Intervention on medication errors

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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.


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,
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)


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).


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)


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

(n = 396)

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

© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society)


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.


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.

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)


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


Identical identification
of PIPs by clinical

pharmacologists and nurses
n (%)

Total number of
changes in patients’
prescriptions made by

physicians following nurses’


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)


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 changing medications must in all likeli-
hood reinforce the possible effect of input from other healthcare
professionals. Therefore, interventions seeking to unveil the
effects of studies depending on physicians’ partaking need to
report on the magnitude of the collaboration between profes-
sionals. It is not known to what extent physicians change pre-
scriptions directly because of nurses’ observations.
In medication error research, it is important to detect all errors

regardless of significance, as errors of minor significance indi-
cate flaws in the medication process that might result in harm
under other circumstances [37]. When acknowledging that all
errors are important, it is interesting that nurses are capable of
identifying not only PIPs with the potential for harm but also
PIPs considered to be of minor importance. Nurses’ achieve-
ments in medication-related activities such as evaluating pre-
scriptions, ensuring patient adherence to medication and
observing effects and side effects of medication improve with
educational level [11]. For example, a nurse with a bachelor’s
degree is associated with more frequent information-seeking
behaviour on pharmacotherapy than one with a diploma [11]. In
Denmark, all nurses who have graduated after 2008 hold bache-
lor degrees [38]. However, it is not possible to investigate
whether this played a role in the results of the present study.
Research indicates that nurses’ participation in courses seeking
to improve medication competencies improve their skills in
pharmacovigilance [22] along with their self-perceived ability to
undertake pharmacovigilant activities [39]. Future research
should investigate the type of pharmacological training nurses
should receive during their education and the skills and compe-
tencies that can be reasonably expected from a qualified nurse
to improve medication safety for psychiatric patients.

Strengths and limitations.
The significant strengths of this study were the training of
nurses in identifying and documenting observations related to
PIP in a consistent and systematic way, the pursued validation
of the nurses’ observations by comparing with medication
reviews by highly skilled SCPPs and documenting the extent to
which physicians adopt nurses’ observations. The use of a
‘DID’ approach reduces the potential bias in the before-and-after
design, heightens the internal validity and thus increases credi-
bility. However, the study also has some limitations. Firstly,
generalization must be made with caution as the study only
involved selected wards and thus represents an incomplete pic-
ture of prescribing patterns. Also, the nurses failed to review

12% of the eligible patients in the intervention period, which
might introduce selection bias. There were, however, no obvious
differences in age, gender, primary psychiatric disorder, comor-
bidities, alcohol or substance abuse, or medication characteris-
tics between the missing patients and the patients included in the
analysis. Secondly, it was not feasible to practice blinding of the
SCPPs or randomization in the study. Blinding was not possible
due to the nature of the intervention and because randomization
on an individual level would have increased the risk of educa-
tional bias between nurses working in the same bed unit.
Thirdly, patient outcome was not evaluated. Fourthly, intrarater-
and interrater reliability was not assessed for the data collectors.
Additionally, the choice of SCPPs’ medication reviews as the
gold standard is somewhat problematic as it leads to questions
concerning the considerable proportion of PIPs identified by the
nurses and responded to by the physicians, which were not sug-
gested as PIPs by the SCPPs. However, this perspective was
beyond the scope of the present study.


In conclusion, pharmacologically trained psychiatric nurses did
not yield a statistically significant reduction in PIPs in a psychi-
atric hospital setting. However, the study and the intervention
were relatively small, and the results ought to spur questions
about other ways nurses might affect medication safety and
medication appropriateness. PIPs were frequent throughout the
study in both the intervention and control group. The leading
category of PIPs identified by nurses and SCPPs was ‘interac-
tion between drugs’ with a small overlap. Additionally, the
results demonstrated that operationalizing nurses’ observations
to achieve any useful improvements in medication safety relies
on the collaboration and actions of physicians. More research
needs to be focused on the effect of registered nurses’ pharma-
cological knowledge on adverse patient outcome in psychiatry,
pharmacological requirements of nurses, as well as the medica-
tion-related collaboration between nurses and physicians to
inform future efforts aimed at improving the quality of prescrib-
ing in psychiatry.

The authors thank Morten Berg for statistical advice and

comments on the manuscript.

Competing Interests
None declared.


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Supporting Information

Additional Supporting Information may be found online in
the supporting information tab for this article:
Figure S1. The process of medication reviews by clinical

Figure S2. The difference-in-difference approach
Table S1. Categories and definitions of potentially inappro-

priate prescriptions (PIP).

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