Tools for the Economic Evaluation of Precision Medicine: A Scoping Review of Frameworks for Valuing Heterogeneity-Informed Decisions

• Published in: PharmacoEconomics 2022-10, Vol.40 (10), p.931-941
• Main Authors: Pataky, Reka E., Bryan, Stirling, Sadatsafavi, Mohsen, Peacock, Stuart, Regier, Dean A.
• Format: Article
• Language: English
• Subjects: Biomarkers; Cost analysis; Decision making; Econometric models; Expected values; Health Administration; Health Economics; Intervention; Medical care, Cost of; Medical research; Medicine; Medicine & Public Health; Medicine, Experimental; Methods; Pharmacoeconomics and Health Outcomes; Precision medicine; Public Health; Quality of Life Research; Scoping Review; Technology assessment
• ISSN: 1170-7690; 1179-2027
• DOI: 10.1007/s40273-022-01176-0

Background and Objective Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine. Methods We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework’s ability to address the methodological challenges of evaluating precision medicine. Results Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider. Conclusions Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions.