Value of information analysis for a new technology: Computer-assisted total knee replacement

Objectives: The aim of this study was to demonstrate how value of information analysis can measure the upper limit on returns to future research and identify the research priorities for computer-assisted total knee replacement (CAS-TKR). Methods: Using a previous economic analysis of CAS-TKR compared with conventional TKR, the population expected value of perfect information (EVPI) was calculated using Monte Carlo simulation to provide an estimate of the upper limit on returns to future research. The population expected value of partial perfect information (EVPPI) for both individual parameters and groups of parameters was estimated to inform specific future research priorities. Results: The UK individual EVPI would be 21.4 pound if the willingness to pay for one QALY (quality-adjusted life-year) were 30,000 pound. The population EVPPI would be 8.3 pound million, assuming a 10-year time horizon for CAS-TKR. In this instance, the expected value of information is positively related to willingness to pay for one QALY for the range of 0 pound to 50,000 pound. Although each individual parameter had an EVPPI of 0 pound, groups of utility parameters had positive EVPPI. Population EVPPI was 25.6 million for utility parameters, 20,000 pound for transition probabilities relating to CAS-TKR, and 5,000 pound for transition probabilities related to conventional TKR. Conclusions: The study provides evidence on which parameters further information may be of most value. Focusing research on the utility values associated with health states relating to TKR would be of greatest value.