contain a Method specification (i.e. the Type of Method part is null) can be treated as a “representative” term that a user could replace with another LOINC term that differed only by specification of Method.For example, LOINC contains an adenovirus panel:55160-6 Adenovirus IgG and IgM panel – Serumwith two elements that lack Method specification:13914-7 Adenovirus IgG Ab [Units/volume] in Serum

1185042-7 Adenovirus IgM Ab [Units/volume] in SerumIf a user had a local panel that was similar but had instead mapped to terms that specified the Method of EIA, they may wonder whether their panel was equivalent to the panel in LOINC. Using this business rule, the answer is yes. Either or both of the methodless LOINC panel elements could be replaced by these method-specific LOINC terms that are equivalent on the other attributes:51822-5 Adenovirus IgG Ab [Units/volume] in Serum by Immunoassay51823-3 Adenovirus IgM Ab [Units/volume] in Serum by ImmunoassayHowever, when a panel element measures an analyte by a particular method, then the LOINC term reported for that analyte would have to be done by that method. Neither replacement by a methodless term nor by a different method would be allowed.12.1.5 Substitutions for mass versus substance PropertiesLOINC defines different terms that distinguish between mass-based and substance-based (moles/milliequivalents) measures for a single analyte. Different jurisdictions vary in whether they favor reporting in mass units (e.g. mg/dL) or molar units (e.g. mmol/L) for certain analytes.In order to promote the international reuse of panels, the LOINC Committee has agreed (at its June 2015 meeting) to allow users to substitute panel elements that a) agree on all other LOINC parts, and b) contain an analogous molar Property to a reference element with a mass Property or vice versa.To illustrate, panel element terms with the Property of mass concentration (MCnc) could be replaced by substance concentration (SCnc) terms, mass rate (MRat) terms could be replaced by substance rate (SRat), terms etc. For example, in the Lipid panel with direct LDL – Serum or Plasma (LOINC: 57698-3) a user could make substitutions as below and still have a comparable panel:Reference term: 2093-3 Cholesterol [Mass/volume] in Serum or PlasmaSubstitute term: 14647-2 Cholesterol [Moles/volume] in Serum or PlasmaReference term: 2571-8 Triglyceride [Mass/volume] in Serum or PlasmaSubstitute term: 14927-8 Triglyceride [Moles/volume] in Serum or PlasmaAnd so forth.12.1.6 No substitutions of quantitative for qualitative (and vice versa)A quantitative panel element (e.g. one that has a Scale of Qn) cannot be replaced by a qualitative term (e.g. one that has a Scale of Ord) and have the panel be considered equivalent. Likewise, qualitative terms cannot be replaced by quantitative terms in the panel definition.12.1.7 Pay attention to reflex elementsLOINC defines different panels for testing that has reflex elements from ones that do not. Thus, users must be aware of the test(s) done as a reflex both in their local panels and in the LOINC definition. The reflex test(s) can be a single test, a group of tests, or a test panel. A user panel is comparable to the LOINC panel if the specification of reflex testing is the same.

11912.1.8 Special case of differential counts (including conventions for not reporting zero counts)Panels, like blood differential counts and urinalyses, for which zero counts (e.g. for the % of blast cells) are usually not reported explicitly present a special case. These are included in the panel definition but are marked as conditional (C) to signal that under some circumstances (e.g., when they have a value of zero), they are not reported. Differential counts present another problem in that a given cell type could be reported as a fraction of the total WBC and/or as an absolute count, so both species are included in the panel for differential counts, but as discussed above, both are not required in the report.12.1.9 Panels with only narrative definitions of the elements they should containAs described above, in certain special cases, such as public health and veterinary testing, LOINC may define a panel term by a narrative definition rather than enumerating the set of child elements. In such cases, the user must read the definition and use their professional judgment as to whether or not their local panel is comparable to the LOINC panel.12.2 Examples of applying the business rules for users mapping their local panels to LOINC panels12.2.1 Comparison Panel: Varicella zoster virus IgG and IgM panel – Serum (LOINC: 45063-5)This user-defined panel is considered comparable since the component tests are the same and it is acceptable to use method- specific LOINC codes for panels defined with methodless LOINC codes.Elements of LOINC PanelLOINC_NUMLong Common NameR/O/C8048-1Varicella zoster virus IgM Ab [Units/volume] in SerumR8047-3Varicella zoster virus IgG Ab [Units/volume] in SerumRElements of User-defined PanelLOINC_NUMLong Common Name5404-9Varicella zoster virus IgM Ab [Units/volume] in Serum by Immunoassay5403-1Varicella zoster virus IgG Ab [Units/volume] in Serum by Immunoassay12.2.2 Comparison Panel: Creatine kinase panel – Serum or Plasma (LOINC: 24335-2)This user-defined panel is not considered to be comparable since it includes two additional measured components that are not in the LOINC Panel.

120Note The inclusion of an Optional component in the LOINC Panel does not have a bearing on the comparability of the user-defined panel.Elements of LOINC PanelLOINC_NUMLong Common NameR/O/C2157-6Creatine kinase [Enzymatic activity/volume] in Serum or PlasmaR20569-0Creatine kinase.MB/Creatine kinase.total in Serum or PlasmaR9642-0Creatine kinase.BB/Creatine kinase.total in Serum or PlasmaR9643-8Creatine kinase.MM/Creatine kinase.total in Serum or PlasmaR5912-1Creatine kinase isoenzymes [interpretation] in Serum or PlasmaOElements of User-defined PanelLOINC_NUMLong Common Name2157-6Creatine kinase [Enzymatic activity/volume] in Serum or Plasma20569-0Creatine kinase.MB/Creatine kinase.total in Serum or Plasma9642-0Creatine kinase.BB/Creatine kinase.total in Serum or Plasma9643-8Creatine kinase.MM/Creatine kinase.total in Serum or Plasma26020-8Creatine Kinase.macromolecular type 2/Creatine kinase.total in Serum or Plasma26019-0Creatine Kinase.macromolecular type 1/Creatine kinase.total in Serum or Plasma12.2.3 Comparison Panel: Drugs of abuse 5 panel – Urine by Screen method (LOINC: 65750-2)This user-defined panel is considered to be comparable since the components use the same method-specific LOINC terms and the additional test is a non-measured component (i.e., it is a variable provided by the requester that is echoed back with the results).Elements of LOINC PanelLOINC_NUMLong Common NameR/O/C19261-7Amphetamines [Presence] in Urine by Screen methodR14314-9Benzoylecgonine [Presence] in Urine by Screen methodR18282-4Cannabinoids [Presence] in Urine by Screen methodR19295-5Opiates [Presence] in Urine by Screen methodR19659-2Phencyclidine [Presence] in Urine by Screen methodRElements of User-defined PanelLOINC_NUMLong Common Name19261-7Amphetamines [Presence] in Urine by Screen method14314-9Benzoylecgonine [Presence] in Urine by Screen method18282-4Cannabinoids [Presence] in Urine by Screen method19295-5Opiates [Presence] in Urine by Screen method19659-2Phencyclidine [Presence] in Urine by Screen method

12141395-5Collection date of Urine12.3 Querying LOINC and creating intensional value set definitions based on LOINC database structureSpecifications that contain queries meant to be run on the LOINC distribution or that contain intensional value set definitions should be expressed with the LOINC attributes contained in Appendix A – LOINC Database Structure. (In JSON representations such as HL7’s FHIR, the LOINC attribute serves as the key in an object’s property definition. Not to be confused with the LOINC notion of Property, in JSON, a key-value pair is often referred to as a property). The available LOINC attributes are the items listed in the Field Name column of that table. Unless Regenstrief publishes a definitive specification otherwise (see discussion of canonical LOINC representation in FHIR below), these names, and their spellings, are the official attribute names. For example, specifying the set of LOINC terms with a scale of document would reference the LOINC attribute SCALE_TYP and its value of DOC.In addition, for LOINC codes that are part of the Document Ontology or those that are radiology procedure codes, there are additional attributes that may be used in attribute-based Value Set Definition components. All attributes will have string values that may be used for the attribute (property) value part of the definition. Some will also have coded identifiers (e.g. LOINC Part codes) that can be used in addition to the string.For Document Ontology:• Document.Kind• Document.TypeOfService• Document.Setting• Document.Role• Document.SubjectMatterDomainThese Document Ontology attributes are currently published in the accessory Document Ontology File (available as a separate download from the LOINC website), and will likely be extended in the future. They will always be the unique values in the PartTypeName field of the Document Ontology File. Starting with the LOINC version 2.61, these are also published in the LOINC Part File artifact (also available as a separate download). For Radiology:• Rad.Guidance for.Presence• Rad.Guidance for.Approach• Rad.Guidance for.Action• Rad.Guidance for.Object• Rad.View.Aggregation• Rad.View.View type• Rad.Reason for Exam

122• Rad.Maneuver.Maneuver type• Rad.Timing• Rad.Pharmaceutical.Substance Given• Rad.Pharmaceutical.Route• Rad.Anatomic Location.Region Imaged• Rad.Anatomic Location.Laterality.Presence• Rad.Anatomic Location.Laterality• Rad.Anatomic Location.Imaging Focus• Rad.Modality.Modality type• Rad.Modality.Modality subtype• Rad.SubjectThese radiology attributes are published in the PartTypeName field of both the LOINC/RSNA Radiology Playbook File and the LOINC Part File. Both of these artifacts are available as a separate download from the LOINC website.12.3.1 Canonical representation of LOINC as a FHIR CodeSystemTogether with the HL7 FHIR® team, we are working to create a specification for the canonical representation of LOINC in FHIR as a CodeSystem resource. This is a work in progress. An initial draft of that specification is available at https://loinc.org/fhir/loinc.xml.This specification is specific to HL7 FHIR®, and it’s definitions of the LOINC attributes would supercede the general guidance about names for attributes (properties) given above. For example, in the canonical representation for FHIR, the radiology LOINC attribute Rad.View.Aggregation will be named closer to the conventions for FHIR-style property names as “rad-view-aggregation”.12.4 The Code System for identifiers assigned by LOINCAll of the identifiers assigned by LOINC, including LOINC codes, Part codes (i.e. LP* codes), Answer codes (i.e. LA* codes), Answer List codes (i.e. LL* codes), and Group codes (i.e. LG codes) collectively belong to the LOINC code system. Depending on your technology or application, you may identify the code system in different ways. For example, in HL7 Version 2 it would typically be the abbreviation “LN”, in CDA documents it would be an OID (2.16.840.1.113883.6.1), and in FHIR it would be the URI “http://loinc.org”.12.5 LOINC term names in HL7 messagesMessaging standards like HL7 typically use a triplet <identifier code>^<descriptive text>^<coding system> for fields that contain coded entries, such as the OBX-3 Observation Identifier field. Given that LOINC now produces at least 3 names for each term (i.e., the six-part Fully-Specified Name, Short Name, and Long Common Name), users have wondered which LOINC name they should use in the <descriptive text> part of that field (or

123the equivalent displayName attribute in HL7 V3).Regenstrief and the LOINC Committee assert that best practice is to send the Long Common Name to accompany the LOINC code in messaging. The Long Common Name is complete, unambiguous, and the most understandable LOINC description for human readers.We recognize that there may still be some information systems today that are not able to accommodate the character length of the Long Common Name. We strongly recommend updating such systems to accommodate longer names. The LOINC Short Name is smaller in size, but not very human friendly and is not populated for all LOINC terms. (We are working to improve on both of these issues). Using the Fully-Specified Name (e.g. a colon-separated aggregate of the six part name) is generally not recommended because they are not as human friendly and contain more instances of ‘reserved characters’ like “^” and “&”, which would need to be properly escaped in the message.Furthermore, we recommend the simultaneous communication of the sender’s local code and local name (in addition to the LOINC code and name) as allowed in the messaging structure to facilitate debugging and detection of mis-mappings. Laboratory local codes are often required to be sent by the performing laboratory to meet CLIA (U.S) and laboratory accreditation regulatory requirements in many countries.It is also worth noting that use of the Long Common Name in messaging does not dictate which test name is displayed in user interfaces to clinicians. There are often regulatory requirements and/or local policies that influence what is shown to clinicians. Many of the implementations around the world using LOINC have a local “interface name” that users see. LOINC is working in the background.12.6 Updating to new versions of LOINCAt the December 2015 Lab LOINC Committee meeting. Regenstrief and the LOINC Committee approved the following best practice:We recommend that users update to the current version of LOINC within 90 days of its publication.12.7 Using URIs to identify LOINC artifactsIn the context of RDF, OWL, and other technologies, URIs are the expected type of identifiers. Some LOINC users have asked for an approved convention for referring to LOINC-created identifiers (e.g. LOINC codes, LOINC Answer List Codes, LOINC Answer String Codes, etc). Here we describe approved patterns for use. Please note that this is an active area of discussion.12.7.1 Using a URI to identify LOINC as a code systemIn HL7 FHIR®, code systems are identified by URIs. As described in the section on LOINC as a code system, the recommended URI for this purpose is:http://loinc.org12.7.2 Using a URI to identify LOINC concepts as resources in RDFThe subject of an RDF statement is a uniform resource identifier (URI), or a blank node. After discussion at the Clinical LOINC Committee meeting in August 2015, we agreed to the following patterns:

124For LOINC Terms:http://loinc.org/rdf/{LOINC code}e.g., http://loinc.org/rdf/2352-3For LOINC Parts:http://loinc.org/rdf/{LOINC Part code}e.g., http://loinc.org/rdf/LP6990-8In our current platform, URLs of these patterns resolve to the concept details pages (as used by search.loinc.org and RELMA).Note: prior versions of the FHIR standard listed the preferred LOINC pattern as http://loinc.org/owl. The current version of FHIR has has updated that guidance to be consistent with our recommendations in this document.12.7.3 Using a URI to identify LOINC concepts as a value setIn some contexts, LOINC Parts, LOINC Answer Lists, and LOINC Groups represent value sets. LOINC represents the Multiaxial Hierarchy as a tree where LOINC Parts comprise all of the branches in the and LOINC terms comprise all of the leaf nodes. LOINC Answer Lists represent collections of coded concepts that can be used as response values to LOINC terms. LOINC Groups aggregate a set of LOINC terms that share certain characteristics. In these cases, LOINC defines an implicit value set associated with the code (e.g. a LP* code, a LL* code, or an LG* code).Here we define a convention to make explicit when you are referring to these entities as either a) a code in the terminology or b) the implicit value set associated with the code.When referencing the code itself, follow the usual pattern of referencing identifiers from the LOINC code system.When referencing the implicit value set, use this pattern for the value set identifier as a URI: http://loinc.org/vs/{id}For LOINC Parts:http://loinc.org/vs/{LOINC Part code}e.g., http://loinc.org/vs/LP148409-8For LOINC Answer Lists:http://loinc.org/vs/{LOINC Answer List code}e.g., http://loinc.org/vs/LL715-4For LOINC Groups:http://loinc.org/vs/{LOINC Group code}e.g., http://loinc.org/vs/LG9568-9

125Appendix A LOINC Database StructureTable 31a: LOINC Table StructureField NameTypeWidthDescription1. LOINC_NUMText10The unique LOINC Code is a string in the format of nnnnnnnn-n.2. COMPONENTText255First major axis-component or analyte3. PROPERTYText255Second major axis-property observed (e.g., mass vs. substance)4. TIME_ASPCTText255Third major axis-timing of the measurement (e.g., point in time vs 24 hours)5. SYSTEMText255Fourth major axis-type of specimen or system (e.g., serum vs urine)6. SCALE_TYPText255Fifth major axis-scale of measurement (e.g., qualitative vs. quantitative)7. METHOD_TYPText255Sixth major axis-method of measurement8. CLASSText255An arbitrary classification of the terms for grouping related observations together. The current classifications are listed in Table 32. We present the database sorted by the class field within class type (see field 23). Users of the database should feel free to re-sort the database in any way they find useful, and/or to add their own classifying fields to the database. The content of the laboratory test subclasses should be obvious from the subclass name.9. VersionLastChangedText255The LOINC version number in which the record has last changed. For records that have never been updated after their release, this field will contain the same value as the loinc.VersionFirstReleased field.10. CHNG_TYPEText255Change Type Code DEL = delete (deprecate) ADD = add PANEL = addition or removal of child elements or change in the conditionality of child elements in the panel or in sub-panels contained by the panel. NAM = change to Analyte/Component (field #2); MAJ = change to name field other than #2 (#3 – #7); MIN = change to field other than name UND = undelete11. DefinitionDescriptionMemo-Narrative text that describes the LOINC term taken as a whole (i.e., taking all of the parts of the term together) or relays information specific to the term, such as the context in which the term was requested or its clinical utility.

12612. STATUSText255ACTIVE = Concept is active. Use at will. TRIAL = Concept is experimental in nature. Use with caution as the concept and associated attributes may change. DISCOURAGED = Concept is not recommended for current use. New mappings to this concept are discouraged; although existing may mappings may continue to be valid in context. Wherever possible, the superseding concept is indicated in the MAP_TO field in the MAP_TO table (see Table 31b) and should be used instead. DEPRECATED = Concept is deprecated. Concept should not be used, but it is retained in LOINC for historical purposes. Wherever possible, the superseding concept is indicated in the MAP_TO field (see Table 31b) and should be used both for new mappings and updating existing implementations.13. CONSUMER_NAMEText255An experimental (beta) consumer friendly name for this item. The intent is to provide a test name that health care consumers will recognize.14. CLASSTYPENumber-1=Laboratory class; 2=Clinical class; 3=Claims attachments; 4=Surveys15. FORMULAMemo-Contains the formula in human readable form, for calculating the value of any measure that is based on an algebraic or other formula except those for which the component expresses the formula. So Sodium/creatinine does not need a formula, but Free T3 index does.16. SPECIESText20The species field has not been maintained and is a source of confusion. The values have been set to NULL for the 2.67 release in preparation for removing the field in the December 2020 release.17. EXMPL_ANSWERSMemo-For some tests and measurements, we have supplied examples of valid answers, such as “1:64”, “negative @ 1:16”, or “55”.18. SURVEY_QUEST_TEXTMemo-Verbatim question from the survey instrument19. SURVEY_QUEST_SRCText50Exact name of the survey instrument and the item/question number20. UNITSREQUIREDText1Y/N field that indicates that units are required when this LOINC is included as an OBX segment in a HIPAA attachment21. SUBMITTED_UNITSText30Units as received from person who requested this LOINC term22. RELATEDNAMES2Memo-This field was introduced in version 2.05. It contains synonyms for each of the parts of the fully specified LOINC name (component, property, time, system, scale, method).23. SHORTNAMEText255Introduced in version 2.07, this field contains the short form of the LOINC name and is created via a table-driven algorithmic process. The short name often includes abbreviations and acronyms.24. ORDER_OBSText15Defines term as order only, observation only, or both. A fourth category, Subset, is used for terms that are subsets of a panel but do not represent a package that is known to be orderable. We have defined them only to make it easier to maintain panels or other sets within the LOINC construct. This field reflects our best approximation of the terms intended use; it is not to be considered normative or a binding resolution.25. CDISC_COMMON_TESTSText1“Y” in this field means that the term is a part of subset of terms used by CDISC in clinical trials.

12726. HL7_FIELD_SUBFIELD_IDText50A value in this field means that the content should be delivered in the named field/subfield of the HL7 message. When NULL, the data for this data element should be sent in an OBX segment with this LOINC code stored in OBX-3 and with the value in the OBX-5.27. EXTERNAL_COPYRIGHT_NOTICEMemo-External copyright holders copyright notice for this LOINC code28. EXAMPLE_UNITSText255This field is populated with a combination of submitters units and units that people have sent us. Its purpose is to show users representative, but not necessarily recommended, units in which data could be sent for this term.29. LONG_COMMON_NAMEText255This field contains the LOINC name in a more readable format than the fully specified name. The long common names have been created via a table-driven algorithmic process. Most abbreviations and acronyms that are used in the LOINC database have been fully spelled out in English.30. UnitsAndRangeMemo-Units of measure (expressed using UCUM units) and normal ranges for physical quantities and survey scores. Intended as tailorable starter sets for applications that use LOINC forms as a way to capture data. Units are separated from normal ranges by a colon (:) and sets of unit:normal range pairs are separated by a semi-colon (;). Syntax for the normal range includes square brackets, which mean that the number adjacent to the bracket is included, and parentheses, which means that the number itself is not included. For example, [2,4] means “two to four”, while [2,4) means “two to less than four” and (2,4) means “between two and four but does not include two and four”.31. EXAMPLE_UCUM_UNITSText255The Unified Code for Units of Measure (UCUM) is a code system intended to include all units of measures being contemporarily used in international science, engineering, and business. (www.unitsofmeasure.org) This field contains example units of measures for this term expressed as UCUM units.32. EXAMPLE_SI_UCUM_UNITSText255The Unified Code for Units of Measure (UCUM) is a code system intended to include all units of measures being contemporarily used in international science, engineering, and business. (www.unitsofmeasure.org) This field contains example units of measures for this term expressed as SI UCUM units.33. STATUS_REASONText9Classification of the reason for concept status. This field will be Null for ACTIVE concepts, and optionally populated for terms in other status where the reason is clear. DEPRECATED or DISCOURAGED terms may take values of: AMBIGUOUS, DUPLICATE, or ERRONEOUS.34. STATUS_TEXTMemo-Explanation of concept status in narrative text. This field will be Null for ACTIVE concepts, and optionally populated for terms in other status.35. CHANGE_REASON_PUBLICMemo-Detailed explanation about special changes to the term over time.36. COMMON_TEST_RANKNumber-Ranking of approximately 2000 common tests performed by laboratories in USA.37. COMMON_ORDER_RANKNumber-Ranking of approximately 300 common orders performed by laboratories in USA.38. COMMON_SI_TEST_RANKNumber-Corresponding SI terms for 2000 common tests performed by laboratories in USA

12839. HL7_ATTACHMENT_STRUCTUREText15This field will be populated in collaboration with the HL7 Attachments Work Group as described in the HL7 Attachment Specification: Supplement to Consolidated CDA Templated Guide. As of Version 2.58, the text will either be “IG exists” (previously STRUCTURED) or “No IG exists” (previously UNSTRUCTURED) for relevant terms. The “IG exists” terms are those that have clinically-relevant HL7 implementation guides that use the U.S. Realm Header. The “No IG exists” terms are those approved by the HL7 Attachments WG for transmission using the Unstructured Document template of the C-CDA.40. EXTERNAL_COPYRIGHT_LINKText255For terms that have a third party copyright, this field is populated with the COPYRIGHT_ID from the Source Organization table (see Table 31c below). It links a external copyright statement to a term.41. PanelTypeText50Describes a panel as a “Convenience group”, “Organizer”, or “Panel”. A “Panel” is an enumerated set of terms that are used together in direct clinical care. The package would typically be thought of as a single orderable item that contains a set of reported observations. A “Convenience group” is an enumerated set of terms used for a common purpose, but not typically orderable as a single unit. An “Organizer” is a subpanel (i.e., a child) within another panel that is only used to group together a set of terms, but is not an independently used entity. They often represent a header in a form, or serve as a navigation concept.42. AskAtOrderEntryText255A multi-valued, semicolon delimited list of LOINC codes that represent optional Ask at Order Entry (AOE) observations for a clinical observation or laboratory test. A LOINC term in this field may represent a single AOE observation or a panel containing several AOE observations.43. AssociatedObservationsText255A multi-valued, semicolon delimited list of LOINC codes that represent optional associated observation(s) for a clinical observation or laboratory test. A LOINC term in this field may represent a single associated observation or panel containing several associated observations.44. VersionFirstReleasedText255The LOINC version number in which the record was first released. For oldest records where the version released number is known, this field will be null.45. ValidHL7AttachmentRequestText50A value of ‘Y’ in this field indicates that this LOINC code can be sent by a payer as part of an HL7 attachment request for additional information.46. DisplayNameText255This field contains a name that is more “clinician-friendly” compared to the current LOINC Short Name, Long Common Name, and Fully Specified Name. It is created algorithmically from the manually crafted display text for each Part and is generally more concise than the Long Common Name.Table 31b: MapTo Table StructureField NameTypeWidthDescription1. LOINCText10The deprecated term to which the replacement term(s) apply.2. MAP_TOText10A replacement term that is to be used in place of the deprecated or discouraged term.3. COMMENTMemo-Narrative text that explains the rational for using the recommended replacement term.

129Table 31c: SourceOrganization Table StructureField NameTypeWidthDescription1. IDNumber-A unique numeric identifier for the source. This identifier does not have any meaning outside of LOINC.2. COPYRIGHT_IDText255Used in the LOINC table as a foreign key.3. NAMEText255Name of the organization or institution.4. COPYRIGHTMemo-Copyright notice to be displayed for the organization or institution.5. TERMS_OF_USEMemo-Terms of use text for an external source.6. URLText255URL link to the reference.

130Appendix B ClassesTable 32a: Clinical Term ClassesAbbreviationClinical Term ClassADMINAdministrativeADMIN.DEMOGDemographic observationsADMIN.FACILITYFacility informationADMIN.IDIdentification numbersADMIN.PATIENTPatient administrative informationADMIN.PATIENT.DEMOGPatient demographicsADMIN.PATIENT.IDPatient identification numbersAPTAAmerican Physical Therapy AssociationARTAntiretroviral therapyAUDIOAudiologyBDYCRC.ATOMBody circumference atomicBDYCRC.MOLECBody circumference molecularBDYHGT.ATOMBody height atomicBDYHGT.MOLECBody height molecularBDYSURF.ATOMBody surface atomicBDYTMP.ATOMBody temperature atomicBDYTMP.MOLECBody temperature molecularBDYTMP.TIMED.MOLECBody temperature timed molecularBDYWGT.ATOMBody weight atomicBDYWGT.MOLECBody weight molecularBP.ATOMBlood pressure atomicBP.CENT.MOLECBlood pressure central molecularBP.MOLECBlood pressure molecularBP.PSTN.MOLECBlood pressure positional molecularBP.TIMED.MOLECBlood pressure timed molecularBP.VENOUS.MOLECBlood pressure venous molecularCARDCardiologyCARD.PROCCardiac proceduresCARD.RISKCardiac Risk Scales FraminghamCARD.USCardiac ultrasound (was US.ECHO)CARD.US.DICOMDICOM Simplified Adult Echo Report conceptsCARDIO-PULMCardiopulmonaryCLINClinical NEC (not elsewhere classified)CLIN.RISKClinical RiskCLIN.VETClinical veterinaryCLINTRIALClinical trailsDENTALDental

131DEVICESMedical devicesDOC.EPSOSSmart Open Services for European Patients (epSOS) documentsDOC.MISCMiscellaneous documentationDOC.ONTOLOGYDocument OntologyDOC.PUBLICHEALTHPublic health documentationDOC.QUALITYQuality documentsDOC.REFReferral documentationDOC.REF.CTPClinical trial protocol documentDOCUMENT.REGULATORYRegulatory documentationEDEmergency (DEEDS)EKG.ATOMElectrocardiogram atomicEKG.IMPElectrocardiogram impressionEKG.MEASElectrocardiogram measuresENDO.GIGastrointestinal endoscopyEYEEyeEYE.ANGIO.NEINEI eyeGENE’s angiography conceptsEYE.CONTACT_LENSOphthalmology contact lensEYE.EOG.NEINEI eyeGENE’s electrooculogram conceptsEYE.ERG.NEINEI eyeGENE’s electroretinogram conceptsEYE.GLASSESOphthalmology glasses: Lens manufacturer (LM) & PrescriptionEYE.HETEROPHORIAOphthalmology heterophoriaEYE.HX.NEINEI eyeGENE’s eye history conceptsEYE.OCTOphthalmology Optical Coherence Tomography (OCT)EYE.OCT.NEINEI eyeGENE’s optical coherence tomography conceptsEYE.PXOphthalmology physical findingsEYE.PX.NEINEI eyeGENE’s eye physical exam conceptsEYE.REFRACTIONOphthalmology refractionEYE.REFRACTION.NEINEI eyeGENE’s refraction conceptsEYE.RETINAL_RXOphthalmology treatmentsEYE.SLITLAMP.NEINEI eyeGENE’s slit lamp biomicroscopy conceptsEYE.TONOMETRYOphthalmology tonometryEYE.TONOMETRY.NEINEI eyeGENE’s tonometry conceptsEYE.USOphthalmology ultrasoundEYE.VISUAL_FIELDOphthalmology visual fieldEYE.VISUAL_FIELD.NEINEI eyeGENE’s visual field conceptsFUNCTIONFunctional status (e.g., Glasgow)GEN.USGeneral ultrasoundGIGastroenterologyH&P.HXHistoryH&P.PXPhysicalH&P.SURG PROCSurgical procedureHEMODYN.ATOMHemodynamics atomicHEMODYN.MOLECHemodynamics molecularHL7.CCDAHL7 Consolidated Clinical Document ArchitectureHRTRATE.ATOMHeart rate atomic

132HRTRATE.MOLECHeart rate molecularHRTRATE.PSTN.MOLECHeart rate positional molecularHRTRATE.TIMED.MOLHeart rate timed molecularIEEE RosettaIEEE RosettaIO.TUBEInput/Output of tubeIO_IN.ATOMInput/Output atomicIO_IN.INFUSInfusion pump intake measuresIO_IN.MOLECInput/Output molecularIO_IN.SUMMARYInput/Output summaryIO_IN.TIMED.MOLECInput/Output timed molecularIO_IN_SALTS+CALSInput/Output electrolytes and caloriesIO_OUT.ATOMInput/Output atomicIO_OUT.MOLECInput/Output molecularIO_OUT.TIMED.MOLEInput/Output timed molecularMEDSMedicationsNEMSISNational EMS Information System dataNEONATNeonatology variablesNEURONeurologyNIH.COGNITIVENIH Toolbox Cognitive DomainNIH.MOTORNIH Toolbox Motor DomainNIH.SENSORYNIH Toolbox Sensory DomainNUTRITION&DIETETICSNutrition and DieteticsOB.USObstetric ultrasoundOBGYNObstetric/GynecologyONCOLOGYOncologyPANEL.ADMINAdministrative information panelPANEL.APTAAmerican Physical Therapy Association panelPANEL.ARTAntiretroviral therapy order setPANEL.BDYTMPBody temperature order setPANEL.BPBlood pressure order setPANEL.CARDIACCardiology panelPANEL.CLINClinical NEC (not elsewhere classified) setPANEL.CLIN.RISKClinical risk panelPANEL.CVCardiovascular panelPANEL.DEVICESMedical device panelPANEL.DOCDocument panelPANEL.EDEmergency (DEEDS) order setPANEL.EYEOphthalmology panelPANEL.FUNCTIONFunction order setPANEL.H&PHistory & Physical order setPANEL.HL7.CCDAHL7 Consolidated Clinical Document Architecture setPANEL.IEEE ROSETTAIEEE Rosetta panelPANEL.IOInput/Output panelPANEL.MEDSMedication panelPANEL.NEMSISNational EMS Information System data set

133PANEL.NEONATNeonatal measure panelPANEL.NIH.COGNITIVENIH Toolbox Cognitive Domain panelPANEL.NIH.MOTORNIH Toolbox Motor Domain panelPANEL.NIH.SENSORYNIH Toolbox Sensory Domain panelPANEL.NUTRITION&DIETNutrition and dietetics panelPANEL.OB.USObstetrical panelPANEL.ONCOOncology panelPANEL.PATIENT SAFETYPatient safety order setPANEL.PHENXPhenX panelPANEL.PHRPersonal health record panelPANEL.PULMPulmonary panelPANEL.RADRadiology panelPANEL.SURGSurgery panelPANEL.TRAUMATrauma panelPANEL.TUMRRGTTumor registry panelPANEL.UPDRSUnified Parkinson’s Disease Rating Scale (UPDRS) setPANEL.US.UROUrology ultrasound panelPANEL.VACCINVaccination panelPANEL.VITALSVital signs panelPATIENT SAFETYPatient safetyPHENXPhenXPUBLICHEALTHPublic HealthPULMPulmonary ventilator managementRADRadiologyRESP.ATOMRespiratory atomicRESP.MOLECRespiratory molecularRESP.TIMED.MOLECRespiratory timed molecularSKNFLD.MOLECSkinfold measurements molecularSURGSurgeryTRAUMATraumaTRNSPLNT.ORGANOrgan transplantTUMRRGTTumor registry (NAACCR)UPDRSUnified Parkinson’s Disease Rating Scale (UPDRS)US.UROUrological ultrasoundVACCINVaccinationsVOLUME.MOLECVolume (specimen) molecularTable 32b: Laboratory Term ClassesAbbreviationLaboratory Term ClassABXBACTAntibiotic susceptibilitiesALLERGYAllergy testingBLDBKBlood bankBLDBK.GENOTYPINGBlood bank genotypingCELLMARKCell markersCHALChallenge tests

134CHAL.ROUTINERoutine challenge testsCHALSKINSkin challenge testsCHEMChemistryCOAGCoagulation studyCYTOCytologyDRUG/TOXDrug levels & ToxicologyDRUGDOSEDrug dose (for transmitting doses for pharmacokinetics)FERTFertilityHEM/BCHematology/Cell countsH&P.HX.LABHistory for laboratory studiesHL7.CYTOGENClinical cytogenetic reportHL7.GENETICSClinical genetic reportHLAHLA tissue typing antigens and antibodiesHNAHuman neutrophil alloantigensHPAHPA typingLABORDERSLaboratory order codesMICROMicrobiologyMISCMiscellaneousMOLPATHMolecular pathologyMOLPATH.DELDUPGene deletions or duplicationsMOLPATH.INVGene inversionMOLPATH.MISCGene miscellaneousMOLPATH.MUTGene mutationMOLPATH.NUCREPEATNucleotide repeatsMOLPATH.PHARMGPharmacogenomicsMOLPATH.REARRANGEGene rearrangementMOLPATH.TRISOMYGene chromosome trisomyMOLPATH.TRNLOCGene translocationNR STATSNormal range statisticsPANEL.ABXBACTAntibiotic susceptibility panelPANEL.ALLERGYAllergy panelPANEL.BLDBKBlood bank panelPANEL.BLDBK.GENOTYPEBlood bank genotyping panelPANEL.CELLMARKCell marker panelPANEL.CHALChallenge panelPANEL.CHEMChemistry panelPANEL.COAGCoagulation panelPANEL.DRUG/TOXDrug level & Toxicology panelPANEL.FERTFertility testing panelPANEL.HEDISHealthcare Effectiveness Data and Information Set panelPANEL.HEM/BCHematology & blood count panelPANEL.HL7.CYTOGENHL7 cytogenetics panelPANEL.HL7.GENETICSHL7 genetics panelPANEL.HLAHLA panelPANEL.HNAHNA panel

135PANEL.HPAHPA panelPANEL.MICROMicrobiology panelPANEL.MISCMiscellaneous panelPANEL.MOLPATHMolecular pathology panelPANEL.MOLPATH.PHARMGPharmacogenomics panelPANEL.OBSObstetrics panelPANEL.PATHPathology panelPANEL.SEROSerology panelPANEL.SPECSpecimen setPANEL.UAUrinalysis panelPATHPathologyPATH.HISTOHistologyPATH.PROTOCOLS.BRSTPathology protocols – breastPATH.PROTOCOLS.GENERPathology protocols – generalPATH.PROTOCOLS.PROSTPathology protocols – prostatePATH.PROTOCOLS.SKINPathology protocols – skinSEROSerology (antibodies and most antigens except blood bank and infectious agents)SPECSpecimen characteristicsUAUrinalysisTable 32c: Attachment Term ClassesAbbreviationAttachment Term ClassATTACHAttachmentATTACH.AMBAmbulance attachmentATTACH.CARDCardiac attachmentATTACH.CLINRPTClinical report attachmentATTACH.CPHSChildren’s Preventative Health System attachmentATTACH.EDEmergency department attachmentATTACH.GENERALGeneral attachmentATTACH.GIGastrointestinal attachmentATTACH.LABLaboratory attachmentATTACH.MEDSMedication attachmentATTACH.MODIFIERModifier attachmentATTACH.OBSObstetrics attachmentATTACH.PERIODONTALPeriodontal attachmentATTACH.REHABRehabilitation attachmentATTACH.REHAB.ABUSEAlcohol/Substance abuse rehabilitation attachmentATTACH.REHAB.CARDIACCardiac rehabilitation attachmentATTACH.REHAB.NURSSpecialized nursing attachmentATTACH.REHAB.OTOccupational therapy attachmentATTACH.REHAB.PSYCHPsychiatric rehabilitation attachmentATTACH.REHAB.PTPhysical rehabilitation attachmentATTACH.REHAB.PULMPulmonary rehabilitation attachmentATTACH.REHAB.RTRespiratory rehabilitation attachmentATTACH.REHAB.SOCIALMedical social work attachment

136ATTACH.REHAB.SPEECHSpeech therapy rehabilitation attachmentATTACH.RESPRespiratory attachmentPANEL.ATTACH.MODModifier attachment panelTable 32d: Survey Term ClassesAbbreviationSurvey Term ClassPANEL.SURVEY.AAOSAmerican Academy of Orthopaedic SurgeonsPANEL.SURVEY.ACTAsthma Control Test (ACT) setPANEL.SURVEY.ADVAULTADVault survey setPANEL.SURVEY.AHRQAgency for Healthcare Research and Quality (AHRQ) survey setPANEL.SURVEY.ALSFRSRALS Functional Rating Scale – Revised setPANEL.SURVEY.AMNARTAmerican National Adult Reading Test (AmNART) setPANEL.SURVEY.BIMSBrief Interview for Mental Health Status (BIMS) setPANEL.SURVEY.BDIBeck Depression Inventory (BDI) setPANEL.SURVEY.BPIBrief Pain Inventory (BPI) setPANEL.SURVEY.CAMConfusion Assessment Method (CAM) setPANEL.SURVEY.CAREContinuity Assessment Record and Evaluation (CARE) setPANEL.SURVEY.CDCCenters for Disease Control (CDC) setPANEL.SURVEY.CESDCenter for Epidemiological Studies Depression (CESD) setPANEL.SURVEY.CMSCenters for Medicare & Medicaid Services setPANEL.SURVEY.COOPDartmouth Cooperative Functional Status Test (COOP) setPANEL.SURVEY.CSSRSColumbia Suicide Severity Rating Scale (CSSRS) setPANEL.SURVEY.DASTDrug Abuse Screening Test setPANEL.SURVEY.DUKE-ADDuke Anxiety Depression Scale (DUKE-AD) setPANEL.SURVEY.EPDSEdinburgh Postnatal Depression Scale setPANEL.SURVEY.ESRDEnd Stage Renal Disease (ESRD) facility survey setPANEL.SURVEY.GDSGeriatric Depression Scale (GDS) setPANEL.SURVEY.GNHLTHGeneral Health survey setPANEL.SURVEY.GPCOGGeneral Practitioner Assessment of Cognition (GPCOG) setPANEL.SURVEY.HABCHealthy Aging Brain Care (HABC) setPANEL.SURVEY.HAQHealth Assessment Questionnaire (HAQ) setPANEL.SURVEY.HARKHumiliation, Afraid, Rape, and Kick (HARK) setPANEL.SURVEY.HHCCHome Health Care Classification setPANEL.SURVEY.HHSDepartment of Health and Humsn Services setPANEL.SURVEY.HIV-SSCSigns and Symptoms checklist for persons living with HIV setPANEL.SURVEY.howRUhowRU outcomes instrument setPANEL.SURVEY.IPAQInternational Physical Activity Questionnaire (IPAQ) setPANEL.SURVEY.LIV-HIVLiving with HIV setPANEL.SURVEY.MDSMinimum Data Set for Nursing Home Resident Assessment and Care Screening setPANEL.SURVEY.MFSMorse Fall Scale setPANEL.SURVEY.MLHFQMinnesota Living with Heart Failure Questionnaire (MLHFQ) setPANEL.SURVEY.MTLHLTHMental Health survey setPANEL.SURVEY.NEURONeurological survey setPANEL.SURVEY.NEUROQQuality of Life Outcomes in Neurological Disorders (NeuroQol) setPANEL.SURVEY.NHANESNational Health and Nutrition Examination Survey (NHANES) set

137PANEL.SURVEY.NIH.EMONIH Toolbox Emotion Domain panelsPANEL.SURVEY.NMMDSNursing Management Minimum Data setPANEL.SURVEY.NORTONNorton Scale survey setPANEL.SURVEY.NSRASNeonatal Skin Risk Assessment Scale surveyPANEL.SURVEY.OASISOutcome and Assessment Information Survey setPANEL.SURVEY.OMAHAOMAHA survey setPANEL.SURVEY.OPTIMALOutpatient Physical Therapy Improvement in Movement a Assessment Log setPANEL.SURVEY.PASPatient Activity Scale (PAS) setPANEL.SURVEY.PASIIPatient Activity Scale II (PAS-II) setPANEL.SURVEY.PCORIPatient-Centered Outcomes Research Institute (PCORI) setPANEL.SURVEY.PCORNETPatient Centered Outcomes Research Network (PCORnet) Common Data Model (CDM) setPANEL.SURVEY.PEGPain intensity, Enjoyment of life, General activity (PEG) setPANEL.SURVEY.PHQPatient Health Questionnaire setPANEL.SURVEY.PRAPAREProtocol for Responding to and Assessing Patients Assets Risks and Experiences (PRAPARE) setPANEL.SURVEY.PROMISPatient Reported Outcomes Measurement System setPANEL.SURVEY.QAMQuality Audit Marker setPANEL.SURVEY.QRDAQuality Health Reporting Document Architecture setPANEL.SURVEY.RFCResidual Functional Capacity setPANEL.SURVEY.SAMHSASubstance Abuse and Mental Health Services Administration (SAMHSA) setPANEL.SURVEY.USSGFHTUnited States Surgeon General Family Health Tool (USSGFHT) setPANEL.SURVEY.WELLRXWellRX Questionnaire setPANEL.TIMPTest of Infant Motor Performance (TIMP) setSURVEY.AAOSAmerican Academy of Orthopaedic Surgeons (AAOS) surveySURVEY.ACTAsthma Control Test (ACT)SURVEY.ADHDAttention Deficit Hyperactivity Disorder (ADHD)SURVEY.ADVAULTADVault surveySURVEY.AHRQAgency for Healthcare Research and Quality (AHRQ) surveySURVEY.ALSFRSRALS Functional Rating Scale – RevisedSURVEY.AMNARTAmerican National Adult Reading Test (AmNART)SURVEY.BDIBeck Depression Inventory (BDI)SURVEY.BPIBrief Pain Inventory (BPI)SURVEY.CAREContinuity Assessment Record and Evaluation (CARE) surveySURVEY.CDCCenters for Disease Control (CDC) surveySURVEY.CESDCenter for Epidemiological Studies Depression (CESD) surveySURVEY.CERNERCerner surveySURVEY.CMSCenters for Medicare & Medicaid Services (CMS) surveySURVEY.COOPDartmouth Cooperative Functional Status Test (COOP)SURVEY.CSSRSColumbia Suicide Severity Rating Scale (CSSRS)SURVEY.DASTDrug Abuse Screening Test (DAST)SURVEY.DUKE-ADDuke Anxiety Depression Scale (DUKE-AD)SURVEY.EPDSEdinburgh Postnatal Depression Scale (EPDS)SURVEY.ESRDEnd Stage Renal Disease (ESRD) facility surveySURVEY.GDSGeriatric Depression Scale (GDS) surveySURVEY.GNHLTHGeneral Health survey

138SURVEY.GPCOGGeneral Practitioner Assessment of Cognition (GPCOG)SURVEY.HABCHealthy Aging Brain Care (HABC) surveySURVEY.HAQHealth Assessment Questionnaire (HAQ)SURVEY.HARKHumiliation, Afraid, Rape, and Kick (HARK)SURVEY.HHSDepartment of Health and Human Services (HHS) surveySURVEY.howRUhowRU outcomes instrument surveySURVEY.HWSHealthy Weight Summary (HWS)SURVEY.IPAQInternational Physical Activity Questionnaire (IPAQ)SURVEY.MDSMinimum Data Set (MDS) for Nursing Home Resident Assessment and Care Screening surveySURVEY.MFSMorse Fall Scale (MFS) surveySURVEY.MISCMiscellaneous surveySURVEY.MLHFQMinnesota Living with Heart Failure Questionnaire (MLHFQ)SURVEY.MTLHLTHMental Health surveySURVEY.NEURONeurological surveySURVEY.NEUROQQuality of Life Outcomes in Neurological Disorders (NeuroQol) surveySURVEY.NHANESNational Health and Nutrition Examination Survey (NHANES)SURVEY.NHCSNational Health Care Survey (NHCS)SURVEY.NIH.EMONIH Toolbox Emotion DomainSURVEY.NIH_TOOLBOXNIH Toolbox surveySURVEY.NMMDSNursing Management Minimum Data Survey (NMMDS)SURVEY.NORTONNorton Scale surveySURVEY.NSRASNeonatal Skin Risk Assessment Scale (NSRAS)SURVEY.NURSE.HHCCHome Health Care Classification (HHCC) surveySURVEY.NURSE.HIV-SSCSigns and Symptoms Checklist (SSC) for persons living with HIV surveySURVEY.NURSE.LIV-HIVLiving with HIV surveySURVEY.NURSE.OMAHAOMAHA surveySURVEY.NURSE.QAMQuality Audit Marker (QAM) surveySURVEY.OASISOutcome and Assessment Information Survey (OASIS)SURVEY.OPTIMALOutpatient Physical Therapy Improvement in Movement and Assessment Log (OPTIMAL)SURVEY.PASPatient Activity Scale (PAS)SURVEY.PASIIPatient Activity Scale II (PAS-II)SURVEY.PCORNETPatient Centered Outcomes Research Network (PCORnet) Common Data Model (CDM)SURVEY.PEGPain intensity, Enjoyment of life, General activity (PEG)SURVEY.PHQPatient Health Questionnaire (PHQ)SURVEY.PRAPAREProtocol for Responding to and Assessing Patients Assets Risks and Experiences (PRAPARE)SURVEY.PROMISPatient Reported Outcomes Measurement System (PROMIS) surveySURVEY.QRDAQuality Health Reporting Document Architecture (QRDA) surveySURVEY.RFCResidual Functional Capacity (RFC) surveySURVEY.SAMHSASubstance Abuse and Mental Health Services Administration (SAMHSA) surveySURVEY.USSGFHTUnited States Surgeon General Family Health Tool (USSGFHT) surveySURVEY.WELLRXWellRX QuestionnaireTIMPTest of Infant Motor Performance (TIMP) survey

139Appendix C Calculating Mod 10 check digitsThe LOINC code is a numeric code with a Mod 10 check digit. The algorithm for calculating a Mod 10 check digit is as follows:InstructionsExample1. Using the number 12345, assign positions to the digits, from right to left.1st = 5 2nd = 4 3rd = 3 4th = 2 5th = 1 2. Take the odd digit positions counting from the right (1st, 3rd, 5th, etc.)5313. Multiply by 2.10624. Take the even digit positions starting from the right (2nd, 4th, etc.).425. Append (4) to the front of the results of (3).4210626. Add the digits of (5) together.4+2+1+0+6+2 = 157. Find the next highest multiple of 10.208. Subtract (6) from (7).Thus, 5 is the Mod 10 check digit for 12345. 20 – 15 = 5Calculating the check digit for LOINC Parts, Answers, and other identifiers with charactersWe use a variant of the basic Mod 10 algorithm to calculate LOINC parts and answer identifiers because those identifiers contain the alpha prefixes “LP” and “LA” (which stand for LOINC Part and LOINC Answer). A detailed description of the method is available here:https://wiki.openmrs.org/display/docs/Check+Digit+AlgorithmThis same method could be used for calculating check digits for user-assigned “X codes” (that contain a leading “X” character) as well.

140Appendix D Procedure for Submitting Additions or Changes to LOINCIntroductionSince its inception, LOINC has been developed as an open standard. We welcome requests for new terms! Submissions from LOINC users have helped us grow and adapt quickly. Likewise, we welcome suggestions for changes to existing terms or other enhancements like additional synonyms or term descriptions.Regenstrief balances the desire to respond quickly to new term submissions with the review processes necessary for a high quality standard. We can only be quick if the requesters provide clear and comprehensive information about the terms they are submitting. A list of information required for a submission is provided below.New requests are often for variations on observations we already have in the database. For example, there may be an existing term for a particular test result with serum as the specimen (system) and a user requests an identical term for a specimen of gastric contents. With the supporting information, these kinds of requests are usually straightforward.Prior to submitting your request, please check the online LOINC Submissions Queue to see if a similar or equivalent term has already been requested.Even when requesters provide complete information with their submission, some requests require discussion and decision by the LOINC Committee before Regenstrief completes them. These kinds of requests are for things like:1. an entirely novel kind of measurement2. use of LOINC codes in ways not previously agreed upon by the LOINC CommitteeBefore you submitPlease note that we tend to avoid the use of methods for chemistry tests. We will not routinely accept requests for method-specific chemistry tests. Only in very special circumstances will we distinguish among analytic methods in chemistry. We do distinguish microbiology, serology, and coagulation tests by method type. Even here, however, we do not distinguish every variation in method. Look in the body of this User’s guide for information about the kinds of distinctions that we make.Note that our policy is to allow both method-vague (no method) as well as method-specific measures in serology (measures of Ab and Ag), and in antibiotic susceptibility testing.Please pay special attention to submissions that include the system of serum or plasma alone. For most chemical analyses there is no important clinical difference between the values obtained from serum and those obtained from plasma, and we would like to represent them in the database as Ser/Plas to indicate our indifference to the distinction. Unfortunately, many requesters of new terms define their request in terms of the one that they

141happen to use (e.g., serum or plasma) without telling us that the measure can really be done on either serum or plasma. Most such requests should be for Ser/Plas as the system (sample). If the measurement MUST be done on either serum or plasma, please scientifically justify your request and send documentation; otherwise you will greatly delay our response to your submission.Survey instrument content has some additional complexity. If the instrument is copyrighted by a third party, Regenstrief will need to obtain permission prior to being able to model it in LOINC. In general, new LOINC terms are required for questions or variables that have different enumerated answer lists.How to submitFirst things firstThe information you provide about your local test/measurement and how it is used is more important than the proposed LOINC name you come up with. Having complete information on what your local test is makes the review process much smoother and helps us create clear term definitions as well as verifying and enhancing other accessory content, which benefits everyone. The kinds of information we need does vary a bit depending on the type of content (lab, radiology, document titles, survey questionnaires, etc.), so not all items are applicable all of the time.Format for submissionsThere are three possible ways to make your request, including: the online request form, RELMA’s built in functions, or one of the spreadsheet templates available on the LOINC web site.For most users, we recommend using the online request form. Regardless of format, we ask that users submit no more than 50 proposed terms at a time.Required informationThe set of information required for a particular submission depends on the content of the request. In order for us to process your request, we need:• Local test/observation name• Local order (panel) name• Name of send out lab (if applicable)• Name of healthcare organization that stimulated the request for this term (if you are submitting on behalf of someone else)• Description of the test • For laboratory tests and clinical measurements, the description should indicate what is measured, how it is performed, and how it is used clinically (e.g., what conditions does it diagnose, monitor, screen for, etc.). • For other kinds of clinical terms, such as clinical documents, the description should indicate the expected information content that would be sent as the result value (i.e., what kinds of information this document or report contains).

142• Units of measure (for quantitative observations)• Answer lists (for qualitative observations) (both normal and abnormal answers)• Sample results, reports (if applicable)• If the request is for a panel, the request should include the tests that comprise the panel. Whether or not each test already has a LOINC code should be included, and for any tests that do not already have a code, all of the above information for each individual test should be provided.• Package inserts, test kit documentation (if applicable)• Vendor, instrument, and/or reagent kit used to perform this test (if applicable)• Description of the project or activity that stimulated the request for this term (e.g., IHE Antepartum Record Profile, Indiana Network for Patient Care health information exchange project, etc.)• Implementation guide (for terms designed for use in the context of a specific messaging implementation guide)• Original survey form (for questionnaires or survey content) • If you are requesting survey terms, we recommend that you find out whether the terms are copyrighted and let us know this information when you submit your request. It would be especially helpful and would facilitate processing for you to contact the copyright-holder prior to submission to find out whether they would be willing to give permission to represent the copyrighted content in LOINC, and then include their contact information with your submission so that we can follow up directly with them. • Occasionally copyright-holders are only willing to grant time-limited permission or grant permission but at a cost, and in such cases, we will not create the requested content because we cannot agree to these terms.• Any other documentation that may assist us in creating the requested codesOnline Request FormNew LOINC terms can be requested directly from the LOINC website using the online request form. The request form can build a set of requested terms by entering the required information for each term and/or by uploading a spreadsheet file with the required fields. Requested terms and supporting information are sent to Regenstrief, and users can review the status of their submissions from the My Submissions section of the LOINC website.RELMA submissionThe RELMA program can aid you in creating submissions by allowing you to create, manage and store submission terms in a way that is similar to how the program creates, manages and stores local working sets. With RELMA, you can create terms for submission over time and submit groups of terms in batches. The program will track when the term was created and the date when you submitted the term. The program will help you organize the terms that you create and it will automate the process of creating the submission files.For detailed instructions on how to use the RELMA propose a term feature, please see Appendix A of the RELMA manual. You can download the RELMA Manual from the LOINC website.

143Excel file submissionIf you are not using RELMA for submission, please use one of the templates provided on our website.Other formats (e.g., distributed database fields, exported internal/local formats) will not be accepted.Please email your submission template and related documents to [email protected] with Regenstrief InstituteWithin a day or two of receipt of your file, you will receive a confirmation email and the submission process will be underway. You may receive additional communication from Regenstrief with requests for further information if required.You can follow the progress of your requested terms as it progresses through the review process by visiting the LOINC Submissions Queue.Once the submission process has completed, you will receive files containing your requested codes.

144Appendix E Examples for LOINC Property Matching1. Content (Cnt). Like concentration except that volume in the denominator is replaced by mass. By extension:CCntCatalytic Content, catalytic activity of a component per unit mass of a sample (System).24048-1|Alpha galactosidase:CCnt:Pt:Fib:QnMCntMass Content, mass of component per unit mass of a sample (System).9435-9|Isopropanol:MCnt:Pt:Tiss:QnNote: All of the heavy metal measurements in hair, nails, and tissue should all be mass contents.8157-0|Arsenic:MCnt:Pt:Nail:QnNCntNumber Content, number of component entities per unit mass of a sample (System).20771-2|Coliform bacteria:NCnt:Pt:Egg:Qn:Viability count2. Fraction (FR). Fraction of component A in a group of entities B, C, Y, N in system 1. By extension:CFrCatalytic Fraction2536-1|Lactatedehydrogenase1/Lactatedehydrogenase.total:CFr:Pt:Ser/Plas:Qn:Electrophoresis 9642-0|Creatine Kinase.BB/Creatine kinase.total:CFr:Pt:Ser/Plas:QnNFrNumber Fraction10602-1|Spermatozoa.abnormal head/100 spermatozoa:NFr:Pt:Semen:Qn 764-1|Neutrophils.band form/100 leukocytes:NFr:Pt:Bld:Qn:Manual countMFrMass Fraction2614-6|Methemoglobin/Hemoglobin.total:MFr:Pt:Bld:QnSFrSubstance Fraction30192-9|Acetylcholine receptor modulation Ab/Acetylcholine Ab.total:SFr:Pt:Ser:QnVFrVolume Fraction4545-0|Hematocrit:VFr:Pt:Bld:Qn:Spun3. Ratio (RTO). Ratio of component A to component B in system 1. By extension:CRtoCatalytic Ratio (previously Catalytic Concentration Ratio, CCRto)2325-9|Gamma glutamyl transferase/Aspartate aminotransferase:CRto:Pt:Ser/Plas:QnSRtoSubstance Ratio (previously Substance Concentration Ratio, SCRto)2958-7|Sodium/Potassium:SRto:Pt:Sweat:Qn

145MRtoMass Ratio (previously Mass Concentration Ratio, MCRto)2768-0|Phenylalanine/Tyrosine:MRto:Pt:Ser/Plas:QnNRtoNumber Ratio11138-5|Myeloid cells/Erythroid cells:NRto:Pt:Bone mar:QnVelRtoVelocity Ratio12022-0|Resistivity index:VelRto:Pt:Uterine artery.right:Qn:Doppler.calculatedVRatRtoVolume Rate Ratio29462-9|Pulmonic flow/Systemic flow:VRatRto:Pt:Circulatory system.XXX:Qn:US.dopplerRatio1811-9|Amylase/Creatinine renal clearance:Ratio:24H:Urine:QnNote CSF/Serum Protein calculation is not a ratio, because the measured components are not in the same system. Its Property type is relative mass concentration, RelMCnc (see below).Note If the units of the denominator and numerator are both mass (e.g., mg/g), use MRto: 13719-0|Carnitine/Creatinine:MRto:Pt:Urine:Qn If the units of the denominator and numerator are both substance (e.g., mmol/mol) use SRto: 22695-1|Carnitine/Creatinine:SRto:Pt:Urine:Qn If the units of the denominator and numerator are different (mmol/g), use Ratio: 17866-5|Carnitine/Creatinine:Ratio:Pt:Urine:Qn 4. Relative (REL). Relative amount of component A in system 1 compared to system 0. By extension: REL should be used anywhere an actual measurement is divided by a measurement on a normal or control. It should also be used when a quotient is created by dividing a measured substance in Serum by the same substance measured in CSF, Urine, etc.RelMCncRelative Mass Concentration (as noted previously)2858-9|Protein.CSF/Protein.serum:RelMCnc:Pt:Ser+CSF:Qn 3235-9|Coagulation factor XII Ag actual/Normal:RelMCnc:Pt:PPP:Qn:ImmRelTimeRelative time3232-6|Coagulation factor XII activity actual/Normal:RelTime:Pt:PPP:Qn:CoagRelCCncRelative Catalytic Concentration28660-9|Plasminogen actual/Normal:RelCCnc:Pt:PPP:Qn:ChromoRelRtoRelative Ratio1756-6|Albumin.CSF/Albumin.SerPl:RelRto:Pt:Ser/Plas+CSF:Qn

146RelVolRelative Volume19853-1|Capacity.inspiratory.bs/Capacity.inspiratory.preop:RelVol:Pt:Respiratorysystem:Qn:SpirometryRelVratRelative Volume Rate20161-6|Voluntaryventilation.max^postbronchodilator/MVV:predicted:RelVRat:Pt:Respiratory system:Qn5. Cmplx. Other divisions of one measurement by another that are not covered by the above rules should be classed as having Complex (Cmplx) properties, and the exact formula for deriving the quantity should be explicitly stated.6. Arbitrary. Arbitrary concentration of items. If we are not measuring the activity of an enzyme then the units of measure and properties are:Possible ValuesPropertyScaleUnits/mL, IU/mL, etc.ACncQnUnits/gm, IU/gm, etc.ACntQnUnit/min, IU/24hr, etc.ARatQnUnitless (Patient/Control)AFrQnNote If we are measuring the activity of an enzyme then the units of measure and properties are:Possible ValuesPropertyScaleU/mL, Units/mL, etc.CCncQnU/gm, Units/gm, etc.CCntQnU/24hr, Unit/min, etc.CRatQnUnitless (Patient/Control)CFrQn7. If the Property is Titr then the Scale is always Qn. For any X Ab or Ag:Possible ValuesPropertyScale<1:2, 1:4, 1:8…TitrQn8. For Any X Ab or Ag:Possible ValuesPropertyScaleNeg, Indeterminate, PosPrThrOrd1+, 2+, 3+…PrThrOrd<1:2, 1:4, 1:8…TitrQnNeg, 1:4, 1:8…TitrQnNeg, 0.90…ACncQn (EIA units)

1479. For any intensive evaluation whose value comes from a finite set of unranked (independent) coded items, the Property will be Prid (or Type) and Scale Nom. Prid is used in cases where the value set includes the option of reporting “none”, “not present”, etc. Type is used in cases where the result always specifies a value from the finite set. For extensive measures whose value comes from a finite set of unranked coded items, the Property will be the extensive property, and the Scale will be Nom.Intensive PropertiesPossible Values (coded)PropertyScaleOrganism IdentifiedE. coli, S. aureus, etcPridNomABO GroupA, B, AB, OTypeNomSurgery (Dis. Summary)Cholecystectomy, AppendectomyPridNomExtensive PropertiesPossible Values (coded)PropertyScaleUrine ColorAmber, straw, etc.TypeNom10. For any intensive evaluation whose value comes from a finite set of unranked (independent) free text items (or a paragraph), the Property will be Prid or Find, and the scale will be Nar to indicate that the result is free text narrative. For extensive measures whose value comes from a finite set of unranked text items (or a paragraph), the Property will be the extensive property, and the Scale will be Nar.Intensive PropertiesPossible Values (coded)PropertyScaleOrganism IdentifiedE. coli, S. aureus, etcPridNarABO GroupA, B, AB, OTypeNarSurgery (Dis. Summary)CholecystectomyPridNarExtensive PropertiesPossible Values (coded)PropertyScaleUrine ColorAmber, straw, etc.TypeNar11. Imp is used to represent the Property when the evaluation is a mental abstraction based on one a collection of measurements and/or data. For example, if several measurements are made relative to immunoglobin levels in Serum and CSF in a myasthenia gravis panel, and if by examining all of the evidence a pathologist decided that this pattern of findings represented active disease (which could be represented as a coded value), the result of the pathologist thought process would be represented as:Possible Values (text)PropertyScaleMyasthenia EvaluationNo disease, chronic diseaseImpNomIf the pathologist evaluation is reported free text or a paragraph of information, the representation would be:Possible Values (text)PropertyScaleMyasthenia EvaluationNo disease, chronic diseaseImpNar12. Methods are only used to distinguish things that are identical in the other five LOINC fields but may differ because the sensitivity or specificity is different for the given methods.13. Be careful in distinguishing end point detection method from Property. For example, if sodium is measured using an ion specific electrode, the Property is not a voltage difference. The voltage difference is just a method for indirectly measuring the sodium concentration. Concentration is the real Property. Likewise, many antigens and

148antibodies are now measured using optical density as the detection method. However, the Property we are really measuring is an arbitrary concentration (ACnc), not the optical density. If it is a ratio of optical densities (as with Gliadin Ab, Parvovirus B19 Ab, etc.) that are compared (patient value divided by a standard control), then the Property should be RelACnc (relative arbitrary concentration).14. ml/min/1.73sqM (Milliliters per min per 1.73 square meters BSA): Similar to the immediately preceding item. This result has the same Property as if it had units of ml/min/sqM. The Property of this measurement should be called “areic volume rate” (ArVRat).

149Appendix F Example Acronyms used in LOINCTable 33: Example Acronyms used in LOINCAcronymMeaningACAbdominal CircumferenceADLActivities of Daily LivingAEAnion Exchange proteinAPAnterio-PosteriorAPADAnteroPosterior Diameter of the AbdomenAUTAutomated Ultrasound TestingB2GP1Beta 2 Glycoprotein 1BDBinocular DistanceBORBrachio-Oto-RenalBPCBiparietal CircumferenceBPDBiparietal diameterCDCluster of differentiationCDACongenital dyserythropoietic anaemiaCDBChildhood Disability BenefitscDNAcomplementary DNACFstCalorie FastCHAMPUSCivilian Health and Medical Program of the Uniformed ServicesCineCinematographicCMSCenters for Medicaid and Medicare ServicesCNR1Cannabinoid receptor 1COCCommission on CancerCOPDChronic Obstructive Pulmonary DiseaseCPTCurrent Procedural TerminologyCRLCrown-Rump LengthCSFCerebral spinal fluidCWContinuous waveCyCD22Cytoplasmic CD22DBGDonna Bennett-GoodspeedDCISDuctal carcinoma in situDISIDADiisopropyliminodiacetic acidDRGDiagnostic Related GroupsDTPADiethylenetriamine pentaacetateDxDiagnosisEBV-LMPEpstein Barr virus – latent membrane proteinEDEmergency Department

150EDDEstimated Delivery DateEEGElectroencephalogramEFWEstimated Fetal WeightEGDEsophagogastro duodenoscopyEKGElectrocardiogramEMSEmergency Medical Service(s)ENTEar, Nose ThroatERCPEndoscopic Retrograde CholangiopancreatographyFLFemur LengthFLACCFace Legs Activity Cry ConsolabilityFNAFine Needle AspiratesFTAFetal Trunk AreaGALOPGait disorder Autoantibody Late-age Onset PolyneuropathyGSDGestational Sac DiameterGSLGestational Sac LengthHCHead CircumferenceHIVHuman immunodeficiency virusHIV-SSCSign and Symptom Check-List for Persons with HIV DiseaseHLHumerus LengthHLAHuman Leukocyte AntigenHMPAOHexamethylpropyleneamine oximeHTLVHuman T-cell Lymphotropic VirusHWLHeight Width LengthICDInternational Classification of DiseasesICD9International Classification of Diseases, Ninth RevisionICD9-CMInternational Classification of Diseases, Ninth Revision, Clinical ModificationICD-OInternational Classification of Diseases for OncologyIDIntradermalINRInternational normalized ratioIODInter Ocular DistanceKUBKidney-Ureter-BladderLHONLeber hereditary optic neuropathyLOINCLogical Observation Identifiers Names and CodesLVOTLeft Ventricular Outflow TractLWLandsteiner-WienerLWTLength Width ThicknessMAAMicroalbumin aggregate albuminMEMSMedication Event Monitoring SystemMERSTHMedical Event Reporting System-Total Health SystemMIB-1Mindbomb homolog 1MIBGMetaiodobenzylguanidineMICMinimum inhibitory concentrationMLCMinimum lethal concentrationMLOMediolateral obliqueMMAMacro aggregate albumin

151MVVMaximum Voluntary VentilationNAACCRNorth American Association of Central Cancer RegistriesNgNasogastricNPINational Provider IdentifierOFDOccipital-Frontal DiameterO-I BPDOuter to Inner Biparietal DiameterOmpCOuter membrane porin of E coliO-O BPDOuter to Outer Biparietal DiameterO-O TDOuter to Outer Tympanum DiameterOODOuter Orbital DiameterPAPostero-AnteriorPCPPrimary Care PhysicianPEGPolyethylene GlycolPHQPatient Health QuestionnairePISAProximal Isovelocity Surface AreaPSRPeridontal Screening and RecordingPYPPyrophosphateQAMQuality Audit MarkerQIDFour times a dayRASTRadioallergosorbent testRFCResidual Functional CapacityRFLPRestriction fragment length polymorphismRUGResource Utilization GroupsSABStreptoavidin-biotinSBTSequence based typingSCSulphur colloidSCBSertoli cell barrierSCLSclerodermaSEERSurveillance Epidemiology and End ResultTADTransverse Abdominal DiameterTCThoracic CircumferenceTCDTransverse Cerebellar DiameterTDTransaxial DiameterTECTubingen electric campimetryTIDThree times a dayTNMTumor, node, metastasisTORCHToxoplasma, Rubella. Cytomegalovirus, Herpes Simplex VirusTTDTransverse Thoracic DiameterTUTuberculin UnitsVTIVelocity Time IntegralVWFvon Willebrand Factor

152Appendix G LOINC Technical BriefsTechnical briefs have been developed for various LOINC terms to clarify either the meaning, current nomenclature, or use case of a given term. The following technical briefs are included in this manual and linked to related LOINC terms in RELMA.• D-Dimer Revisions in LOINC• Cockcroft-Gault formula for estimating creatinine clearance, Schwartz equation for Glomerular Filtration Rate and MDRD formulae• Inducible Clindamycin Resistance in Staphylococcus and Streptococcus• KIR Gene Family• Oxygen Saturation and LOINC® • Nomenclature of Salmonella Species, Subspecies, and Serovars• Segmented Neutrophils Versus Polymorphonuclear WBC• Vitamin D • Free Thyroxine Index Variants • Streptococcus pneumoniae serotype nomenclature

153D-Dimer Revisions in LOINCAuthor: J. Gilbert Hill, MD, PhDDate Written: 2006-11-24The problemFor many years a test known as “D-dimer” has been used for the assessment of patients with DIC, and more recently, for the exclusion of the diagnosis of DVT or PE. The units used in expressing results are usually ng/mL or ug/L, so that a report might look like:D-dimer = nn ug/L orD-dimer = nn ng/mL Occasionally, this expression is modified to readD-dimer = nn ug/L DDU, (where the DDU stands for D-dimer units) With time, new test procedures have been developed, in which newer methods of analysis and of preparation of the test standard have led to the use of new “units” in expressing results. With these reagent sets, a report might look like:D-dimer = xx FEU ug/L orD-dimer = xx ug FEU/L orD-dimer = xx ug/L FEU, (where FEU is an acronym for fibrinogen equivalent units) The location of FEU in the unit is not consistent: some users place the FEU before the “ug”, some after the “ug”, and some after the “L”.From a clinical perspective, the D-dimer test is potentially of greatest value in ruling out DVT or PE: for results expressed as ng/mL (= ug/L), the exclusion value is generally less than 250; for results expressed as ng/mL FEU, the exclusion value is less than 500, and these values are compatible with a rule-of-thumb conversion published by bioMerieux, July 2003:600 ng/mL FEU = 300 ng/mL D-dimerSo . . . now we have the use of single name for a test – D-dimer – but with results falling into two separate families. The difference between the two families is that the results differ by a factor of approximately two. This has led to a chaotic situation in the lab, and by extension, to the bedside, a situation in which both laboratory staff and clinicians are confused as to what “D-dimer” is being measured and reported. The world-wide web has dozens of references to the problem, and the CAP has commented frequently, with a series of feature articles in CAP Today (Feb 2000, Jan 2003, April 2005, May 2005, Summer 2005).

154In LOINC terms, we have a component representing two different entities, with identical primary attributes (component, property, scale, system, time aspect and scale), differentiated only by method and units, both of which are very weak discriminators.The fundamental problem is the lack of a useful standard. The International Society on Thrombosis and Haemostasis has had a subcommittee working for more than ten years on D-dimer standardization, without success, and it is said that a seat on the committee comes with retirement benefits.The following figures provide an estimate of the scope of the problem: in a 2004 US (CAP) survey, 59% of labs reported FEU, 41% reported D-DU and 8% did not know the units they were using; in a 2005 Canadian (QMPLS) survey, 68% of labs reported D-DU, 31% reported FEU, and 1% did not know the units they were using.Resolving the problemThe obvious solution to the problem is to have different names for the two “families” of D-dimer. But what should these names be?Contributing to the original problem is the unfortunate choice of the acronym FEU, for fibrinogen equivalent units. The inclusion of the word “unit” gives the impression that FEU is a unit in the metrological sense, whereas it would be more reasonable to think of it as a unit in the structural sense – e.g., a unit such as glucose in a larger molecule such as starch.Given this interpretation, FEU may be more closely related to, or equivalent to the “component” (in the LOINCian sense), rather than to the metrological unit. In other words, FEU is the name of what is measured: just as the amount of glucose can be measured in a sample, so can the amount of FEU.From this it is logical to propose that existing entries in LOINC retain the component name FIBRIN D-DIMER, but that a new entry be created with the name FIBRIN D-DIMER.FEU. In accordance with LOINC naming conventions, a dot (.) separates the analyte name from the “subspecies”. This proposed name protects the connection with the D-dimer family, but efficiently separates it as a different entity.The fully specified name would beFIBRIN D-DIMER.FEU:MCNC:PT:PPP:QN:EIAThere is at least one precedent in LOINC for this type of component modification – see LOINC 4539-3, Erythrocyte Sedimentation Rate.Zeta.The quantitative D-dimer entries in LOINC 2.17 are as follows:D-dimer results from American Proficiency Institute 2004 Testing Program

155These tables hint at some of the problems associated with the measurement of D-dimer, in particular the inaccuracy and imprecision, but also proved a convenient example of the problem under discussion: bioMerieux pioneered the use of the acronym FEU, but bioMerieux results are shown in the first, ug/L table, rather than the second, ug FEU/mL table.

156Cockcroft-Gault formula for estimating creatinine clearance, Schwartz equation for Glomerular Filtration Rate and MDRD formulaeAuthors: Gilbert Hill, MD, PhD with edits by Clement J McDonald, MDDate Written: 2007-11-201 Estimating creatinine clearance from serum creatinine1.1 Cockcroft-Gault – not adjusted for body surface area (BSA)The Cockcroft-Gault formula is used to estimate creatinine clearance from age, weight and serum creatinine. The original paper from these two authors was Prediction of Creatinine Clearance from Serum Creatinine, Nephron 1976;16:31- 41 hence the name. Note that Creatinine clearance is a proxy for Glomerular Filtration Rate (GFR) and some clinical settings describe this as an estimated GFR (see below).The basic formula without normalization for BSA is represented in the LOINC data base by the following term:35591-7Creatinine renal clearance.predictedVRatPtSer/PlasQnCockcroft-Gault formulaAnd the formula is as follows:The equation as shown requires weight to be recorded in kg and creatinine in mg/dL, and is valid for male patients. If the patient is female, the result should be multiplied by 0.85.Web calculator for creatinine in mg/dLIf the patient’s weight is recorded in kg and the creatinine is reported in umol/L then results from the above equation must be multiplied by 1.23 for men and 1.04 in women.Web calculator for creatinine in umol/LFrom http://www.sydpath.stvincents.com.au/other/CalcsCrClCGumol.htm1.2 Cockcroft-Gault – adjusted for body surface areaIt is now common practice for the creatinine clearance calculated by the Cockcroft-Gault formula to be normalized for a body surface area of 1.73 m2.In particular, the Cockcroft-Gault BSA adjusted formula is used by many pharmacy departments for medication dosage adjustments.

157LOINC terms for BSA adjusted creatinine clearance35592-5Creatinine renal clearance/1.73 sq M.predictedVRatPtSer/PlasQnCockcroft-Gault formula, corrected for BSA50380-5Creatinine renal clearance/1.73 sq M.predicted.femaleVRat24HSer/PlasQnCockcroft-Gault formula, corrected for BSA50381-3Creatinine renal clearance/1.73 sq M.predicted.maleVRat24HSer/PlasQnCockcroft-Gault formula, corrected for BSA2 Direct prediction of GFR2.1 Creatinine-based prediction of GFR2.1.1 Schwartz formula for PediatricsThe Schwartz formula is used to predict GFR in pediatrics. The original paper by G F Schwartz et al, is A Simple Estimate of GFR in Children Using Body Length and Plasma Creatinine, Pediatrics 1976;58:259-263 has become more relevant in the last few years because the MDRD formula (below) is specifically stated NOT to be applicable to patients under 18 years of age. The Schwartz formula depends on age, sex, and body height and serum creatinine. The equation can be stated as follows:GFR Calculator for ChildrenSchwartz FormulaGFR (mL/min/1.73 m2) = k (Height) / Serum Creatinine• k = Constant • k = 0.33 in Preemie Infants • k = 0.45 in Term infants to 1 year old • k = 0.55 in Children to 13 years • k = 0.65 in Adolescent males (Not females because of the presumed increase in male muscle mass. The constant remains .55 for females.)• Height in cm• Serum Creatinine in mg/dlWeb calculator for Schwartz FormulaLOINC term for Schwartz formula50384-7Glomerular filtration rate/1.73 sq M.predictedVRat24HSer/PlasQnCreatinine-based formula (Schwartz)2.1.2 MDRD 4 variablesThe MDRD 4 variable equation is the principle equation recommended by professional nephrology societies to estimate the GFR. It depends upon serum creatinine, age, sex and race. It also includes a BSA adjustment term of

1581.73 – the average body surface area in an adult male. (Equations incorporating height and weight can be used to correct this equation when patients are far from the mean in BSA – but they are not routinely used.)The following was taken from NKF MDR web site on December 4, 2006 (http://www.kidney.org/professionals/KLS/gfr.cfm#2):The National Kidney Disease Education Program (NKDEP) of the National Institute of Diabetes and Diseases of the Kidney (NIDDK), National Kidney Foundation (NKF) and American Society of Nephrology (ASN) recommend estimating GFR from serum creatinine using the MDRD Study equation. This equation depends upon the serum creatinine age, sex and race to estimate the GFR and therefore improves upon several of the limitations with the use of serum creatinine alone. The MDRD Study equation has been rigorously developed and validated, and is more accurate than measured creatinine clearance from 24-hour urine collections. The equation is:GFR = 186 x (PCr)-1.154 x (age)-0.203 x (0.742 if female) x (1.210 if black)GFR is expressed in ml/min/1.73 m2. In this equation Pcr serum creatinine must be expressed in mg/dl, and age in years. (Of course other units can be used if the right side of the above equation is multiplied by the appropriate constant). (all taken from NKF web site – Web calculator for MDRDThe glomerular filtration rate predicted by the MDRD formula may be reported in at least three ways:• All four variables are known and used in the equation. The result would be race and sex adjusted creatinine clearance.• Only two variables (serum creatinine and age) are used in the equation. In this circumstance, the report may: • include a comment saying – “if patient is black, multiply result by 1.21” and/or “if patient is female, multiply the result by .742”, or • may include two values: N1 if white and N2 if black, and a correction factor for sex: if patient is female, multiply the result by .742.LOINC codes for MDRD formula33914-3Glomerular filtration rate/1.73 sq M.predictedVRatPtSer/PlasQnCreatinine-based formula (MDRD)48642-3Glomerular filtration rate/1.73 sq M.predicted.non blackVRatPtSer/PlasQnCreatinine-based formula (MDRD)48643-1Glomerular filtration rate/1.73 sq M.predicted.blackVRatPtSer/PlasQnCreatinine-based formula (MDRD)50044-7Glomerular filtration rate/1.73 sq M.predicted.femaleVRatPtSer/PlasQnCreatinine-based formula (MDRD)2.1.3 MDRD 6 variablesA six variable version of the MDRD exists. This one depends on the patient’s serum albumin and serum urea nitrogen values in addition to the MDRD-4 variables, but is not the preferred equation for this estimate.

159Where PCr=serum creatinine concentration (mg/dl) (alkaline picrate method); SUN=serum urea nitrogen concentration (mg/dl) (urease method); Alb=serum albumin concentration (g/dl) (bromocresol green method).Taken from:Stoves J,Lindley E,Barnfield M,Burniston T, Newstead C. MDRD equation estimates of glomerular filtration rate in potential living kidney donors and renal transplant recipients with impaired graft function.Nephrol Dial Transplant.2002,17: 2036-20372.2 Cystatin-based prediction of GFRAlthough the MDRD equation, based on the measurement of serum creatinine, is the most widely used method for estimating GFR, an alternative, based on the measurement of serum cystatin is claimed to have certain advantages.Estimating Glomerular Filtration Rate in Kidney Transplantation: A Comparison between Serum Creatinine and Cystatin C-Based Methods, J Am Soc Nephrol 16: 3763–3770, 2005Web calculator for Cystatin-based GFRLOINC code for GFR predicted by a cystatin-based formula50210-4Glomerular filtration rate/1.73 sq M.predictedVRatPtSer/PlasQnCystatin-based formula

160Inducible Clindamycin Resistance in Staphylococcus and StreptococcusAuthor: David Baorto, MD, PhDDate Written: 2011-05-12 Macrolide-Lincosamide-Streptogramin B (MLSb) resistanceThere is a phenomenon by which the organism can appear to be susceptible to lincosamindes such as clindamycin when tested in vitro, yet exposure to an appropriate macrolide (such as erythromycin) can INDUCE resistance to the clindamycin. This mechanism of resistance involves methylation of the 23S rRNA binding site that is shared by 3 antibiotic classes (macrolides, lincosamides, and group B streptogramins) and prevents their binding to the site and exerting their effect. This resistance mechanism is known (for short) as MLSB.When one of the erm methylases is produced constitutively, the resistance is constitutive and requires no induction. However, in some cases, the translation of the erm methylase protein is suppressed and is activated only after the binding of a macrolide antibiotic to upstream sequences, which alters the mRNA conformation, allowing it to be translated. Once this occurs, active methylase enzyme is produced which methylates the binding site for all 3 antibiotic classes, potentially preventing the binding of any of these antibiotic classes and inducing co-resistance. Detection of this resistance pattern can be detected phenotypically using disc diffusion (Clindamycin.induced [Susceptibility] by Disk diffusion (KB), 42720-3).The detection of the presence of either the ermA or ermC geneThe methylase enzyme is encoded by one of the erm genes, generally ermA or ermC in staph, ermB in strep. Finding ermA or ermC similarly indicates the possibility for resistance to both erythromycin and clindamycin in Staph (either constitutive or inducible for clinda), so reporting both genes has been combined in some assays to indicate that one of the two has been detected (Erythromyin+ clindamycin resistance ermA + ermC genes [Presence] by Molecular method, 62258-9).

161KIR Gene FamilyAuthor: David Baorto, MD, PhDWritten: 2011-04-17Clinical significanceKIR (Killer cell Immunoglobulin-like Receptor) molecules, a novel category of lymphocyte receptors, are predominantly found on the surface of natural killer (NK) cells. Through their interaction with HLA class I molecules, they modulate NK cell activity, central to the ability of those cells to distinguish between healthy cells and those either infected or transformed. The KIR family of molecules demonstrates extensive diversity at the gene level, stemming from multiple genes as well as multiple alleles. As a result of this polymorphism, KIR genotype is unlikely to be identical between individuals (in a sense similar to their molecular ligand, HLA Class I). The relationship between KIR genotype and disease is beginning to be elucidated, and is likely to interact with HLA. Needless to say it is a growing area, but there is evidence that which KIR genes are expressed in an individual may be related to susceptibility to infections (e.g., HCV, HIV), autoimmune diseases, and certain cancers. Importantly, the success of hematopoietic cell transplantation for some leukemias may be closely tied to KIR type or KIR compatibility, and be an additional predictor (with HLA).Nomenclature of KIR genes and allelesThe KIR genes have been classified under the CD nomenclature as a set of CD158 molecules (CD158a, CD158b, etc.), but the CD names are not commonly used because they do not specifically reflect structure, function and gene polymorphism. The frequently used KIR gene nomenclature is developed by the HUGO Genome Nomenclature committee (HGNC). It includes over 15 genes and is based on molecular structure. They all begin with “KIR”, the next digit is the number of Immunoglobulin-like domains, next is “D” for domain, next is a description of the cytoplasmic tail, either “L” for long, “S” for short, or “P” for pseudogenes. The last digit is an integer to distinguish among different KIR genes having that same structure (e.g., KIR2DL1, KIR2DL2, etc.). Different alleles of a KIR gene are named in a fashion similar to that of HLA alleles, with an asterisk following the gene name, followed by digits indicating differences in encoded proteins and non-coding regions.ReferencesMarsh S G, Parham P, Dupont B, Geraghty D E, Trowsdale J, Middleton D, Vilches C, Carrington M, Witt C, Guethlein L A, Shilling H, Garcia C A, Hsu K C, Wain H. Killer-cell immunoglobulin-like receptor (KIR) nomenclature report, 2002. Immunogenetics 2003; 55(4):220-226. [PubMed: 12838378]Parham P. MHC class I molecules and KIRs in human history, health and survival. Nat Rev Immunol. 2005; 5(3):201-214. [PubMed: 15719024]Carrington M, Norman P. The KIR Gene Cluster. Bethesda (MD): National Center for Biotechnology Information (US); May 28, 2003. [PubMed: NBK10135]

162Oxygen Saturation and LOINC® Authors: Gilbert Hill and Clement J. McDonaldDate Written: 2007-10-19 – Revised: 2009-07-09 (See NCCLS 46-A Blood Gas and pH Analysis and Related Measurements: Approved Guideline.)1 Oxygen saturationThe term “oxygen saturation” is often used to refer to two distinctly different quantities, hemoglobin oxygen saturation (recommended symbol = sO2) and fractional oxyhemoglobin (recommended symbol = FO2Hb).2 NCCLS 46-A defines the two as follows:2.1 Hemoglobin oxygen saturationHemoglobin oxygen saturation = the amount of oxyhemoglobin in blood expressed as a percent of the total amount of hemoglobin able to bind oxygen (i.e., oxyhemoglobin (O2Hb) + deoxyhemoglobin (HHb). Note that carboxyhemoglobin (COHb), methemoglobin (MetHb) and Sulfhemoglobin (SulfHb), the so-called dyshemoglobins (dysHb) are unable to bind oxygen, so are not included in the denominator of this fraction:sO2 = 100 x O2Hb/(O2Hb + HHb)More important some instruments, e.g., the pulse oximeter, cannot pick up the dyshemoglobins. So they always report sO2.This quantity may be referred to as “oxygen saturation”; terms such as “functional” oxygen saturation or oxygen saturation of “available” or “active” hemoglobin, but NCCLS should not be used to name this quantity.2.2 Fractional oxyhemoglobinFractional oxyhemoglobin = the amount of oxyhemoglobin expressed as a percent of the total hemoglobin (where total Hb = O2Hb + HHb + [COHb + MetHb + SulfHb] taken all together O2Hb HHb and the three DysHb’s represent the total Hb.FO2Hb = O2Hb/tHbA key point here is that it takes a more sophisticated machine to measure Fractional Oxyhemoglobin than sO2.3 When there are no dyshemoglobins present (the usual situation), sO2 =FO2Hb4 Oxygen saturation obtained by measuring pH and pO2An “oxygen saturation” can also be obtained by measuring pH and pO2 and substituting the values into an empirical formula for the oxyhemoglobin dissociation curve (Hill equation). However, this calculated approach is prone to many kinds of errors and “oximetry” based on differential spectrophotometry is now the method of choice.

1635 Three principal classes of oximetryThere are at least three principal classes of oximetry, commonly known as:• Pulse (or transcutaneous) oximetry (sensor attached to body surface)• Hemoximetry (sample of blood injected into instrument)• Co-oximetryHistorically a Co-oximeter measures Carbon monoxide bound hemoglobins and the other two dyshemoglobins and could only be done in the laboratory with an injected blood sample. Today (i.e., 2009) most laboratory blood analyzers measure all three dyshemoglobins and are really Co-oximeters, but may not be named as such.A pulse co-oximeter was placed on the market in 2005. This device reports the oxyhemoglobin %, Carbon monoxide %, and the Pleth variability index; it also measures each of the dyshemoglobins. So it provides an accurate fractional oxygen saturation as well as information about CO poisoning. 6 Instruments used for pulse and hemoximetryThe instruments used for pulse and hemoximetry base results on calculations from readings at two different wavelengths, which means they do not reflect the presence of any dyshemoglobins, and therefore the result they produce will be sO2 (LOINC component Oxygen saturation = NCCLS hemoglobin oxygen saturation).7 Instruments used for co-oximetryThe instruments used for co-oximetry base results on calculations from readings at four to eight different wavelengths, which means they are able to reflect the presence of any dyshemoglobins, and therefore the result they produce will be FO2Hb (LOINC component Oxyhemoglobin/Hemoglobin. total = NCCLS fractional oxyhemoglobin).LOINC will name its components according to the NCCLS recommendation, and apply the corresponding NCCLS synonyms, i.e., sO2 and FO2Hb to the components, oxygen saturation and Hemoglobin Oxygen fraction, respectively and include the defining equation (see above) for the terms that carry these respective components. We will retain oxygen saturation as a synonym for both sO2 and FO2Hb so that mappers who may not know the official names will still be able to find the terms.LOINC will use the property of MFR (mass fraction) to identify the property of these terms. There would only be an imperceptible difference between the numerical representation of this quantity as a MFR versus an SFR (substance or molar fraction). By LOINC convention we use MFR rather than SFR in such cases.Depending upon the naming precision of laboratory, it may be difficult to determine whether a result called an Oxygen saturation is really an sO2 or FO2Hb. The other tests in the panel, and the inclusion of method names in the test order or battery and the source of the term (clinical laboratory, cardiac cath laboratory, respiratory therapy, nursing) all provide guidance for the mapping. But it may be necessary to contact the source to be sure in some cases.If a battery reports both a fractional oxyhemoglobin and oxygen saturation, then the situation should be clear. If the method is co-oximetry or the battery includes a separate measure of Carboxyhemoglobin (or any of the other dyshemoglobins), then it will be reporting a fractional oxyhemoglobin. If the method is pulse oximetry, then you have an sO2. Most central and ICU based blood gas measures will produce a fractional oxyhemoglobin.Finally, in the U.S. these results are almost always reported with units of percent (%), but these results are reported as pure fractions (e.g., 20% becomes 0.2) in some environments.

164Nomenclature of Salmonella Species, Subspecies, and SerovarsAuthor: David Baorto, MD, PhDDate Written: 2011-07-09Salmonella nomenclature is complex and has caused confusion. At the present time, by molecular methods the genus Salmonella is known to have only two species: Salmonella enterica and Salmonella bongori. Salmonella enterica is divided into six subspecies, each of which is further divided into numerous serovars (or serotypes) based on serological testing of somatic (O) and flagellar (H) antigens. Serovars are then designated by a formulaic concatenation of the antigens, known as the “antigenic formula”. The terms “serovar” and “serotype” appear to be used interchangeably, however, there has been a preference expressed for the term “serovar” by the Association of Public Health Laboratories and the World Health Organization (which uses “serovar” in its documentation). As a result, that will be the term used in this document.A significant number of what are now known to be serovars were originally thought to be distinct species of Salmonella, and those species names became rooted in common clinical usage. As a result, Salmonella nomenclature deviates from that of other bacteria, which, for the most part, do not have common names assigned to serovars. (Even the well-known E. coli O157:H7 is known by its antigenic formula.) Salmonella, on the other hand consists of 2579 individual serovars (2007 WHO documentation), about 1400 of which have common names.Here is where it gets tricky(er). While it would be impractical to eradicate commonly used names for important serovars, formatting is used to indicate that the names are not that of species, generally by NOT italicizing and instead capitalizing the first letter of the serovar name as follows: “Salmonella enterica subsp. enterica serovar Typhimurium”. Since all the commonly named serovars are in the subspecies enterica, that middle designation can be left off, resulting in the name “Salmonella enteric serovar Typhimurium”.LOINC® Terms associated with Salmonella SerotypingSalmonella sp identified [Type] in Isolate (59846-6)This code has one of seven possible answers to differentiate the two species and six subspecies in the case of enterica. When performed by the CDC, the answer is derived from a series of about 50 biochemical tests and consists of seven possibilities:Salmonella enterica subspecies enterica (type I)Salmonella enterica subspecies salamae(type II)Salmonella enterica subspecies arizonae(type IIIa)Salmonella enterica subspecies diarizonae(type IIIb)Salmonella enterica subspecies houtenae(type IV)Salmonella bongoriSalmonella enterica subspecies indica(type VI)

165Salmonella sp antigenic formula [Identifier] in Isolate by Agglutination (56475-7)This code has a discrete set of over 2500 possible answers representing the antigenic formula concatenated from the O and H antigens and sometimes other antigens found by agglutination testing. This code is intended to report only the antigenic formulae of the serovar, not the common name for the serovar.The format of the antigenic formula generally is expected to contain the subspecies type (I,II,IIIa, etc.), then followed by somatic (O) antigens, flagellar (H) phase 1 antigens, flagellar (H) phase 2 antigens, and other antigens separated by a colon. So, a Salmonella type IV (Salmonella enteric subspecies houtenae) with O antigen 43 and H (phase 1) antigens z36, z38 would be reported as “IV 43:z36,z38:-”.Salmonella sp serovar [Type] in Isolate (65756-9)This code is intended to report a final answer for the serovar found, thus has an answer list similar in size to 56475-7. It will report the common name for the antigenic formula reported by that code (if there is a common name). If there is no common name, it will report the antigenic formula. In about 90% of cases the antigenic formula reported by 56475-7 will cleanly map to a serovar to report by this code. In the remaining 10% of cases, however, serovars can be further distinguished even in the light of identical antigenic formulas. These distinctions can involve further biochemical testing or sometimes further antigen testing.

166Segmented Neutrophils Versus Polymorphonuclear WBCAuthor: David Baorto, MD, PhDDate Written: 2011-04-17Segmented neutrophils are commonly referred to as polymorphonuclear neutrophils, PMNs, or “polys”. Therefore, in common usage the term polymorphonuclear leukocyte (or polymorphonuclear WBC) refers to neutrophils. Caution coding in this area should be applied because there is a usage whereby all granulocytes, including neutrophils, basophils and eosinophils, can be referred to as polymorphonuclear cells due to the variable shape of their nuclei. Basophils can therefore be referred to as polymorphonuclear basophil (PMB), eosinophils as polymorphonuclear eosinophils (PME), in addition to neutrophils (polymorphonuclear neutrophil, PMN).Refer to the following Wikipedia page for more information: http://en.wikipedia.org/wiki/Granulocyte.

167Vitamin D Author: David Baorto, MD, PhDDate Written: 2011-02-19 General summaryVitamin D is a prohormone that is involved in calcium and phosphate homeostasis, bone formation, and immune regulation. The determination of vitamin D is complex because it is not a single component, but has two major forms, each of which has several metabolic stages leading to an active end product. Vitamin D3, also known as cholecalciferol, is the form that occurs naturally in humans and is produced in the skin of vertebrates from 7-dehydrocholesterol exposed to UV B radiation from the sun. Vitamin D3 can also be obtained from certain dietary animal products and supplementation. Vitamin D2, also known as ergocalciferol, is introduced into humans primarily by commercial supplementation. It is produced by UV irradiation of ergosterol, a substance that occurs in yeast, molds and certain plants.Despite their distinct origins, both vitamin D2 and D3 share similar chemical structure, metabolic activation in humans, and presumably bioactivity as well, although the literature suggests that vitamin D2 is biologically inferior. Their structures differ only by a side chain, and the starting forms of both in humans, cholecalciferol and ergocalciferol, are hormonally inactive. Both undergo hydroxylation to 25-hydroxyvitamin D (2 or 3) in the liver, followed by further conversion to the active hormone, 1,25-dihydroxyvitamin D (2 or 3) in the kidney (or the placenta during pregnancy). 25-hydroxyvitamin D3 is also known as calcidiol, while the active form 1,25-dihydroxyvitamin D3 is also known as calcitriol. It is more difficult to find trivial name forms for the vitamin D2 group, although IUPAC recommends ercalcitriol for the active form of D2 (see nomenclature table).“Vitamin D” based NameTrivial NameVitamin D2ergocalciferolVitamin D3cholecalciferol25-Hydroxyvitamin D2-none found-25-Hydroxyvitamin D3calcidiol1,25-dihydroxyvitamin D2ercalcitriol1,25-dihydroxyvitamin D3calcitriolMeasurement of the vitamin D parent compound, whether D3 or D2, has limited clinical value because, with a half-life of about one day, the value reflects mostly recent sun exposure or intake (there may be a utility in assessing absorption from the gut). Vitamin D status is generally determined by measuring the intermediate 25-hydroxyvitamin D form, the major circulating form with a half-life of 2-3 weeks. Whether there is a value to distinguishing the relative contribution of 25-hydroxyvitamin D2 compared to D3 depends on the objective. Understanding vitamin D status generally requires a total number; however, the need to assess response to supplementation with vitamin D2, for example, may be helped with distinct reports on both forms. The active hormone, 1,25-dihydroxyvitamin D (2 or 3), has a short half- life of 4-6 hours, and its concentration is tightly regulated. This makes it a poor candidate for assessing nutritional vitamin D status, although its measurement has utility in differential diagnosis of hyper and hypocalcemia and bone and mineral disorders.An alternative metabolism pathway in the kidney yields a 24,25-dihydroxyvitamin D form. This is the most prevalent dihydroxylated metabolite in circulation, but (unlike the 1,25-dihydroxyvitamin D forms), it is not hormonally active. The physiological role of 24,25-dihydroxyvitamin D is unclear, although it has been suggested that the active hormone may self-modulate by shunting toward this pathway.

168Specific partsVitamin D3 Vitamin D plays important roles in maintaining calcium and phosphate levels, and in immune regulation, but its determination is complex due to multiple metabolic intermediates and two major forms. Vitamin D3, also known as cholecalciferol, is the parent compound of one of the two major families of vitamin D (D2 and D3). Vitamin D3 is the form of vitamin D that is endogenously produced in the skin of vertebrates (including humans) upon exposure to sunlight (specifically UV B). It can also be obtained from dietary animal products, or dietary supplements. Vitamin D3, whether produced endogenously or ingested, is a prohormone form that is not active until further metabolism first to 25-hydroxyvitamin D3 (in the liver), then finally to 1,25-hydroxyvitamin D3 (in the kidney or placenta) . Measurement of the vitamin D parent compound, whether D3 or D2, has limited clinical value because, with a half-life of about one day, the value reflects mostly recent sun exposure or intake (there may be a utility in assessing absorption from the gut). Vitamin D status is generally determined by measuring the intermediate 25-hydroxyvitamin D form, the major circulating form with a half-life of 2-3 weeks. The need to assess response to supplementation with vitamin D2, for example, may be helped with distinct reports on both forms.Vitamin D2Vitamin D plays important roles in maintaining calcium and phosphate levels, and in immune regulation, but its determination is complex due to multiple metabolic intermediates and two major forms. Vitamin D2, also known as ergocalciferol, is the parent compound of one of the two major families of vitamin D (D2 and D3). Vitamin D2 is the form of vitamin D that is not endogenously produced in the skin. It is produced upon UV radiation of ergosterol, which occurs in molds, yeast, and certain plants, and its major introduction into humans is via commercial supplementation. Vitamin D2 is a prohormone form that is not active until further metabolism first to 25-hydroxyvitamin D2 (in the liver), then finally to 1,25-hydroxyvitamin D2 (in the kidney or placenta) . Measurement of the vitamin D parent compound, whether D3 or D2, has limited clinical value because, with a half-life of about 1 day, the value reflects mostly recent sun exposure or intake (there may be a utility in assessing absorption from the gut). Vitamin D status is generally determined by measuring the intermediate 25-hydroxyvitamin D form, the major circulating form with a half-life of 2-3 weeks. The need to assess response to supplementation with vitamin D2, for example, may be helped with distinct reports on both forms.25-Hydroxyvitamin D, 25-Hydroxyvitamin D2, and 25-Hydroxyvitamin D3The 25-hydroxyvitamin D intermediate is the major circulating metabolite of vitamin D with a half-life of 2-3 weeks, and it is the most useful measure of vitamin D status. The determination of vitamin D is complex due to multiple metabolic intermediates and two major forms, vitamin D2 and D3. The lack of specification of the form generally indicates that both are included. Vitamin D3 is the form of vitamin D that is endogenously produced in the skin of vertebrates (including humans) upon exposure to sunlight (specifically UV B), whereas vitamin D2 is produced upon UV radiation of ergosterol, which occurs in molds, yeast, and certain plants, and its major introduction into humans is via commercial supplementation, although both D3 and D2 can be included as supplements. The 25-hydroxyvitamin D metabolites of both forms (also known as calcidiol in the case of D3) are produced in the liver from the corresponding parent compound. Whether there is a value to distinguishing the relative contribution of 25-hydroxyvitamin D2 compared to D3 depends on the objective. Understanding vitamin D status generally requires a total number; however, the need to assess response to supplementation with vitamin D2, for example, and other specific cases, may be helped with a distinct reports on both forms.1,25-Hydroxyvitamin D, 1, 25-Hydroxyvitamin D2, and 1, 25-Hydroxyvitamin D3

1691,25-hydroxyvitamin D is the physiologically active form of vitamin D. When metabolically activated to this form, vitamin D plays important roles in maintaining calcium and phosphate levels, and in immune regulation. It increases intestinal absorption of calcium and phosphorus, and in concert with parathyroid hormone increases bone resorption. There are two major forms of vitamin D, each of which can be activated to a 1,25-dihydroxy form (also known as calcitriol in the case of D3 and ercalcitriol in the case of D2). Vitamin D3 is the form of vitamin D that is endogenously produced in the skin of vertebrates (including humans) upon exposure to sunlight (specifically UV B). It can also be obtained from dietary animal products, or dietary supplements. Vitamin D2 is the form of vitamin D that is not endogenously produced in the skin. It is produced upon UV radiation of ergosterol, which occurs in molds, yeast, and certain plants, and its major introduction into humans is via commercial supplementation. Vitamin D, whether produced endogenously or ingested, is a prohormone form that is not active until further metabolism first to 25 hydroxyvitamin D3 (in the liver), then finally to the active 1,25 hydroxyvitamin D3 (in the kidney or placenta). The active hormone, 1,25-dihydroxyvitamin D (2 or 3), has a short half-life of 4-6 hours, and its concentration is tightly regulated. This makes it a poor candidate for assessing nutritional vitamin D status, although its measurement has utility in differential diagnosis of hyper and hypocalcemia and bone and mineral disorders.24,25-Dihydroxyvitamin D324,25-dihydroxyvitamin D3 is a compound which is closely related to 1,25-dihydroxyvitamin D3, the active form of vitamin D3, but (like vitamin D3 itself and 25-hydroxyvitamin D3) is inactive as a hormone. It is produced from 25-hydroxyvitamin D3 by alternative metabolic pathway in the kidney. The physiological role of 24,25-dihydroxyvitamin D is unclear, although it has been suggested that the active hormone may self-modulate by shunting toward this pathway.ReferencesHoughton, L A, Vieth R. The case against ergocalciferol (vitamin D2) as a vitamin supplement. American Journal of Clinical Nutrition 2006; 84 (4):694-697. [PubMed: 17023693]Morris, H A. Vitamin D: A Hormone for All Seasons – How much is enough? Understanding the New Pressures. Clinical Biochemist Reviews 2005; 26(1):21-32. [PubMed: 16278774]St-Arnaugh, R, Glorieux, F H. 24, 25-Dihydroxyvitamin D—Active Metabolite or Inactive Catabolite? Endocrinology 1998;139:3371-3374. [PubMed: 9681484]IUPAC-IUB Joint Commission on Biochemical Nomenclature (JCBN). Nomenclature of vitamin D. Recommendations 1981. Pure & Appl.Chem. 1982; 54(8): 1511—1516.Burtis, C A, Ashwood, E R. Tietz Textbook of Clinical Chemistry, 3rd ed.: Saunders; 1994.Wikipedia: http://en.wikipedia.org/wiki/Vitamin_D

170Free Thyroxine Index Variants Author: David Baorto, MD, PhDDate Written: January 2012 Although direct measurement of the free hormones has recently become more prevalent, the older methods to estimate free hormone levels by deriving an index still persist. The index methods involve adjusting the total thyroid hormone concentration (TT4) for the thyroid binding capacity of the serum (T3 uptake or thyroid binding globulin TBG) to yield an indicator or estimate of the free hormone level, free thyroxine index (FTI). Over time and across labs this calculation has been and is done in different ways, yielding different results sometimes with different properties. This is mostly due to distinctions in what is known as “T uptake”. Here are some variations:1. FTI = TT4(ug/ml) x T3 uptake (%)/100 a. This has sometimes been noted leaving off the division by 100, but not in practice: FTI = TT4(ug/ml) x T3 uptake(%).2. FTI = TT4(ug/ml) x (T3 uptake patient/T3 uptake control) (ratio) a. Here, “T3 uptake” used in the calculation is actually the thyroid hormone binding ratio noted throughout the literature (THBR), the ratio of patient to reference serum values of T3 uptake.3. FTI = TT4(ug/ml) / T uptake units (ratio) a. Here “T uptake units” is ratio of patient to reference serum levels of thyroxine binding globulin (TBG).Notes• In variation 1, the uptake is a %, while in variations 2 and 3 the uptake is a unit-less ratio normalized to control, known in the literature as the thyroid hormone binding ratio (THBR).• Variation 1 is apparently the reporting approach used by Mayo, ARUP, and LabCorp and many hospital labs (such as one large NY hospital). It adjusts the total T4 by a T3 uptake % (approximate range 25-40%), and yields FTI values often in the approximate range of 1 to 5 (adults) and is reported as unit-less.• Variation 2 is apparently the reporting approach used by Quest Diagnostics-Nichols and some hospital labs (such as another large NY hospital), and variation 3 apparently the primary method used by Abbott Axsym (although values can be converted).• Variations 2 and 3 both adjust the total T4 (TT4) by a ratio referenced to a control value of 1, so FTI numerically is in the approximate range of TT4 concentration 5 – 12 (adults). While it is usually reported as unit-less, there is a case that it is really an adjusted TT4 concentration, and in fact the Abbott AxSym package insert (variation 3 above) notes units of ug/dl for its calculated FTI value.• THBR is a normalized T3 uptake which represents how much labeled T3 did NOT find a binding site in patient serum, meaning it is the INVERSE of available binding sites. Conversely, in the AxSYM method “T uptake units” is a control normalized ratio of TBG, a measure proportional to the binding sites. This may account for why one MULTIPLIES and the other DIVIDES by the ratio. The TBG is not the only thyroid hormone binding protein, another distinction between 2 and 3.• Historically T3 instead of T4 has been more commonly used as the tracer in uptake assays for practical

171reasons. T3 has a lower affinity for TBG, so more would be available to be taken up by the scavenger and easier to count. With non-isotopic techniques, this may be less of an issue, and it has been suggested that T4 uptake would be more appropriate to adjust TT4 concentration. T4 uptake assays do exist.

172Streptococcus pneumoniae serotype nomenclatureAuthor: Swapna Abhyankar, MDDate written: May 2017Streptococcus pneumoniae is an important human pathogen whose virulence is based primarily on its polysaccharide capsule, which protects it by shielding it from the immune system. Over time, study of the polysaccharide capsule has identified multiple serogroups and serotypes. Serotypes are defined based on the chemical structure and immunologic properties of the polysaccharide, and each serogroup contains one or more serotypes that elicit the same antibody response.Over time, two parallel serotype naming systems arose, one in the U.S. and one in Denmark. Initially in LOINC, our intent was to create terms based on the U.S. serotype number, but that was not clearly stated in the Component. Over time, as the number of serotypes that have been identified increased in number and were assigned new serogroup, U.S. serotype, and Danish serotype numbers, many of our existing terms became ambiguous because the number in the Component could potentially represent any of the three. More recently, it has come to our attention that the Danish naming system is the one that has been widely adopted, including in the U.S.Beginning with the June 2017 release, LOINC adopted the Danish numbering system in the Component for all pneumococcal terms and explicitly include the words “Danish serotype” in the Component. To that end, we deprecated any existing term that could be ambiguous as to whether the number in the Component referred to the serogroup, U.S. serotype, or Danish serotype, and mapped it to a new term for the corresponding Danish serotype (assuming that the original term was, indeed, created to represent the U.S. serotype as stated above). For existing terms in which the existing Component could only represent the U.S. serotype (i.e., there are no corresponding serogroups or Danish serotypes with the same number), we updated the Component to the corresponding Danish serotype.In the RELATEDNAMES2 field, we have included the corresponding U.S. serotype number for each of the Danish serotypes, as well as information about whether each serotype is included in each of the 23-valent polysaccharide vaccine (PPSV23), 13-valent pneumococcal conjugate vaccine (PCV13), or 7-valent pneumococcal conjugate vaccine (PCV7), respectively. This same information is also provided in the following table, though please note that the table does not contain every identified serotype, only the ones for which LOINC codes exist.Danish serotype numberU.S. serotype numberVaccine(s) that include this strain11PCV13, PPSV2322PPSV2333PCV13, PPSV2344PCV7, PCV13, PPSV2355PCV13, PPSV236A6PCV136B26PCV7, PCV13, PPSV237A77F51PCV13, PPSV2388PPSV239N9PPSV239V68PCV7, PCV13, PPSV2310A34PPSV2311A43PPSV23

17312F12PPSV231414PCV7, PCV13, PPSV2315B54PPSV2316F1617F17PPSV2318C56PCV7, PCV13, PPSV2318F1819A57PCV13, PPSV2319B5819F19PCV7, PCV13, PPSV2320A2022F22PPV2323A4623F23PCV7, PCV13, PPSV2333F70PPSV23ReferencesGeno K A, Gilbert G L, Song J Y, Skovsted I C, Klugman K P, Jones C, Konradsen H B, Nahm M H. Pneumococcal capsules and their types: past, present, and future. Clinical Microbiology Reviews 2015; 28(3):871-899. [PubMed: 26085553]

174Appendix H LOINC CommitteeAs secretariat, Regenstrief Institute has adopted a new, lightweight structure and governance principles for the LOINC Committee. These principles were unanimously approved by the Clinical LOINC Committee at the September 2017 meeting and by the Laboratory LOINC Committee at the December 2017 meeting.The LOINC Committee is comprised of the members of its composite committees:• Laboratory LOINC Committee• Clinical LOINC Committee • Nursing Subcommittee • Document Ontology Subcommittee• LOINC/RadLex CommitteeInterested parties may formally apply for inclusion in one or more of the composite committees as an individual, organization, Standards Development Organization (SDO), or international affiliate. The application form and membership requirements are available on the LOINC website at loinc.org/committee. We welcome applications for new members who meet the qualifications. Committee membership remains free of charge.A roster of LOINC Committee members is available on the LOINC website at loinc.org/committee.

A1Annex LOINC/RSNA Radiology Playbook User Guide1 IntroductionWelcome to the LOINC/RSNA Radiology Playbook User Guide. This work is the result of a multi-year collaboration between Regenstrief Institute and the Radiological Society of North America (RSNA), supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB). The participants have developed a model that combines and unifies the useful aspects of LOINC Radiology and the RSNA RadLex Playbook. Both of these terminology initiatives are designed to represent concepts of radiology orderables and results and their attributes.Each term in the unified Playbook model has a name (a.k.a. description), and takes on a number of attributes. This guide is intended to describe the semantics, syntax, and proper usage of those attributes. Within the terminology, these attributes are used as building blocks to construct several types of standard names, including a fully specified name, long name, and short name. A list of the Playbook attributes is shown below. Attributes are organized according to attribute groups, consisting of the major bullet headings below, and by more specific sub-attributes, shown in the minor bullets below and denoted by a dot after the attribute group, such as Pharmaceutical.Route. • Modality • Modality.Modality Type • Modality.Modality Subtype• Anatomic Location • Anatomic Location.Region Imaged • Anatomic Location.Imaging Focus • Anatomic Location.Laterality.Presence • Anatomic Location.Laterality• View • View.Aggregation • View.View Type• Timing• Maneuver • Maneuver.Maneuver Type

A2• Pharmaceutical • Pharmaceutical.Substance Given • Pharmaceutical.Route• Reason for Exam• Guidance • Guidance for.Presence • Guidance for.Approach • Guidance for.Action • Guidance for.Object• SubjectThe chapters that follow provide a guide to the usage of each of the above attributes.1.1 Codes and workflowsRadiology procedure codes impact a variety of workflows in the health care enterprise, including ordering, scheduling, billing, protocol specification, image acquisition, and image interpretation, among others. In each case, the codes serve specific purposes in identifying imaging exams. While there is a great deal of overlap between these workflows, there are also important differences. For example, radiology billing is often concerned with a less detailed description of an imaging exam, while the radiology ordering process often involves more information about the requested study.The Playbook work has been primarily focused on addressing the needs of the radiology ordering workflow. The semantic model described in this document is intended principally to characterize radiology “orderables.” This then raises the question of what constitutes an orderable exam, an issue which is complicated by several factors. First, different institutions may expose different levels of granularity at the point of radiology order entry. While one may consider “CT abdomen / pelvis with contrast” to be an appropriate option in an order entry system, another institution may wish to provide the choice “CT abdomen / pelvis with contrast, liver mass.” Second, in certain circumstances, what is actually done to satisfy an imaging request may not match the ordered procedure precisely. For example, image-guided interventions often entail procedural modifications at the time of the exam. In such cases, modified or additional orderables may be entered, even though these may not have been exposed in the clinical ordering interface. Third, some institutions have separate orderable codes for interpretations of studies performed at outside institutions (“interpretation only”).The model aims to allow for the type of variation described above, so as to broadly fulfill the needs of radiology ordering workflows at a variety of institutions. We discussed the concept of “interpretation only” and decided not to create a duplicate set of orderables for the interpretations of outside films. Instead, we created a single LOINC code, 86371-2 Study Interpretation of outside study, that can be used with the primary study code to report whether the study being interpreted was performed at an outside institution. Regarding the technical factors in image acquisition, related work at a more granular level is being done by the DICOM Standards Committee.11 http://dicom.nema.org/Dicom/News/oct2013/docs_oct2013/sup121_pc.pdf, Accessed 14 May 2016.

A32 Syntax2.1 OperatorsThe model uses several logical operators (“.”, “+”, “>”, “&”, “^”, “()”, “&&”) to express combinations of atoms.2.1.1 “.” (Dot)Used to specify refinement of a given attribute or attribute component. For example, the dot operator may be used with the Imaging focus component of the Anatomic Location attribute to specify a more granular focus (e.g. Ribs.lower). For modality subtypes, it is used to indicate a certain type of imaging technique (e.g. “CT.angio”). 2.1.2 “+” (Plus)Used to combine atoms, such as Anatomy atoms or View atoms, with AND semantics.2.1.3 “>” (Greater than)Used exclusively to separate the Region Imaged from the anatomic Imaging Focus.2.1.4 “&” (Ampersand)Used to separate Region imaged and Imaging focus pairs when more than one anatomic location across more than one region is imaged. May alternatively be used as a low-precedence AND, such as in the Timing attribute WO & W, which has a combined “before and after” notation.2.1.5 “^” (Carat)Used primarily to separate the Maneuver attribute from the View attribute.2.1.6 “()” (Parentheses)Used to indicate bindings between Maneuver and View values when more than one View.Aggregation and/or View.View Type exists and the maneuver(s) only applies to a subset of the View values.2.1.7 “&&” (Double ampersand)Used to indicate parallelism in cases where the relationships between values across multiple attributes needs to be specified. In earlier versions the “&” was used for parallelism, but since we started using “&” to separate Region imaged and Imaging focus pairs, we created a new delimiter for parallelism in order to distinguish the two concepts. 2.1.8 PrecedenceOperator precedence, from greatest to least is as follows: “.”, “+”, “>”, “&”, “^”, “()”, “&&”

A42.2 ParallelismIn selected circumstances, it is necessary to specify multiple values for two or more specific attributes or components. In such cases, the correspondences between values across attributes or components may be modeled by maintaining a consistent ordering of values. For example, a radiographic exam of the ribs often includes a radiograph of the chest. The specific views may include an AP view of the chest, and an oblique view of the ribs. Multiplicity of the Anatomic Location attribute as well as the View attribute is modeled using parallelism and the “&&” operator. That is, with Anatomic Location Chest && Ribs and View AP && Oblique the appropriate correspondence between Chest and AP as well as between Ribs and Oblique is maintained by virtue of the relative positions of the atoms (i.e., both Chest and AP are listed first in their respective attributes).3 Modality3.1 DefinitionsModality is used to represent the device used to acquire imaging information. Modalities consist predominantly of a subset of the two-letter DICOM modality codes. DICOM modality codes are listed in PS3.3, Section C.7.3.1.1.1 in the 2016 release of the DICOM standard.2 In addition, the Modality code {Imaging modality} is used to indicate image-guided procedures for which the specific type of imaging is not explicitly modeled.A Modality subtype may be listed, separated by a “.”, to signify a particularly common or evocative configuration of the modality.Note that when such Modality subtypes are specified, the given type of technique is included in a study, although this does not necessarily imply that the study consists exclusively of that subtype of imaging. For example, an exam with Modality and subtype US.doppler does not mean that only Doppler imaging was performed. On the other hand, XR.portable generally does indicate that only portable images were obtained.3.2 Usage Notes1. Subtype angio: This Subtype is used for procedures designed to give angiographic images of the vessels (either blood or lymphatic vessels). This should not be used for US; Doppler should be used instead. Angio is not a synonym for contrast administration because some angiographic MR studies do not require intravenous contrast administration.2. Mammography tomosynthesis Subtype: This Subtype, also known as digital breast tomography (DBT), is a type of digital mammography that is distinct from the concept of full field digital. MG.tomosynthesis is used for 3-dimensional imaging, while typical digital mammography is 2-dimensional. Digital 2D mammograms may also be reconstructed into 3D images, but these would not be classified under MG.tomosynthesis.3. Obsolete mammography subtypes: We originally included MG.analog and MG.full field digital (FFD) in the list of allowed MG Subtypes to specify analog mammography and digital mammography, respectively, while MG without a Subtype signified a procedure that could be done with digital or analog equipment. However, given that over the past several years digital mammography has become standard practice, we recommend that moving forward, FFD does not need to be specified as a subtype of MG. 2 http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf, Accessed 14 May 2016.

A5Instead, the generic MG LOINC codes should be used for 2D mammography, which in most cases will be digital images but may also include analog images.4. CR (computed radiography) vs DX (digital radiography) vs RG (radiographic imaging/conventional film screen): XR will be adopted generically to signify orders for planar radiography. When the images are acquired, the imaging modality may wish to insert a more specific modality code in the DICOM files.5. Doppler Subtype vs DICOM modality codes DD (duplex Doppler) and CD (color flow Doppler): US.Doppler will be used as the attribute of the orderable procedure. When the images are acquired, the imaging modality may wish to insert a more specific modality code in the DICOM files.6. Portable indicates whether the device is movable or whether the patient will come to the radiology department for imaging.7. SPECT will be represented as a Modality subtype of the NM Modality (NM.SPECT) rather than using ST, the DICOM modality code for SPECT.8. Because there is no DICOM modality code for DEXA, DXA will be adopted as the Modality code.9. When an imaging study involves more than one imaging Modality, “+” is used to concatenate the two Modalities, such as PT+CT or NM.SPECT+CT. The Modality listed first corresponds to the departmental area where the device is typically located. E.g., PT+CT, not CT+PT10. For studies with two Modalities that have separate attributes and are performed consecutively (e.g., RF Upper GI with XR abdomen), “&&” is used in the harmonized model and in LOINC to separate the values of each attribute, including Modality, to maintain parallelism across attributes, e.g., XR && RF. However, note that in the Radiology Lexicon (RadLex) imaging modality hierarchy, such Modalities that are commonly performed consecutively are represented as a single entity under the combined modalities node using a “+”, e.g., XR+RF.11. Precedence of operators is “.”, “+”, “&&” (the other delimiters are not used in the Modality attribute).12. The perfusion Modality subtype indicates the study is intended to measure tissue perfusion; if the study is designed to image the vessels, use the angio Modality subtype.13. 3D is an image processing step, and can be performed on images from a variety of modalities. Its use is discouraged. If adopted locally, it may be used as shown in Reason for Exam section.14. Modality {Imaging modality} is used to refer to image-guided procedures, where the particular type of imaging used is not specified in the orderable. For example, liver biopsies may be performed under ultrasound or CT guidance, although the particular modality used may be at the discretion of the operator. In such cases, {Imaging modality} indicates that the order is modality-agnostic.3.3 Allowed Modality/Subtype Combinations• CT • CT.angio • CT.scanogram • CT.densitometry • CT.perfusion • CT.portable

A6• DXA • DXA.densitometry• MG • MG.tomosynthesis • MG.stereotactic• MR • MR.angio • MR.functional • MR.spectroscopy• NM • NM.dosimetry • NM.SPECT • NM.SPECT+CT• PT • PT.perfusion • PT+CT• RF • RF.angio • RF.video • RF.portable• US • US.densitometry • US.Doppler • US.portable• XR • XR.tomography • XR.portable• {Imaging modality}4 Anatomic Location

A7This chapter describes how anatomic terms are used to identify the body region and anatomic focus of imaging. It also specifies the syntax to be used when more than one anatomy term applies to a given exam code, and delineates how laterality should be specified when necessary.4.1 DefinitionsThe Anatomic Location attribute specifies the body part or body region that is imaged and includes the sub-attributes, Region Imaged and Imaging Focus. The most specific anatomic structure should be specified. Multiple Anatomic Locations may be specified using the syntax specified below and should be specified only when necessary to distinguish the code from other codes. Anatomic Location terms are generally drawn from the RadLex anatomic hierarchy. Region imaged is used in two ways. First, as a coarse-grained descriptor of the area imaged and a grouper for finding related imaging exams; or, it is used just as a grouper. For example, when an abdominal CT focuses on the liver, it images the abdomen as a whole and also would be a relevant comparison for other abdominal CT exams (e.g., renal CT), thus making abdomen a coarse-grained descriptor as well as a grouper. Similarly, a head CT focusing on the brain may also be a relevant comparison for other head CT exams (e.g., orbit CT), making it both a descriptor and grouper. Alternatively, for most studies with Upper extremity or Lower extremity as the Region imaged and a specific Imaging focus, such as Wrist or Knee, the Region imaged is a grouper only, because the entire extremity is typically not imaged.Imaging focus is defined as a more fine-grained descriptor of the specific target structure of an imaging exam. In many areas, the focus should be a specific organ. For example, in the Region imaged Abdomen, the Imaging focus might be Liver, Pancreas, Adrenal gland, Kidney, etc. In other areas, the Imaging focus will simply be a more specific area within a given region. For example, in the Region imaged Upper extremity, the Imaging focus might be Shoulder, Upper arm, Elbow, Forearm, Wrist, Hand, etc.Our goals are to populate both the Region imaged and Imaging focus sub-attributes for all terms, except where the Region Imaged is the focus of the study (see Section 4.2.1). We will also constrain Region Imaged to the following short list of regions:• Head• Neck• Chest• Breast• Abdomen• Pelvis• Extremity• Upper extremity• Lower extremity• Whole body (used when the Imaging focus exists throughout the body and is being imaged in its entirety, such as Bones or Bone marrow)• Unspecified (represented in LOINC as XXX, used when the Imaging focus exists in multiple parts of the body but only one specific instance is being imaged, such as a Blood vessel)

A8Pathologic entities may not serve as an anatomic location (e.g., renal tumor). If there is a need to specify a pathologic entity to distinguish to exam codes, the pathologic entity should be specified with the Reason for Exam attribute or Guidance for.Object sub-attribute.4.2 Syntax and Modeling PrinciplesThe syntax used to describe the Anatomic Location attribute is as follows:<body region imaged> “>” <imaging focus>For example, for an abdominal CT with a focus on the liver, the Anatomic Location would be specified as: Abdomen>Liver4.2.1 Specifying Region(s) imaged without an Imaging focusIf there is a single anatomic context associated with a code, it should be specified as <body region imaged> without an <imaging focus>, for example, for an abdominal CT, the Anatomic Location would be specified as:AbdomenWhen multiple regions are imaged without an imaging focus, such as CT of the head and neck, the two regions are separated by a “+”:Head+Neck4.2.2 Imaging foci that cross body regionsCertain Imaging foci cross multiple body regions, such as Pharynx, which is included in both the Head and Neck Imaging regions. In this case, the regions will be separated by a “+” as follows:Head+Neck>Pharynx4.2.3 Specifying multiple Anatomic locationsWhen more than one Anatomic location is imaged, where each location has a different Region imaged and Imaging focus pair, they are separated by an “&” according to the syntax:<body region imaged A> “>” <imaging focus A> “&” <body region imaged B> “>” <imaging focus B>For example, a study of the chest and abdomen focused on the lung and liver would be specified as follows:Chest>Lung & Abdomen>Liver4.2.4 Broad region combined with a specific focusIn other situations, a specific Imaging focus in one Region imaged may be imaged at the same time as a different Region imaged without a focus. Consider an MRI examination of the face and neck. Face is an Imaging focus of the Region imaged Head. Neck is an additional Region imaged. In such situations, the lower precedence of the “&”

A9compared to the “>” operator is used to combine these areas as follows:Head>Face & Neck4.2.5 Specifying terms without an anatomic locationIn some cases, such as fluoroscopic guidance codes, a specific Anatomic Location may not be relevant, in which case we use the general unspecified Region imaged.4.2.6 ParallelismIn rare instances, a complex study may require parallelism to model correctly. In this instance, a double ampersand is used to separate the elements of the study. For example, a study that consists of PA and lateral views of the chest plus 4 oblique views of the right ribs could be represented as with the following Anatomic location and Views Chest && Chest>Ribs.Right Views 2 PA+Lateral && Views 4 Right oblique4.2.7 Operator precedenceThe precedence of operators is “.”, “+”,“>”,”&”,”&&”. For example:Head+Neck > Pharynxis equivalent to(Head+Neck)> Pharynx4.2.8 Region imaged as grouper +/- coarse-grained descriptorThe nature of the study should make it clear whether the Region imaged is functioning as both a coarse-grained descriptor of the area imaged and a grouper or as a grouper only. The following are additional guidelines to help users make that determination:1. In general, when the Region imaged is the Head, Neck, Chest, Abdomen or Pelvis, it is both a coarse-grained descriptor and a grouper; 2. For spine studies, the Region imaged is typically a grouper only (this is an exception to rule #1). For example, a C-spine exam will have the Anatomic location specified as Neck>Spine.cervical, but typically the exam would focus on the spine and not include general imaging of the neck; 3. When the Region imaged is Upper extremity or Lower extremity, it typically functions as a grouper only.4.2.9 LateralityMany exams require laterality to be specified in order to be performed. These exams will be signified with an Anatomic Location.Laterality.Presence attribute set to True. For terms with Laterality.Presence = True, the Laterality

A10attribute must not be null. Valid values of the Laterality attribute are:• Left• Right• Bilateral• Unilateral• UnspecifiedThe recommended practice is to specify one of Left, Right, or Bilateral for Anatomic Location.Laterality whenever Anatomic Location.Laterality.Presence = True. If the Laterality.Presence attribute is False, the Laterality attribute must be null. Laterality applies to the most specific anatomic part associated with the exam code.4.2.10 SubjectSome exams are relevant only to a Fetus or a Gestation. This distinction will be represented when necessary by the Subject attribute.4.2.11 Ectopic AnatomyEctopic anatomy, such as a transplanted kidney, if needed to distinguish an exam code, should be specified as a Reason for Exam, not as an Anatomic Location. Anatomic Location corresponds to where the transplanted kidney is located, e.g., Pelvis.4.2.12 Anatomic terminology in the extremitiesIn the upper extremity, the term Upper arm is preferred over the term “arm.” Even though these are technically equivalent, the redundancy of Upper arm provides for greater clarity. Upper arm is also preferred over “humerus” for this area, as the latter is bone-specific and could be construed as excluding soft tissues. Similarly, in the lower extremity, Lower leg is preferred over “leg,” “calf” and “tibia / fibula.”4.2.13 Singular vs. PluralThe singular form of an anatomic structure is typically used, except in a few specific cases that primarily apply to vasculature, as noted below.4.2.14 Singular vs. Plural in the context of VasculatureFor the set of vessels associated with a particular region, organ or a specific group of vessels, we use the plural “Vessels”, “Veins” and “Arteries” to mean “set of”, for example, Adrenal vessels or Cerebral arteries. One use case for such pre-coordination is angiography, for example, CT angiography of the renal vessels would have the following Anatomic Location: Abdomen>Renal vesselsThe plural form does not imply laterality, which is still specified using the Laterality attribute (see 4.2.9 – Laterality). For example, Abdomen>Renal vessels.right means the set of renal vessels supplying the right kidney.

A11Specific named vessels use the singular form, e.g., Femoral vein and Superior mesenteric artery.When vessels in an extremity are imaged for a specific reason, such as varicose vein treatment, and there are different CPT codes for treatment of a single vessel and treatment of multiple vessels, we use the plural form to mean multiple and also created a singular form to represent treatment of a single vessel even though that vessel is not named, i.e., Extremity veins and Extremity vein.5 ViewThis chapter describes the View attribute, which is used to indicate the orientation of the patient in the image. This may reflect a combination of patient position and x-ray beam direction, or may alternatively be captured in a named, or eponymous, View. While this most commonly refers to radiography (e.g. a lateral radiograph of the chest), it may also be used with other modalities (e.g. prone CT of the chest, or an RF.angio study of the abdominal aorta with runoff views). Attribute values such as Runoff and Perfusion indicate that these views are included in the study but do not imply that the study is limited to only these views. Portable is specified as part of the Modality attribute rather than the View.In many instances, the View attribute will not be specified at all (e.g. MRI of the brain) in the Playbook model. However, note that in the LOINC model, the Component part of all radiology terms specifies the type of image acquired based on the modality: Views for XR, MG, and NM, and Multisection for MR, CT, US, NM.SPECT, PT, and XR.tomography.5.1 DefinitionsThe View attribute includes optional sub-attributes, including Aggregation and View Type.The Aggregation component is used to describe the extent of the imaging performed, whether in quantitative terms (e.g., 3 or more views) or subjective terms (e.g., Complete). The use of “Follow-up” as a value of the Aggregation attribute is replaced by the value Limited.View Type is used to name specific views, such as Lateral or Prone. View Type is an indicator of the orientation of the patient in an image, often carrying an implication of passive positioning (i.e. positioning which is not unduly onerous for the patient). This may reflect a combination of patient position and imaging direction (e.g. x-ray beam direction), and may be captured in a named or eponymous term (e.g. Norgaard view). The positioning involved in view types is designed to permit visualization of specific anatomic targets or particular orientations (e.g. open mouth odontoid view, swimmer’s view). Note that this positioning is usually not passive in the strict sense (i.e. performed by someone else), but rather passive in the sense that it is neither onerous for the patient, nor intended as a challenge to the patient. We considered creating a separate attribute for patient position, however, given that relatively few terms would include this attribute, we decided to include it within the View Type.5.2 SyntaxThe syntax used to describe the View attribute is as follows:<Aggregation> <View Type>For example, for a cervical spine X-ray with AP and lateral views, the View would be specified as:

A12 Views AP + lateral5.2.1 AggregationAs stated above, the Aggregation attribute is optional and, when included, specifies the extent of imaging performed in qualitative or quantitative terms. Qualitative descriptors include concepts such as Limited, Complete, and Multiple days. Quantitative aggregation values can specify a fixed number or range of views. The syntax for representing greater than or equal to and less than or equal to a specific number of views is “GE <#>” and “LE <#>, respectively. All of the following are examples of Aggregation: Views multiple areas Views 2 or 3 Views GE 5When the number of views is specified for a bilateral exam, the number refers to the number of views per side (e.g., XR Knee Bilateral 2 Views specifies 2 views of each knee)5.2.2 View TypeIn studies that specify a View Type, one or more values can be specified, separated by a “+”. For example: View lateral Views PA + lateral Views PA + lateral + R-oblique + L-oblique5.2.2.1 Eponymous View TypesEponymous views imply patient position and beam direction, as well as anatomic focus. Anatomic focus will continue to be specified separately as described in the previous chapter, recognizing this redundancy.5.2.2.2 Laterality in the viewLaterality may optionally be specified in certain views (e.g., “Lateral,” “Right lateral” or “Left lateral”). The laterality specified in this case indicates patient position relative to the beam, not the side of the patient being imaged, and is thus independent of the Anatomic Location.Laterality sub-attribute.5.2.3 Specifying Aggregation and View TypeIn many cases, both an Aggregation and one or more View Type values are specified. If the Aggregation value includes the specified View Types, the two values will not be separated by a delimiter. However, if the View Types are in addition to the number of views specified in the Aggregation value, the two values are separated by a “+”.For example, 2 views including an oblique view is represented as: Views 2 oblique

A13And 2 views and an additional oblique view is given by: Views 2 + oblique 5.2.4 ParallelismSometimes, parallelism is required to show which attributes are associated with which views. As described earlier, the double ampersand (“&&”) is used to show parallelism. For example, an exam that includes a PA view of the chest and at least three rib views would be modeled with the following View and Anatomic location attributes:Views GE 3 && View PA Chest>Ribs && ChestThat is, the atoms Chest>Ribs and Views GE 3 form one group, and Chest and View PA another group. Note that this parallelism relies on a consistent ordering of atoms to maintain proper groupings.6 TimingThe Timing/Existence attribute may be used in conjunction with both the Maneuver and Pharmaceutical attributes. This attribute specifies the existence of a Maneuver or a Pharmaceutical, or, in some cases, the existence of one Maneuver (or Pharmaceutical) and the absence of another, for example, views of the thoracolumbar spine without and with lateral bending.The Timing/Existence attribute can be either simultaneous:WOWA combined “before and after” notation that denotes separate sets of images:WO & WOr describing an image taken at a specified time after administration of the pharmaceutical:48H post7 Maneuver7.1 DefinitionsManeuvers relate to a challenge presented to a patient, often with the goal of elucidating or testing some dynamic aspect of anatomy or physiology. Maneuvers often carry an implication of patient exertion (e.g. Valsalva maneuver), although some maneuvers do not involve patient exertion (e.g. pharmacologic cardiac stress). Timing/Existence specifies the existence of that Maneuver, or, in some cases, the existence of one Maneuver and the absence of another. For example, flexion and extension views of the cervical spine are used to detect instability as indicated by changes in spinal alignment. Similarly, views of the thoracolumbar spine

A14without and with lateral bending may be done to evaluate scoliosis. Inspiratory and expiratory maneuvers as part of chest imaging may be used to evaluate the lungs. Maneuvers may occur in pairs (e.g. Flexion and Extension). As above, these factors distinguish maneuvers from patient actions used purely to gain a desired perspective. For example, the cross-table lateral radiograph of the hip requires the patient to be lying supine with the contralateral leg bent and raised, though the purpose of this is to obtain a lateral angle on the hip rather than to test stability or dynamic change. In such cases, the patient position is embodied in the named View Type (e.g. Danelius Miller) as described in the View definitions section, rather than with a maneuver.In general, Maneuver values, when included, are specified together with a Timing attribute value, such as W or WO, similar to Pharmaceuticals as defined in the next chapter. If no maneuver is specified, it is assumed that the patient is at rest.7.2 SyntaxManeuvers are separated from the View attribute by “^” (a carat or a “hat”). By default, the specified Maneuver(s) applies to all of the Aggregation and View Types preceding the carat, and vice versa. For example, in the first example below, W standing applies to the Lateral View, and in the second, to both the AP and Lateral Views. In the third, Standing and Flexion both apply to the PA View: View lateral^W standing View AP+lateral^W standing Views PA^W standing+W flexion7.2.1 Maneuvers that only apply to a subset of the Aggregation and/or View TypesIn some cases, a given Maneuver or set of Maneuvers will only apply to some of the Aggregation or View Types that are specified. In such cases, parentheses are used to indicate which Aggregation or View Type(s) the Maneuver is related to. For example, a study that includes 2 views plus one or more unspecified views with standing is given by: (Views 2) + (views^W standing)A more complicated example is a study that has two sets of Maneuvers, each of which is related to a different View Type: (Views AP^W R-bending + W L-bending) + (view lateral^W flexion + W extension)8 Pharmaceutical8.1 DefinitionsThe Pharmaceutical attribute specifies the presence or absence of chemical agents relevant to the imaging procedure. We use this attribute to specify administered contrast agents, radiopharmaceuticals, medications, or other clinically important agents and challenges during the imaging procedure.

A158.2 SyntaxThe syntax used to describe the Pharmaceutical attribute specifies several optional components:<timing/existence><substance given><route>Only the components required for specifying the pharmaceutical at a clinically important level are included in the attribute value.8.3 ExamplesUsing this syntax, a common contrast specification of without then with IV contrast would be denoted:WO & W contrast IVIn other cases, the time delay is a key component:48H post contrast PO8.4 Specifying more than one pharmaceuticalThe syntax above can also be used to specify more than one pharmaceutical that may be influence the imaged physiology. For example, a nuclear medicine cardiac stress test may involve administration of a radiopharmaceutical and a stress agent such as Adenosine, Dobutamine, or Regadenoson. The attribute value list will contain only single pharmaceuticals. We specify multiple instances of the Pharmaceutical attribute by combining them with “+”:W adenosine + W radionuclide IVW dipyridamole + W Tc-99m Sestamibi8.5 Usage NotesSome pharmaceuticals will be more fully specified than others. For example, some may specify the specific substance:W Tc-99m Sestamibi IVwhereas others name a more generic class:W radionuclide IVW anesthesia8.5.1 Preference for Generic NamesWe use the generic name of a pharmaceutical, not the brand name, e.g., Tc-99m Sestamibi, not Cardiolite. We will usually include the brand or trade names as synonyms. In rare cases, we use the brand name when a generic form does not exist (e.g., Theraspheres).

A168.5.2 RouteWhere possible, we denote the Route of administration by abbreviations for medication routes (Table 6 of the LOINC Users’ Guide). An oral route of administration would be denoted by PO, an intravenous route by IV.8.5.3 Intra versus ViaWhen describing administration of contrast into specific spaces for which abbreviations do not exist, the space is spelled out in full, and preceded by intra or via according to these guidelines.• We use intra when the contrast injected goes directly into an anatomic space, and this space is what is visualized in the study. For example:W contrast intra lymphatic• We use via when the contrast injected goes through a device or anatomic space into the separate anatomic space being visualized. For example:W contrast via catheterW contrast via urethra8.5.4 Existence versus AbsenceThe Existence component of the pharmaceutical attribute allows specification of whether or not the imaging occurs in the presence of the agent where existence is denoted W, WO, or WO & W. The existence of WO & W denotes separate images, without and with the pharmaceutical.8.5.5 Relationship to View.Maneuver sub-attributeLike the physical maneuvers described in the section on the View attribute, pharmaceutical agents are also intended to test a dynamic aspect of the anatomy, with similarities in how these are modeled. In some cases, an exam may use one or the other that are intended to produce a similar anatomic response (e.g., W exercise or W adenosine). Where needed, they can also be used together as different attributes of the overall term model. For example, in defecography, both a maneuver and contrast are specified:W contrast PR & during defecation8.6 Issues• [Decision: YES] LOINC to change order (WO then W) pattern• [Decision: NO] Should the existence convention be changed to the more redundant but more clear full expression: • WO contrast IV & W contrast IV• [Decision: NO] Should the combination pharmaceuticals be items in the attribute value list?• Is there a more up to date specification of Routes? Not really. FHIR uses this same table. Some were added in 2.3.1

A17• [Decision: YES] Should we remove the amount sub-attribute?• Intra articular -> IS (Intrasynovial)• We will use quotes for keeping together separate words within an attribute. We’ll look for naming conventions to eliminate the need for this. We will convert WO & W to WO&W.• Include the Modifiers from Views: • Deprecate usage of “1 phase” in LOINC (it is implied unless stated as 3 phase) • 3 Phase • 30M post • 45M post • Delayed • Runoff9 Reason For Exam9.1 DefinitionsReason for exam is used to describe a clinical indication or a purpose for the study. This may refer to a patient diagnosis, a clinical indication, a clinical status (e.g., Post op), an intended measurement, altered anatomy (e.g., Endograft), or some other indicator of the purpose of the exam (e.g. Screening).The terms Diagnostic and Screening are used as values of the Reason for exam attribute, and these are potentially confusing for two reasons. First, diagnostic is often thought of as complementary to screening, in which case the terms refer to the patient’s clinical status (i.e., asymptomatic patients undergo screening exams, whereas symptomatic patients undergo diagnostic exams). However, diagnostic is also frequently used in the context of mammography, in which case it is an indicator of the views to be obtained (specifically, that additional non-standard views may be performed), not an indicator of the patient’s symptom status. In both cases, diagnostic refers to an exam being performed for the purpose of further work-up. Here we have chosen to model these terms as part of the Reason for exam semantics, rather than the View semantics.Second, the question of screening and diagnostic exams “for what” may be another source of confusion. Here, we take the position that the answer is typically understood: Screening mammography screens for breast cancer; screening colonography screens for colon cancer. Further, note that the use of the terms Diagnostic and Screening is intended to be limited to those exams where these are needed to distinguish from some other type of study.We also use the Reason for exam attribute to distinguish studies that are primarily done in the pediatric domain. For example, the codes for bilateral hip ultrasound and cranial ultrasound both have the Reason for exam specified as For pediatrics.We do not create separate codes with pediatrics as the Reason for exam in cases where the same study is commonly done in both the adult and pediatric population. For example, “Head CT” will be used for both pediatric and adult studies.

A18Also note that 3D post processing is included here as a value of the Reason for exam attribute. This refers to image rendering done after image acquisition. Some facilities bill for such renderings, which may be used for surgical planning or other purposes. As a result, these renderings (at least sometimes) constitute an end-product of the exam, and we have thereby chosen to model such processing as a reason for performing the exam. While 3D post processing may also be used simply as a diagnostic tool in image interpretation (and thus not technically a reason for performing the study), we have elected to simply model any description of 3D post processing here.9.2 Examples<Reason(s)>XREyeForeign bodyMGBreastDiagnosticMGBreastDiagnostic + Call backUSPregnancy + Less than 14 weeksUSMultiple gestation + Greater than 14 weeksNMStomachLiquid gastric emptyingCTHeartCalcium score9.3 Notes1. 10/17/14: Values removed – “mass,” “obstruction,” “patency,” “pre op”2. 10/17/14: Values added – “intra op,” “endograft”3. 10/17/14: “Twin pregnancy” replaced with “multiple gestation.”4. “Call back” is only to be used in relation to mammography.10 Guidance10.1 DefinitionsThe Guidance attribute is used to describe image-guided interventions. Such procedures may range from the very general (e.g., “CT guided needle placement”) to the very specific (e.g., “fluoroscopy guided lumbar vertebroplasty, with bone biopsy, additional level”).We recommend using these image-guided intervention terms to represent both the imaging part of the procedure and the intervention itself, so for example, the term for “CT guided needle placement” would be used to order and report both the CT guidance as well as the placement of the needle. If there are use cases for which separate codes are necessary for each of the two aspects, we will determine how best to model those individual concepts, but until we receive feedback from users about such use cases, we will continue to recommend using a single code for both the imaging and the action.Imaging guidance for procedures is modeled with three sub-attributes:<Approach> <Action> <Object>

A19Approach refers to the primary route of access used, such as Percutaneous, Transcatheter, or Transhepatic. Action indicates the intervention performed, such as Biopsy, Aspiration, or Ablation. Object is used to specify the target of the action, such as Mass, Abscess or Cyst. For complex procedures, operators may be used to combine instances of the Guidance attribute.Specific definitions for certain actions and interventions:• Aspiration: withdrawal of fluid with a device that is removed at the end of the procedure• Drainage: withdrawal of fluid with a device that is left in place at the end of the procedure• Thoracentesis: drainage of fluid with placement of chest tube• Arthrocentesis: aspiration of fluid from a joint space (this does not include aspiration of soft tissue surrounding the joint)10.2 Usage Notes10.2.1 Guidance for.PresenceImage-guided intervention codes are signified with a Guidance for.Presence attribute value of Guidance. This attribute is primarily used as an indicator that one or more of the Guidance for.Approach, Guidance for.Action, and Guidance for.Object attributes will be valued.10.2.2 Guidance for.ApproachThe Approach sub-attribute will generally be included in the formal code specification. For some procedures like fluid aspiration or biopsy, the percutaneous route is the “default” and often assumed route. Local procedure names will often not include the word “percutaneous” in the name. For purposes of modeling, we will include Percutaneous in the attribute specification. But, to avoid extraneous “clutter”, the display name for the pre-coordinated term will only include the approach if we have two variants, one with percutaneous and one with some other route.In some cases, “percutaneous” may be part of the overall route used for a procedure (e.g., “percutaneous transhepatic”). In such cases, the primary, or most evocative, route will be used (e.g., Transhepatic).10.2.3 Guidance for.ActionThe Action sub-attribute will generally be required to adequately specify an image-guided procedure. Examples include: Placement of; Replacement/Exchange of; Removal of; Repositioning of; Retrieval of; Infusion of; Injection of; Localization of; Check of.For the Actions biopsy and aspiration, in most cases the type of device used (e.g., needle, fine needle, core needle) does not need to be specified in the procedure name. Therefore, for most terms that include the biopsy or aspiration Actions, we will not include information about the device. In those select cases where a particular type of device is used for a specific purpose, however, we will include the device-specific information in this sub-attribute. For example, percutaneous aspiration of fluid using a fine needle is performed in order to obtain a specimen for cytologic examination, so for this context we will make terms that have aspiration.fine needle as the Action.

A2010.2.3.1 Aspiration and DrainageWe have adopted the American College of Radiology and American Medical Association’s definitions of aspiration and drainage as described above. Based on those definitions, any term that specifies drainage will also specify placement of a drainage catheter and vice versa, as follows:Guidance for drainage + placement of drainage catheterTerms that specify chest tube placement are not required to also specify drainage because chest tube placement can be done without draining fluid, such as for patients with a pneumothorax.10.2.3.2 Injection and Nerve block For terms that specify a nerve or set of nerves as the Anatomic focus, such as Peripheral nerve or Celiac plexus, the Action should be Nerve block. For those that have a more generic focus such as Spine.lumbar, then Injection may be used.10.2.4 Guidance for.ObjectThe Object sub-attribute specifies the target of the Action and can represent a variety of concepts, including a device that is being manipulated, a biological substance, or a pathologic lesion. Examples include: Drainage catheter, Nephrostomy tube, CSF, Calculus, Abscess.Note that the Object sub-attribute is optional. Some procedures will specify an Action as well as an Object, while others may only specify an Action. For example:Guidance for aspiration Guidance for aspiration of CSFBeginning with LOINC version 2.66, the LOINC/Radlex Committee agreed upon a constrained list of values for the Object associated with the Aspiration and Drainage Actions in order to prevent an explosion of terms for very similar concepts that are sometimes difficult to distinguish. This list contains the concepts listed below. Requests for new, more specific values will be considered by the Committee on a case-by-case basis.• Fluid• Abscess• Hematoma• Cyst• CSF• Amniotic fluid• UrineThe Committee also decided that Drainage catheter will be the preferred Object for the Placement Action, but specific named catheters such as Chest tube and Nephrostomy tube will also be allowed.10.2.4.1 Relationship between Anatomic Location and Guidance for.Object

A21For most procedures, the body region or organ of interest is specified outside of the Guidance attribute, using the Anatomic Location attribute. On the other hand, when there is a specific site of pathology targeted by an intervention, this is modeled using the Guidance for.Object sub-attribute. The expectation is that when normal anatomic specifiers such as Liver or Abdomen are used, these are modeled using Anatomic Location. When a site of disease such as Mass or Abscess is described, this is modeled using Guidance for.Object.In some cases, neither Anatomic Location nor Guidance for.Object will be specified (e.g., “US guided fine needle aspiration”).10.2.6 Modality attributeThe Guidance attribute will generally be used in conjunction with the Modality attribute. Recall that the modality code {Imaging modality} is used for image-guided procedures where the particular imaging modality is not specified (e.g., “image guided liver biopsy”).10.2.7 Specifying more than one procedureAlthough uncommon, the syntax above can also be used to specify more than one procedure by repeating the triplet of sub-attributes (remember, only the Action sub-attribute is required).As defined in the Syntax section (2.1), use of “+” to join two procedures means logical conjunction (i.e., both procedures were done).For example:Guidance for cholangioscopy+removal of calculus10.3 Examples<Anatomic Loc><Approach><Action><Object> CTLiverPercutaneousBiopsyCTLiverPercutaneousBiopsyMass{Imaging modality}PercutaneousPlacementDrain{Imaging modality}PercutaneousDrainageAbscess{Imaging modality}GallbladderTranshepaticPlacementDrainUSPercutaneousPlacementNon-tunneled CVC{Imaging modality}PercutaneousBiopsyUSPleural spacePercutaneousDrainageUSThyroidPercutaneousAspirationFluid{Imaging modality}PercutaneousExchangeGastrojejunal tube11 Subject11.1 Definitions

A22The Subject attribute is intended for use when there is a need to distinguish between the patient associated with an imaging study, and the target of the study. This situation may occur for pregnant patients undergoing prenatal imaging exams. The potential for multiple gestation further motivates the need for the Subject attribute, as an exam may be targeted at a particular one of multiple fetuses. The Subject attribute may also be used in cases of surgical specimens, such as specimen radiographs at lumpectomy.

Unit 4 Readings/Resources

Unit 4

Required

Burke, J. (2013). Health Analytics: Gaining the Insights to Transform Health Care – chapters 7 and 12

CDC Comprehensive Diabetes Care- HEDIS Requirements, 2017

Resources

LOINC Manual Users’ Guide (Regenstrief), February 2017 (see link below to register for this site for free)

Clinical Documentation Web Links

RXNorm Overview:

RXNorm Technical Documentation:

RxNorm Web Browser:

Find-a-Code Browser for ICD-10 and Other Medical Codes:

ICD-10 Codes Browser:

CPT Codes Browser:

LOINC Documentation and Codes Search (Regenstrief):

(register for free)

Intro to LOINC video from Regenstrief:

UNIT 4 ASSIGNMENT

Unit 4 Assignment

1. Read the Unit Introduction.

2. Complete the assigned readings and review recording of the Unit 3 live lecture as necessary.

3. By the deadline, post your Healthcare Effectiveness Data and Information Set (HEDIS) Measure Development Exercise for evaluation in assignment folder in this unit. Include your name and the unit number on the document.

Summary of changes: updates for the current year (measures are typically updated annually).

Description: basic summary of the measure.

Eligible population: defines inclusion criteria.

Denominator: the number representing the total population.

Numerator: definition criteria for identification of patients for the measure.

Hybrid Specification: other criteria combinations for the measure (FYI – will not be utilized for this exercise).

Example table:

Step 1. Define eligible population in a table format and label it Eligible Population Table. 10 points.

Step 2. Define the denominator in table format and label it Denominator Table. 10 points.

Step 3. Define the numerator in a table format and label it Numerator Table. 10 points.

We continue applying the same strategy to define the numerator. In this section:

a. LOINC would be your main vocabulary that also includes some of the value sets listed in the measure specification.

b. RxNorm may be necessary for drug definitions.

e. You can skip the Eye Exam section on Page 6: there is no easy way for you to locate relevant codes.

f. On page 7, use RxNORM search to locate codes for ACE Inhibitors.

g. We stop on page 8 and do not take on Hybrid Specification that concludes measure definition.

Follow the steps described in the NCQA measure for the numerator, accounting for the notes above.

Your deliverables for this assignment:

Tables – Upload your assignment as one document (Word or PDF ) to this assignment folder. Please include your name and unit number at the top of the first page.

Eligible Population Table -10 pts.

Denominator Table -10pts.

Numerator Table -10 pts.

NOTE: Partial credit may be provided for incomplete analytical and quantitative work submitted in fulfillment of this assignment per instructor evaluation.

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Detailed analysis of the actual 2017 HEDIS clinical measure supplied by National Committee for Quality Assurance (NCQA)

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