Comparative Modeling to Inform Health Policy Decisions: A Step Forward
Authors: David D. Kim, Peter J. Neumann
Journal: Annals of Internal Medicine (2019)

Editorials3 December 2019Comparative Modeling to Inform Health Policy Decisions: A Step ForwardDavid D. Kim, PhD and Peter J. Neumann, ScDDavid D. Kim, PhDTufts Medical Center, Boston, Massachusetts (D.D.K., P.J.N.)Search for more papers by this author and Peter J. Neumann, ScDTufts Medical Center, Boston, Massachusetts (D.D.K., P.J.N.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M19-2797 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Decision analytic models should be seen as essential tools of evidence-based medicine. They provide a framework for integrating many data sources, evaluating the strength of evidence, testing assumptions and scenarios, exploring uncertainty, and ultimately informing decisions about the likely value of alternative strategies for improving health. Over the years, such models have helped challenge prevailing wisdom and have brought clarity to various health policy debates—underscoring, for example, that prevention programs usually do not save money and that very expensive technologies may sometimes provide good value for the money.If decision analytic models to address clinical and policy questions are useful, ...References1. Box GEP. Robustness in the strategy of scientific model building. In: Launer RL, Wilkinson GN, eds. Robustness in Statistics. New York: Academic Pr; 1979:201-36. Google Scholar2. Neumann PJ, Kim DD, Trikalinos TA, et al. Future directions for cost-effectiveness analyses in health and medicine. Med Decis Making. 2018;38:767-777. [PMID: 30248277] doi:10.1177/0272989X18798833 CrossrefMedlineGoogle Scholar3. de Koning HJ, Meza R, Plevritis SK, et al. Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive Services Task Force. Ann Intern Med. 2014;160:311-20. [PMID: 24379002]. doi:10.7326/M13-2316 LinkGoogle Scholar4. Palmer AJ, Si L, Tew M, et al. Computer modeling of diabetes and its transparency: a report on the eighth Mount Hood Challenge. Value Health. 2018;21:724-731. [PMID: 29909878] doi:10.1016/j.jval.2018.02.002 CrossrefMedlineGoogle Scholar5. Eaton JW, Menzies NA, Stover J, et al. Health benefits, costs, and cost-effectiveness of earlier eligibility for adult antiretroviral therapy and expanded treatment coverage: a combined analysis of 12 mathematical models. Lancet Glob Health. 2014;2:e23-34. [PMID: 25104632] doi:10.1016/S2214-109X(13)70172-4 CrossrefMedlineGoogle Scholar6. Criss SD, Cao P, Bastani M, et al. Cost-effectiveness analysis of lung cancer screening in the United States. A comparative modeling study. Ann Intern Med. 2019;171:796-804. doi:10.7326/M19-1795 LinkGoogle Scholar7. Sanders GD, Neumann PJ, Basu A, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316:1093-103. [PMID: 27623463] doi:10.1001/jama.2016.12195 CrossrefMedlineGoogle Scholar8. Kovalchik SA, Tammemagi M, Berg CD, et al. Targeting of low-dose CT screening according to the risk of lung-cancer death. N Engl J Med. 2013;369:245-254. [PMID: 23863051] doi:10.1056/NEJMoa1301851 CrossrefMedlineGoogle Scholar9. Green AK, Bach P. Model-based eligibility for lung cancer screening: where theory meets practice [Editorial]. Ann Intern Med. 2018;168:223-224. [PMID: 29297001]. doi:10.7326/M17-3316 LinkGoogle Scholar10. Kim DD, Cohen JT, Wong JB, et al. Targeted incentive programs for lung cancer screening can improve population health and economic efficiency. Health Aff (Millwood). 2019;38:60-67. [PMID: 30615528] doi:10.1377/hlthaff.2018.05148 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Tufts Medical Center, Boston, Massachusetts (D.D.K., P.J.N.)Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M19-2797.Corresponding Author: Peter J. Neumann, ScD, Tufts Medical Center, Center for Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, 800 Washington Street, #063, Boston, MA 02111; e-mail, [email protected]org.Current Author Addresses: Drs. Kim and Neumann: Tufts Medical Center, Center for Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, 800 Washington Street, #063, Boston, MA 02111.This article was published at Annals.org on 5 November 2019. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoCost-Effectiveness Analysis of Lung Cancer Screening in the United States Steven D. Criss , Pianpian Cao , Mehrad Bastani , Kevin ten Haaf , Yufan Chen , Deirdre F. Sheehan , Erik F. Blom , Iakovos Toumazis , Jihyoun Jeon , Harry J. de Koning , Sylvia K. 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