Mapping from health status measures onto generic preference-based measures is becoming a common solution when health state utility values are not directly available for economic evaluation. However the accuracy and reliability of the models employed is largely untested, and there is little evidence of their suitability in patient datasets. This paper examines whether mapping approaches are reliable and accurate in terms of their predictions for a large and varied UK patient dataset. SF-36 dimension scores are mapped onto the EQ-5D index using a number of different model specifications. The predicted EQ-5D scores for subsets of the sample are compared across inpatient and outpatient settings and medical conditions. This paper compares the results to those obtained from existing mapping functions. Our results suggest that models mapping the SF-36 onto the EQ-5D have similar predictions across inpatient and outpatient setting and medical conditions. However, the models overpredict for more severe EQ-5D states; this problem is also present in the existing mapping functions
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