Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program.

Kendra J Grande,Khoa A Nguyen,Rachel Dalton,Meghan J Arwood,Kristine C Ashcraft,Rhonda M Cooper-Dehoff,Jill Sumfest,Nicolas A Moyer

doi:10.3390/jpm12020161

Kendra J Grande, Khoa A Nguyen + Show 6 more

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https://doi.org/10.3390/jpm12020161

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Abstract

We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system’s list of medications for pharmacogenomic testing. The automated method used YouScript’s pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug–drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.

Highlights

Clinical information regarding the utility of pharmacogenomics (PGx) is widely available but the best way to identify patients who would benefit from testing is not well defined [1,2,3,4]
Pharmacogenetic guidelines for many drug–gene combinations are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC), providing support for the implementation of clinical practice decisions based on pharmacogenomic test results [5,6,7]
In addition to CPIC, pharmacogenetic guidance is present in hundreds of U.S Food and Drug Administration (FDA) approved medication package inserts and in other sources [8,9]

Summary

Introduction

Clinical information regarding the utility of pharmacogenomics (PGx) is widely available but the best way to identify patients who would benefit from testing is not well defined [1,2,3,4]. Infrastructure resources and cost constraints may limit the ability of health systems to perform pharmacogenomic testing on all patients [3,10,11,12]. Identifying those patients who will benefit most from pharmacogenomic testing has been a goal of healthcare institutions and the pharmacogenomics community, and may allow for the most effective and efficient use of information technology, laboratory, and clinical resources [13,14]. A recently published tutorial outlines the many necessary steps required to transition from single gene testing when a medication is being considered to a preemptive panel-based genotyping approach [15]

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