Associations of physicians' prescribing experience, work hours, and workload with prescription errors. (29th October 2020)

• Record Type: Journal Article
• Authors: Leviatan, Ilona; Oberman, Bernice; Zimlichman, Eyal; Stein, Gideon Y.
• Is Part Of: Journal of the American Medical Informatics Association. Volume 28:Number 6(2021)
• Page Start: 1074
• Page End: 1080
• Publication Date: 2020-10-29
• Subjects: adverse drug events -- prescription errors -- physician fatigue -- clinical decision support system; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa219
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: We aimed to assess associations of physician's work overload, successive work shifts, and work experience with physicians' risk to err. Materials and Methods: This 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. Results: 1 652 896 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. Conclusion: Restricting successive shifts, reducing workload, increasing training and supervision, and implementing smart clinical decision support systems may help reduce prescription errors.