Identification of Prescribing Errors in an Electronic Health Record Using a Retract-and-Reorder Tool: A Pilot Study.

OBJECTIVES

The aims of this study were to develop and to validate an adapted Retract-and-Reorder (RAR) tool to identify and quantify near-miss/intercepted prescribing errors in an electronic health record.

METHODS

This is a cross-sectional study between February and March 2021 in an Irish maternity hospital. We used the RAR tool to detect near-miss prescribing errors in audit log data. Potential errors flagged by the tool were validated using prescriber interviews. Chart reviews were performed if the prescriber was unavailable for interview. Errors were judged to be clinical decisions in chart reviews through review of narrative notes, order components, and patient's clinical history. Interviews were analyzed with reference to the London Protocol, a process of incident analysis that categorizes causes of errors into various contributory factors including patient factors, task and technology factors, and work environment. Logistic regression with robust clustered standard errors was used to determine predictors for near-miss prescribing errors. We calculated the positive predictive value of the RAR tool by dividing the number of confirmed near-miss prescribing errors by the total number of RAR events identified.

RESULTS

Eighty-four RAR events were identified in 27,407 medication orders. Seventy-one events were confirmed near-miss prescribing errors, resulting in a positive predictive value of 85.0% (95% confidence interval, 75%-91%) and an estimated near-miss prescribing error rate of 259/100,000 medication orders. Duplicate prescribing errors were most common (54/71, 76.1%). No errors were reported by prescribers. Consultants were less likely to make an error than nonconsultant hospital doctors (adjusted odds ratio, 0.10; 95% confidence interval, 0.01-0.84). Factors associated with errors included workload, staffing levels, and task structure.

CONCLUSIONS

Our adapted RAR tool identified a variety of near-miss prescribing errors not otherwise reported. The tool has been implemented in the study hospital as a patient safety resource. Further implementations are planned across Irish hospitals.