Criteria for assessing high-priority drug-drug interactions for clinical decision support in electronic health records

Abstract

BackgroundHigh override rates for drug-drug interaction (DDI) alerts in electronic health records (EHRs) result in the potentially dangerous consequence of providers ignoring clinically significant alerts. Lack of uniformity of criteria for determining the severity or validity of these interactions often results in discrepancies in how these are evaluated. The purpose of this study was to identify a set of criteria for assessing DDIs that should be used for the generation of clinical decision support (CDS) alerts in EHRs.MethodsWe conducted a 20-year systematic literature review of MEDLINE and EMBASE to identify characteristics of high-priority DDIs. These criteria were validated by an expert panel consisting of medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use.ResultsForty-four articles met the inclusion criteria for assessing characteristics of high-priority DDIs. The panel considered five criteria to be most important when assessing an interaction- Severity, Probability, Clinical Implications of the interaction, Patient characteristics, and the Evidence supporting the interaction. In addition, the panel identified barriers and considerations for being able to utilize these criteria in medication knowledge bases used by EHRs.ConclusionsA multi-dimensional approach is needed to understanding the importance of an interaction for inclusion in medication knowledge bases for the purpose of CDS alerting. The criteria identified in this study can serve as a first step towards a uniform approach in assessing which interactions are critical and warrant interruption of a provider’s workflow.

Potential drug-related problems detected by electronic expert support system: physicians’ views on clinical relevance

“…Perhaps the results indicate DDI alerts involving acetylsalicylic acid being less clinically relevant. These results are valuable for increasing the specificity of alerts [42,43]. Table 2 The 10 most common substances prescribed in the study population (n = 2868 medications), involved in alerts (n = 1141 medications), and changed as stated for an alert (n = 94)…”

Analysis of drug interactions at the end of life

“…However, clinicians have been shown to frequently override drug interaction alerts when using computerised prescribing software, with rates up to 90% 34 35. Recent studies have shown an improved acceptance of computerised alerts where the alerts were deemed to be of a high clinical value 36 37. Weingart demonstrated that clinicians were more likely to accept alerts that had been assessed by an expert panel to have greater scientific evidence, a higher probability of an actual ADR, increased severity of ADR, and where there was opportunity to act on the information 37…”

Pilot evaluation of an optimized context-specific drug–drug interaction alerting system: A controlled pre-post study

“…The alerts were designed based on feedback from the endusers regarding the old system, discussion rounds in the working group, and the published knowledge regarding alert design, including human factor principles [12,28,30,[32][33][34][35][36]. This was an iterative process and several test rounds with the project team and end-users preceded the final design.…”

“…A first step for improving alert acceptance is the tiering of alerts [6,10,11]. Criteria for evaluating the clinical importance of DDIs and tiering of alerts have been proposed [1,6,11,12]. However, even with tiering high override rates remain [6,10,11].…”