Identification of problem and impact on nursing practice Clearly describe the research process, including what went well, barriers encountered, and
Identification of problem and impact on nursing practice.
2. Clearly describe the research process, including what went well, barriers encountered, and what is still needed.
3. Correlates research findings to identified clinical issue.
4. Summarizes validity of qualitative and quantitative evidence.
5. Findings are clearly identified.
6. Recommends practice change with measurable outcomes and addresses feasibility issues.
7. Suggestions for implementation.
all questions has to be answered in three powerpoint slides
8. Conclusion of content findings.
Improving Medication Safety in Psychiatry – A Controlled Intervention Study of Nurse Involvement in Avoidance of
Potentially Inappropriate Prescriptions Ann L. Soerensen1,2, Marianne Lisby3, Lars P. Nielsen4, Birgitte K. Poulsen4 and Jan Mainz5,6,7
1Danish Center for Healthcare Improvements, Faculty of Social Science, Aalborg University, Aalborg, Denmark, 2University College of Northern Denmark, Aalborg, Denmark, 3Research Center for Emergency Medicine, Aarhus University Hospital, Aarhus, Denmark, 4Department of Clinical
Pharmacology, Aarhus University Hospital, Aarhus, Denmark, 5Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark, 6Department of Clinical Medicine, Faculty of Health, Aalborg University, Aalborg, Denmark and 7Department of Community Mental Health, The
University of Haifa, Haifa, Israel
(Received 9 October 2017; Accepted 12 February 2018)
Abstract: The aim of this controlled, before-and-after study in the Department of Psychiatry in a university hospital in Denmark was to examine the potential effects and characteristics of nurses reviewing psychiatric patients’ medication records to identify potentially inappropriate prescriptions (PIPs). The control group and the intervention group each consisted of two bed units cho- sen based on patients’ diagnoses and age categories. There were 396 patients (age ≥18 years) included in the study. Senior clini- cal pharmacology physicians performed medication reviews for all patients in the study; these medication reviews were considered gold standard. The intervention group: nurses were given a pharmacology course after which the nurses reviewed medication lists and subsequently conferred any identified PIPs with physicians. The control group: medication was reviewed as usual and nurses did not participate. Primary outcome measure was the potential difference in PIPs between the control group and the intervention group, analysed in two ways: (i) difference in mean number of PIPs and (ii) difference in number of patients exposed to ≥1 PIP, using regression analysis with an approximated difference-in-difference (DID) approach. Secondary outcome measure was characteristics of PIPs where physicians responded to nurse-identified PIPs. The DID between intervention group and control group for mean number of PIPs per patient was �0.23 (�1.07 to 0.60), and for number of patients receiving ≥1 PIP, the odds ratio was 0.61 (0.25 to 1.46). Physicians changed most prescriptions in the category interaction between drugs. Nurses could not significantly reduce the prevalence of PIPs for psychiatric patients.
Potentially inappropriate prescriptions (PIPs) are common and significant in older patients [1,2] and present a specific chal- lenge in psychiatry [3–6]. There appears to be limited research on PIP in general psychiatric populations that include younger patients. However, a Danish study estimated the prevalence of PIPs in newly admitted psychiatric patients to affect 59% of patients, and 12% of the identified PIPs were assessed as poten- tially fatal [7]. There is a need to reinforce medication safety ini- tiatives in psychiatry by exploring new initiatives and engaging other staff groups such as nurses [8]. Nurses are professionals who have received training in pharmacology and medicines management during their education. However, researchers sug- gest nurses have insufficient knowledge of the medications they handle [9,10] and should receive regular medication manage- ment courses [11]. Nurses are also the staff group who spend most time at the patients’ bedside, continually observing and monitoring the patient for both effects and side effects of medi- cations [12]. Nurses are key members of the psychiatric team surrounding the patient [13,14] and provide continuous vital knowledge about patients and their medications [15]. In studies on nurses’ role in identifying and mitigating medi-
cal errors, nurses often appear to be the last barricade between
patients and many medical errors [16–19]. In much of the litera- ture mentioned above, errors relating to medications are the most prevalent issue. Studies demonstrate how nurses identify drug-related problems (DRP) and improve medicines manage- ment [20–24], but similar studies are scarce in psychiatry. One Japanese study demonstrated improvement in Global Assess- ment of Functioning and a trend towards better acceptance of medication by psychiatric patients when physicians – based on nurses’ reports and suggestions – changed medications [25], and a British cluster randomized study demonstrated significant improvement in total Positive and Negative Syndrome Scale (PANSS) score in patients with schizophrenia after a medication management training course for mental health nurses [26]. The aim of this study was to examine the characteristics and magni- tude of PIPs as well as the potential effect of nurses’ systematic reviews of medication records on the appropriateness of medica- tions prescribed to newly admitted psychiatric patients. Our hypothesis was that pharmacological training of nurses and a general increased awareness of medication safety have the potential to reduce PIPs in adult psychiatric inpatients.
Method
Definitions. Potentially inappropriate prescription is defined as prescribing that introduces a significant risk of an adverse drug-related event where there is evidence of an equally or more effective but lower-
Author for correspondence: Ann Lykkegaard Soerensen, Aalborg University, Department of Clinical Medicine, Danish Center for Healthcare Improvements, Fibigerstraede 11, 9220 Aalborg, Denmark (e-mail: [email protected]).
© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)
Basic & Clinical Pharmacology & Toxicology, 2018, 123, 174–181 Doi: 10.1111/bcpt.12989
risk alternative therapy available for the same condition [2,27]. Additionally, PIP includes the use of drug combinations with known drug–drug interactions, drug–disease interactions, overdosing, use of drugs for a longer time than clinically indicated, as well as the omission of prescribing drugs that are clinically indicated [2,27]. Studies on elderly patients provide this understanding of PIP but do not include the scenario of omission of therapeutic drug monitoring (TDM). TDM is a quantification of drug concentrations in blood plasma or serum to titrate the dose of individual patients. This quantification helps to obtain a drug concentration associated with the highest possible probability of response and tolerability with an acceptably low risk of toxicity [28]. TDM is central to the prescribing of, for example, tricyclic antidepressants and certain antipsychotic- as well as mood-stabilizing drugs [28]. In this study, omission of TDM was included and extended to encompass electrocardiography and other general paraclinical data required for appropriate prescribing, for example, electrolytes in blood plasma. Categories and elaboration on definitions of PIPs are given in Table S1.
Setting and study design. This controlled, interventional before-and- after study took place in the Aalborg University Hospital of Psychiatry and enrolled patients from November 2014 until June 2015. The baseline measurements were performed for a 2-month period in November 2014 and December 2014, and the intervention was performed for a 6-month period from January to June 2015. The psychiatric hospital has 249 beds across 14 bed units. Two bed units with 18 beds each were selected as the intervention group, and two bed units with 12 and 22 beds were selected as the control group. The intervention group and the control group each contained one bed unit specializing in psychotic disorders and one bed unit specializing in affective disorders. The bed units were purposely selected and matched on patients’ diagnoses and age categories to prevent, if possible, other factors influencing outcome.
Ethical considerations. The Regional Ethical Committee for Medical Research in the North Denmark Region assessed the study and reported that ethical approval was not required according to Danish national law on medical research. The Danish Health and Medicines Authority, The Danish Data Protection Agency and hospital management approved the study. Furthermore, the study was registered with Clinicaltrials.gov, NCT02052505, 29 January 2014. Patients’ informed consent was not required according to Danish regulations as all measures to maintain patients’ anonymity were taken. Senior clinical pharmacology physicians (SCPPs) performed medication reviews during the study which were only used descriptively and not in patients’ treatment. However, the SCPPs were ethically obliged to intervene in cases where patients’ safety was assessed acutely endangered. This happened on three separate occasions.
Participants. The study included all patients admitted to the four bed units, either from the psychiatric emergency department or through the patient’s general practitioner, between November 2014 and June 2015. Exclusion criteria were as follows: terminally ill patients with an anticipated short life expectancy; an expected length of stay of less than 48 hr; patients transferred from another psychiatric unit or previous inclusion in the study; and patients whom nurses failed to include and consequently whose medication lists were not reviewed.
Intervention. Senior clinical pharmacology physicians performed medication reviews in both intervention and control bed units during the baseline and the intervention period according to the method used and described in a previous study [7]. It was not possible to blind the SCPPs to time period nor allocation of group. A graphical overview of the medication review procedure is provided as Figure S1. The medication reviews served as a gold standard against which to
compare the intervention period and as a benchmark for the nurses’ observations. After the baseline period, the intervention consisted of a 5-day course for the participating nurses from the intervention bed units followed by the same nurses carrying out reviews of medication lists for newly admitted patients. The 5-day course covered general pharmacology, psychopharmacology and treatment principles for some of the major mental disorders, principles for medication reviews, exercises in identifying PIPs and how to systematically document relevant observations. Lecturers were SCPPs (authors LPN and BKP), psychiatrists, physicians, a pharmacist and the course leader (author ALS). After the course, 22 registered nurses, across the two interventional bed units, would review patients’ electronic medication records to identify PIPs. The review was carried out within 1–2 days after admission and after the physician reviewed and released the medications to be administered. The nurses used the electronic medication records, the electronic patient records, paraclinical data, their clinical knowledge in general and their knowledge of the individual patient and consulted with nursing colleagues. The nurses recorded their observations and supplemented these
records with a short text explaining the rationale for assessing the pre- scription(s) as a PIP. The nurses also recorded the physicians’ subse- quent responses to the reported observations.
Data collection. Data included demographic details, clinical status, medications and a medication review performed by the SCPP. All patient records and medication records were electronic. The primary outcome was the potential difference in PIPs between the control group and the intervention group following the nurses’ observations in the intervention group. Secondary outcome included prevalence and types of PIPs where physicians responded to nurses’ observations and changed medications.
Data analysis. The primary outcome was analysed in two ways: firstly, an estimation of potential difference in mean number of PIPs, and secondly, an estimation of potential difference in patients receiving ≥1 PIP using linear regression and logistic regression with an approximated difference-in-difference (DID) approach, respectively. The DID method permits an interpretation of data similar to a randomized controlled trial as differences that are constant over time are taken into account [29]. An illustration of the DID method has been provided as Figure S2. Regarding the first analysis of the primary outcome, mean number of PIPs was considered the dependent variable and time (before/after), group (control/intervention bed units) and interaction between time and the group as independent variables in a linear regression. The estimated interaction variable is a DID between intervention and control bed units. Regarding the second analysis of the primary outcome: patients receiving ≥1 PIP (presence of PIP was coded: 1 and for absent: 0) were considered the dependent variable and time, group and interaction between time and the group as independent variables in a logistic regression. The DID approach as described above was applied; however, due to the nonlinear nature of the logistic regression, this cannot be interpreted as a genuine DID. The estimated odds ratio for the interaction variable is an estimated DID between intervention and control bed units. A statistical significance level of 0.05 was applied for both main outcomes. Secondary outcome included prevalence and types of PIPs where
physicians responded to nurses’ observations and changed medications. Characteristics of the study population were provided using descrip-
tive statistics. Baseline measurements by the SCPPs were descriptive and consisted of prevalence, categories and potential severity of PIPs for all four bed units. The presentation of prevalence and proportions of PIPs were in absolute numbers and percentages. Sample size calcu- lations preceded the intervention. Based on a previous study investi- gating PIP in a psychiatric population, the mean number of PIPs per patient was assumed to be 1.8, the standard deviation 2.19 [7], and a
© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)
IMPROVING MEDICATION SAFETY IN PSYCHIATRY 175
reduction by 50% considered clinically relevant. To detect a reduction from 1.8 to 0.9 in mean number of PIPs per patient, at a two-sided 0.05 significance level, a sample size of 94 patients per group during the intervention period was needed to ensure 80% power. Also based on a previous study [7], and the composition of diagnoses represented in the included bed units, it was assumed that 50% of patients would be affected by at least one PIP at baseline [7], and a reduction to 30% of patients affected by at least one PIP would be clinically relevant. To detect a difference of 20 percentage points in the proportion of
patients receiving at least one PIP, at a two-sided 0.05 significance level, a sample size of 94 patients per group during the intervention period was needed to ensure 80% power. It was eventually decided to set the sample size at 120 patients to account for potential loss of patients. Data analysis was performed in Stata/IC 14.0 (Stata Corp, College Station, TX, USA).
Results
Characteristics of patients. Inclusion and exclusion of patients, as illustrated in fig. 1, resulted in 396 patients in the study during baseline and inter- vention. Furthermore, there was no observable difference between the two groups regarding patient characteristics
(table 1). Moreover, during the intervention, there were no dif- ferences between patients reviewed by the nurses (n = 121) and included in the analysis and patients whom the nurses failed to include (n = 15); these differences had been evalu- ated based on the following variables: age (p = 0.43), gender (p = 0.21), primary psychiatric disorder (p = 0.75), comorbidi- ties (p = 0.89), alcohol or substance abuse (p = 0.93) and medication characteristics (p = 0.47).
Potentially inappropriate prescriptions. The distribution of PIPs was consistent on intervention and control wards for the baseline period and the subsequent fol- low-up period indicating no other external factors influencing the prevalence of PIP in the control wards. Over the 8-month data collection period, 396 patients and
2625 prescriptions, differentiated as 1894 regular prescriptions and 758 pro re nata (p.r.n. (medication administered ‘as needed’)) prescriptions, were reviewed by the SCPPs. All medication reviews by the SCPPs yielded a prevalence of patients with at least one PIP (n = 262) of (262/396) 66%. In
Fig. 1. Flow chart illustrating the inclusion and exclusion of patients in the study (n = 396).
© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)
176 ANN L. SOERENSEN ET AL.
total, 761 PIPs were identified by the SCPPs. The leading cat- egories of PIPs were interactions between drugs (232/761 (30%)), omission of indication for treatment (119/761 (16%)), drug dosage too high (96/761 (13%)) and interaction between
drug and disease (84/761 (11%)). The primary outcome is dis- played in table 2 and demonstrates the scenario of potential improvement if all PIPs identified by SCPPs and nurses had received relevant alterations.
Table 1. Characteristics of the entire study population (n = 396).
Patient characteristics Total
(n = 396) Intervention
bed unit A (n = 85) Intervention bed unit B (n = 94)
Control bed unit A (n = 56)
Control bed unit B (n = 161)
Age distribution Median (years), IQR (years) 43, 30–56 42, 32–53 44, 26–61 36, 26–47 46, 32–58
Age category (years), n (%) <30 108 (27) 24 (28) 28 (30) 21 (38) 35 (22) 30–44 112 (28) 27 (32) 22 (23) 19 (34) 44 (27) 45–59 94 (24) 23 (27) 20 (21) 8 (14) 43 (27) ≥60 82 (21) 11 (13) 24 (26) 8 (14) 39 (24)
Males, n (%) 169 (43) 43 (51) 35 (37) 30 (54) 61 (38) Primary psychiatric disorders, n (%) Schizophrenia and other psychotic disorders 121 (31) 59 (69) 3 (3) 45 (80) 14 (9) Affective disorders 175 (44) 7 (8) 64 (68) 4 (7) 100 (62) Other 100 (25) 19 (23) 27 (29) 7 (13) 47 (29)
Comorbidities1, n (%)
Cardiac disease2 96 (24) 16 (19) 21 (22) 12 (21) 47 (29) Diabetes mellitus 2 38 (10) 11 (13) 5 (5) 7 (13) 15 (9) Allergies 15 (4) 3 (4) 2 (2) 3 (5) 7 (4) COPD 29 (7) 5 (6) 6 (6) 6 (11) 12 (7) Other 97 (24) 14 (16) 23 (24) 10 (18) 50 (31) No comorbidities 273 (69) 64 (75) 67 (71) 41 (73) 101 (63)
Patients with alcohol and/or substance abuse, n (%) 118 (30) 28 (33) 21 (22) 18 (32) 51 (32) Medication characteristics Patients prescribed regular medications, n (%) 358 (90) 75 (88) 84 (89) 55 (98) 144 (89) Median number of prescriptions (excluding p.r.n. medications), IQR
4, 2–7 4, 2–7 3, 2–6 5, 3–8 4, 2–7
Median number of prescriptions (including p.r.n. medications), IQR
5, 3–9 5, 2–9 5, 3–8 7, 4–11 5, 3–9
0 medications, n (%) 15 (4) 5 (6) 5 (5) 0 5 (3) 1–5 medications, n (%) 185 (47) 41 (48) 50 (49) 22 (40) 76 (47) 6–9 medications, n (%) 107 (27) 20 (24) 27 (26) 17 (30) 46 (29) ≥10 medications, n (%) 89 (23) 19 (22) 20 (20) 17 (30) 34 (21)
IQR, interquartile range; COPD: chronic obstructive pulmonary disorder; p.r.n: pro re nata (medication administered ‘as needed’). 1The levels of prevalence and percentages do not round up correctly because each patient could have had more than one diagnosis. 2Cardiac disease includes patients with coronary artery disease, arrhythmias, congestive heart failure and subsequent conditions thereof.
Table 2. Potential improvements in number of potentially inappropriate prescriptions (PIPs) had all PIPs common for SCPPs and nurses been altered relevantly.
Baseline period Intervention period Difference, 95% confidence interval p-Value
Mean number of PIP per patient (�SD) Interventional bed units 1.69 � 1.79 1.55 � 2.00 0.14 (�0.47 to 0.76) 0.30 Control bed units 1.84 � 1.99 1.92 � 2.34 �0.09 (�0.72 to 0.54) 0.92 Difference-in-difference �0.23 (�1.07 to 0.60) 0.59
Baseline period Intervention period OR, 95% confidence interval p-Value
Number of patients prescribed ≥1 PIP (%) Interventional bed units 38 (65.5) 65 (53.7) 0.61 (0.32–1.17) 0.14 Control bed units 48 (65.8) 95 (66.0) 1.01 (0.56–1.83) 0.97 Difference-in-difference 0.61 (0.25–1.46) 0.26
SD, standard deviation. Differences in means were compared using a Wilcoxon rank sum test, and difference-in-difference was estimated with a linear regression model. Odds ratios for the intervention and control bed units comparing before-and-after was estimated using logistic regression, and difference-in-difference was estimated by the OR for the coefficient for interaction between groups (intervention bed unit/control bed unit) and time (before/after) using logistic regression.
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IMPROVING MEDICATION SAFETY IN PSYCHIATRY 177
The DID between control and intervention bed units in mean number of PIPs per patient was statistically non-signifi- cant. The proportion of patients receiving ≥1 PIP in the inter- vention bed units was potentially reduced by 11.8 percentage points, compared to almost no variation observed in the con- trol bed units. However, this result was statistically insignifi- cant. Table 3 provides both an overview of types of PIPs identified by SCPPs and nurses as well as physicians’ responses to nurses’ observations in the intervention wards during the intervention. Categories containing five or fewer PIPs are not included in table 3. The excluded categories were as follows: inappropriate dosing time, inappropriate dosage form, inappropriate route of administration and inappropriate duration of treatment.
Nurses’ identifications of PIP. In the six months nurses recorded observations of PIPs they reviewed 121 patients with a total of 756 prescriptions. The 756 prescriptions were distributed on 548 regular prescriptions and 208 p.r.n. prescriptions (table 3). The nurses identified (62/121) 51% of patients as having one or more PIP. The overlap between nurses and SCPPs, in the sample of patients reviewed by nurses, consisted of 38 PIPs equalling (38/224) 17% of the SCPPs’ identifications. When only including PIPs overlapping with SCPPs’ assessments, the nurses identified two PIPs per 100 prescriptions.
Secondary outcome. Nurses identified and presented physicians with PIPs in 11 cate- gories and physicians altered or wrote prescriptions in 10 of the 11 categories, distributed across 25 patients. Physicians altered or wrote most prescriptions in the category interaction between drugs, followed by omission of indication for treatment, as seen in table 3. Only in the category interaction between drugs did physicians alter prescriptions assessed to be potentially harmful. During the intervention, the proportion of PIPs altered or written by physicians in response to nurses’ observations was 47/137 (34%). In contrast, only (8/47) 17% of the PIPs identified by the nurses and leading to an intervention by the physicians were also PIPs identified and assessed for severity by SCPPs.
Discussion
This is the first study to investigate nurses’ skills in identifying PIPs in a psychiatric department of a university hospital by com- paring with SCPP’s medication reviews. The most important finding was a non-significant reduction in the mean number of PIPs per patient and a non-significant reduction in the propor- tion of patients receiving ≥1 PIP. The study did not have enough power to demonstrate a statistically significant reduction in PIPs, as the nurses’ identification of PIPs was less extensive than that, which was considered clinically relevant for the study.
Implications. This is only the second study of PIPs in general psychiatric patients and the only study dealing with nurses’ role in
identifying and drawing attention to PIPs. In this study, nurses identified PIPs but were not able to facilitate a statistically sig- nificant reduction in PIPs whether it was measured as mean number of PIPs per patient or proportion of patients prescribed at least one PIP. Unfortunately, we have not been able to iden- tify comparable studies; thus, the results are being discussed in general. The prevalence of patients having at least one PIP was
found to be 66%, which is higher than the 59% previously reported [7]. In comparison, researchers reported prevalences between 21% and 79% in an extensive systematic review of criteria used to identify PIPs in the elderly [30]. However, such comparisons must be interpreted with caution as psychi- atric patients may be vulnerable to certain practices of inap- propriate prescribing [31–32] and may not be directly comparable to the elderly. Recently, in one of the first studies of the prevalence of potentially inappropriate medications in older patients admitted to psychiatric hospitals, a prevalence of 47% and 79% using Beers criteria [33] and screening tool of older person’s prescriptions (STOPP)/START criteria [34], respectively, was found. These levels of prevalence support our finding of 66%, although the methodologies differ because we used an implicit approach (medication reviews) and owing to the fact that both Beers and STOPP/START consist of explicit criteria for prescriptions to be avoided. One important finding was nurses identifying 17% of all
PIPs identified by SCPPs and that the majority of PIPs for both SCPPs and nurses were in the category interaction between drugs. In general, there was only a small overlap between PIPs identified by nurses and SCPPs. SCPPs will per- form medication reviews based on an extensive understanding of pharmacological and medical properties. In comparison, nurses review medications using their clinical knowledge of the patient, the often limited pharmacology training they received during their education, occasional self-studies and, in this study, an intensive 5-day training course. A Swedish study on nurses identifying DRP demonstrated that, after an educational intervention, 22% of DRPs identified by nurses were potential drug interactions [35] as opposed to 45% of all nurse-identified PIPs in this present study. However, the Swedish study used a tool based on symptoms that are more likely to identify adverse drug reactions and our study focused on PIP, which primarily relies on prescriptions. Omission of indication for treatment was the nurses’ second largest cate- gory of PIPs and shared only a few PIPs identified by the SCPPs. This might be explained by the fact that nurses pri- marily use nursing documentation rather than the patient’s medical record, possibly leading to not fully understanding the indications given for each drug. The nurses in the present study observed and presented physi-
cians with PIPs of differing potential clinical severity, from potentially non-significant to potentially fatal. However, of the prescriptions altered or written by the physicians, only (8/47) 17% were common to SCPPs and nurses, although physicians altered or wrote prescriptions for little more than a third of all PIPs presented to them by the nurses. It is possible that SCPPs and physicians view appropriateness of prescribing somewhat
© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)
178 ANN L. SOERENSEN ET AL.
Table 3. Types of potentially inappropriate prescriptions (PIPs) and assessments of severity in the intervention wards.
Types of PIP and assessment of potentially clinical consequences1
PIPs identified by clinical pharmacologists
in sample of patients reviewed by nurses n (%)2
PIPs identified by nurses after the intervention
n
Identical identification of PIPs by clinical
pharmacologists and nurses n (%)
Total number of changes in patients’ prescriptions made by
physicians following nurses’ observations
n
Omission of indication for treatment3
32 (14) 20 4 (11) 9
Potentially non-significant 6 (19) 2 1 Potentially significant 16 (50) 0 0 Potentially serious 9 (28) 2 0 Potentially fatal 1 (3) N/A 0 0
Drug dosage too low 11 (5) 8 1 (3) 5 Potentially non-significant 0 0 0 Potentially significant 9 (82) 1 0 Potentially serious 2 (18) 0 0 Potentially fatal 0 N/A 0 0
Drug dosage too high 35 (16) 13 6 (16) 4 Potentially non-significant 4 (11) 1 1 Potentially significant 14 (40) 3 2 Potentially serious 15 (43) 2 0 Potentially fatal 2 (6) N/A 0 0
Interaction between drugs 64 (29) 61 24 (63) 12 Potentially non-significant 1 (2) 0 0 Potentially significant 12 (19) 6 0 Potentially serious 42 (66) 13 3 Potentially fatal 9 (14) N/A 5 0
Interaction between drug and disease
14 (6) 13 1 (3) 6
Potentially non-significant 0 0 0 Potentially significant 4 (29) 0 0 Potentially serious 7 (50) 0 0 Potentially fatal 3 (21) N/A 1 0
Duplicate drug 2 (<1) 0 0 0 Potentially non-significant 0 Potentially significant 1 (50) Potentially serious 1 (50) Potentially fatal 0 N/A N/A N/A
Inappropriate dosing interval 20 (9) 1 1 (3) 1 Potentially non-significant 3 (15) 1 0 Potentially significant 16 (80) 0 0 Potentially serious 1 (5) 0 0 Potentially fatal 0 N/A 0 0
Omission of a potentially useful medication
9 (4) 1 0 0
Potentially non-significant 2 (22) Potentially significant 4 (44) Potentially serious 3 (33) Potentially fatal 0 N/A N/A N/A
Omission of therapeutic drug monitoring
16 (7) 3 1 (3) 3
Potentially non-significant 0 0 0 Potentially significant 8 (50) 1 1 Potentially serious 7 (44) 0 0 Potentially fatal 1 (6) N/A 0 0
Other 17 (8) 7 0 4 Potentially non-significant 2 (18) 0 0 Potentially significant 11 (65) 0 0 Potentially serious 4 (24) 0 0 Potentially fatal 0 N/A 0 0
1Only categories containing five or more PIPs are displayed. 2The number of patients in the sample reviewed by nurses was 121. 3The categories contain the levels of prevalence of PIPs identified by nurses that resulted in an alteration or writing of a prescription by the physician.
© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)
IMPROVING MEDICATION SAFETY IN PSYCHIATRY 179
differently, as one would have expected physicians to alter a higher proportion of the PIPs common to SCPPs and nurses. This is in line with a review suggesting that acceptance rate by physicians is a measure for perceived clinical relevance [36]. Other reasons for reluctance to alter prescriptions might be lack of knowledge, a conservative unwillingness to adopt new guide- lines and procedures or fear of making a mistake that will harm the patient. The suggested reasons remain speculative as the issue has not been subjected to much research. Physicians’ acceptance rate to changing medications, for instance according to pharmacists’ suggestions, is moderate [36]. High acceptance rates by physicians to chan
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