ArticleJournal of the American Medical Informatics Association : JAMIA2021
Associations of physicians' prescribing experience, work hours, and workload with prescription errors.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Determinants, patterns, and gaps in patient safety and quality of care research in Israel: a scoping review.Israel journal of health policy research · 2026Article
- Prescription Errors in a Mental Healthcare Facility: A Content Analysis of Brief Interviews.Acta medica Philippina · 2026Article
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- A quality improvement initiative aimed at reducing service strain and improving physician wellness in internal medicine.BMC medical education · 2025Article
- Antimicrobial prescription KAP among physicians in primary care institutions in Southwest China.PloS one · 2025Article
- GP workload and patient safety.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024Article
- A Case-Study of Metoclopramide Prescription Error : A Grim Reminder.Journal of medical systems · 2024Article
- Application of Multidimensional Quality Management Tools in the Management of Medical Adverse Events.Risk management and healthcare policy · 2024Article
- Herding-like behaviour in medical decision making: An experimental study investigating general practitioners' prescription behaviour.PloS one · 2024Article
- Impact of pharmaceutical validation on prescribing errors in a neonatal intensive care unit. Randomised and controlled study.Frontiers in pediatrics · 2024Article
- Salient Measures of Hospitalist Workload.JAMA network open · 2023Article
- Trends and Patterns of Systemic Glucocorticoid Prescription in Primary Care Institutions in Southwest China, from 2018 to 2021.Risk management and healthcare policy · 2023Article
- Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit.Frontiers in pharmacology · 2023Article
- A retrospective observational study analyzing work and study motivation based on the work environment of 15,677 Japanese clinicians in 2016.Scientific reports · 2022Observational
- Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms.Biomedical instrumentation & technology · 2022Article
- Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.BMC anesthesiology · 2022Article
- Hybrid Method Incorporating a Rule-Based Approach and Deep Learning for Prescription Error Prediction.Drug safety · 2022Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to assess associations of physician's work overload, successive work shifts, and work experience with physicians' risk to err. MATERIALS AND
methodsThis large-scale study included physicians who prescribed at least 100 systemic medications at Sheba Medical Center during 2012-2017 in all acute care departments, excluding intensive care units. Presumed medication errors were flagged by a high-accuracy computerized decision support system that uses machine-learning algorithms to detect potential medication prescription errors. Physicians' successive work shifts (first or only shift, second, and third shifts), workload (assessed by the number of prescriptions during a shift) and work-experience, as well as a novel measurement of physicians' prescribing experience with a specific drug, were assessed per prescription. The risk to err was determined for various work conditions.
results1 652 896 medical orders were prescribed by 1066 physicians; The system flagged 3738 (0.23%) prescriptions as erroneous. Physicians were 8.2 times more likely to err during high than normal-low workload shifts (5.19% vs 0.63%, P < .0001). Physicians on their third or second successive shift (compared to a first or single shift) were more likely to err (2.1%, 1.8%, and 0.88%, respectively, P < .001). Lack of experience in prescribing a specific medication was associated with higher error rate (0.37% for the first 5 prescriptions vs 0.13% after over 40, P < .001). DISCUSSION: Longer hours and less experience in prescribing a specific medication increase risk of erroneous prescribing.
conclusionRestricting successive shifts, reducing workload, increasing training and supervision, and implementing smart clinical decision support systems may help reduce prescription errors.
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