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.
Highlights
High 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
By validating these criteria with the medication knowledge base vendors we were able to arrive on barriers for employing these criteria and provide considerations for how they should be employed in order to improve DDI alerting in EHRs
This study describes the complexity of assessing DDIs for clinical decision support in EHRs
Summary
High 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. 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. Medication-related decision support (MDS) alerts generated at the point of prescribing have the potential to prevent adverse drug events (ADEs) and improve patient safety [1]. A major limitation in being able to develop such a list of high-priority DDIs was the lack of consensus on criteria that should be used to evaluate these interactions in order to prioritize them as clinically significant. We employed a mixed approach, first, assessing the state-of-the-art in terms of DDI assessment as described in the literature We validated these criteria with a panel of experts, both from the content and implementation perspective to assess both the validity and the feasibility of utilizing these criteria for the assessment of DDIs in medication knowledge bases used in EHRs
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