Advancing the use of evidence-based decision-making in local health departments with systems science methodologies

Objectives: We assessed how systems science methodologies might be used to bridge resource gaps at local health departments (LHDs) so that they might better implement evidence-based decision-making (EBDM) to address population health challenges. Methods: We used the New York Academy of Medicine Cardiovascular Health Simulation Model to evaluate the results of a hypothetical program that would reduce the proportion of people smoking, eating fewer than 5 fruits and vegetables per day, being physically active less than 150 minutes per week, and who had a body mass index (BMI) of 25 kg/m₂ or greater. We used survey data from the Behavioral Risk Factor Surveillance System to evaluate health outcomes and validate simulation results. Results: Smoking rates and the proportion of the population with a BMI of 25 kg/m₂ or greater would have decreased significantly with implementation of the hypothetical program (P < .001). Two areas would have experienced a statistically significant reduction in the local population with diabetes between 2007 and 2027 (P < .05). Conclusions: The use of systems science methodologies might be a novel and efficient way to systematically address a number of EBDM adoption barriers at LHDs.