Evidentiary needs of US public health departments with a mission to advance equity and health: a qualitative analysis

Designing for dissemination among public health and clinical practitioners in the USA

Introduction

The slow adoption of evidence-based interventions reflects gaps in effective dissemination of research evidence. Existing studies examining designing for dissemination (D4D), a process that ensures interventions and implementation strategies consider adopters' contexts, have focused primarily on researchers, with limited perspectives of practitioners. To address these gaps, this study examined D4D practice among public health and clinical practitioners in the USA.

Methods

We conducted a cross-sectional study among public health and primary care practitioners in April to June 2022 (analyzed in July 2022 to December 2022). Both groups were recruited through national-level rosters. The survey was informed by previous D4D studies and pretested using cognitive interviewing.

Results

Among 577 respondents, 45% were public health and 55% primary care practitioners, with an overall survey response rate of 5.5%. The most commonly ranked sources of research evidence were email announcements for public health practitioners (43.7%) and reading academic journals for clinical practitioners (37.9%). Practitioners used research findings to promote health equity (67%) and evaluate programs/services (66%). A higher proportion of clinical compared to public health practitioners strongly agreed/agreed that within their work setting they had adequate financial resources (36% vs. 23%, p < 0.001) and adequate staffing (36% vs. 24%, p = 0.001) to implement research findings. Only 20% of all practitioners reported having a designated individual or team responsible for finding and disseminating research evidence.

Conclusions

Addressing both individual and modifiable barriers, including organizational capacity to access and use research evidence, may better align the efforts of researchers with priorities and resources of practitioners.

Quantifying the Value of Prevention: A Survey of Public Health Departments' Quantitative and Economic Modeling Capacity

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.