Associations of physicians' prescribing experience, work hours, and workload with prescription errors

J Am Med Inform Assoc. 2021 Jun 12;28(6):1074-1080. doi: 10.1093/jamia/ocaa219.


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.

Keywords: adverse drug events; clinical decision support system; physician fatigue; prescription errors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Medical Centers
  • Clinical Competence
  • Datasets as Topic
  • Fatigue
  • Humans
  • Israel
  • Medical Staff, Hospital*
  • Medication Errors / statistics & numerical data*
  • Practice Patterns, Physicians'
  • Workload*