Quality of drug interaction alerts in prescribing and dispensing software

Abstract

Objective: To investigate the quality of drug interaction decision support in selected prescribing and dispensing software systems, and to compare this information with that found in a range of reference sources. Design and setting: A comparative study, conducted between June 2006 and February 2007, of the support provided for making decisions about 20 major and 20 minor drug interactions in six prescribing and three dispensing software systems used in primary care in Australia. Five electronic reference sources were evaluated for comparison. Main outcome measures: Sensitivity, specificity and quality of information; for major interactions: whether information on clinical effects, timeframe and pharmacological mechanism was included, whether management advice was helpful, and succinctness. Results: Six of the nine software systems had a sensitivity rate ≥ 90%, detecting most of the major interactions. Only 3/9 systems had a specificity rate of ≥ 80%, with other systems providing inappropriate or unhelpful alerts for many minor interactions. Only 2/9 systems provided adequate information about clinical effects for more than half the major drug interactions, and 1/9 provided useful management advice for more than half of these. The reference sources had high sensitivity and in general provided more comprehensive clinical information than the software systems. Conclusions: Drug interaction decision support in commonly used prescribing and dispensing software has significant shortcomings.

Evaluation of eight drug interaction databases commonly used in the German healthcare system

“…Overall, the evaluated databases showed high values for sensitivity and low values for specificity, which is confirmed by previous research 6 8 9 30–32. All databases failed to provide evidence for many clinically non-relevant interactions in our investigation.…”

“…Previous research on drug interaction databases has mainly focused on accuracy6 8 10 11 32 or only on sensitivity and specificity 9. We agree that accuracy is the most important element of an analysis.…”

“…All drugs were commonly prescribed in the University Hospital Erlangen. The identified pairs were validated using three reference databases (Stockley's, DrugDex, iFacts),27–29 which were chosen due to their proven superiority in several evaluations 5 6 9. Interactions were defined as clinically relevant when all three reference databases rated them as severe to moderate and clinical management was required.…”

Evaluation of features to support safety and quality in general practice clinical software

“…From a research perspective, some of the features could be evaluated in more depth, as we have done previously for drug interaction decision support[18]. It was evident during the study that more work needs to be done to develop high quality knowledge bases that provide content for decision support, and that usability is a crucial issue that warrants evaluation and development of guidelines for software developers.…”

Identifying patient safety problems associated with information technology in general practice: an analysis of incident reports

“…For example, one UK study tested four common prescribing packages in a laboratory setting, and the best system only detected 7 out of 18 clinical scenarios with potential for significant errors 8. In Australia, the National Prescribing Service (NPS) tested prescribing software for common drug–drug interactions with the potential to harm patients 9. Only three of the six prescribing systems examined by the NPS alerted users to all 20 of the major drug–drug interactions tested.…”