THE SIMULATION MODEL FOR INTERVENTIONS LINKING EVIDENCE TO SOCIAL DETERMINANTS OF HEALTH (SMILES): A PLATFORM FOR EVALUATING THE LONG-TERM COST-EFFECTIVENESS OF LOCAL AND STATE POLICIES FOR CHRONIC DISEASE PREVENTION
Author(s)
Benjamin Allaire, MS1, Joëlla Adams, PhD, MPH1, Sofia Oviedo, MPH1, Rainer Hilscher, PhD1, Wendi Rotunda, PhD1, Naomi Buell, BA1, Nicholas Kruskamp, PhD, MS1, Caroline Kroma, MS1, Shichao Tang, PhD2.
1RTI International, Research Triangle Park, NC, USA, 2Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.
1RTI International, Research Triangle Park, NC, USA, 2Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.
OBJECTIVES: The Simulation Model of Interventions Linking Evidence to Social Determinants of Health (SDOH) (SMILES) is a microsimulation projecting long-term health outcomes and costs associated with programs, practices, and policies (PPPs) focused on SDOH. SMILES evaluates SDOH-related PPPs on chronic disease incidence, mortality, and disease costs at state and county levels.
METHODS: SMILES uses a geospatially explicit synthetic population derived from the National Health and Nutrition Examination Survey (NHANES) and integrates validated disease transition equations and epidemiologic data to estimate population-level impacts of 26 PPPs across five SDOH domains: built environment, food and nutrition security, community-clinical linkages (CCL), social connectedness, and tobacco-free policies. As a proof of concept, we modeled the impact of increasing the number of Community Health Worker (CHW) integrated into care teams and improved care coordination in two demographically distinct counties with health workforce shortages: McDowell County, West Virginia, and Holmes County, Mississippi. We assumed that 25% of individuals who reported not seeing a health care professional would have been reached with improved access to care. SMILES projected incidence, mortality, and direct and indirect disease costs over a 15-year period for six chronic conditions: chronic kidney disease, diabetes, stroke, coronary heart disease, lung cancer, and dementia.
RESULTS: The CHW intervention had the greatest impact on diabetes, stroke, and coronary heart disease incidence. For McDowell County, expanding CHW reach to 25% coverage averted 2-5% of incident cases from baseline. Holmes County experienced larger reductions, with 6-11% averted. Mortality was reduced by 1-2% and disease costs were reduced by 2-3% for both counties over the 15-year timeframe.
CONCLUSIONS: SMILES is a geospatially explicit microsimulation enabling rigorous evaluation of SDOH-focused interventions across multiple populations and geographic contexts. In our simulation study, we find that counties choosing to expand CHW reach both reduce disease burden and medical costs over a 15-year period.
METHODS: SMILES uses a geospatially explicit synthetic population derived from the National Health and Nutrition Examination Survey (NHANES) and integrates validated disease transition equations and epidemiologic data to estimate population-level impacts of 26 PPPs across five SDOH domains: built environment, food and nutrition security, community-clinical linkages (CCL), social connectedness, and tobacco-free policies. As a proof of concept, we modeled the impact of increasing the number of Community Health Worker (CHW) integrated into care teams and improved care coordination in two demographically distinct counties with health workforce shortages: McDowell County, West Virginia, and Holmes County, Mississippi. We assumed that 25% of individuals who reported not seeing a health care professional would have been reached with improved access to care. SMILES projected incidence, mortality, and direct and indirect disease costs over a 15-year period for six chronic conditions: chronic kidney disease, diabetes, stroke, coronary heart disease, lung cancer, and dementia.
RESULTS: The CHW intervention had the greatest impact on diabetes, stroke, and coronary heart disease incidence. For McDowell County, expanding CHW reach to 25% coverage averted 2-5% of incident cases from baseline. Holmes County experienced larger reductions, with 6-11% averted. Mortality was reduced by 1-2% and disease costs were reduced by 2-3% for both counties over the 15-year timeframe.
CONCLUSIONS: SMILES is a geospatially explicit microsimulation enabling rigorous evaluation of SDOH-focused interventions across multiple populations and geographic contexts. In our simulation study, we find that counties choosing to expand CHW reach both reduce disease burden and medical costs over a 15-year period.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
MSR202
Topic
Methodological & Statistical Research
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity), SDC: Urinary/Kidney Disorders