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. 2021 Jan-Dec:58:46958021990516.
doi: 10.1177/0046958021990516.

Simulating the Fiscal Impact of Anti-Obesity Medications as an Obesity Reduction Strategy

Mina Kabiri  1 , Alison Sexton Ward  1 , Abhilasha Ramasamy  2 , Rebecca Kee  1 , Rahul Ganguly  2 , Brian Gabriel Smolarz  2 , Tracy Zvenyach  2 , James R Baumgardner  1 , Dana P Goldman  3
Affiliations

Simulating the Fiscal Impact of Anti-Obesity Medications as an Obesity Reduction Strategy

Mina Kabiri et al. Inquiry. 2021 Jan-Dec.

Abstract

While substantial public health investment in anti-smoking initiatives has had demonstrated benefits on health and fiscal outcomes, similar investment in reducing obesity has not been undertaken, despite the substantial burden obesity places on society. Anti-obesity medications (AOMs) are poorly prescribed despite evidence that weight loss is not sustained using other strategies alone.We used a simulation model to estimate the potential impact of 100% uptake of AOMs on Medicare and Medicaid spending, disability payments, and taxes collected relative to status quo with negligible AOM use. Relative to status quo, AOM use simulation would result in Medicare and Medicaid savings of $231.5 billion and $188.8 billion respectively over 75 years. Government tax revenues would increase by $452.8 billion. Overall, the net benefit would be $746.6 billion. Anti-smoking efforts have had substantial benefits for society. A similar investment in obesity reduction, including broad use of AOMs, should be considered.

Keywords: Medicaid; Medicare; anti-obesity agents; economic modeling; health policy; microsimulation; obesity; public health; weight loss.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Rebecca Kee and James Baumgardner are employees of precisionHEOR, a research consulting firm paid by Novo Nordisk Inc. to conduct this study. Mina Kabiri and Alison Sexton Ward were employees of precisionHEOR at the time that this research was conducted. Abhilasha Ramasamy, B. Gabriel Smolarz, Tracy Zvenyach, and Rahul Ganguly are employees of Novo Nordisk Inc. and hold equity in this company. Dana Goldman was a consultant to precisionHEOR and is a professor at the University of Southern California. He holds equity (<1%) in precisionHEOR; and reports personal fees or honoraria from the Aspen Institute, ACADIA Pharmaceuticals, Amgen, Avanir Pharmaceuticals, and Celgene, outside this study.

Figures

Figure 1.
Figure 1.
THEMIS mechanistic diagram. Note. “Health Status” represents risk factors, health conditions, and survival status of a simulated individual per 2-year model cycle. In each cycle, a simulated individual accessed treatment (if applicable) and accrued costs based on consumption of medical services. Health outcomes translated into health utility. The individual faced transitional probabilities in terms of acquiring new conditions and surviving, informing “Health Status” in the next cycle. Health spending was estimated according to health status. Other model outcomes included cost of absenteeism and presenteeism based on obesity status, labor force participation (full-time, part-time, or not employed) and earned income, quality adjusted life-years.
Figure 2.
Figure 2.
Number of treated patients given 100% anti-obesity medication uptake among patients.
Figure 3.
Figure 3.
Net fiscal impacts of 100% uptake of anti-obesity medications over 75 years. Note. Net fiscal impact = revenues + savings. Savings reflect negative government expenditures.
See this image and copyright information in PMC

References

    1. Center for Disease Control and Prevention. Obesity and Overweight. 2016. Accessed November 14, 2019. https://www.cdc.gov/nchs/fastats/obesity-overweight.htm
    1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311(8):806-814. - PMC - PubMed
    1. Wang YC, Pamplin J, Long MW, Ward ZJ, Gortmaker SL, Andreyeva T. Severe obesity in adults cost state medicaid programs nearly $8 billion in 2013. Health Aff (Project Hope). 2015;34(11):1923-1931. - PubMed
    1. Apovian CM. Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 2016;22(7 Suppl):s176-s185. - PubMed
    1. Allen L, Thorpe K, Joski P. The effect of obesity and chronic conditions on medicare spending, 1987-2011. Pharmacoeconomics. 2015;33(7):691-697. - PubMed

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