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Mapping the Michigan Hand Questionnaire and Disabilities of the Arm, Shoulder and Hand onto the EuroQol-5 Dimension
Gordon C Wong1, Wenchu Pan2, Sandra V Kotsis1
1From the Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School.
Background:
Cost-utility analyses require utilities data, which are often unavailable in hand surgery, where functional scores are more commonly used. This study aims to develop predictive models to accurately map 2 dominant legacy questionnaires for the hand specialty, Michigan Hand Outcomes Questionnaire (MHQ) and Disabilities of the Arm, Shoulder, and Hand (DASH) scores onto the 5-level EuroQol-5 Dimension (EQ-5D). This will facilitate more economic evaluations of the growing number of hand procedures.
Methods:
Data were collected prospectively from 354 patients diagnosed with various hand conditions at the University of Michigan Hospital. Participants completed the MHQ, DASH, and EQ-5D surveys. We evaluated 6 statistical models to determine the best fit for mapping MHQ and DASH onto EQ-5D. Model performance was assessed using mean absolute error (MAE), root mean squared error (RMSE), R², and proportion of predictions within 0.1 and 1 SD of true EQ-5D values.
Results:
The logarithmic response mapping model was the best fit for mapping MHQ to EQ-5D (MAE, 0.1119; RMSE, 0.1584; R² , 0.445), whereas the ordinary least squares model performed best for DASH (MAE, 0.0934; RMSE, 0.1347; R² , 0.601). Both models showed strong predictive accuracy, with 58% (MHQ) and 68% (DASH) of predictions within 0.1 of observed EQ-5D scores, and over 85% within 1 SD.
Conclusions:
Response mapping and ordinary least square models are reliable methods to map MHQ and DASH onto EQ-5D. These mapping algorithms offer a valuable alternative for obtaining utilities in the absence of direct data.
