Every health care organization collects data from its patients, and with access to this data comes the responsibility of securing and using data in a
Every health care organization collects data from its patients, and with access to this data comes the responsibility of securing and using data in applications that are ethical, legal, and with studied outcomes. While organizational health information management supports many of these responsibilities, the decision makers ultimately shape an organization and its future. In this assessment, you analyze the data provided and consider its potential impact in the scenario.
Part I: Cases by City
Read the following scenario:
Data has been collected to identify specific cases of people who are infected with a dangerous virus. Your organization has an interest in knowing where the population is most affected in an effort to move resources to areas that need them.
Create a bar chart using Microsoft Excel® and the data provided in the Cases by City spreadsheet to identify the cities with the highest counts of cases.
Write a 525- to 700-word analysis of the data. Include an answer to the following questions:
- What are the top 5 cities for infected cases?
- How many infected cases do each of those cities have?
- What is the prevalence rate per 100,000 people?
- What else can be deduced after evaluating the chart?
Include your bar chart with the analysis.
Part II: Ages Impacted
Now that we know where the outbreaks are located, your organization wants to know more about who it affects. The age of the patient will determine what kind of resources will be needed in those areas.
Create a side-by-side bar graph using Microsoft Excel® and the data provided in the Ages Impacted spreadsheet to identify the age groups affected by the virus.
Note: This information will be used for further analysis in future assessments.
Write a 525- to 700-word analysis of the data. Include an answer to the following questions:
- Which age groups are most affected?
- Which age groups are least affected?
- What is the prevalence rate per age demographic?
- What else can be deduced after evaluating the chart?
Include your side-by-side bar graph with the analysis.
Format your citations according to APA guidelines.
Compile Part I and Part II into a report that could be submitted to the leadership in your organization.
Sheet1
City | Date | Cases | <18 | 19-30 | 31-60 | 61+ |
New York | 4/24/17 | 189 | 68 | 15 | 34 | 72 |
Los Angeles | 4/2/17 | 201 | 64 | 16 | 56 | 65 |
Chicago | 4/27/17 | 14 | 4 | 1 | 3 | 6 |
Houston | 4/27/17 | 272 | 98 | 16 | 52 | 106 |
Philadelphia | 4/24/17 | 5 | 2 | 0 | 1 | 2 |
Phoenix | 4/2/17 | 289 | 145 | 20 | 32 | 92 |
San Antonio | 4/7/17 | 95 | 46 | 6 | 12 | 31 |
San Diego | 4/2/17 | 258 | 114 | 15 | 34 | 95 |
Dallas | 4/24/17 | 83 | 42 | 8 | 12 | 21 |
San Jose | 4/23/17 | 109 | 49 | 9 | 17 | 31 |
Austin | 4/17/17 | 281 | 151 | 12 | 39 | 79 |
Jacksonville | 4/14/17 | 322 | 93 | 19 | 61 | 149 |
San Francisco | 4/9/17 | 76 | 27 | 5 | 25 | 19 |
Indianapolis | 4/11/17 | 7 | 3 | 0 | 1 | 3 |
Columbus | 4/9/17 | 14 | 7 | 1 | 2 | 4 |
Fort Worth | 4/29/17 | 98 | 47 | 7 | 12 | 32 |
Charlotte | 4/10/17 | 19 | 11 | 1 | 2 | 5 |
Seattle | 4/12/17 | 65 | 36 | 7 | 10 | 12 |
Denver | 4/2/17 | 30 | 16 | 2 | 1 | 11 |
El Paso | 4/28/17 | 29 | 14 | 2 | 5 | 8 |
Detroit | 4/28/17 | 35 | 10 | 2 | 7 | 16 |
Washington D.C. | 4/3/17 | 61 | 22 | 4 | 12 | 23 |
Boston | 4/13/17 | 28 | 10 | 1 | 4 | 13 |
Memphis | 4/25/17 | 31 | 16 | 2 | 5 | 12 |
Nashville | 4/24/17 | 23 | 11 | 2 | 2 | 8 |
Portland | 4/2/17 | 18 | 8 | 1 | 2 | 7 |
Oklahoma City | 4/27/17 | 11 | 6 | 1 | 2 | 2 |
Las Vegas | 4/27/17 | 146 | 59 | 12 | 37 | 41 |
Baltimore | 4/24/17 | 26 | 15 | 2 | 2 | 7 |
Louisville | 4/2/17 | 17 | 5 | 1 | 3 | 8 |
Milwaukee | 4/7/17 | 12 | 4 | 1 | 2 | 5 |
Albuquerque | 4/2/17 | 51 | 19 | 3 | 7 | 22 |
Tucson | 4/24/17 | 114 | 51 | 8 | 19 | 36 |
Fresno | 4/23/17 | 187 | 93 | 13 | 19 | 62 |
Sacramento | 4/17/17 | 51 | 22 | 3 | 7 | 9 |
Kansas City | 4/14/17 | 38 | 19 | 4 | 6 | 9 |
Long Beach | 4/9/17 | 215 | 76 | 17 | 40 | 82 |
Mesa | 4/11/17 | 231 | 129 | 12 | 25 | 65 |
Atlanta | 4/9/17 | 220 | 63 | 13 | 42 | 102 |
Colorado Springs | 4/29/17 | 5 | 2 | 0 | 1 | 2 |
Virginia Beach | 4/10/17 | 4 | 1 | 0 | 1 | 2 |
Raleigh | 4/12/17 | 8 | 4 | 1 | 1 | 2 |
Omaha | 4/2/17 | 3 | 1 | 0 | 0 | 2 |
Miami | 4/28/17 | 299 | 170 | 18 | 30 | 81 |
Oakland | 4/28/17 | 84 | 42 | 8 | 18 | 16 |
Minneapolis | 4/3/17 | 9 | 6 | 1 | 1 | 3 |
Tulsa | 4/13/17 | 127 | 71 | 10 | 32 | 118 |
Wichita | 4/25/17 | 83 | 24 | 5 | 22 | 32 |
New Orleans | 4/10/17 | 248 | 89 | 15 | 47 | 97 |
Arlington | 4/12/17 | 11 | 4 | 1 | 2 | 4 |
Sheet2
Sheet3
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Sheet1
City | Date | Cases |
New York | 4/24/17 | 189 |
Los Angeles | 4/2/17 | 201 |
Chicago | 4/27/17 | 14 |
Houston | 4/27/17 | 272 |
Philadelphia | 4/24/17 | 5 |
Phoenix | 4/2/17 | 289 |
San Antonio | 4/7/17 | 95 |
San Diego | 4/2/17 | 258 |
Dallas | 4/24/17 | 83 |
San Jose | 4/23/17 | 109 |
Austin | 4/17/17 | 281 |
Jacksonville | 4/14/17 | 322 |
San Francisco | 4/9/17 | 76 |
Indianapolis | 4/11/17 | 7 |
Columbus | 4/9/17 | 14 |
Fort Worth | 4/29/17 | 98 |
Charlotte | 4/10/17 | 19 |
Seattle | 4/12/17 | 65 |
Denver | 4/2/17 | 30 |
El Paso | 4/28/17 | 29 |
Detroit | 4/28/17 | 35 |
Washington D.C. | 4/3/17 | 61 |
Boston | 4/13/17 | 28 |
Memphis | 4/25/17 | 31 |
Nashville | 4/24/17 | 23 |
Portland | 4/2/17 | 18 |
Oklahoma City | 4/27/17 | 11 |
Las Vegas | 4/27/17 | 146 |
Baltimore | 4/24/17 | 26 |
Louisville | 4/2/17 | 17 |
Milwaukee | 4/7/17 | 12 |
Albuquerque | 4/2/17 | 51 |
Tucson | 4/24/17 | 114 |
Fresno | 4/23/17 | 187 |
Sacramento | 4/17/17 | 51 |
Kansas City | 4/14/17 | 38 |
Long Beach | 4/9/17 | 215 |
Mesa | 4/11/17 | 231 |
Atlanta | 4/9/17 | 220 |
Colorado Springs | 4/29/17 | 5 |
Virginia Beach | 4/10/17 | 4 |
Raleigh | 4/12/17 | 8 |
Omaha | 4/2/17 | 3 |
Miami | 4/28/17 | 299 |
Oakland | 4/28/17 | 84 |
Minneapolis | 4/3/17 | 9 |
Tulsa | 4/13/17 | 127 |
Wichita | 4/25/17 | 83 |
New Orleans | 4/10/17 | 248 |
Arlington | 4/12/17 | 11 |
Sheet2
Sheet3
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