Providing feedback to hospital doctors about prescribing errors; a pilot study

Pharm World Sci. 2007 Jun;29(3):213-20. doi: 10.1007/s11096-006-9075-x. Epub 2007 Feb 20.

Abstract

Objective: To assess the feasibility and acceptability of obtaining data on prescribing error rates in routine practice, and presenting feedback on such errors to medical staff.

Setting: One clinical directorate of a London teaching trust.

Methods: Ward pharmacists recorded all prescribing errors identified in newly written medication orders on one day each fortnight between February and May 2005. We examined prescribing errors reported on the trust's medication incident database for the same period.

Main outcome measures: Prescribing errors identified and recorded by ward pharmacists, prescribing errors reported as incident reports; prescribing error rates per clinical specialty; lead consultants' views on receiving feedback on errors for their specialty.

Results: During eight data collection days, 4,995 new medication orders were examined. Of these, 462 (9.2%; 95% confidence interval 8.5 -10.1%) contained at least one prescribing error. There were 474 errors in total. Pharmacists indicated that they would have reported 19 (4%) of the prescribing errors as medication incidents. Eight prescribing errors were reported for the entire four-month study period on non-data collection days. Feedback was presented to lead clinicians of 10 clinical specialties. This included graphical summaries showing how the specialty compared with others, and a list of errors identified. This information was well-received by clinicians.

Conclusion: Prescribing errors identified by ward pharmacists can be systematically fed back at the level of the clinical specialty; this is acceptable to the consultants involved. Incident report data is subject to gross under-reporting. Routinely providing feedback for each consultant team or for individual prescribers will require more focussed data collection.

Publication types

  • Evaluation Study

MeSH terms

  • Data Collection / methods*
  • Documentation
  • Feedback*
  • Hospitals, Teaching / statistics & numerical data
  • Humans
  • London
  • Medication Errors*
  • Pharmacists
  • Physicians*
  • Pilot Projects
  • Practice Patterns, Physicians' / standards*