An analysis of the sensitivity and stability of patients’ preferences can lead to more appropriate medical decisions

M. Gabriela Sava (), Luis G. Vargas, Jerrold H. May and James G. Dolan
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M. Gabriela Sava: Clemson University
Luis G. Vargas: University of Pittsburgh
Jerrold H. May: University of Pittsburgh
James G. Dolan: University of Rochester Medical Center

Annals of Operations Research, 2020, vol. 293, issue 2, No 18, 863-901

Abstract: Abstract Patients are faced with multiple alternatives when selecting the preferred method for colorectal cancer screening, and there are multiple criteria to be considered in the decision-making process. We model patients’ choices using a multicriteria decision model, specifically an Analytic Hierarchy Process-based model, and propose a new approach for characterizing the idiosyncratic preference regions for individual patients. The new approach involves the development of a personalized sensitivity and stability analysis of preferences that provides pertinent insights about the changes that occur in a patient’s preferences, as he/she learns additional relevant medical information. We show how the insights derived from the sensitivity and stability of patients’ preferences could be used by a healthcare provider within the medical decision-making process.

Keywords: Multicriteria decision-making; Analytic Network Process (ANP); Analytic Hierarchy Process (AHP); Sensitivity and stability analysis; Medical decision-making (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10479-018-3109-3

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