Journal
MEDICAL DECISION MAKING
Volume 31, Issue 6, Pages 853-865Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0272989X11399921
Keywords
Bayesian decision theory; expected value of information; research design; cost-effectiveness analysis
Funding
- Medical Research Council [G0802659, MC_U145079308] Funding Source: researchfish
- MRC [G0802659, MC_U145079308] Funding Source: UKRI
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Methods to estimate the cost-effectiveness of technologies are well developed with increasing experience of their application to inform adoption decisions in a timely way. However, the experience of using similarly explicit methods to inform the associated research decisions is less well developed despite appropriate methods being available with an increasing number of applications in health. The authors demonstrate that evaluation of both adoption and research decisions is feasible within typical time and resource constraints relevant to policy decisions, even in situations in which data are sparse and formal elicitation is required. In addition to demonstrating the application of expected value of sample information (EVSI) in these circumstances, the authors examine and carefully distinguish the impact that the research decision is expected to have on patients while enrolled in the trial, those not enrolled, and once the trial reports. In doing so, the authors are able to account for the range of opportunity cost associated with research and evaluate a number of research designs including length of follow-up and sample size. The authors also explore the implications for research design of conducting research while the technology is approved for widespread use and whether approval should be withheld until research reports. In doing so, the authors highlight the impact of irrecoverable opportunity costs when the initial costs of a technology are compensated only by later gains in health outcome.
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