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Frequency and nature of medication errors and adverse drug events in mental health hospitals: a systematic review Short version of title: Medication errors and adverse drug events in mental health hospitals Ghadah H Alshehri MPharm 1 Richard N Keers PhD 1,2,3 Darren M Ashcroft PhD 1,2 1 Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre (MAHSC), Manchester, United Kingdom, M13 9PT 2 NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health Sciences Centre (MAHSC), University of Manchester, Manchester, United Kingdom M13 9PT. 3 Pharmacy Department, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom M8 5RB Tel: (+44)161 275 2415, Email: [email protected] Acknowledgements: Ghadah H Alshehri gratefully acknowledges the Princess Nora Bint Abdul Rahman University for funding her PhD programme at the University of Manchester. Conflict of interest: All authors declare that they have no conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors. 1

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Frequency and nature of medication errors and adverse drug events in mental health hospitals: a systematic

review

Short version of title: Medication errors and adverse drug events in mental health hospitals

Ghadah H Alshehri MPharm1

Richard N Keers PhD1,2,3

Darren M Ashcroft PhD1,2

1Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health

Sciences, University of Manchester, Manchester Academic Health Sciences Centre (MAHSC), Manchester,

United Kingdom, M13 9PT

2NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester Academic Health

Sciences Centre (MAHSC), University of Manchester, Manchester, United Kingdom M13 9PT.

3Pharmacy Department, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United

Kingdom M8 5RB

Tel: (+44)161 275 2415, Email: [email protected]

Acknowledgements: Ghadah H Alshehri gratefully acknowledges the Princess Nora Bint Abdul Rahman

University for funding her PhD programme at the University of Manchester.

Conflict of interest: All authors declare that they have no conflict of interest.

This article does not contain any studies with human participants or animals performed by any of the authors.

1

Tables and figures

Figure 1: Flow diagram of the systematic process applied in medication error studies.

Table 1: Characteristics of studies examining medication errors and adverse drug events in mental health

hospitals

Table 2: Quality assessment criteria applied to the included studies

2

Abstract Background

Little is known about the frequency and nature of medication errors (MEs) and adverse drug events (ADEs) that

occur in mental health hospitals.

Objective:

This systematic review aims to provide an up-to-date and critical appraisal of the epidemiology and nature of

MEs and ADEs in this setting.

Method

Ten electronic databases were searched including: MEDLINE, EMBASE, CINAHL, International

Pharmaceutical Abstracts, PsycINFO, Scopus, British Nursing Index, ASSIA, Web of Science, and Cochrane

Database of Systematic Reviews (1999 to October 2016). Studies that examined the rate of MEs or ADEs in

mental health hospitals were included and quality appraisal of the included studies was conducted.

Result

In total, 20 studies were identified. The rate of MEs ranged from 10.6 to 17.5 per 1000 patient-days (n= 2) and

ADEs from 10.0-42.0 per 1000 patient-days (n=2) with 13.0 -17.3% of ADEs found to be preventable. ADEs

were rated as clinically significant (66.0-71.0%), serious (28.0-31.0%), or life threatening (1.4-2.0%).

Prescribing errors occurred in 4.5-6.3% of newly written or omitted prescription items (n=3); dispensing errors

occurred in 4.6% of opportunities for error (n=1) and in 8.8% of patients (n=1); medication administration errors

in 3.3-48.0% of opportunities for error (n=5). MEs and ADEs frequently associated with psychotropic, with

atypical antipsychotic drugs commonly involved. Variability in study setting and data collection methods

limited direct comparisons between studies.

Conclusion

Medication errors occur frequently in mental health hospitals and are associated with risk of patient harm.

Effective interventions are needed to target these events and improve patient safety.

Key points:

Medication errors (MEs) and adverse drug events (ADEs) are common in mental health hospitals Psychotropic medication was often involved in MEs and accounted for the majority of harm associated with

medication use. Further research is needed to examine the rate of ADEs, dispensing errors and unintentional medication

discrepancies at interface between primary and secondary care mental health settings. Future research is needed to examine the organisational and system context and its influence on medication

safety in mental health settings so that effective interventions can be implemented.

3

1. Introduction

The prevention of medication errors (MEs) and adverse drug events (ADEs) in hospitals is recognised

internationally as an important health care priority [1]. A systematic review of eight studies from the US, UK,

New Zealand, Australia, and Canada found that the median incidence rate of in-hospital adverse events was

9.2% of patients, with ADEs found to be common, accounting for 15.1% of adverse events [2]. Other systematic

reviews have examined the frequency of prescribing errors (PEs), medication administration errors (MAEs) and

dispensing errors (DEs) in hospitals worldwide, with reported median rates of error being 7% (inter-quartile

range (IQR) 2.0–14.0%) of medication orders, 19.0% (IQR 8.6-28.3%) of total opportunities for error, and a

range of 0.1- 2.7% for items dispensed, respectively [3-5]. Whilst these reviews have contributed to our

understanding of the extent and nature of medication-related problems in general hospitals, these estimates

cannot be assumed to represent more specialist settings, such as mental health hospitals, where different patient

population characteristics and ways of working may create distinct medication safety challenges than those seen

in general hospital settings [6-8].

Patients with serious mental illness have a set of vulnerabilities and risks associated with nature of mental

illnesses and pharmacological treatment [6, 7, 9]. For instance, the cognitive impairment associated with mental

illness may be associated with non-adherence with medical treatment and poor reporting of medication related

problems [8, 10, 11]. In addition, mental health care practice also differs with regard to the unique medicines

related legislation, such as the UK Mental Health Act 1983 (amended 2007), that requires strict documentation

of prescribing practice and allows administration of treatment for mental disorders against the patient’s will

[12]. The type of medications used and the way in which these medicines are managed in mental health may

also create unique safety challenges compared to general hospitals. For example, psychotropic medication such

as antipsychotics, antidepressants and benzodiazepines are used frequently in the hospitalised mental health

population, many of which contribute to physical health problems such as impaired glucose tolerance,

dyslipidaemia, sexual dysfunction and extrapyramidal side effects [6, 9, 13, 14]. Polypharmacy [15], high dose

antipsychotic prescribing [16, 17] and drug-drug/disease interactions are also prevalent in the mental health

population [18], which can increase the risk of medication- related problems.

Taking all these issues into account, the need to explore the burden of medicines safety issues in mental health

hospital is therefore warranted. Earlier literature reviews have focussed on MEs and/or ADEs exclusively in

mental health hospitals [8, 19-21] but only three of these were systematic in nature [19-21]. Whilst informative,

these reviews are now outdated as more recent publications relating to ME and ADE in mental health hospitals

have emerged[22-25]. They were also restricted to English language publications [20, 21] or were specific to

elderly patients [21], which limits understanding across wider mental health settings and populations. Some of

these earlier reviews also included studies that reported error rates based on incident report data [26, 27], which

are known to underestimate error rates substantially [28], or focussed exclusively on MEs without consideration

of ADEs [20, 21]. Therefore, the aim of this systematic review was to provide an up-to-date and critical

assessment of the frequency and nature of ME and ADE in mental health hospitals.

4

2. Method

2.1. Definitions

ADEs were defined as: “any injury resulting from medical intervention related to a drug” [29, 30] and those

associated with medication errors classified as preventable adverse drug events (pADEs). Medication errors

were defined according to the National Coordinating Council for Medication Error Reporting and Prevention

(NCCMERP) as: “any preventable event that may cause or lead to inappropriate medication use or patient harm

while the medication is in the control of the health care professional, patient, or consumer. Such events may be

related to professional practice, health care products, procedures, and systems, including prescribing, order

communication, product labelling, packaging, and nomenclature, compounding, dispensing, distribution,

administration, education, monitoring, and use”[31]. Unintentional medication discrepancies were also

examined and defined as “unexplained differences in documented medication regimens at the point of transition

of care”[32].

2.2. Search strategy

We searched ten electronic databases from January 1999 to October 2016: MEDLINE, EMBASE, Cumulative

Index to Nursing and Allied Health Literature (CINHAL), International Pharmaceutical Abstracts (IPA),

PsycINFO, Scopus, British Nursing Index (BNI), Applied Social Science Index and Abstract (ASSIA), Web of

Science, and Cochrane Database of Systematic Reviews. The start date of the search was selected to coincide

with the publication of the landmark report To Err Is Human: Building a Safer Health System [33], which is

generally considered to have instigated extensive patient safety research [34], and to also ensure that the

included studies related to current medication safety practices in mental health hospitals. For each database, the

search keywords used were divided into three groups: error-related terms (including error(s), medication

error(s), medical error, drug error, treatment error, therapeutic error, medication safety, drug safety, drug-related

problem, adverse drug event, preventable adverse drug event, potential adverse drug event, near miss,

medication incident, clinical incident, drug incident, incident report, prescribing error, prescription error,

administration error, dispensing error, transcription error, omission, discrepancy); epidemiology-related terms

(including rate, prevalence, incidence); and setting-related terms (including psychiatry, psychiatric hospital,

mental health hospital, adult psychiatry, child psychiatry, adolescent psychiatry, geriatric psychiatry, and

forensic psychiatry). The reference lists of all included articles and relevant reviews were also examined to

identify any additional studies that could be eligible for inclusion. Any additional studies identified by the

project team were also included as long as they fulfilled the study’s inclusion criteria. Study authors were

contacted when additional information was required.

5

2.3. Inclusion and exclusion criteria

Inclusion criteria: studies published between 1999 to October 2016 that reported the rate of ME/ADE in one or

more stage(s) of the treatment process (prescribing, administration, transcription, dispensing and monitoring) for

patients in mental health hospitals (in-patient and outpatient services). Studies that examined the rate of

unintentional medication discrepancies at the point of transition of care between mental health hospitals and

other settings (such as primary care) were also included. However, studies that failed to differentiate between

intentional and unintentional discrepancies using a robust method (e.g. by contacting the medical team) were not

included. In addition, studies that examined the impact of interventions on ME or ADE rates were only included

if a baseline error rate could be determined. Conference abstracts were also included if they provided sufficient

data that allowed for the rate of ME or ADE to be calculated.

Exclusion criteria: studies that utilised incident reports as the primary source of collecting data were excluded

(as they greatly underestimate the error rate)[28], as were those that used an estimated denominator to calculate

the rate of ME or ADE (as the provided rate may not be reflective of the actual rate) [3]. Studies that reported

ME or ADE rates for a single drug, single drug class or disease were excluded, as were studies that only

examined specific prescribing, administration, transcription or dispensing error subtypes such as wrong dose.

Studies that reported the rate of potentially inappropriate prescribing (PIP) in mental health hospitals were

excluded, as they were not considered to be medication errors [35]. Whilst review articles were excluded, we

screened the reference lists of any identified reviews to identify other relevant studies.

2.4. Data extraction

A standardized data collection form was developed and used to collect information concerning: publication

year; country of origin; study setting; definitions used; study design (retrospective or prospective); and error

detection method. In addition, information related to the main findings of the study, including the rate of ME or

ADE (including the rate of pADEs), type of denominator used, type of errors, class of medication involved, and

severity of reported errors, was also retrieved. For each study, data was extracted by two of the authors

independently, with any disagreements in extraction being resolved by discussion between all authors.

2.5. Quality assessment

The quality of the included studies was assessed on the basis of criteria originally developed by Allan and

Barker [36], which has been used in other systematic reviews of medication safety [37-39], including one in

mental health settings[21]. The criteria require a clear description of the following: aim/objectives of the study;

outcome definition; error categories specified; error categories defined (applicable for general ME studies only);

denominator; data collection method; study setting; validity and reliability measures used; and consideration of

study limitations.

6

2.6. Data analysis

The included studies were heterogeneous in nature, which prevented any meta-analysis of data. Although a

comparable denominator (opportunities for error) was observed among studies reporting medication

administration error rates, differences in study setting and types of administration error being studied meant that

pooled analysis was not appropriate; therefore, the findings were summarised narratively. The percentage rate of

ME was determined by dividing the number of actual errors that occurred or number of patients/prescriptions

affected by MEs by the total number of prescriptions/patients/OE multiplied by 100. The rate of ADE/pADE per

1000 patient days was calculated by dividing number of ADEs/pADEs by the total number of patient days

multiplied by 1000.

3. Literature search results

In all, 20 unique studies were included in this systematic review, as shown in Fig. 1. Six studies examined

overall ME rates[40-45], including two that measured ADEs [40, 41] and some studies also reporting additional

data on PEs [40, 42-45], MAEs[40, 42, 44, 45], transcription errors (TEs) [40, 43, 45] and DEs[42-44]. In total,

14 studies reported data on the rate of PE [24, 25, 40, 42-52] , one on unintentional discrepancies [53], and eight

on MAEs [22, 23, 40, 42, 44, 45, 54, 55]. A summary of the characteristics of the included studies is presented

in Table 1.

3.1. Quality assessment

The aim and objectives for each study were clearly stated and definitions provided for MEs/ADEs in all (n=16,

80%) but four studies [43, 46, 52, 53] ME categories were specified in all ME studies, and defined in one study

[44]. The denominators were explicitly described in all studies. The data collection method and study setting

were also described clearly in all studies. A process of validation to confirm the error had occurred was applied

in eleven (55%) studies [22-25, 40, 41, 43, 45, 48, 51, 53], all of which used different approaches to error

validation. Reliability measures were applied only in three studies (15%) [40, 41, 44]. In terms of study

limitations, all except five studies did not state key limitation(s) [43, 48, 50, 51, 55]. Three of which were

conference abstracts [43, 51, 55]. Conference abstract made quality assessment of study reporting a challenging

task, as the nature of abstracts precludes sufficient information for such an assessment. A summary of the

quality assessment criteria is shown in Table 2.

7

Fig. 1 Flow diagram of the systematic process applied in medication error studies

8

Records retrieved from electronic search

(n = 41,631)

Sc ree

nin g

Inc

lud ed

Eli

gib

ilit y

Ide

nti

fic ati

on

Records of titles screened (n = 22,181)

Records for abstract screened(n = 820)

(n = )

Records excluded

(n = 21,361)

Full-text articles assessed for eligibility

(n =35)

Studies included in systematic review

(n =20)

Including 3 conference abstracts

Records excluded (n = 785)

Additional records

identified through other

sources (n = 11)

9 studies from reference list

screening

2 conference abstract

suggested by project team

Number of duplicates removed

(n = 19,450)

Full-text articles excluded, with reasons

(n = 26)

4 review articles 11 studies with no

denominator/error given 2 discrepancy studies

without using a robust method to distinguish between intentional/unintentional discrepancies

1 study used estimated denominator

3 studies that relied solely on incident report as method for collecting data

1 study on single mental health disease

2 Potential inappropriate prescribing studies

2 abstract that did not provide sufficient data for inclusion

3.2. Frequency of medication errors and adverse drug events

3.2.1. Overall Rates of Medication Errors and Adverse Drug Events

Six studies reported an overall ME rate covering all stages of the medication treatment process from prescribing

through to dispensing (Table 1). Of these, two studies examined both MEs and ADEs [40, 41], and some studies

also reported additional data on the rate of ME categories, including PEs [40, 42-45], MAEs [40, 42, 44, 45],

TEs [40, 43, 45] and DEs [42-44]. Three studies were prospective [40, 42, 43], two studies used both a

retrospective and a prospective design [44, 45] and one study used retrospective chart review [41].

Five studies used different error definitions, including the definition of ME developed by Bates et al. [40, 41],

Reason [44] and the NCCMERP [42, 45]. One study did not provide any error definition [43]. Additional

variability was apparent in the denominators used, the study setting (inpatient or outpatient), the patient

population (child or adult), and data collection methods, which limited our ability to compare the studies

directly. Four studies used different health professions to collect data such as nurses, pharmacists, physicians or

psychiatrists [40, 41, 43, 45]. The remaining two studies did not specify the professional role of the data

collector [42, 44].

Two studies with similar denominators reported an overall ME rate of 10.6–17.5 per 1000 patient-days [40, 41].

Other studies found that MEs occurred in 2.4% of complete prescriptions checked (in a paediatric outpatient

setting) [43], 17.4% of total OE [44] and in 61.4% of patients [42]. MEs commonly occurred during prescribing

[40, 41], transcription [43] and medication administration stages [42, 44, 45] and also occurred due to a lack of

treatment monitoring [41]. Psychotropic therapy was most often associated with error (41.0–68.0%), particularly

involving atypical antipsychotics (19.3–32.0%) [40, 43, 44]. In child outpatient settings, methylphenidate and

trihexyphenidyl were most frequently associated with error [43]. The assessment of potential severity was

carried out either by using the NCCMERP criteria [42] or based on methods used in other published studies [40,

44]. Data on ME severity found that 28.0–50.7% of errors were of significant severity, 42.3–44.8% were of

serious severity and 2.1–4.4% were potentially life threatening [40, 44].

In terms of ADEs, two studies undertaken in the USA and Japan reported rates of 10.0–42.0 per 1000 patient-

days, and 10.8–213.0 per 100 admissions, respectively [40, 41]. Preventable ADE rates accounted for 13.0–

17.3% of all ADEs giving a rate of 1.3–7.3 per 1000 patient-days and 1.3–37.1 per 100 admissions, respectively

[40, 41]. Chart review and incident report were the two methods used to detect ADEs [40, 41]. One study also

used pharmacy and nurse report to detect ADEs [40]. The study from Japan [41] found the incidence rate of

ADEs was higher in medical care units—where psychiatric patients with physical comorbidities are more likely

to be treated—than in acute and nursing units. Psychotropic medicines were commonly involved with ADEs

(79.8–92.0%), including the pADE subset (58.4–68%). Atypical antipsychotic medicines were the most

common psychotropic class associated with ADEs [40, 41]. The severity of ADEs was commonly rated as

significant (66.0–71.0%), serious (28.0–31.0%) or life-threatening (1.4–2.0%) [40, 41]. For pADEs, the

9

corresponding severity ratings were significant 68.0%, serious 24.0 and 8.0% life threatening in the US study

[40].

10

Table 1 Characteristics of studies examining medication errors and adverse drug events in mental health hospitals

Study Country:study site

(studysetting)

Studydesign

(duration)

Patientgroup

Datacollectionmethod

Numerator Denominator Error rate Severity %

Medication error

Rothschild etal. [40]

USA:Academic psychiatrichospital inNewEnglandarea(inpatient)

P (6 months)

Adult Chartreview,incidentreport,nurse–pharmacyreports

203 MEs19,180 pt-days

10.6 per 1000 pt-days

Significant 50.7; serious 44.8; life-threatening 4.4

Grasso et al.[45]

USA:AugustaMentalHealthInstitute, aState psychiatrichospital(inpatient)

R(5Months)

Adult Chart review239 PEs498 TEs 1443MAEsa

1448 pt-days 156 PE per 1000 pt-days344 TE per 1000 pt-days997 MAE per 1000 pt-days

Low 19.0; moderate 23.0; high 58.0b

Sirithongthavonet al. [43]

Thailand:tertiarypsychiatriccarehospital (outpatient)

P(12 months)

Paediatric Chart review 180 MEsc 7444Prescriptions

2.4% of prescription Not assessed

Sørensen et al.[44]

Denmark: 3psychiatricwards atAalborgUniversityHospital(inpatient)

P/R(4 months)

Adult Directobservation,unannouncedcontrolvisits, chartreview

189 MEs 1082 OEs 17.4% of total OEs Non-significant 17.4; Significant 28; serious 42.3;

life-threatening 2.1

11

Hema et al.[42]

India:psychiatrydepartmentof JSSHospital(inpatientandoutpatient)

P (6 months)

Adult Chart review 215 MEs in 102pts

166 ptsd 61.4% of pts experienced MEs

Category A 0Category B 19.0Category C 80.0Category D 0.9

Ayani et al.[41]

Japan: 1Psychiatric hospital and 1 tertiaryCare teachinghospital(inpatient)

R (1 year)

Adult Chartreview,incidentreport,laboratoryresult

398 MEs 22,733 pt-days 17.5 per 1000 pt-days

Not assessed

Prescribing errorNirodi andMitchell [46]

UK: 2psychiatricinpatientunits (inpatient)

R (7 years) Elderly Chart review 92 pts experienced PEs

112 pts 82.1% of pts experienced PEse

Not assessed

Grasso et al.[52]

USA: Augusta Mental Health Institute, astate psychiatrichospital (inpatient)

R (4 months)

Adult Chart review 20 medication lists affected by PEs

110 dischargemedicationlists

18.0% of discharge medication lists affected by PEs

Not assessed

Haw andStubbs [48]

UK: StAndrew’shospital(inpatient)

P (1 month)

Adult Chart review 311 PEs in 50 prescription items

2274prescriptionitems

2.2% of prescription items affected by PEs

55.6 minimal clinical significance: 35.7 clinically significant, 8.7 could cause potential harm; 0 potentially life-threatening

12

Grasso et al.[45]

USA: Augusta Mental Health Institute, aState psychiatricHospital (inpatient)

R(5Months)

Adult Chart review 239 PEs 1448 pt-days 165.5 PE per 1000 pt-days

Not assessed

Stubbs et al.[47]

UK: 9centres (8acute ormentalhealthtrusts andoneindependentpsychiatrichospital)(inpatient)

P (1 week) Adult Chart review 523 PEs in 523 prescription items

22,036prescriptionitems

2.4% of prescription items affected by PEs

47.8 negligible 45.9 minor; 3.3 serious; 1.0 fatal

Shawahna andUr-Rahman [50]

Pakistan:psychiatrydepartmentin ahospital inLahore(inpatient)

P (15 days) Adult Chart review 33 PEs in 77 prescription items

84prescriptionitems

91.6% of prescription items affected by PEse

Not assessed

Jhanjee et al.[49]

India: psychiatryoutpatientdepartmentof GuruTeghBahadurhospital inDelhi(outpatient)

P (Mar 2009to Nov2011)

Adult Chart review 1131 PEsc

899 PEsc

648Prescriptions

464antipsychoticonlyprescriptions

175.0 per 100 prescription ef

193.7 per 100 antipsychotic only prescriptions ef

Not assessed

13

Sørensen et al. [44]

Denmark: 3psychiatricwards atAalborgUniversityHospital(inpatient)

R (4 months)

Adult Chart review 10 PEs 267 OE 4.0% of total OE Significant 40.0; serious 40.0; life-threatening 20.0

Keers et al. [24] UK: 3mentalhealth NHStrusts basedin NorthWest ofEngland(inpatient)

P (10 days) Adult Chart review 288 PEs in281 newlywritten,or omitteditems

4427 ofnewly writtenor omittedprescriptionitems

6.3% (95% CI5.6–7.1) ofnewly writtenor omittedprescriptionitems affected by PEs

Minor 43.8;significant

49.3; serious 6.6; life-threatening 0.3

Keers et al. [25] UK: 3 Mental health NHS trust basedin North West ofEngland(inpatient)

P (6 weeks)

Adult Chart review 74 PEs in 74 newly written or omitted items(dischargeprescriptiononly)

1456 newlywritten oromitted items

5.1% (95% CI4.0–6.2) of newly written or omitted items affected by PEs

Minor 27; significant 67.6, severe 5.4; life threatening 0

Scott et al. [51] UK: NR(inpatient)

P (NR) Adult Chart review 288 PEs in 231newlyprescribed,or omitteditems

5127 newlywritten oromitted items

4.5% (95% CI4.0–5.1) ofnewlyprescribed,or omitteditems affected by PEs

Not assessed

Hema et al. [42] India: psychiatrydepartment of JSShospital (inpatientand outpatient)

P (6 months)

Adult Chart review 59 PEs in 47 inpatients

90 inpatientsd 52.2% of inpatients experienced PEse

Not assessed

14

13 PEs in 12 outpatients

12 outpatientsd100% of outpatients experienced PEse

Rothschild etal. [40]

USA:Academic psychiatrichospital inNewEnglandarea(inpatient)

P (6 months)

Adult Chartreview,incidentreport,nurse–pharmacyreports

138 PEs 19,180 pt-days 7.2 PE per 1000 pt-dayse

Not assessed

Sirithongthavonet al. [43]

Thailand:tertiarypsychiatriccarehospital (outpatient)

P (12 months)

Paediatric Chart review 68 PEsc 7444Prescriptions

0.9% of prescriptionse

Not assessed

Transcription errorGrasso et al.[45]

USA: Augusta Mental Health Institute, aState psychiatricHospital (inpatient)

R(5Months)

Adult Chart review 498 TEs 1448 pt-days 344 TE per 1000 pt-days

Not assessed

Rothschild etal. [40]

USA:Academic psychiatrichospital inNewEnglandarea(inpatient)

P (6 months)

Adult Chartreview,incidentreport,nurse–pharmacyreports

40 TEs 19,180 pt-days 2.1 TE per 1000 pt-dayse

Not assessed

15

Sirithongthavonet al. [43]

Thailand:tertiarypsychiatriccarehospital (outpatient)

P (12 months)

Paediatric Chart review 86 TEsc 7444Prescriptions

1.1% of prescriptionse

Not assessed

Unintentional medication discrepancyBrownlie et al.[53]

UK: SouthEssexPartnershipUniversity NHSFoundationTrustAssessmentUnit(inpatient)

P (3 months)

Adult Chart review 601unintentionaldiscrepancies in 212 admissions

377 ptadmissions

56.0% of admissions affected by unintentional medication discrepancies

If error corrected:62.3 minor; 37.7

moderate.If discrepancy continued to primary care: 23 minor; 76.3 moderate

Medication administration error

Grasso et al.[45]

USA:Augusta MentalHealth Institute, aState psychiatricHospital (inpatient)

R(5months)

Adult Chart review 1443 MAEs 1448 pt-days997 MAE per 1000 pt-days

Not assessed

Haw et al. [54] UK: 2 long staywards at St. Andrew’sHospital(inpatient)

P (4 weeks)

Elderly Directobservation,chart review,incidentreport

369 MAEs 1423 OE 25.9% of total OE Doubtful importance 69.0; minor 7.3, serious 0.3; could not be rated 23.3

Sørensen et al. [44]

Denmark: 3 psychiatricwards at AalborgUniversity Hospital(inpatient)

R(4 months)

Adult Directobservation

142 MAEs 340 OE 42.0% of total OE Non-significant 20.0; significant 27.0; serious 51.0; life-threatening 1.0

Cottney[22]

UK: 21-bed acuteMental health ward

P (3 weeks)

Adult Directobservation

138 MAEs 1542 OE 8.9% of total OE Negligible 40.0; 60.0 minor

16

at East LondonNHS FoundationTrust (inpatient)

Cottney andInnes [23]

UK: 43 wards in East London NationalHealth Trust (inpatient)

P (NR) Adult Directobservation

139 MAEs 4177 OE 3.3% of total OE Negligible 19.0, minor 71.0, serious 11.0; fatal 0

Abduldaeem etal. [55]

UK: 2 acuteMental health wards inPharmacy BerkshireHealthcare NHSfoundation trust(inpatient)

P (NR) Adult Directobservation

153 MAEs 317 OE 48.0% of total OE Not assessed

Hema et al.[42]

India: psychiatry department of JSS Hospital (inpatient)

P (6 months)

Adult Chart review 133 MAEs in 88 pts

90 patientsd 97.7% of inpatients experienced MAEse Not assessed

Rothschild etal. [40]

USA:Academic psychiatrichospital inNew England area(inpatient)

P (6 months)

Adult Chartreview,incidentreport,nurse–pharmacyreports

20 MAEs 19,180 pt-days 1.0 MAE per 1000 pt-dayse

Not assessed

Dispensing errorSørensen et al. [44]

Denmark: 3 psychiatricwards at AalborgUniversity Hospital (inpatient)

P (4 months)

Adult Directobservation,unannouncedcontrol visit

18 DEs 391 OE 4.6% of total OE Non-significant 22.2; significant 61.0; serious 33.0; life-threatening 0

Hema et al.[42]

India: Psychiatry department of JSSHospital (inpatient)

P (6 months)

Adult Chart review 10 DEs in 8 pts

90 patientsd 8.8% of pts experienced DEse

Not assessed

Sirithongthavonet al. [43]

Thailand: tertiaryPsychiatric care hospital (outpatient)

P (12 months)

Paediatric Chart review 17 DEsc 7444Prescriptions

0.2% of prescriptionse

Not assessed

Adverse drug events

17

Rothschild etal. [40]

USA: 172-Bed academicpsychiatrichospital inNew EnglandArea (inpatient)

P (6 months)

Adult Chartreview,incidentreport,nurse–pharmacyreports

191 ADEs,25 pADEs

19,180 pt-days 10 ADEs per 1000 pt-days;

1.3 pADE per 1000 pt-days

ADE: significant 66.0; serious 31.0;

life-threatening 2.0;fatal 0

pADE: significant 68;serious 24; life-

threatening 8Ayani et al. [41] Japan: psychiatric

units at one psychiatrichospital and one tertiary care teaching hospital (inpatient)

R (1 year) Adult Chartreview,incidentreport,laboratoryresult

955 ADEs,166 pADEs

22,733 pt-days 42 ADE per 1000 pt-days

7.3 pADE per 1000 pt-days

ADE: significant 71.0; serious 28.0; life-threatening 1.4, fatal 0pADEs: NR

ADE(s) adverse drug event(s), CI confidence interval, DE(s) dispensing error(s), MAE(s) medication administration error(s), ME(s) medication error(s), NR reported, OE opportunity for error, P prospective, pADE(s) preventable adverse drug event(s), PE(s) prescribing error(s), TE(s) transcription error(s), pt(s) patient(s), R retrospective

a The number of dispensing errors excluded as the study relied only in incident report to detect dispensing errorb The data presented include dispensing error severity datac The number of prescriptions affected by medication errors was not reportedd All included patients were received at least one antipsychotic agente Self-calculatedf There was more than one type of ME in prescriptions (the total number of MEs identified is more than the number of prescriptions/items examined)

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Table 2 Quality assessment criteria applied to the included studies

Reference/yearAim/

objectives

ME/ADE definition

Error categories specified

Error categories

defined

Denominator defined

Data collection method

described

Study setting described

Validity measure applied to confirm the

occurrence of error

Reliability measures applieda

Limitation listed

Total score of criteria achieved

(out of 10)

Grasso et al. [52] √ X √ X √ √ √ X X √ 6

Nirodi and Mitchell [46] √ X √ X √ √ √ X X √ 6

Haw and Stubbs [48] √ √ √ X √ √ √ √ X X 7

Grasso et al. [45] √ √ √ X √ √ √ √ X √ 8

Stubbs et al. [47] √ √ √ X √ √ √ X X √ 7

Rothschild et al. [40] √ √ √ X √ √ √ √ √ √ 9

Haw et al. [54] √ √ √ X √ √ √ X X √ 7

Shawahna and Rahman [50] √ √ √ X √ √ √ X X X 6

Sirithongthavorn et al. [43] √ X √ X √ √ √ √ X X 6

Jhanjee et al. [49] √ √ √ X √ √ √ X X √ 7

Brownlie et al. [53] √ X √ X √ √ √ √ X √ 7

Soerensen et al. [44] √ √ √ √ √ √ √ X √ √ 9

Keers et al. [24] √ √ √ X √ √ √ √ X √ 8

Cottney [22] √ √ √ X √ √ √ √ X √ 8

Hema et al. [42] √ √ √ X √ √ √ X X √ 7

Keers et al. [25] √ √ √ X √ √ √ √ X √ 8

Cottney and Innes [23] √ √ √ X √ √ √ √ X √ 8

Ayani et al. [41] √ √ √ X √ √ √ √ √ √ 9

19

Abduldaeem et al. [55] √ √ √ X √ √ √ X X X 6

Scott et al. [51] √ √ √ X √ √ √ √ b X X 7

ADE adverse drug event, ME medication error, H and X indicate criteria achieved or not achieved by study, respectivelya Inter-rater reliabilityb Information obtained from study author

20

3.2.2. Prescribing errors

In total, 14 studies reported data concerning the frequency of PEs, making it the most frequent error type studied

[24, 25, 40, 42-52]. A total of 50.0% of studies [24, 25, 47-51] used the PE definition proposed by Dean et al.

[56], namely ‘‘a clinically meaningful prescribing error occurs when, as a result of a prescribing decision or

prescription writing process, there is an unintentional significant (1) reduction in the probability of treatment

being timely and effective or (2) increase in the risk of harm when compared with generally accepted practice’’.

However, in the mental health setting, several additional clinical scenarios were added to adapt this definition,

including prescribing a drug without registering a patient with the drug company and performing the necessary

monitoring (e.g. for clozapine) or prescribing a drug to mental health patients without a Mental Health Act form

authorization. One study [44] used the definition of a PE by Lisby et al. [57], and the remaining six studies

(42.8%) did not state any definition at all [40, 42, 43, 45, 46, 52]. The majority of studies (n = 10 [71.4%]) were

conducted prospectively [24, 25, 40, 42, 43, 47-51] except for four studies that used a retrospective design [44-

46, 52]. All studies were conducted in inpatient settings except two studies that took place in an outpatient

setting [43, 49] and another which took place across both inpatients and outpatients [42]. Chart review was the

method used for detecting PEs by all studies except one study which also used incident reports and

nurse/pharmacy staff reports [40].

Pharmacists collected the data in six studies [24, 25, 47, 48, 51, 52], combinations of health care professionals

were used in three studies [40, 43, 45] and physicians in one study [46]. Four studies did not specify the

professional status of the data collectors [42, 44, 49, 50]. The presence of PE was confirmed either by using one

reviewer (medical director) in one study [45] or a panel of healthcare professionals in four studies [24, 25, 40,

48, 51]; the rest did not report any process of error validation [42-44, 46, 47, 49, 50, 52]. Across the studies,

there were differences in the types of denominator used to determine PE rates. Three studies (one focused on

PEs on hospital discharge) [25] provided the PE rate per newly written or omitted item checked, the rate of

which ranged from 4.5 to 6.3% [24, 25, 51]. A further three PE studies reported a rate of errors for all

prescription items affected by PEs, with a rate range of 2.2–91.6% [47, 48, 50]. A range of 52.2–82.1% of

patients [42, 46], 7.2–165 per 1000 patient-days [44] (see Table 1). In paediatric outpatient setting, the rate of

PE was 0.9% of complete prescriptions checked [43].

Two studies from the UK found that senior physicians were more likely than more junior physicians to make

PEs [24, 25]. In addition, the use of an electronic prescription pro forma and the number of medication items

prescribed were found to increase the risk of PEs on discharge prescriptions [25]. The most frequent PEs

reported involved the omission of regularly prescribed medication (12.5%) [24], missing or incorrect dose

(23.3%) [51] and writing incomplete prescriptions [47, 48]. Three studies found that psychotropic therapies

were more commonly associated with PEs [25, 44, 47], in contrast to two studies that found that non-

psychotropic therapy was commonly involved, particularly antimicrobial medication [48, 51]. The severity of

harm classified for most PEs was potentially significant (9.0–49.3%) or minor (27.0–44.0%). Some PEs were

21

assessed as having the potential to cause serious harm (3.3–40%) or even death (0.3–20%) if not prevented [24,

25, 44, 47].

3.2.3. Unintentional Medication Discrepancy

One study investigated the rate of unintentional discrepancy at the time of hospital admission for 382 patients

[53]. Medication chart review was conducted prospectively by pharmacy technician to detect discrepancies. The

medication discrepancies were validated by approaching the clinical team involved with each identified

discrepancy. Fifty six percent of hospital admissions were associated with unintentional medication

discrepancies. Increasing age and polypharmacy found to increase the risk of unintentional medication

discrepancy at hospital admission. Drug omission was the most frequent type of discrepancy reported (77.2%)

followed by wrong/unclear dose prescribed (7.0%). The potential severity of unintentional medication

discrepancies was rated as moderate in 37.7% and minor in 62.3% of cases [53].

3.2.4. Transcription errors

Three studies investigated the rate of transcription errors with two studies conducted in the US [40, 45] and one

study conducted in Thailand [43]. Two studies used chart review to detect TEs [43, 45], whereas the other used

a combination of chart review, incident report review and pharmacy and nurse staff reports [40]. All studies

were conducted in inpatient settings [40, 45] except one study that took place in an outpatient paediatric setting

[43]. None of these studies provided a definition of transcription error. However, two studies specified

transcription error categories [43, 45]. Two studies used nurse, pharmacist, and physician data collectors [40,

43] and the other used nurse and pharmacist data collectors [45]. The reported rate of TE was between 1.1–344

per 1000 patient-days [40, 43, 45]. Situations in which the medication order was not transcribed [45] or

transcribed incorrectly [43, 45] were found to be the most common TE subtypes reported.

3.2.5. Medication Administration Errors

Eight studies assessed the rate of MAEs. All studies [22, 23, 54, 55] used the MAE definition developed by

Baker et al. [58] except two studies, one of which [44] used the definition proposed by Lisby et al. [57], and the

other three studies did not state any definition [40, 42, 45]. Six studies used a prospective design [22, 23, 40, 42,

44, 55], and one was conducted retrospectively [45]. One study used both a retrospective and a prospective

design to detect MAE [54]. Direct observation was the most common method for detecting MAEs, representing

the sole data collection method in four studies [22, 23, 44, 55]. Two studies relied only on chart review to detect

error [42, 45], while the other two studies used a combination of the above methods in addition to incident

reports [54] and nurse and pharmacy reports [40]. Pharmacists collected the data in four studies [22, 23, 54, 55],

a pharmacy director and nurse in two studies [40, 45], whereas the remaining studies did not specify the

professional status of the data collector [42, 44]. In three studies, MAEs were validated independently either by

senior pharmacists [22, 23] or by a medical director [45], and the remaining two studies used a consensus

meeting of the research team [44, 54].

22

The total OE was used as the error denominator by most MAE studies [22, 23, 44, 54, 55], except for three that

used patient-days [40, 45] or number of patients [42] as the denominator. The Barker et al. definition of OE was

used by three studies [22, 23, 55], and the remaining studies either developed their own definition [44] or did

not state any [54]. The rate of MAEs reported in studies using similar denominators ranged from 3.3 to 48.0%

of total OE [22, 23, 44, 54, 55], 1.0–997.0 per 1000 patient-days [40, 45] or 97.7% of patients [42]. One study

found that greater numbers of interruptions, patients on the ward, doses administered, and medication doses due

significantly increased the rate of MAEs [23]. Other factors, such as non-oral route of medication

administration, presence of organic brain disease (e.g. dementia), swallowing difficulties or patients who

regularly refused to take their medication were associated with MAEs in elderly patients [54]. Wrong time

errors (1.9–39.2%) and drug omissions (7.5–57%) were reported to be the two most common MAE types

identified across the studies [22, 23, 42, 44, 54, 55]. Only two studies examined whether psychotropic or non-

psychotropic drugs were more likely to be related to MAEs; their conclusions were conflicting [44, 54]. Severity

ratings varied across the studies, with 7.3–71.0% classified as minor severity and 0.3–5.0% as potentially

serious [22, 23, 44, 54].

3.2.6. Dispensing Errors

The rate of DEs was assessed by three studies [42-44]. Two studies were conducted in an adult inpatient setting

[42, 44] and one took place in an outpatient paediatric setting [43]. Dispensing errors were detected by direct

observation and unannounced control visits in one study [44] and by chart review in two studies [42, 43]. In

adult inpatient settings, DE reported rates were 4.6% of total OE [44] and 8.8% of patients [42], while the

reported rate in paediatric outpatient setting was 0.2% of complete prescriptions checked [43]. The most

common types of DE were wrong medication brand (87.5%), dose omission (50.0%), and incorrect labelling of

medication (22.0%) [42, 44]. The potential severity was assessed in one study using two senior clinical

pharmacologists; 61.1% of DE were assessed as having potentially clinically significant effects, with the

remainder classed as potentially serious [44].

4. Discussion

Our systematic review found that MEs in mental health hospitals are common and do cause harm to psychiatric

patients. Such risks affect multiple stages of the medication use process (prescribing, dispensing and

administration) and are common at points of care transfer and outpatient hospital settings. Of the 20 studies

identified, only two examined actual harm due to medication use. The reported ranges of ME and ADE rates in

mental health hospitals appear to overlap with reported IQRs of MEs and ADEs in general hospitals [3-5].

However, the risk associated with these errors differed according to the type of medication involved.

Psychotropic medication was found to be more frequently associated with MEs and ADEs than were non-

psychotropic medicines. Atypical antipsychotics were the most common class of psychotropic medication

involved with ADEs and MEs [40, 41]. In general hospitals, analgesics [29], anti-infective agents [59, 60] and

cardiovascular medications were commonly associated with ADEs [61], whereas anti-infectives [3] and

cardiovascular and gastrointestinal medications [4] were found to be more often associated with PEs and MAEs,

respectively. Therefore, understanding the risks associated with psychotropic medicines is crucial for improving

23

safety in mental health hospitals. Drug omission, incorrect dose and wrong time errors were by far the most

commonly observed ME subtypes in mental health hospitals. This is similar to results reported in systematic

reviews of PE and MAE in general hospitals [3, 4, 39]. Other evidence from the US also found that wrong time

error, drug omission, and incorrect dose were the three most common types of MEs in 36 healthcare facilities

[58]. Future research should target these types of MEs to improve medication safety in mental health hospitals.

The majority of studies assessed the severity of MEs and ADEs. However, variations in the scales used to assess

severity precluded direct comparisons. This variability has also been recognised as a limitation in other reviews

of MEs [3, 4]. For studies that used a similar assessment scale, the majority of MEs that caused actual patient

harm were of significant severity [40, 41]. Future research should seek standardization between severity

assessment scales to allow for direct comparison. We found that around 65.0% of the included studies were

conducted after 2006, highlighting that research examining MEs and ADEs in mental health settings is a

developing area. In addition, the majority of ME studies were conducted in the UK, [22-25, 46-48, 51, 53-55],

whereas only a few were published in other Western (Denmark, USA) [40, 44] and Asian (Japan, Thailand,

Pakistan and India) regions [41-43, 49, 50]. To gain deeper insight into the scale of MEs in mental health

hospitals, it is important to obtain additional epidemiological evidence from other countries, which would be

important in understanding the differences in healthcare practices within mental health hospitals from a global

perspective. In terms of ADEs, only two studies from the USA and Japan have investigated the frequency of

ADEs [40, 41]; as no information is available from other countries, this should be considered an important target

for future research. Overall, whilst the included studies varied in terms of outcome definitions and research

methods, it is important to highlight the emerging consistency in study design that has been achieved in studies

investigating ADE, PE and MAE emerging recently. For instance, in MAE studies based in the UK, consistency

was achieved in terms of the data collection method (direct observation, a recognised gold standard) [62] and

denominator used (OE, the most common in the wider literature) [4]. PE studies (also based in the UK) used

similar PE definitions [56], denominators (newly omitted and written items [n = 3 studies]) [24, 25, 51] and data

collection methods (chart review) [24, 25, 44-52]. Such homogeneity could be used as a benchmark for ongoing

research projects in the field as well as to facilitate comparisons of ME rates in mental health hospitals. Greater

standardisation in study methodology is needed, not only to support direct comparisons between different

studies but also to address deficits in the global knowledge on medication safety in mental health settings. This

review showed that MEs at the mental healthcare interface between secondary and primary care frequently

present a risk of causing harm to patients [24, 52, 53]. However, the majority of these data were from secondary

care, and little is known about the frequency of such errors after hospital discharge back to the community [63-

65]. Evidence from the UK found that a ME occurs in 69.0% and 43.0% of medications at the time of admission

to and discharge from mental health hospitals, respectively [66]. Other recent evidence from the USA suggests

that 23.3% of psychiatric patients had at least one unintentional discrepancy at the time of hospital discharge

[67]. These estimates clearly highlight the importance of medication reconciliation at care interfaces in mental

health settings to improve safe care transfer [68, 69]. This is supported by recent studies reporting on the clinical

benefit of medication reconciliation at the mental healthcare interface [66, 67, 70, 71]. Accordingly, a recent

national UK survey [72] found that medication reconciliation is now common practice in the majority of mental

health services in the UK. Further research is required to identify the burden of MEs at interfaces between

24

mental healthcare settings. Few studies have been published that evaluate interventions to reduce the number of

MEs in mental health hospitals [22, 52, 73]. A study based in a US psychiatric hospital found that using a

personal digital assistant (PDA) reduced the rate of MEs in discharge lists from 18.0 to 8.0% [52]. Another

study investigated the effectiveness of implementing a provider order entry (POE) programme to reduce error in

mental health hospitals [73]. However, none of these studies described the type of MEs involved or their

potential to cause harm to patients. Another UK-based study examined the impact on the rate of MAEs of

implementing an automated dispensing cabinet in a mental health hospital; it found the cabinet to be associated

with a reduction in MAE rate from 8.9 to 7.2% as well as a reduction in the time spent by nurses administering

medication from 2.9 to 2.3 min per dose [22]. However, implementing a successful intervention to reduce the

number of MEs in a hospital is largely based on understanding the causes and risk factors associated with their

occurrence [74-76]. Although this is beyond the scope of this study, some of the included studies highlighted

some of the risk factors associated with the occurrence of MEs in mental health hospitals [23-25], and the first

in-depth qualitative study of the causes of MAEs in this setting has emerged [77]. Future qualitative studies are

needed to identify the root causes and risk factors associated with MEs and ADEs in mental health hospitals to

help design effective remedial interventions. To our knowledge, this is the most up-to-date systematic appraisal

of the evidence examining the frequency, nature and severity of MEs and ADEs in mental health hospitals. A

comprehensive search strategy was used to identify eligible studies from a wide range of databases without

language restriction, and the reference lists of included studies and relevant review papers were manually

searched. Moreover, our inclusion criteria with respect to study designs were stricter than previously published

systematic reviews [20, 21], as we excluded studies based only on incident reports as the sole method of data

collection. However, we were faced with a number of limitations in the studies identified—heterogeneity in the

denominator used, the population involved, and the outcome definition—which limited the opportunity for

direct comparisons between different studies. In addition, studies differed in the way they presented the

classification of drugs involved in MEs/ADEs, with some not reporting any at all. Likewise, different schemes

were used to classify error subtypes. This can be seen, for example, in some MAE studies that considered

nurses’ behaviour, such as unauthorized tablet crushing or failure to report patient identity, as an MAE whereas

other studies did not—all of which eventually affected the reported MAE frequency. With this in mind, these

specific study limitations should be considered when drawing conclusions from the findings of this review.

5. Conclusion

MEs and ADEs are common in mental health hospitals. Medication safety interventions should target risks

associated with psychotropic medicines, especially at the prescribing and administration stages of the medicine

use process. Further research is required to investigate the rate of DEs, unintentional discrepancies and ADEs in

mental health hospitals. Future research should examine the underlying causes of MEs and ADEs so theory-

based interventions can be developed and evaluated to improve patient safety in this specialist healthcare

setting.

25

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