Hengjin Dong1, Doug Coyle, Martin Buxton. 1. Department of Tropical Hygiene and Public Health, Heidelberg University, Germany. dong@uni-heidelberg.de
Abstract
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 pound21.4 if the willingness to pay for one QALY (quality-adjusted life-year) were pound30,000. The population EVPPI would be pound8.3 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 pound0 to pound50,000. Although each individual parameter had an EVPPI of pound0, groups of utility parameters had positive EVPPI. Population EVPPI was pound5.6 million for utility parameters, pound20,000 for transition probabilities relating to CAS-TKR, and pound5,000 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.
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 pound21.4 if the willingness to pay for one QALY (quality-adjusted life-year) were pound30,000. The population EVPPI would be pound8.3 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 pound0 to pound50,000. Although each individual parameter had an EVPPI of pound0, groups of utility parameters had positive EVPPI. Population EVPPI was pound5.6 million for utility parameters, pound20,000 for transition probabilities relating to CAS-TKR, and pound5,000 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.
Authors: Nicholas Latimer; Joanne Lord; Robert L Grant; Rachel O'Mahony; John Dickson; Philip G Conaghan Journal: Pharmacoeconomics Date: 2011-03 Impact factor: 4.981