The role of the expected value of individualized care in cost-effectiveness analyses and decision making
Value in Health , Volume 15 - Issue 1 p. 13- 21
Objective: To explore the feasibility and potential role of the expected value of individualized care (EVIC) framework. Methods: The EVIC quantifies how much benefits are forgone when a treatment decision is based on the best-expected outcomes in the population rather than in the individual patient. We have reviewed which types of patient-level attributes contribute to the EVIC and how they affect the interpretation of the outcomes. In addition, we have applied the EVIC framework to the outcomes of a microsimulation-based cost-effectiveness analysis for glaucoma treatment. Results: For EVIC outcomes to inform decisions about clinical practice, we need to calculate the parameter-specific EVIC of known or knowable patient-level attributes and compare it with the real costs of implementing individualized care. In the case study, the total EVIC was €580 per patient, but patient-level attributes known at treatment decision had minimal impact. A subgroup policy based on individual disease progression could be worthwhile if a predictive test for glaucoma progression could be developed and implemented for less than €130 per patient. Conclusions: The EVIC framework is feasible in cost-effectiveness analyses and can be informative for decision making. The EVIC outcomes are particularly informative when they are (close to) zero. When the EVIC has a high value, implications depend on the type of patient-level attribute. EVIC can be a useful tool to identify opportunities to improve efficiency in health care by individualization of care and to quantify the maximal investment opportunities for implementing subgroup policy.
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|Value in Health|
|Organisation||Erasmus MC: University Medical Center Rotterdam|
van Gestel, A, Grutters, J.C, Schouten, J.S.A.G, Webers, C.A.B, Beckers, H, Joore, M.A, & Severens, J.L. (2012). The role of the expected value of individualized care in cost-effectiveness analyses and decision making. Value in Health, 15(1), 13–21. doi:10.1016/j.jval.2011.07.015