In a budget-constrained health-care system, decisions about investing in strategies to promote implementation have to be made alongside decisions about health-care provision and research funding. Using a Bayesian decision-theoretic approach, an analytic framework has been developed to inform these separate but related decisions, establishing the expected value of both perfect information (EVPI) and perfect implementation (EVPIM). We applied this framework to inform decision-making about resource allocation to metastatic hormone-refractory prostate cancer (mHRPC) in the UK.
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