ABSTRACT
OBJECTIVES: We estimated national and state-level potential medical care cost savings achievable through modest reductions in the prevalence of several diseases associated with the same lifestyle-related risk factors. METHODS: Using Medical Expenditure Panel Survey Household Component data (2003-2005), we estimated the effects on medical spending over time of reductions in the prevalence of diabetes, hypertension, and related conditions amenable to primary prevention by comparing simulated counterfactual morbidity and medical care expenditures to actual disease and expenditure patterns. We produced state-level estimates of spending by using multivariate reweighting techniques. RESULTS: Nationally, we estimated that reducing diabetes and hypertension prevalence by 5% would save approximately $9 billion annually in the near term. With resulting reductions in comorbidities and selected related conditions, savings could rise to approximately $24.7 billion annually in the medium term. Returns were greatest in absolute terms for private payers, but greatest in percentage terms for public payers. State savings varied with demographic makeup and prevailing morbidity. CONCLUSIONS: Well-designed interventions that achieve improvements in lifestyle-related risk factors could result in sufficient savings in the short and medium term to substantially offset intervention costs.
Subject(s)
Chronic Disease/prevention & control , Diabetes Mellitus/prevention & control , Health Care Costs , Hypertension/prevention & control , Primary Prevention/economics , Adult , Chronic Disease/economics , Chronic Disease/epidemiology , Cost Control , Diabetes Complications/economics , Diabetes Complications/epidemiology , Diabetes Complications/prevention & control , Diabetes Mellitus/economics , Diabetes Mellitus/epidemiology , Health Expenditures , Heart Diseases/economics , Heart Diseases/epidemiology , Heart Diseases/prevention & control , Humans , Hypertension/economics , Hypertension/epidemiology , Kidney Diseases/economics , Kidney Diseases/epidemiology , Kidney Diseases/prevention & control , Life Style , Linear Models , Medicaid/economics , Medicare/economics , Models, Econometric , Prevalence , Risk Factors , Stroke/economics , Stroke/epidemiology , Stroke/prevention & control , United States/epidemiologyABSTRACT
The National Neighborhood Indicators Partnership (NNIP), a collaborative effort, uses local information in community building and policy making. A local intermediary in 19 NNIP partnership cities builds local data systems. Partners have learned five important lessons: (1) neighborhood-level data are essential for developing public policy, (2) technological advances have made it possible to maintain detailed local databases at relatively low cost, (3) various types of local organizations can serve as local partners, (4) good leadership is critical to building bridges across agencies, and (5) providing data is only the first step. Data must be used in ways that are visible, useful, and responsive to the community if the project is to succeed.