Using Simulation to Compare 4 Categories of Intervention for Reducing Cardiovascular Disease Risks

Overview

Journal Am J Public Health

Specialty Public Health

Date 2014 May 17

PMID 24832142

Citations 17

Authors

Gary Hirsch

Jack Homer

Justin Trogdon

Kristina Wile

Diane Orenstein

Affiliations

Soon will be listed here.

Abstract

The Prevention Impacts Simulation Model (PRISM) projects the multiyear impacts of 22 different interventions aimed at reducing risk of cardiovascular disease. We grouped these into 4 categories: clinical, behavioral support, health promotion and access, and taxes and regulation. We simulated impacts for the United States overall and also for a less-advantaged county with a higher death rate. Of the 4 categories of intervention, taxes and regulation reduce costs the most in the short term (through 2020) and long term (through 2040) and reduce deaths the most in the long term; they are second to clinical interventions in reducing deaths in the short term. All 4 categories combined were required to bring costs and deaths in the less-advantaged county down to the national level.

Citing Articles

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References

Frieden T . A framework for public health action: the health impact pyramid. Am J Public Health. 2010; 100(4):590-5. PMC: 2836340. DOI: 10.2105/AJPH.2009.185652. View

Adler N, Stewart J . Preface to the biology of disadvantage: socioeconomic status and health. Ann N Y Acad Sci. 2010; 1186:1-4. DOI: 10.1111/j.1749-6632.2009.05385.x. View

Satcher D, Fryer Jr G, McCann J, Troutman A, Woolf S, Rust G . What if we were equal? A comparison of the black-white mortality gap in 1960 and 2000. Health Aff (Millwood). 2005; 24(2):459-64. DOI: 10.1377/hlthaff.24.2.459. View

Homer J, Hirsch G . System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006; 96(3):452-8. PMC: 1470525. DOI: 10.2105/AJPH.2005.062059. View

Hirsch G, Edelstein B, Frosh M, Anselmo T . A simulation model for designing effective interventions in early childhood caries. Prev Chronic Dis. 2012; 9:E66. PMC: 3366771. DOI: 10.5888/pcd9.110219. View

Glanz K, Bishop D . The role of behavioral science theory in development and implementation of public health interventions. Annu Rev Public Health. 2010; 31:399-418. DOI: 10.1146/annurev.publhealth.012809.103604. View

Murray C, Kulkarni S, Michaud C, Tomijima N, Bulzacchelli M, Iandiorio T . Eight Americas: investigating mortality disparities across races, counties, and race-counties in the United States. PLoS Med. 2006; 3(9):e260. PMC: 1564165. DOI: 10.1371/journal.pmed.0030260. View

Kirtland K, Zack M, Caspersen C . State-specific synthetic estimates of health status groups among inactive older adults with self-reported diabetes, 2000-2009. Prev Chronic Dis. 2012; 9:E89. PMC: 3406741. View

Milstein B, Homer J, Hirsch G . Analyzing national health reform strategies with a dynamic simulation model. Am J Public Health. 2010; 100(5):811-9. PMC: 2853627. DOI: 10.2105/AJPH.2009.174490. View

10.

Flores G . Technical report--racial and ethnic disparities in the health and health care of children. Pediatrics. 2010; 125(4):e979-e1020. DOI: 10.1542/peds.2010-0188. View

11.

Homer J, Milstein B, Wile K, Trogdon J, Huang P, Labarthe D . Simulating and evaluating local interventions to improve cardiovascular health. Prev Chronic Dis. 2009; 7(1):A18. PMC: 2811513. View

12.

Kenealy T, Rees D, Sheridan N, Moffitt A, Tibby S, Homer J . A 'whole of system' approach to compare options for CVD interventions in Counties Manukau. Aust N Z J Public Health. 2012; 36(3):263-8. DOI: 10.1111/j.1753-6405.2011.00812.x. View

13.

Milstein B, Homer J, Briss P, Burton D, Pechacek T . Why behavioral and environmental interventions are needed to improve health at lower cost. Health Aff (Millwood). 2011; 30(5):823-32. DOI: 10.1377/hlthaff.2010.1116. View

14.

Orsi J, Margellos-Anast H, Whitman S . Black-White health disparities in the United States and Chicago: a 15-year progress analysis. Am J Public Health. 2009; 100(2):349-56. PMC: 2804622. DOI: 10.2105/AJPH.2009.165407. View

15.

Jones A, Homer J, Murphy D, Essien J, Milstein B, Seville D . Understanding diabetes population dynamics through simulation modeling and experimentation. Am J Public Health. 2006; 96(3):488-94. PMC: 1470507. DOI: 10.2105/AJPH.2005.063529. View

16.

Loyo H, Batcher C, Wile K, Huang P, Orenstein D, Milstein B . From model to action: using a system dynamics model of chronic disease risks to align community action. Health Promot Pract. 2012; 14(1):53-61. DOI: 10.1177/1524839910390305. View

17.

Hirsch G, Homer J, Evans E, Zielinski A . A system dynamics model for planning cardiovascular disease interventions. Am J Public Health. 2010; 100(4):616-22. PMC: 2836333. DOI: 10.2105/AJPH.2009.159434. View

18.

Kessler R, Andrews G, Colpe L, Hiripi E, Mroczek D, Normand S . Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002; 32(6):959-76. DOI: 10.1017/s0033291702006074. View