Files
Abstract
Transfer to utility (TTU) or mapping methodology allows researchers to estimate a health utility from a disease-specific measure and calculate quality adjusted life years for economic evaluations. The purpose of this study was to develop regression algorithms to map five common disease specific TJA outcome measures to three preference-based health utility scores. An online survey was completed by 438 total hip arthroplasty (THA) patients and 550 total knee arthroplasty patients (TKA). THA patients completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC®), Harris Hip Score (HHS), and the Hip Disability and Osteoarthritis Outcomes Score (HOOS). Knee patients completed the WOMAC®, Knee Society Score (KSS), and Knee Disability and Osteoarthritis Outcomes Score (KOOS). All patients completed three preference based questionnaires, the SF-6D, EQ-5D and HUI-3, and responses were used to calculate health utilities. A total of 30 THA mapping models and 30 TKA mapping models were developed and validated. Forecast error measures including ME, MAE, RMSE were defined as our prediction performance criterion. For the THA models, the regression model with HOOS subscores most precisely estimated an EQ-5D health utility. The best performing TKA model mapped the KSS to the EQ-5D. Clinician-researchers can input their disease specific data into these models to estimate health utilities to consider the cost-effectiveness of osteoarthritis-related interventions relative to interventions for very different diseases and conditions.