Patient-centered Treatment Decisions for Urethral Stricture: Conjoint Analysis Improves Surgical Decision-making

Abstract

Objective: To determine whether the use of a choice-based conjoint analysis (CA) exercise decreased patients' decisional conflict about treatment preferences for surgical management of urethral stricture disease. Understanding patient preferences for treatment decisions assists in shared decision-making and emphasizes patient-centered outcomes. CA offers a method to understand what risks patients are willing to take for what gains.

Methods: The CA methodology was used by providing participants with case-based choices to elucidate the relative importance that individuals place on various treatment aspects. Patients' decisional conflict regarding surgery for urethral stricture was assessed before and after the CA exercise to assess the impact the exercise had on their decisional conflict.

Results: Completion of the CA exercise resulted in a significant decrease in decisional conflict (P < .001). The majority (59.5%) of participants with decisional conflict before the CA exercise experienced a decrease in decisional conflict afterwards, with only a minority (16.5%) experiencing new decisional conflict after the exercise. Participants felt the choice-based CA exercise was helpful in deciding what was important in making treatment decisions (70%) and in expressing their priorities and treatment preferences (82%). The number needed to counsel to achieve a decrease in decisional conflict was 1.69 and to achieve no decisional conflict was 3.65.

Conclusion: Choice-based CA improves patients' ability to express their treatment preferences and decreases decisional conflict. CA may be a new tool that physicians and patients can use to aid in shared decision-making with a focus on patient-centered outcomes.

Copyright © 2016 Elsevier Inc. All rights reserved.

Figures

Figure 1.

Reference guide provided to patients before participating in the conjoint analysis exercise. Participants were required to acknowledge understanding of each attribute before proceeding with the exercise.

Figure 2.

Examples of two case-based scenarios offering a choice between two randomly generated treatment options. Attributes are listed along the left, and each choice scenario was generated with changes in the attribute level to elicit patient preferences. (Color version available online.)