PRECISE-VALUE: PhaRmacogEnomics Clinical Support Economic VALUE
Background and Objectives
Pharmacogenomics (PGx) – guiding drug therapy based on individuals’ genetic make-up – offers significant potential to improve drug outcomes, as 97% of the US population carries at least one potentially actionable variant. Providing PGx test results using clinical decision support (PGx-CDS) alerts embedded in electronic health records may be a useful way to guide drug therapy. Yet, Learning Health Systems (LHSs) resist adoption because they are unsure of the value of investing in CDS systems for PGx. Determining the value of providing population-specific PGx-CDS alerts would enable LHSs to invest in those alerts with the greatest potential for improving health care quality and outcomes. Our project aims to fill this gap.
Project Aims:
Aim 1: Estimate the clinical effectiveness and cost-effectiveness of PGx-CDS alerts, compared to no PGx-CDS alerts, from the perspective of LHSs.
We developed a decision-analytic model to evaluate the implementation outcomes, clinical outcomes, and economic value of developing and implementing PGx-CDS alerts. The implementation outcomes inform LHSs about the consequences of establishing infrastructure for PGx-CDS; the clinical outcomes inform the number of adverse events prevented by PGx-CDS alerts, compared to no alerts; and the incremental cost-effectiveness ratio (ICER) comparing PGx-CDS alerts to no alerts will inform value of PGx-CDS alerts.
Aim 2: Create a web-based, interactive, customizable, publicly tool, that provides estimates of the effectiveness and cost-effectiveness of developing and implementing PGx-CDS alerts.
We adapted our model from Aim 1 into an online platform built-in R Shiny, where key input parameters are customizable to users from LHSs, thereby enabling the generation of tailored estimates of effectiveness and cost-effectiveness of PGx-CDS alerts for users. We performed pilot testing to improve tool design by interviewing stakeholders at collaborating academic institutions in LHSs who are key decision-makers of the investment of PGx-CDS alerts.
Investigators:
Beth Devine, PharmD, PhD, MBA
Patrick Mathias, MD, PhD
David Veenstra, PharmD, PhD
Brian Shirts, MD, PhD
Peter Tarczy-Hornoch, MD, FACMI
Graduate student:
Shangqing (Joyce) Jiang, MPH, PhD student
Post-doctoral fellow:
Nathaniel D Hendrix, PhD.
Presentations:
Customizing Value-based Methods to Prioritize Implementation of Pharmacogenomic Clinical Decision Support for Learning Health Systems: A Cost-Effectiveness Analysis. ISPOR 2021.
Customizing Value-based Methods to Prioritize Implementation of Pharmacogenomic Clinical Decision Support for Learning Health Systems: A Cost-Effectiveness Analysis. University of Washington, School of Pharmacy, Corporate Advisory Board Meeting 2020
Publications:
Jiang S, Mathias P, Hendrix N, Shirts B, Veenstra DL, Devine B. Customizing value-based methods to prioritize implementation of pharmacogenomic clinical decision support for Learning Health Systems: A cost-utility analysis. (under revision at The Pharmacogenomics Journal, December 2021)
Mathias P, Jiang S, Hendrix N, Shirts B, Veenstra DL, Devine B. Customizing value-based methods to prioritize implementation of pharmacogenomic clinical decision support for Learning Health Systems: An R Shiny model. (in preparation for Journal of the American Medical Informatics Association, December 2021)