Economic evaluation conducted in terms of cost per quality-adjusted life-year (QALY) provides information that decision makers find useful in many parts of the world. Ideally, clinical studies designed to assess the effectiveness of health technologies would include outcome measures that are directly linked to health utility to calculate QALYs. Often this does not happen, and even when it does, clinical studies may be insufficient for a cost-utility assessment. Mapping can solve this problem. It uses an additional data set to estimate the relationship between outcomes measured in clinical studies and health utility. This bridges the evidence gap between available evidence on the effect of a health technology in one metric and the requirement for decision makers to express it in a different one (QALYs). In 2014, ISPOR established a Good Practices for Outcome Research Task Force for mapping studies. This task force report provides recommendations to analysts undertaking mapping studies, those that use the results in cost-utility analysis, and those that need to critically review such studies. The recommendations cover all areas of mapping practice: the selection of data sets for the mapping estimation, model selection and performance assessment, reporting standards, and the use of results including the appropriate reflection of variability and uncertainty. This report is unique because it takes an international perspective, is comprehensive in its coverage of the aspects of mapping practice, and reflects the current state of the art.

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Keywords economic evaluation, health utility, mapping, quality of life
Persistent URL dx.doi.org/10.1016/j.jval.2016.11.006, hdl.handle.net/1765/98073
Journal Value in Health
Citation
Wailoo, A.J. (Allan J.), Hernandez-Alava, M. (Monica), Manca, A. (Andrea), Mejia, A. (Aurelio), Ray, J. (Joshua), Crawford, B.T, … van Busschbach, J.J. (2017). Mapping to Estimate Health-State Utility from Non–Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report. Value in Health, 20(1), 18–27. doi:10.1016/j.jval.2016.11.006