Temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system

J Am Med Inform Assoc. 2015 Jan;22(1):206-12. doi: 10.1136/amiajnl-2014-002822. Epub 2014 Jul 29.

Abstract

Background: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders.

Aims: We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order.

Setting: A large university teaching hospital using a locally developed CPOE system with an extensive audit database.

Design: We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012.

Results: The geometric mean time taken to generate a prescription order within the CPOE system was 11.75 s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59 s (24.43 to 24.76); p<0.001) or previously unseen (18.87 s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29 s (11.23 to 11.35)) than on weekdays (11.88 s (11.84 to 11.91); p<0.001), in the first (11.25 s (11.16 to 11.34); p<0.001) and final (11.56 s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system.

Conclusions: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency.

Keywords: Decision Support Systems, Clinical; Electronic Prescribing; Medication errors; Order Entry Systems; Temporal factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Decision Support Systems, Clinical
  • Drug Therapy, Computer-Assisted
  • Electronic Prescribing*
  • Hospitals, University
  • Humans
  • Medical Order Entry Systems*
  • Medication Errors / prevention & control
  • Medication Errors / statistics & numerical data
  • Retrospective Studies
  • Time Factors
  • United Kingdom