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Combining patient preferences with expected treatment outcomes to inform decision-making

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Abstract

Patient-centered care involves patients in decision-making about their medical care. Effective shared decision-making requires relevant evidence on the expected health outcomes of treatment, assessment of patient preferences for possible health outcomes, and a method to synthesize this information. Few tools exist to help clinicians and patients synthesize clinical evidence and personal preferences. We develop a statistical framework that combines multiple data sources on expected treatment outcomes with individual preferences to produce a personalized preference-weighted outcome score (PWOS). The PWOS can be calculated for multiple treatments and compared to determine which will provide the best balance of risks and benefits given a patient’s preferences. We demonstrate our method by evaluating adjuvant chemotherapy regimens for colorectal cancer. We begin by identifying heterogeneity in patient preferences for health outcomes associated with colorectal cancer disease and treatment, finding classes of patients who value efficacy and side effects differently. Then we fit a hierarchical Bayesian model to randomized clinical trials and produce posterior distributions of expected outcomes under three chemotherapy regimens. We use the PWOS to combine distinct sets of patient preferences with these expected outcomes. Our method preserves estimation uncertainty and accounts for correlation among outcomes. In a simulation study of applying PWOS to make decisions at the population level, we find that our methods are most useful when there are large differences in individual preferences and small distinctions in treatment efficacy (i.e., preference-sensitive settings).

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Acknowledgements

The authors wish to thank the Marshall J. Seidman Center for Studies in Health Economics and Health Care Policy at Harvard Medical School for supporting Dr. Schuler’s work. The authors are grateful to Jennie Best and Lou Garrison for sharing their data on patient utilities and to Dan Sargent and the ACCENT Investigators for sharing the colorectal clinical trial data. Finally, the authors thank Dan Sargent, Tom Kelley, Arlene Ash, the associate editor, and two anonymous reviewers for their helpful comments on the manuscript.

Funding

This work was funded by the generous support Marshall J. Seidman Center for Studies in Health Economics and Health Care Policy at Harvard Medical School (Dr. Schuler).

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  1. Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA, 02215, USA

    Megan S. Schuler & Laura A. Hatfield

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  1. Megan S. Schuler
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  2. Laura A. Hatfield
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Correspondence to Megan S. Schuler.

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This article does not contain any studies with human participants or animals performed by any of the authors.

Appendices

Appendix 1: Modeling code

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Appendix 2: Simulation code

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Schuler, M.S., Hatfield, L.A. Combining patient preferences with expected treatment outcomes to inform decision-making. Health Serv Outcomes Res Method 17, 144–174 (2017). https://doi.org/10.1007/s10742-016-0166-4

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