The elicitation of patient preferences for hip replacement surgery: a discrete choice experiment
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: The calculation of aggregated composite measures is a widely used approach to reduce the amount of quality-related data on hospital report cards (HRCs). This study aims to elicit patient preferences for hospital choice concerning publicly available hospital quality information for total hip replacement surgery. The results may assist in the development of weighted composite measures for elective hip replacement, which facilitates a conscious selection of the hospital. METHODS: We collect primary survey data on a sample of 364 randomly selected users of the German HRC "Weisse Liste" (WL) (4/5 2023). The key attributes for hospital choice are based on the information provided in WL. We run various model specifications to identify patient preferences, allowing the analysis of unobserved preference heterogeneity. RESULTS: ). Patients consider the "Quality of treatment" (26.95%; level range 1.734) and "Number of cases treated" (24.78%; level range 1.594) to be the most important. In contrast, "EndoCert Certificate" (17.50%; level range 1.126), "Equipment and qualification" (15.83%; level range 1.018), and "Recommendation from other patients" (14.94%; level range 0.960) remain less important. We find no evidence for unobserved heterogeneity regarding the preferences for hospital choice. CONCLUSION: Based on our findings, HRC users value publicly available hospital quality information for elective hip replacement differently. These differences should be taken into account when calculating aggregated composite measures. Our results may allow the calculation of a weighted aggregate composite measure from the perspective of HRC users.
Source: BMC Health Services Research
Authors: Stefan Rohrbacher, Martin Emmert
Institution: University of Bayreuth
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,290
Funder: Universität Bayreuth
OpenAlex ID: W4407719077
