Pharmacogenomic Clinical Decision Support: A Scoping Review

Abstract

Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed.

Clinician Response to Pharmacogenetic Clinical Decision Support Alerts

“…A scoping review of PGx CDS alerts found clinical response was reported in 7 of 10 articles included and ranged from 19.5% to 71% 46 . The study that found a clinical response rate of 71% may not be an accurate representation due to a limited sample size ( n = 7 alerts) 47 .…”

“…to 71%. 46 The study that found a clinical response rate of 71% may not be an accurate representation due to a limited sample size (n = 7 alerts). 47 Herr et al found recommendations were followed 42% of the time, which is more than double the recommendation acceptance rate observed in this study.…”

Evolving From Discrete Molecular Data Integrations to Actionable Molecular Insights Within the Electronic Health Record

“…Data quality, computational processing, and standardization have all reached a point where third-party, EHR-integrated CDS tools can improve clinical care in oncology through the strategies described (Fig 1B). Recent studies have investigated the impact of deploying CDS and identified potential areas for improvement, 3,7,11,33,39 a necessary next step to enhance value for clinicians and patients. However, real-world assessments of CDS tools in oncology are limited.…”