Shared decision-making

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Abstract

Shared decision-making is a collaborative process whereby patients and their providers make healthcare decisions together, taking into account both the best scientific evidence available and the patient's values and preferences. Effective implementation of shared decision-making therefore requires ready access to current evidence comparing expected outcomes of decision alternatives, assessment of decision-related values and preferences, and integration of this information to identify the most suitable course of action. Multi-criteria decision analysis (MCDA) is designed to help people make better choices when faced with complex decisions that involve trade-offs between competing objectives. MCDA methods fulfill all of the required elements of shared decision-making. This similarity suggests that MCDA methods could be used effectively to facilitate shared decision-making in practice. The evidence currently available supports this hypothesis. This chapter will illustrate how two MCDA methods - the conjoint analysis and analytic hierarchy process (AHP) - have been used to foster shared decision-making in clinical settings. Conjoint analysis refers to methods that derive an individual's decision-related preferences by examining how they make a series of hypothetical decisions that involve alternatives that differ in how well they achieve a set of decision objectives. We illustrate the use of conjoint analysis to foster shared decision-making by discussing how it has successfully been used to facilitate osteoarthritis treatment choices in real time and improve physician understanding of patient preferences for treatment of lupus nephritis. The analytic hierarchy process (AHP) is an example of a value-based multi-criteria method. Value-based methods provide a framework for structuring a decision, comparing alternatives relative to specific criteria, defining the relative priorities of criteria in achieving the decision goal, and synthesizing this information to create scores that summarize how well the alternatives are judged to meet the decision goal. They also allow for sensitivity analyses that allow users to explore the effects of different judgments and perspectives on the relative evaluations of the alternatives. We will illustrate the use of the AHP to foster shared decision-making in practice by describing how it has been used to facilitate decisions regarding colorectal cancer screening. We conclude with a list of suggestions regarding further research to continue this line of investigation with an emphasis on research needed to effectively implement these methods in routine practice settings.

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APA

Dolan, J. G., & Fraenkel, L. (2017). Shared decision-making. In Multi-Criteria Decision Analysis to Support Healthcare Decisions (pp. 199–215). Springer International Publishing. https://doi.org/10.1007/978-3-319-47540-0_11

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