Dataset Information

Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicentre study.

ABSTRACT:

Objective

To determine the prevalence, nature and predictors of prescribing errors (PEs) in three mental health hospitals.

Setting

Inpatient units in three National Health Service (NHS) mental health hospitals in the North West of England.

Participants

Trained clinical pharmacists prospectively recorded the number of PEs in newly written or omitted prescription items screened during their routine work on 10 data collection days. A multidisciplinary panel reviewed PE data using established methods to confirm (1) the presence of a PE, (2) the type of PE and (3) whether errors were clinically relevant and likely to cause harm.

Primary outcome measures

Frequency, nature and predictors of PEs.

Results

Of 4427 screened prescription items, 281 were found to have one or more PEs (error rate 6.3% (95% CI 5.6 to 7.1%)). Multivariate analysis revealed that specialty trainees (OR 1.23 (1.01 to 1.51)) and staff grade psychiatrists (OR 1.50 (1.05 to 2.13)) were more likely to make PEs when compared to foundation year (FY) one doctors, and that specialty trainees and consultant psychiatrists were twice as likely to make clinically relevant PEs (OR 2.61 (2.11 to 3.22) and 2.03 (1.66 to 2.50), respectively) compared to FY one staff. Prescription items screened during the prescription chart rewrite (OR 0.52 (0.33 to 0.82)) or at discharge (OR 0.87 (0.79 to 0.97)) were less likely to be associated with PEs than items assessed during inpatient stay, although they were more likely to be associated with clinically relevant PEs (OR 2.27 (1.72 to 2.99) and 4.23 (3.68 to 4.87), respectively). Prescription items screened at hospital admission were five times more likely (OR 5.39 (2.72 to 10.69)) to be associated with clinically relevant errors than those screened during patient stay.

Conclusions

PEs may be more common in mental health hospitals than previously reported and important targets to minimise these errors have been identified.

SUBMITTER: Keers RN

PROVIDER: S-EPMC4185335 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicentre study.

Keers Richard N RN Williams Steven D SD Vattakatuchery Joe J JJ Brown Petra P Miller Joan J Prescott Lorraine L Ashcroft Darren M DM

BMJ open 20141001 9

<h4>Objective</h4>To determine the prevalence, nature and predictors of prescribing errors (PEs) in three mental health hospitals.<h4>Setting</h4>Inpatient units in three National Health Service (NHS) mental health hospitals in the North West of England.<h4>Participants</h4>Trained clinical pharmacists prospectively recorded the number of PEs in newly written or omitted prescription items screened during their routine work on 10 data collection days. A multidisciplinary panel reviewed PE data us ...[more]

PMID: 25273813

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Project description:It has been suggested that doctors in their first year of post-graduate training make a disproportionate number of prescribing errors.This study aimed to compare the prevalence of prescribing errors made by first-year post-graduate doctors with that of errors by senior doctors and non-medical prescribers and to investigate the predictors of potentially serious prescribing errors.Pharmacists in 20 hospitals over 7 prospectively selected days collected data on the number of medication orders checked, the grade of prescriber and details of any prescribing errors. Logistic regression models (adjusted for clustering by hospital) identified factors predicting the likelihood of prescribing erroneously and the severity of prescribing errors.Pharmacists reviewed 26,019 patients and 124,260 medication orders; 11,235 prescribing errors were detected in 10,986 orders. The mean error rate was 8.8 % (95 % confidence interval [CI] 8.6-9.1) errors per 100 medication orders. Rates of errors for all doctors in training were significantly higher than rates for medical consultants. Doctors who were 1 year (odds ratio [OR] 2.13; 95 % CI 1.80-2.52) or 2 years in training (OR 2.23; 95 % CI 1.89-2.65) were more than twice as likely to prescribe erroneously. Prescribing errors were 70 % (OR 1.70; 95 % CI 1.61-1.80) more likely to occur at the time of hospital admission than when medication orders were issued during the hospital stay. No significant differences in severity of error were observed between grades of prescriber. Potentially serious errors were more likely to be associated with prescriptions for parenteral administration, especially for cardiovascular or endocrine disorders.The problem of prescribing errors in hospitals is substantial and not solely a problem of the most junior medical prescribers, particularly for those errors most likely to cause significant patient harm. Interventions are needed to target these high-risk errors by all grades of staff and hence improve patient safety.

Project description:OBJECTIVE:Limited evidence concerning the burden and predictors of omitted medication doses within mental health hospitals could severely limit improvement efforts in this specialist setting. This study aimed to determine the prevalence, nature and predictors of omitted medication doses affecting hospital inpatients in two English National Health Service (NHS) mental health trusts. METHODS:Over 6 data collection days trained pharmacy teams screened inpatient prescription charts for scheduled and omitted medication doses within 27 adult and elderly wards across 9 psychiatric hospitals. Data were collected for inpatients admitted up to two weeks prior to each data collection day. Omitted doses were classified as 'time critical' and 'preventable' based on established criteria. Omitted dose frequencies were presented with 95% confidence intervals (CI). Multilevel logistic regression analyses determined the predictors of omitted dose occurrence, with omission risks presented as adjusted odds ratios (OR) with 95% CI. RESULTS:18,664 scheduled medication doses were screened for 444 inpatients and 2,717 omissions were identified, resulting in a rate of 14.6% (95% CI 14.1-15.1). The rate of 'time critical' omitted doses was 19.3% (95% CI 16.3-22.6%). 'Preventable' omitted doses comprised one third of all omissions (34.5%, 930/2694). Logistic regression analysis revealed that medicines affecting the central nervous system were 55% less likely to be omitted compared to all other medication classes (9.9% vs. 18.8%, OR 0.45 (0.40-0.52)) and that scheduled doses administered using non-oral routes were more likely to be omitted compared the oral route (inhaled OR 3.47 (2.64-4.57), topical 2.71 (2.11-3.46), 'other' 2.15 (1.19-3.90)). 'Preventable' dose omissions were more than twice as likely to occur for 'time critical' medications than non-time critical medications (50.4% vs. 33.8%, OR 2.24 (1.22-4.11)). CONCLUSIONS:Omitted medication doses occur commonly in mental health hospitals with 'preventable' omissions a key contributor to this burden. Important targets for remedial intervention have been identified.

Project description:ObjectiveWe conducted a prospective cohort study of the Clinical Practice Research Database to estimate rates of varenicline and nicotine replacement therapy (NRT) prescribing and the relative effects on smoking cessation, and mental health.MethodsWe used multivariable logistic regression, propensity score matched regression, and instrumental variable analysis. Exposure was varenicline or NRT prescription. Mental disorders were bipolar, depression, neurotic disorder, schizophrenia, or prescriptions of antidepressants, antipsychotics, hypnotics/anxiolytics, mood stabilizers. Outcomes were smoking cessation, and incidence of neurotic disorder, depression, prescription of antidepressants, or hypnotics/anxiolytics. Follow-ups were 3, 6, and 9 months, and at 1, 2, and 4 years.ResultsIn all patients, NRT and varenicline prescribing declined during the study period. Seventy-eight thousand four hundred fifty-seven smokers with mental disorders aged ≥18 years were prescribed NRT (N = 59 340) or varenicline (N = 19 117) from September 1, 2006 to December 31, 2015. Compared with smokers without mental disorders, smokers with mental disorders had 31% (95% CI: 29% to 33%) lower odds of being prescribed varenicline relative to NRT, but had 19% (95% CI: 15% to 24%) greater odds of quitting at 2 years when prescribed varenicline relative to NRT. Overall, varenicline was associated with decreased or similar odds of worse mental health outcomes than NRT in patients both with and without mental disorders, although there was some variation when analyses were stratified by mental disorder subgroup.ConclusionsSmoking cessation medication prescribing may be declining in primary care. Varenicline was more effective than NRT for smoking cessation in patients with mental disorders and there is not clear consistent evidence that varenicline is adversely associated with poorer mental health outcomes.ImplicationsPatients with mental disorders were less likely to be prescribed varenicline than NRT. We triangulated results from three analytical techniques. We found that varenicline was more effective than NRT for smoking cessation in patients with mental disorders. Varenicline was generally associated with similar or decreased odds of poorer mental health outcomes (ie, improvements in mental health) when compared with NRT. We report these findings cautiously as our data are observational and are at risk of confounding.

Project description:Background: Health information technology (HIT) is known to reduce prescribing errors but may also cause new types of technology-generated errors (TGE) related to data entry, duplicate prescribing, and prescriber alert fatigue. It is unclear which component behaviour change techniques (BCTs) contribute to the effectiveness of prescribing HIT implementations and optimisation. This study aimed to (i) quantitatively assess the HIT that reduces prescribing errors in hospitals and (ii) identify the BCTs associated with effective interventions.Methods: Articles were identified using CINAHL, EMBASE, MEDLINE, and Web of Science to May 2020. Eligible studies compared prescribing HIT with paper-order entry and examined prescribing error rates. Studies were excluded if prescribing error rates could not be extracted, if HIT use was non-compulsory or designed for one class of medication. The Newcastle-Ottawa scale was used to assess study quality. The review was reported in accordance with the PRISMA and SWiM guidelines. Odds ratios (OR) with 95% confidence intervals (CI) were calculated across the studies. Descriptive statistics were used to summarise effect estimates. Two researchers examined studies for BCTs using a validated taxonomy. Effectiveness ratios (ER) were used to determine the potential impact of individual BCTs.Results: Thirty-five studies of variable risk of bias and limited intervention reporting were included. TGE were identified in 31 studies. Compared with paper-order entry, prescribing HIT of varying sophistication was associated with decreased rates of prescribing errors (median OR 0.24, IQR 0.03-0.57). Ten BCTs were present in at least two successful interventions and may be effective components of prescribing HIT implementation and optimisation including prescriber involvement in system design, clinical colleagues as trainers, modification of HIT in response to feedback, direct observation of prescriber workflow, monitoring of electronic orders to detect errors, and system alerts that prompt the prescriber.Conclusions: Prescribing HIT is associated with a reduction in prescribing errors in a variety of hospital settings. Poor reporting of intervention delivery and content limited the BCT analysis. More detailed reporting may have identified additional effective intervention components. Effective BCTs may be considered in the design and development of prescribing HIT and in the reporting and evaluation of future studies in this area.

Project description:To evaluate the prevalence, type and severity of prescribing errors observed between grades of prescriber, ward area, admission or discharge and type of medication prescribed.Ward-based clinical pharmacists prospectively documented prescribing errors at the point of clinically checking admission or discharge prescriptions. Error categories and severities were assigned at the point of data collection, and verified independently by the study team.Prospective study of nine diverse National Health Service hospitals in North West England, including teaching hospitals, district hospitals and specialist services for paediatrics, women and mental health.Of 4238 prescriptions evaluated, one or more error was observed in 1857 (43.8%) prescriptions, with a total of 3011 errors observed. Of these, 1264 (41.9%) were minor, 1629 (54.1%) were significant, 109 (3.6%) were serious and 9 (0.30%) were potentially life threatening. The majority of errors considered to be potentially lethal (n=9) were dosing errors (n=8), mostly relating to overdose (n=7). The rate of error was not significantly different between newly qualified doctors compared with junior, middle grade or senior doctors. Multivariable analyses revealed the strongest predictor of error was the number of items on a prescription (risk of error increased 14% for each additional item). We observed a high rate of error from medication omission, particularly among patients admitted acutely into hospital. Electronic prescribing systems could potentially have prevented up to a quarter of (but not all) errors.In contrast to other studies, prescriber experience did not impact on overall error rate (although there were qualitative differences in error category). Given that multiple drug therapies are now the norm for many medical conditions, health systems should introduce and retain safeguards which detect and prevent error, in addition to continuing training and education, and migration to electronic prescribing systems.

Project description:ObjectivesStudy objectives were to investigate the prevalence and causes of prescribing errors amongst foundation doctors (i.e. junior doctors in their first (F1) or second (F2) year of post-graduate training), describe their knowledge and experience of prescribing errors, and explore their self-efficacy (i.e. confidence) in prescribing.MethodA three-part mixed-methods design was used, comprising: prospective observational study; semi-structured interviews and cross-sectional survey. All doctors prescribing in eight purposively selected hospitals in Scotland participated. All foundation doctors throughout Scotland participated in the survey. The number of prescribing errors per patient, doctor, ward and hospital, perceived causes of errors and a measure of doctors' self-efficacy were established.Results4710 patient charts and 44,726 prescribed medicines were reviewed. There were 3364 errors, affecting 1700 (36.1%) charts (overall error rate: 7.5%; F1:7.4%; F2:8.6%; consultants:6.3%). Higher error rates were associated with : teaching hospitals (p<0.001), surgical (p = <0.001) or mixed wards (0.008) rather thanmedical ward, higher patient turnover wards (p<0.001), a greater number of prescribed medicines (p<0.001) and the months December and June (p<0.001). One hundred errors were discussed in 40 interviews. Error causation was multi-factorial; work environment and team factors were particularly noted. Of 548 completed questionnaires (national response rate of 35.4%), 508 (92.7% of respondents) reported errors, most of which (328 (64.6%) did not reach the patient. Pressure from other staff, workload and interruptions were cited as the main causes of errors. Foundation year 2 doctors reported greater confidence than year 1 doctors in deciding the most appropriate medication regimen.ConclusionsPrescribing errors are frequent and of complex causation. Foundation doctors made more errors than other doctors, but undertook the majority of prescribing, making them a key target for intervention. Contributing causes included work environment, team, task, individual and patient factors. Further work is needed to develop and assess interventions that address these.

Project description:BackgroundDispensing errors, known to result in significant patient harm, are preventable if their nature is known and recognized. However, there is a scarcity of such data on dispensing errors particularly in resource poor settings, where healthcare is provided free-of-charge. Therefore, the purpose of this study was to determine the types, and prevalence of dispensing errors in a selected group of hospitals in Sri Lanka.MethodsA prospective, cross sectional, multi-center study on dispensing errors was conducted, in a single tertiary care, and two secondary care hospitals, in a cohort of 420 patients attending medical, surgical, diabetic and pediatric clinics. The patients were selected according to the population size, through consecutive sampling. The prescription audit was conducted in terms of dispensing errors which were categorized as i) content, ii) labelling, iii) documentation, iv) concomitant, and v) other errors based on in-house developed definitions.ResultsA total of 420 prescriptions (1849 medicines) were analyzed (Hospital-I, 248 prescriptions-1010 medicines; Hospital-II, 84 prescriptions-400 medicines; Hospital-III, 88 prescriptions-439 medicines), and a cumulative total of 16,689 dispensing errors (at least one dispensing error in a prescription) were detected. Labelling errors were the most frequent dispensing error (63.1%; N = 10,523; Mostly missing information on the dispensing label), followed by concomitant prescribing and dispensing errors (20.5%; N = 3425; Missing prescribing information overlooked by the pharmacist), documentation errors (10.6%; N = 1772 Missing identification of pharmacist on dispensing label), clinically significant medication interactions overlooked by pharmacists (0.5%; N = 82), content errors (4.9%; N = 812; Discrepancies between medication dispensed and prescription order), medications dispensed in unsuitable packaging (0.4%; N = 74), and lastly medication dispensed to the wrong patient (0.01%; N = 1).ConclusionsDispensing errors are frequent in Sri Lankan hospitals which operate with limited resources and provide free healthcare to all citizenry. Over one half of the errors were labeling errors with minimal content errors. Awareness on common types of dispensing errors and emphasis on detecting them could improve medication safety in Sri Lankan hospitals.

Project description:BackgroundElectronic continuous surveillance databases are ideal for monitoring antibiotic use (ABU) in hospitalised patients for antibiotic stewardship programmes (ASP). However, such databases are scarce in low-resource settings. Point prevalence surveys (PPS) are viable alternatives. This report describes ABU and identifies ASP implementation improvement areas in Limpopo Province, South Africa.MethodsThis cross-sectional descriptive study extracted patient-level ABU data from patients' files using a modified global PPS tool. Data were collected between September and November 2021 at five regional hospitals in Limpopo Province, South Africa. All patients in the wards before 8 a.m. on study days with an antibiotic prescription were included. Antibiotic use was stratified by Anatomic Therapeutic Chemical and Access, Watch, Reserve classifications and presented as frequencies and proportions with 95% confidence intervals (CI). Associations between categorical variables were assessed using the chi-square test. Cramér's V was used to assess the strength of these associations.ResultsOf 804 inpatients surveyed, 261 (32.5%) (95% CI 29.2-35.7) were prescribed 416 antibiotics, 137 were female (52.5%) and 198 adults (75.9%). One hundred and twenty-two (46.7%) patients received one antibiotic, 47.5% (124/261) received two, and 5.7% (15/261) received three or more antibiotics. The intensive care units had a higher ABU (68.6%, 35/51) compared to medical (31.3%, 120/384) and surgical (28.5%, 105/369) wards (p = 0.005, Cramér's V = 0.2). Lower respiratory tract infection (27.4%, 104/379), skin and soft tissue infections (SST) (23.5%, 89/379), and obstetrics and gynaecology prophylaxis (14.0%, 53/379) were the common diagnoses for antibiotic prescriptions. The three most prescribed antibiotic classes were imidazoles (21.9%, 91/416), third-generation cephalosporins (20.7%, 86/416) and combination penicillin (18.5%, 79/416). Access antibiotics accounted for 70.2% (292/416) of prescriptions and Watch antibiotics for 29.6% (123/416) (p = 0.110, Cramér's V = 0.1). Reasons for prescribing and treatment plans were documented in 64.9% (270/416) (95% CI 60.3-69.5) and 21.4% (89/416) (95% CI 17.3-25.3) of prescriptions, respectively.ConclusionsThe study serves as a baseline for ABU surveillance at the five regional hospitals in Limpopo Province. Lack of documentation indicates poor prescribing practices; ASP should address gaps by deploying evidence-based, multifaceted and stepwise interventions.

Dataset Information

Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicentre study.

Objective

Setting

Participants

Primary outcome measures

Results

Conclusions

Publications

Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicentre study.

Similar Datasets

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