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.
|Number of pages||7|
|Journal||Journal of the American Medical Informatics Association : JAMIA|
|State||Published - 12 Jun 2021|
- adverse drug events
- clinical decision support system
- physician fatigue
- prescription errors