Jonathan Karnon1, Andrew Partington2. 1. School of Population Health, University of Adelaide, Level 7, 178 North Terrace, Adelaide, SA, 5005, Australia. jonathan.karnon@adelaide.edu.au. 2. School of Population Health, University of Adelaide, Level 7, 178 North Terrace, Adelaide, SA, 5005, Australia.
Abstract
BACKGROUND: Cost-value analysis aims to address the limitations of the quality-adjusted life-year (QALY) by incorporating the strength of public concerns for fairness in the allocation of scarce health care resources. To date, the measurement of value has focused on equity weights to reflect societal preferences for the allocation of QALY gains. Another approach is to use a non-QALY-based measure of value, such as an outcome 'equivalent to saving the life of a young person' (a SAVE). OBJECTIVE: This paper assesses the feasibility and validity of using the SAVE as a measure of value for the economic evaluation of health care technologies. METHODS: A web-based person trade-off (PTO) survey was designed and implemented to estimate equivalent SAVEs for outcome events associated with the progression and treatment of early-stage breast cancer. The estimated equivalent SAVEs were applied to the outputs of an existing decision analytic model for early breast cancer. RESULTS: The web-based PTO survey was undertaken by 1094 respondents. Validation tests showed that 68 % of eligible responses revealed consistent ordering of responses and 32 % displayed ordinal transitivity, while 37 % of respondents showing consistency and ordinal transitivity approached cardinal transitivity. Using consistent and ordinally transitive responses, the mean incremental cost per SAVE gained was £ 3.72 million. CONCLUSION: Further research is required to improve the validity of the SAVE, which may include a simpler web-based survey format or a face-to-face format to facilitate more informed responses. A validated method for estimating equivalent SAVEs is unlikely to replace the QALY as the globally preferred measure of outcome, but the SAVE may provide a useful alternative for localized decision makers with relatively small, constrained budgets-for example, in programme budgeting and marginal analysis.
BACKGROUND: Cost-value analysis aims to address the limitations of the quality-adjusted life-year (QALY) by incorporating the strength of public concerns for fairness in the allocation of scarce health care resources. To date, the measurement of value has focused on equity weights to reflect societal preferences for the allocation of QALY gains. Another approach is to use a non-QALY-based measure of value, such as an outcome 'equivalent to saving the life of a young person' (a SAVE). OBJECTIVE: This paper assesses the feasibility and validity of using the SAVE as a measure of value for the economic evaluation of health care technologies. METHODS: A web-based person trade-off (PTO) survey was designed and implemented to estimate equivalent SAVEs for outcome events associated with the progression and treatment of early-stage breast cancer. The estimated equivalent SAVEs were applied to the outputs of an existing decision analytic model for early breast cancer. RESULTS: The web-based PTO survey was undertaken by 1094 respondents. Validation tests showed that 68 % of eligible responses revealed consistent ordering of responses and 32 % displayed ordinal transitivity, while 37 % of respondents showing consistency and ordinal transitivity approached cardinal transitivity. Using consistent and ordinally transitive responses, the mean incremental cost per SAVE gained was £ 3.72 million. CONCLUSION: Further research is required to improve the validity of the SAVE, which may include a simpler web-based survey format or a face-to-face format to facilitate more informed responses. A validated method for estimating equivalent SAVEs is unlikely to replace the QALY as the globally preferred measure of outcome, but the SAVE may provide a useful alternative for localized decision makers with relatively small, constrained budgets-for example, in programme budgeting and marginal analysis.
Authors: Karl Claxton; Steve Martin; Marta Soares; Nigel Rice; Eldon Spackman; Sebastian Hinde; Nancy Devlin; Peter C Smith; Mark Sculpher Journal: Health Technol Assess Date: 2015-02 Impact factor: 4.014