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

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. We used the New York Academy of Medicine Cardiovascular Health Sim...

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Bibliographic Details
Published in:American journal of public health (1971) 2015-04, Vol.105 Suppl 2 (S2), p.S217-S222
Main Authors: Li, Yan, Kong, Nan, Lawley, Mark, Weiss, Linda, Pagán, José A
Format: Article
Language:English
Subjects:
Adult
Body mass index
Chronic Disease - prevention & control
Chronic illnesses
Community
Cybernetics
Decision Making
Departments
Design
Diabetes
Diabetic retinopathy
Diet
Disease prevention
Evidence-Based Practice
Exercise
Female
Health Behavior
Health care
Health surveillance
Humans
Lifestyles
Local Government
Local population
Male
Medicine
Middle Aged
Models, Theoretical
New York
Population
Public health
Public Health Practice
Research and Practice
Risk factors
Risk taking
Simulation
Smoking
Stroke
Studies
Surveillance
Systems Analysis
Systems science
Validity
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Summary: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. 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/m(2) or greater. We used survey data from the Behavioral Risk Factor Surveillance System to evaluate health outcomes and validate simulation results. Smoking rates and the proportion of the population with a BMI of 25 kg/m(2) 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). The use of systems science methodologies might be a novel and efficient way to systematically address a number of EBDM adoption barriers at LHDs.
ISSN:0090-0036
1541-0048
DOI:10.2105/AJPH.2014.302077