Introduction

The 2011 Institute of Medicine Report “Crossing the Quality Chasm” placed patient-centered care at the forefront of medical reform, specifically focusing on ensuring that patient values and preferences guide clinical decision making.¹ Goal-concordant patient-centered decision making requires knowing and understanding the best available evidence around risks and benefits across all available treatment options, while ensuring patients’ values and preferences are taken into account.^2–5 For those seeking surgical consultation, providers must explain surgical options, review the common risks and benefits, and weigh patient comorbidities and priorities in order to help guide patients to the best treatment option for them. This can be an overwhelming process, and often physicians (and sometimes patients themselves) do not actually know what the patients’ goals and values are, thus making it difficult to incorporate this into the decision-making process. Patient values and preferences can be determined through a better understanding of the preferences of the patient population as a whole, as well as on an individual patient level.

Applying a Conjoint Analysis Approach

Conjoint analysis utilizing discrete choice experiments (DCEs) can be a useful method to evaluate patient preference in health care decision making. This method utilizes patient choices to systematically elicit risk-benefit trade-offs and quantify the relative preferences and risk acceptance for attributes of medical interventions. DCEs have a long-standing track record of use by industry to facilitate priority setting and in market research to determine preferences, and are emerging as a novel tool for use in health care research to determine treatment preferences, including surgical treatments.^6–9 Conducting a DCE for treatment decisions first requires defining the treatment attributes of interest. Ideally, this work is done from the ground up, finding out what patients themselves think rather than merely relying on what physicians believe is important to the decision-making process. Next, these attributes are used to populate paired hypothetical scenarios, where individuals must choose their preferred treatment between 2 choices where the attribute levels are varied. Conjoint analysis can then determine the ranked importance and utility of the treatment attributes among the population, how preferences are associated with various treatment attributes and what patient characteristics are associated with these preferences. This analysis can provide robust information about preferences that can inform treatment counseling.

Figure. Discrete Choice Experiment (DCE) case-based conjoint analysis scenario examples.⁷

Employing Conjoint Analysis: An Example in Urethral Stricture Surgery

Conjoint analysis with DCEs has been used to improve understanding of what patients value when making surgical treatment decisions for urethral stricture surgery.¹⁰ Patient-derived treatment attributes including success rate, recovery time and need for additional procedures were integrated into paired treatment scenarios. Participants were presented with a series of paired treatment scenarios from which they needed to choose their preferred treatment (see figure). Conjoint analysis of the DCEs determined that success rate was by far the most important attribute to participants, as well as strong preferences against longer catheter duration.⁷ Attributes such as recovery time and procedure type actually played a small role in participants’ treatment decisions. In addition, subgroup analysis showed that older participants preferred a higher success rate with fewer procedures even in the face of a more invasive surgery, whereas younger participants preferred a less invasive approach and were willing to accept a higher number of future procedures if needed. These data help to inform counseling and provide data toward changing practice patterns. In this example, knowing the preferences of older men can help anchor treatment counseling in patient preferences instead of provider biases, perhaps moving away from repeated urethral dilation or endoscopic incision.

Conjoint Analysis as a Decision Tool

In addition to understanding patient preferences of a treatment population, these DCEs can also be used to effectively help patients define their own values related to treatment decisions. Research has shown that the process of preference assessment via hypothetical case-based scenarios used in DCEs helps individuals understand their own values and preferences related to treatment decisions.¹⁰ In a study of men who completed a series of case-based scenarios regarding urethral stricture treatment, 70% of participants felt the exercise was helpful in deciding what was important in making treatment decisions, and 82% felt it helped them to express their priorities and treatment preferences. These data provide support for utilizing hypothetical case-based scenarios as the basis of determining individuals’ own values and preferences related to surgical treatment. For example, some patients may put more value on success rate, while others may value risk of complication more strongly. A DCE-based tool can help to highlight the key attributes that patients value and guide them toward the treatment choice that best fits their needs and preferences.

Conclusions

Conjoint analysis is a novel, useful tool to understand patient preference in treatment decision making, as well as to help patients define their own preferences. Given the importance of determining patient preference for surgical treatment, particularly when it comes to reconstructive urology oriented toward improving quality of life, one can see the utility of employing conjoint analysis for many preference-sensitive decisions such as reconstruction after cystectomy, management of incontinence and gender-affirming surgical reconstruction. Ultimately, it is vital to incorporate patient preference into treatment decisions; to do so, we need to identify preferences on both an individual and a population level in order to ensure that treatment decisions are truly patient centered and values driven.