Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework

Hadley Stevens Smith (), Dean A. Regier, Ilias Goranitis, Mackenzie Bourke, Maarten J. IJzerman, Koen Degeling, Taylor Montgomery, Kathryn A. Phillips, Sarah Wordsworth, James Buchanan and Deborah A. Marshall
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Hadley Stevens Smith: Harvard Medical School and Harvard Pilgrim Health Care Institute
Dean A. Regier: University of British Columbia
Ilias Goranitis: University of Melbourne
Mackenzie Bourke: University of Melbourne
Maarten J. IJzerman: University of Melbourne
Koen Degeling: University of Melbourne
Taylor Montgomery: Harvard Medical School and Harvard Pilgrim Health Care Institute
Kathryn A. Phillips: UCSF Center for Translational and Policy Research on Precision Medicine (TRANSPERS)
Sarah Wordsworth: University of Oxford and Oxford NIHR Biomedical Research Centre
James Buchanan: Queen Mary University of London
Deborah A. Marshall: University of Calgary

Applied Health Economics and Health Policy, 2025, vol. 23, issue 3, No 2, 337-358

Abstract: Abstract Introduction Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention’s cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations. The objective of this study was to explore approaches for incorporating preferences into model-based economic evaluations of genomic medicine and to develop a conceptual framework to consider preferences in health economic models. Methods We conducted a critical interpretive synthesis of published literature guided by the following question: how have preferences been incorporated into model-based economic evaluations of genomic medicine interventions? We integrated findings from the literature and expert opinion to develop a conceptual framework of ways in which preferences influence economic value in the context of genomic medicine. Results Our synthesis included 14 articles. Revealed and stated preference data were used to estimate choice probabilities and to value outcomes. Our conceptual framework situates preference data in the context of health system, patient, clinician, and family characteristics. Preference data were sourced from clinicians, patients and families impacted by a condition or intervention, and the general public. Evaluations employed various types of models, including discrete event simulation, microsimulation, Markov, and decision tree models. Conclusion When evaluating the broad benefits and costs of implementing new interventions, sufficiently accounting for preferences in the form of model inputs and valuation of outcomes in economic evaluations is important to avoid biased implementation decisions. Incorporation of preference data may improve alignment between predicted and real-world uptake and more accurately estimate welfare impacts, and this study provides critical insights to support researchers who seek to incorporate preference information into model-based health economic evaluations.

Date: 2025
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DOI: 10.1007/s40258-025-00945-0

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