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Medication error is an important cause of patient morbidity and mortality, yet it can be a confusing and underappreciated concept. This article provides a review for practicing physicians that focuses on medication error (1) terminology and definitions, (2) incidence, (3) risk factors, (4) avoidance strategies, and (5) disclosure and legal consequences. A medication error is any error that occurs at any point in the medication use process. It has been estimated by the Institute of Medicine that medication errors cause 1 of 131 outpatient and 1 of 854 inpatient deaths. Medication factors (eg, similar sounding names, low therapeutic index), patient factors (eg, poor renal or hepatic function, impaired cognition, polypharmacy), and health care professional factors (eg, use of abbreviations in prescriptions and other communications, cognitive biases) can precipitate medication errors. Consequences faced by physicians after medication errors can include loss of patient trust, civil actions, criminal charges, and medical board discipline. Methods to prevent medication errors from occurring (eg, use of information technology, better drug labeling, and medication reconciliation) have been used with varying success. When an error is discovered, patients expect disclosure that is timely, given in person, and accompanied with an apology and communication of efforts to prevent future errors. Learning more about medication errors may enhance health care professionals' ability to provide safe care to their patients.

AimTo evaluate the effectiveness of a ‘Do not interrupt’ bundled intervention to reduce non-medication-related interruptions to nurses during medication administration.MethodsA parallel eight cluster randomised controlled study was conducted in a major teaching hospital in Adelaide, Australia. Four wards were randomised to the intervention which comprised wearing a vest when administering medications; strategies for diverting interruptions; clinician and patient education; and reminders. Control wards were blinded to the intervention. Structured direct observations of medication administration processes were conducted. The primary outcome was non-medication-related interruptions during individual medication dose administrations. The secondary outcomes were total interruption and multitasking rates. A survey of nurses' experiences was administered.ResultsOver 8 weeks and 364.7 hours, 227 nurses were observed administering 4781 medications. At baseline, nurses experienced 57 interruptions/100 administrations, 87.9% were unrelated to the medication task being observed. Intervention wards experienced a significant reduction in non-medication-related interruptions from 50/100 administrations (95% CI 45 to 55) to 34/100 (95% CI 30 to 38). Controlling for clustering, ward type and medication route showed a significant reduction of 15 non-medication-related interruptions/100 administrations compared with control wards. A total of 88 nurses (38.8%) completed the poststudy survey. Intervention ward nurses reported that vests were time consuming, cumbersome and hot. Only 48% indicated that they would support the intervention becoming hospital policy.DiscussionNurses experienced a high rate of interruptions. Few were related to the medication task, demonstrating considerable scope to reduce unnecessary interruptions. While the intervention was associated with a statistically significant decline in non-medication-related interruptions, the magnitude of this reduction and its likely impact on error rates should be considered, relative to the effectiveness of alternate interventions, associated costs, likely acceptability and long-term sustainability of such interventions.

BackgroundMedication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP) and perceived workload using the NASA Task Load Index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify the workflow steps most vulnerable to error and to gain participant feedback.MethodsA simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semistructured interviews. A concurrent triangulation design combined quantitative and qualitative data.Results24 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 orders) compared with standard practice (28.3% of 120 orders; odds ratio 0.18, p<0.01), a shorter TTP and lower overall NASA-TLX scores (p<0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, ‘search by indication’ and targeting specific patient and staff groups.ConclusionThe intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required.Trial registration numberNCT05493072.

Medication errors are common in primary care and are associated with considerable risk of patient harm. We tested whether a pharmacist-led, information technology-based intervention was more effective than simple feedback in reducing the number of patients at risk of measures related to hazardous prescribing and inadequate blood-test monitoring of medicines 6 months after the intervention. In this pragmatic, cluster randomised trial general practices in the UK were stratified by research site and list size, and randomly assigned by a web-based randomisation service in block sizes of two or four to one of two groups. The practices were allocated to either computer-generated simple feedback for at-risk patients (control) or a pharmacist-led information technology intervention (PINCER), composed of feedback, educational outreach, and dedicated support. The allocation was masked to general practices, patients, pharmacists, researchers, and statisticians. Primary outcomes were the proportions of patients at 6 months after the intervention who had had any of three clinically important errors: non-selective non-steroidal anti-inflammatory drugs (NSAIDs) prescribed to those with a history of peptic ulcer without co-prescription of a proton-pump inhibitor; β blockers prescribed to those with a history of asthma; long-term prescription of angiotensin converting enzyme (ACE) inhibitor or loop diuretics to those 75 years or older without assessment of urea and electrolytes in the preceding 15 months. The cost per error avoided was estimated by incremental cost-effectiveness analysis. This study is registered with Controlled-Trials.com, number ISRCTN21785299. 72 general practices with a combined list size of 480 942 patients were randomised. At 6 months' follow-up, patients in the PINCER group were significantly less likely to have been prescribed a non-selective NSAID if they had a history of peptic ulcer without gastroprotection (OR 0·58, 95% CI 0·38–0·89); a β blocker if they had asthma (0·73, 0·58–0·91); or an ACE inhibitor or loop diuretic without appropriate monitoring (0·51, 0·34–0·78). PINCER has a 95% probability of being cost effective if the decision-maker's ceiling willingness to pay reaches £75 per error avoided at 6 months. The PINCER intervention is an effective method for reducing a range of medication errors in general practices with computerised clinical records. Patient Safety Research Portfolio, Department of Health, England.

Background Adverse drug events from preventable medication errors can result in patient morbidity and mortality, and in cost to the healthcare system. Medication reconciliation can improve communication and reduce medication errors at transitions in care. Objective Evaluate the impact of medication reconciliation and counselling intervention delivered by a pharmacist for medical patients on clinical outcomes 30 days after discharge. Setting Sultan Qaboos University Hospital, Muscat, Oman. Methods A randomized controlled study comparing standard care with an intervention delivered by a pharmacist and comprising medication reconciliation on admission and discharge, a medication review, a bedside medication counselling, and a take-home medication list. Medication discrepancies during hospitalization were identified and reconciled. Clinical outcomes were evaluated by reviewing electronic health records and telephone interviews. Main outcome measures Rates of preventable adverse drug events as primary outcome and healthcare resource utilization as secondary outcome at 30 days post discharge. Results A total of 587 patients were recruited (56 ± 17 years, 57% female); 286 randomized to intervention; 301 in the standard care group. In intervention arm, 74 (26%) patients had at least one discrepancy on admission and 100 (35%) on discharge. Rates of preventable adverse drug events were significantly lower in intervention arm compared to standard care arm (9.1 vs. 16%, p = 0.009). No significant difference was found in healthcare resource use. Conclusion The implementation of an intervention comprising medication reconciliation and counselling by a pharmacist has significantly reduced the rate of preventable ADEs 30 days post discharge, compared to the standard care. The effect of the intervention on healthcare resource use was insignificant. Pharmacists should be included in decentralized, patient-centred roles. The findings should be interpreted in the context of the study’s limitations.

BackgroundComputerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.MethodsMEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.ResultsThirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I2 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I2 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I2 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I2 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62–1.70), I2 28%, n = 7), length of stay (MD − 0.18 (95% − 1.42, 1.05), I2 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I2 74%, n = 9). The quality of evidence was rated very low.DiscussionElectronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

Background Several classification systems for medication errors (MEs) have been established over time, but none of them apply optimally for classifying severe MEs. In severe MEs, recognizing the causes of the error is essential for error prevention and risk management. Therefore, this study focuses on exploring the applicability of a cause-based DRP classification system for classifying severe MEs and their causes. Methods This was a retrospective document analysis study on medication-related complaints and authoritative statements investigated by the Finnish National Supervisory Authority for Welfare and Health (Valvira) in 2013–2017. The data was classified by applying a previously developed aggregated DRP classification system by Basger et al. Error setting and harm to the patient were identified using qualitative content analysis to describe the characteristics of the MEs in the data. The systems approach to human error, error prevention, and risk management was used as a theoretical framework. Results Fifty-eight of the complaints and authoritative statements concerned MEs, which had occurred in a wide range of social and healthcare settings. More than half of the ME cases (52%, n  = 30) had caused the patient’s death or severe harm. In total, 100 MEs were identified from the ME case reports. In 53% ( n  = 31) of the cases, more than one ME was identified, and the mean number of MEs identified was 1.7 per case. It was possible to classify all MEs according to aggregated DRP system, and only a small proportion (8%, n  = 8) were classified in the category “Other,” indicating that the cause of the ME could not be classified to specific cause-based category. MEs in the “Other” category included dispensing errors, documenting errors, prescribing error, and a near miss. Conclusions Our study provides promising preliminary results for using DRP classification system for classifying and analyzing especially severe MEs. With Basger et al.’s aggregated DRP classification system, we were able to categorize both the ME and its cause. More research is encouraged with other ME incident data from different reporting systems to confirm our results.

BackgroundIntravenous medication administrations have a high incidence of error but there is limited evidence of associated factors or error severity.ObjectiveTo measure the frequency, type and severity of intravenous administration errors in hospitals and the associations between errors, procedural failures and nurse experience.MethodsProspective observational study of 107 nurses preparing and administering 568 intravenous medications on six wards across two teaching hospitals. Procedural failures (eg, checking patient identification) and clinical intravenous errors (eg, wrong intravenous administration rate) were identified and categorised by severity.ResultsOf 568 intravenous administrations, 69.7% (n=396; 95% CI 65.9 to 73.5) had at least one clinical error and 25.5% (95% CI 21.2 to 29.8) of these were serious. Four error types (wrong intravenous rate, mixture, volume, and drug incompatibility) accounted for 91.7% of errors. Wrong rate was the most frequent and accounted for 95 of 101 serious errors. Error rates and severity decreased with clinical experience. Each year of experience, up to 6 years, reduced the risk of error by 10.9% and serious error by 18.5%. Administration by bolus was associated with a 312% increased risk of error. Patient identification was only checked in 47.9% of administrations but was associated with a 56% reduction in intravenous error risk.ConclusionsIntravenous administrations have a higher risk and severity of error than other medication administrations. A significant proportion of errors suggest skill and knowledge deficiencies, with errors and severity reducing as clinical experience increases. A proportion of errors are also associated with routine violations which are likely to be learnt workplace behaviours. Both areas suggest specific targets for intervention.

Background Paediatric patients are prone to medication errors, and only a few studies have explored errors in high-alert medications in children. The present study aimed to investigate the prevalence and nature of medication errors involving high-alert medications and whether high-alert medications are more likely associated with severe patient harm and higher error risk classification compared to other drugs. Methods This study was a cross-sectional report of self-reported medication errors in a paediatric university hospital in 2018–2020. Medication error reports involving high-alert medications were investigated by descriptive quantitative analysis to identify the prevalence of different drugs, Anatomical Therapeutic Chemical groups, administration routes, and the most severe medication errors. Crosstabulation and Pearson Chi-Square (χ2) tests were used to compare the likelihood of more severe consequences to the patient and higher error risk classification between medication errors involving high-alert medications and other drugs. Results Among the reported errors ( n  = 2,132), approximately one-third (34.8%, n  = 743) involved high-alert medications ( n  = 872). The most common Anatomical Therapeutic Chemical subgroups were blood substitutes and perfusion solutions (B05; n  = 345/872, 40%), antineoplastic agents (L01; n  = 139/872, 16%), and analgesics (N02; n  = 98/872, 11%). The majority of high-alert medications were administered intravenously ( n  = 636/872, 73%). Moreover, IV preparations were administered via off-label routes ( n  = 52/872, 6%), such as oral, inhalation and intranasal routes. Any degree of harm (minor, moderate or severe) to the patient and the highest risk classifications (IV-V) were more likely to be associated with medication errors involving high-alert medications ( n  = 743) when compared to reports involving other drugs ( n  = 1,389). Conclusions Preventive risk management should be targeted on high-alert medications in paediatric hospital settings. In these actions, the use of intravenous drugs, such as parenteral nutrition, concentrated electrolytes, analgesics and antineoplastic agents, and off-label use of medications should be prioritised. Further research on the root causes of medication errors involving high-alert medications and the effectiveness of safeguards is warranted.

Medication errors are more prevalent in settings with acutely ill patients and heavy workloads, such as in an emergency department (ED). A pragmatic, controlled study compared partnered pharmacist medication charting (PPMC) (pharmacist-documented best-possible medication history [BPMH] followed by clinical discussion between a pharmacist and medical officer to co-develop a treatment plan and chart medications) with early BPMH (pharmacist-documented BPMH followed by medical officer-led traditional medication charting) and usual care (traditional medication charting approach without a pharmacist-collected BPMH in ED). Medication discrepancies were undocumented differences between medication charts and medication reconciliation. An expert panel assessed the discrepancies’ clinical significance, with ‘unintentional’ discrepancies deemed ‘errors’. Fewer patients in the PPMC group had at least one error (3.5%; 95% confidence interval [CI]: 1.1% to 5.8%) than in the early BPMH (49.4%; 95% CI: 42.5% to 56.3%) and usual care group (61.4%; 95% CI: 56.3% to 66.7%). The number of patients who need to be treated with PPMC to prevent at least one high/extreme error was 4.6 (95% CI: 3.4 to 6.9) and 4.0 (95% CI: 3.1 to 5.3) compared to the early BPMH and usual care group, respectively. PPMC within ED, incorporating interdisciplinary discussion, reduced clinically significant errors compared to early BPMH or usual care.