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Accounting for Nonhealth and Future Costs in Cost-Effectiveness Analysis: Distributional Impacts of a US Cancer Prevention Strategy
OBJECTIVE: To provide up-to-date and comprehensive US data tables to estimate future net resource use, including nonlabor market production, and examine distributional impacts of including nonhealth and future costs in cost-effectiveness results. METHODS: Using a published US cancer prevention simul...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189225/ https://www.ncbi.nlm.nih.gov/pubmed/37195368 http://dx.doi.org/10.1007/s40273-023-01275-6 |
Sumario: | OBJECTIVE: To provide up-to-date and comprehensive US data tables to estimate future net resource use, including nonlabor market production, and examine distributional impacts of including nonhealth and future costs in cost-effectiveness results. METHODS: Using a published US cancer prevention simulation model, the paper evaluated the lifetime cost effectiveness of implementing a 10% excise tax on processed meats across age- and sex-specific population subgroups. The model examined multiple scenarios accounting for cancer-related healthcare expenditure (HCE) only, cancer-related and unrelated background HCE, adding productivity benefits (i.e., patient time, cancer-related productivity loss, and background labor and nonlabor market production), and with nonhealth consumption costs, adjusted for household economies of scale. Additional analyses include using population-average versus age–sex-specific estimates for quantifying production and consumption value, as well as comparing direct model estimation versus postcorrections with Meltzer’s approximation for incorporating future resource use. RESULTS: Accounting for nonhealth and future costs impacted cost-effectiveness results across population subgroups, often leading to changes in “cost-saving” determination. Including nonlabor market production had a noticeable impact on estimating future resource use and reduced the bias toward undervaluing productivity among females and older populations. The use of age–sex-specific estimates resulted in less favorable cost-effectiveness results compared with population-average estimates. Meltzer’s approximation provided reasonable corrections among the middle-aged population for re-engineering cost-effectiveness ratios from a healthcare sector to a societal perspective. CONCLUSION: With updated US data tables, this paper can help researchers conduct a comprehensive value assessment to reflect net resource use (health and nonhealth resource use minus production value) from a societal perspective. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40273-023-01275-6. |
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