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 Our sample consists of 177 respondents (mean age 56.46; 43.5% female). All attributes used are statistically significant for hospital choice (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12913_2025_12393_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="62" /> </InlineMediaObject> <EquationSource Format="TEX">$p<0.01$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo><</mo> <mn>0.01</mn> </mrow> </math></EquationSource> </InlineEquation>). 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.

The elicitation of patient preferences for hip replacement surgery: a discrete choice experiment

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2025年2月18日

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Stefan Rohrbacher,
Martin Emmert

摘要

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

Our sample consists of 177 respondents (mean age 56.46; 43.5% female). All attributes used are statistically significant for hospital choice ( $p<0.01$ $p < 0.01$ ). 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.