Objective: To improve the understanding of local health departments' (LHDs') capacity for and perceived barriers to using quantitative/economic modeling information to inform policy and program decisions.
Design: We developed, tested, and deployed a novel survey to examine this topic.
Setting: The study's sample frame included the 200 largest LHDs in terms of size of population served plus all other accredited LHDs (n = 67). The survey was e-mailed to 267 LHDs; respondents completed the survey online using SurveyMonkey.
Participants: Survey instructions requested that the survey be completed from the perspective of the entire health department by LHD's top executive or designate. A total of 63 unique LHDs responded (response rate: 39%).
Main outcome measure(s): Capacity for quantitative and economic modeling was measured in 5 categories (routinely use information from models we create ourselves; routinely use information from models created by others; sometimes use information from models we create ourselves; sometimes use information from models created by others; never use information from modeling). Experience with modeling was measured in 4 categories (very, somewhat, not so, not at all).
Results: Few (9.5%) respondents reported routinely using information from models, and most who did used information from models created by others. By contrast, respondents reported high levels of interest in using models and in gaining training in their use and the communication of model results. The most commonly reported barriers to modeling were funding and technical skills. Nearly all types of training topics listed were of interest.
Conclusions: Across a sample of large and/or accredited LHDs, we found modest levels of use of modeling coupled with strong interest in capacity for modeling and therefore highlight an opportunity for LHD growth and support. Both funding constraints and a lack of knowledge of how to develop and/or use modeling are barriers to desired progress around modeling. Educational or funding opportunities to promote capacity for and use of quantitative and economic modeling may catalyze use of modeling by public health practitioners.