Mapping the Oxford hip score onto the EQ-5D utility index

To assess different mapping methods for the estimation of a group’s mean EQ-5D score based on responses to the Oxford hip score (OHS) questionnaire.

Four models were considered: a) linear regression using total OHS as a continuous regressor; b) linear regression employing responses to the twelve OHS questions as categorical predictors; c) two-part approach combining logistic and linear regression; and d) response mapping. The models were internally validated on the estimation data set, which included OHS and EQ-5D scores for total hip replacements, both before and six months after procedure for 1,759 operations. An external validation was also performed.

All models estimated the mean EQ-5D score within 0.005 of an observed health-state utility estimate, ordinary least squares (OLS) continuous being the most accurate and OLS categorical the most consistent. Age, gender and deprivation did not improve the models. More accurate estimations at the individual level were achieved for higher scores of observed OHS and EQ-5D.

Based on these results, when EQ-5D scores are not available, answers to the OHS questionnaire can be used to estimate a group’s mean EQ-5D with a high degree of accuracy.