학술논문
Using the Online Elicitation of Personal Utility Functions Approach to Derive a Patient-Based 5-Level Version of EQ-5D Value Set: A Study in 122 Patients With Rheumatic Diseases From Germany.
Document Type
Academic Journal
Author
Schneider P; ScHARR, University of Sheffield, Sheffield, England, UK; CINCH, University of Duisburg/Essen, Essen, Germany; Valorem Health, Bochum, Germany. Electronic address: schneider@valorem.health.; Blankart K; CINCH, University of Duisburg/Essen, Essen, Germany.; Brazier J; ScHARR, University of Sheffield, Sheffield, England, UK.; van Hout B; ScHARR, University of Sheffield, Sheffield, England, UK; Open Health, York, England, UK.; Devlin N; University of Melbourne, Melbourne, VIC, Australia.
Source
Publisher: Elsevier Country of Publication: United States NLM ID: 100883818 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1524-4733 (Electronic) Linking ISSN: 10983015 NLM ISO Abbreviation: Value Health Subsets: MEDLINE
Subject
Language
English
Abstract
Objectives: Traditional preference elicitation methods, such as discrete choice experiments or time trade-off, usually require large sample sizes. This can limit their applicability in patient populations, where recruiting enough participants can be challenging. The objective of this study was to test a new method, called the Online elicitation of Personal Utility Functions (OPUF) approach, to derive an EQ-5D-5L value set from a relatively small sample of patients with rheumatic diseases.
Methods: OPUF is a new type of online survey that implements compositional preference elicitation techniques. Central to the method are 3 valuation steps: (1) dimension weighting, (2) level rating, and (3) anchoring. An English demo version of the OPUF survey can be accessed at https://valorem.health/eq5d5l. From the responses, a personal EQ-5D-5L utility function can be constructed for each participant, and a group-level value set can be derived by aggregating model coefficients across participants.
Results: A total of 122 patients with rheumatic disease from Germany completed the OPUF survey. The survey was generally well received; most participants completed the survey in less than 20 minutes and were able to derive a full EQ-5D-5L value set. The precision of mean coefficients was high, despite the small sample size.
Conclusions: Our findings demonstrate that OPUF can be used to derive an EQ-5D-5L value set from a relatively small sample of patients. Although the method is still under development, we think that it has the potential to be a valuable preference elicitation tool and to complement traditional methods in several areas.
Competing Interests: Author Disclosures Links to the disclosure forms provided by the authors are available here.
(Copyright © 2024. Published by Elsevier Inc.)
Methods: OPUF is a new type of online survey that implements compositional preference elicitation techniques. Central to the method are 3 valuation steps: (1) dimension weighting, (2) level rating, and (3) anchoring. An English demo version of the OPUF survey can be accessed at https://valorem.health/eq5d5l. From the responses, a personal EQ-5D-5L utility function can be constructed for each participant, and a group-level value set can be derived by aggregating model coefficients across participants.
Results: A total of 122 patients with rheumatic disease from Germany completed the OPUF survey. The survey was generally well received; most participants completed the survey in less than 20 minutes and were able to derive a full EQ-5D-5L value set. The precision of mean coefficients was high, despite the small sample size.
Conclusions: Our findings demonstrate that OPUF can be used to derive an EQ-5D-5L value set from a relatively small sample of patients. Although the method is still under development, we think that it has the potential to be a valuable preference elicitation tool and to complement traditional methods in several areas.
Competing Interests: Author Disclosures Links to the disclosure forms provided by the authors are available here.
(Copyright © 2024. Published by Elsevier Inc.)