TY - JOUR
T1 - Quantifying the Value of Prevention
T2 - A Survey of Public Health Departments' Quantitative and Economic Modeling Capacity
AU - Mccullough, J. Mac
AU - Narain, Kimberly
AU - Rhoads, Natalie
AU - Fielding, Jonathan E.
AU - Teutsch, Steven M.
AU - Zimmerman, Frederick J.
N1 - Funding Information:
This work was supported by the de Beaumont Foundation, grant number 20164698. This study was granted exempt status by the University of California Los Angeles Institutional Review Board. The authors have no financial disclosures or conflicts of interest to declare. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (http:// www.JPHMP.com).
Publisher Copyright:
© 2018 Wolters Kluwer Health, Inc.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - 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.
AB - 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.
KW - economic modeling
KW - public health practice
KW - quantitative modeling
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U2 - 10.1097/PHH.0000000000000988
DO - 10.1097/PHH.0000000000000988
M3 - Article
C2 - 31136521
AN - SCOPUS:85067271335
SN - 1078-4659
VL - 25
SP - E18-E26
JO - Journal of Public Health Management and Practice
JF - Journal of Public Health Management and Practice
IS - 4
ER -