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.

expected value of individualized care, glaucoma, heterogeneity, personalized medicine, value of information
dx.doi.org/10.1016/j.jval.2011.07.015, hdl.handle.net/1765/34770
Value in Health
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