Does one size fit all? Investigating heterogeneity in men's preferences for benign prostatic hyperplasia treatment using mixed logit analysis.

In this study, the authors demonstrate how mixed logit analysis of discrete choice experiment (DCE) data can provide information about unobserved preference heterogeneity. Their application investigates unobserved heterogeneity in men's preferences for benign prostatic hyperplasia (BPH) treatment. They use a DCE to elicit preferences for seven characteristics of BPH treatment: time to symptom improvement, sexual and nonsexual treatment side effects, risks of acute urinary retention and surgery, cost of treatment, and reduction in prostate size. They investigate the importance of these characteristics and the trade-offs men are willing to make between them. Preferences are elicited from a sample of 100 men attending an outpatient clinic in Ireland. The authors find all treatment characteristics are significant determinants of treatment choice. There is significant preference heterogeneity in the population for four treatment characteristics: time to symptom improvement, treatment reducing prostate size, risk of surgery, and sexual side effects. The importance of preference heterogeneity at the policy level within the context of shared decision making is discussed.