摘要：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. Local health departments (LHDs) play a vital role in protecting the health of communities and improving population health by leading and coordinating surveillance and health promotion efforts. There are more than 2800 LHDs in the United States, and they collaborate closely with public and private organizations to develop programs and enhance the capacity of local communities to address public health challenges. 1 To carry out these responsibilities in an effective manner, it is necessary to incorporate scientific evidence into program design and decision-making processes. 2–4 Evidence-based decision-making (EBDM) involves “making decisions on the basis of the best available scientific evidence, using data and information systems systematically, applying program-planning frameworks, engaging the community in decision making, conducting sound evaluation, and disseminating what is learned.” 2 (p175), 5 Although there is increasing support for the use of EBDM in public health practice, many LHDs use evidence-based approaches inconsistently because of a lack of expertise and resources, as well as the lack of availability of evidence-based programs that are adaptable to local contexts. This is the case despite the general interest of LHD leadership in the systematic use of EBDM to inform program design, development, and adoption. 5 Systems science methodologies may provide a logical and cost-effective approach to implementing EBDM at LHDs that face resource constraints. A 2010 report from the Institute of Medicine ( For the Public’s Health: The Role of Measurement in Action and Accountability ) made key recommendations to improve health data analysis and reporting, and proposed that the US Department of Health and Human Services should, coordinate the development and evaluation and advance the use of predictive and system-based simulation models to understand the health consequences of underlying determinants of health. HHS should also use modeling to assess intended and unintended outcomes associated with policy, funding, investment and resource options. 6 (p9) We assessed how systems science methodologies might be useful to bridge resource gaps at LHDs; these gaps impede the implementation of EBDM to solve local population health challenges. Although there are many systems science approaches that can be used to understand complex systems (e.g., network analysis, system dynamics modeling, discrete-event simulation), we focused on agent-based modeling (ABM) because this methodological framework allowed us to evaluate how individuals behave and naturally evolve based on a set of rules that might be more consistent with reality and the way people think about health progression and human and social interactions. ABM is a relatively new modeling approach compared with other systems science methodologies. Examples of its use in public health include studies of epidemics and health behaviors (e.g., drinking and smoking). 7–10 To demonstrate how ABM could be used to embed EBDM in public health practice at the LHD level, we studied the potential effects—in terms of health outcomes over time—of a lifestyle program or intervention in different local populations and compared the results with the natural progression of outcomes for these populations. More specifically, we looked at how LHDs located in 4 areas of New York State could use EBDM, within a systems science model, to help them understand the potential impact of implementing lifestyle interventions targeting cardiovascular disease (CVD) prevention. These model interventions were designed to be consistent with the goals of the state prevention agenda because they relate to conducting activities and developing programs to prevent chronic disease and improve cardiovascular health. 11 LHDs in the state have conducted community health planning and developed improvement plans that are used to track progress toward meeting the health objectives of the Prevention Agenda at the local level. 11 As such, systems science methodologies might prove useful to help LHDs achieve their objectives by incorporating EBDM into their approach.
