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Estimating Joint Health State Utilities

2022

Estimating health utility for a health state defined by a single health condition is relatively straightforward but becomes more complicated when 2 or more health conditions co-occur. Estimating health utility for so-called “joint health states” is particularly critical for health conditions that commonly co-occur with other conditions or for treatments in which adverse events are common or serious.  In these cases, ignoring the utility loss associated with the joint health state can bias CEA results and lead to faulty policy recommendations. Although the preferred approach is to use empirically estimated utilities for joint health states, the number of possible joint states often makes this impractical. Theoretically-derived estimation algorithms have, therefore, been proposed to estimate joint health state utilities using the utilities of the relevant single health states.

This article explores the performance of existing joint health state utility estimators when data are not available on utilities that isolate single-condition health states excluding any co-occurring condition. The investigators conclude that existing algorithms usually assume that investigators have different information available to them than is in fact actually so, resulting in biased estimates when algorithms are employed. They therefore recommend use of the “minimum estimator” –the lesser of all single health state utilities—be used based on its ease of use, consistency (and therefore a predictable direction of bias), and lower root mean squared error.

 

Source:

Bray JW, Thornburg BD, Gebreselassie AW, LaButte CA, Barbosa C, Wittenberg E. Estimating Joint Health State Utility Algorithms under Partial Information. Value in Health 2022. https://doi.org/10.1016/j.jval.2022.09.009