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FACIT Utilities

Utility Assessment

“Utilities” can broadly be defined as methods to measure health outcomes using preferences (either an individual’s or societal). In this way researchers can examine not just a quantity of life-years gained from an intervention, but the quality of that time. Utility is the metric used to quality adjust survival, i.e. to obtain the quality adjusted life year (QALY). Thus, cost utility analysis (CUA) permits the evaluation of health outcomes adjusted by patient preferences. For example, using CUA, researchers may compare the value of extending a life versus the side effects of the intervention.

There are different approaches to capturing preferences, including Time-Trade-Off (TTO), Standard-Gamble (SG), and Discrete Choice Experiments (DCE). However, because preferences/utilities are subjective, they can be influenced by many factors, including culture, disease, and change over time. Because cultures differ across countries, country-specific utilities may be required. Given the unique preferences of varying patient populations and country-specific payment systems for healthcare treatment, there are ongoing discussions of the value of disease- and country-specific utility weights and value sets.

Recommendations: The FACT-8D, developed by Dr. Madeleine King and her team, has produced the best direct measure. The FACT-8D is based on the FACT-G, one of the most widely-used cancer-specific HRQL measures and included as part of the core of a large suite of FACT measurements. Utilities can be scored from FACT-G data using the FACT-8D scoring algorithm. This can be done prospectively or retrospectively, facilitating the inclusion of FACT-G data in economic evaluation and health technology assessment. Importantly, the FACT-8D captures dimensions reflecting cancer symptoms and impact that are not included in generic instruments, specifically nausea, fatigue, sleep problems and worry about future health. Finally, the utilities provided by the FACT-8D's  algorithm have a stronger theoretical base than those derived from mapping algorithms. 

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