Supporting rural public health practice to address local-level social determinants of health across Northwest states: Development of an interactive visualization dashboard

Backonja, Uba; Park, Seungeun; Kurre, Amae; Yudelman, Hayley; Heindel, Sam; Schultz, Melinda; Whitman, Greg; Turner, Anne M.; Marchak, Natasza T.; Bekemeier, Betty

doi:10.1016/j.jbi.2022.104051

Cited by 16 publications

(20 citation statements)

References 53 publications

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“…Similarly, a standardized data reporting system of public health services delivery, developed by Bekemeier, Pui‐Yan Yip, et al (2018) allows US local and state health departments to compare and evaluate their spending against other health departments and better estimate program and prioritize resource allocation. More recently, Backonja et al (2022) and Bekemeier, Park, and Whitman (2019) developed the SHARE‐NW Dashboard which emphasizes SDOH data and a focus on rural LHDs across four Northwest states, to build capacity for DDDM in rural public health systems. Better access to and use of data such as these examples have been found to influence the activities that leaders of LHDs take on, as one study found that the number of information systems implemented in LHDs significantly increased the odds of performing health disparities activities in their jurisdiction (odds ratio [OR] = 1.22, p < 0.01) (Shah, Mase, et al, 2019).…”

Section: Resultsmentioning

confidence: 99%

The DASH model: Data for addressing social determinants of health in local health departments

et al. 2022

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Recent frameworks, models, and reports highlight the critical need to address social determinants of health for achieving health equity in the United States and around the globe. In the United States, data play an important role in better understanding community‐level and population‐level disparities particularly for local health departments. However, data‐driven decision‐making—the use of data for public health activities such as program implementation, policy development, and resource allocation—is often presented theoretically or through case studies in the literature. We sought to develop a preliminary model that identifies the factors that contribute to data‐driven decision‐making in US local health departments and describe relationships between them. Guided by implementation science literature, we examined organizational‐level capacity and individual‐level factors contributing to using data for decision‐making related to social determinants of health and the reduction of county‐level disparities. This model has the potential to improve implementation of public health interventions and programs aimed at upstream structural factors, by elucidating the factors critical to incorporating data in decision‐making.

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Section: Resultsmentioning

confidence: 99%

The DASH model: Data for addressing social determinants of health in local health departments

et al. 2022

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“…Innovations such as dashboards and surveillance efforts that have increased data availability have recently offered opportunity to improve SDOH decision making in LHDs 15,32,47. Designing training that thoughtfully combines these skills could make implementation of data dashboards that have SDOH and health outcome data more effective 15,48…”

Section: Discussionmentioning

confidence: 99%

Grouping Public Health Skills to Facilitate Workforce Development: A Factor Analysis of PH WINS

Petrovskis

Bekemeier

Draanen

et al. 2022

Journal of Public Health Management and Practice

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Objectives: This study examined whether distinct factors exist among public health skills, measured through the Public Health Workforce Interests and Needs Survey (PH WINS). Understanding how workforce training needs group is important for developing targeted and appropriate public health workforce training sessions. Design: Exploratory factor analysis was used to examine public health skills among tier 1 staff (nonmanagers) and a combined group of tier 2 and 3 staff (managers and executives). Setting: Data for this study come from the 2017 PH WINS, which assessed public health workforce perceptions of training needs, workplace environment, job satisfaction, perceptions about national trends, and demographics. The analysis included 22 items. Participants: All public health staff in participating agencies were eligible to complete the survey. The national data set included participants from 47 state health agencies, 26 large local health departments (LHDs), and 71 mid-sized LHDs across all 10 Health and Human Services regions in the United States (including LHDs from all states). The analytic sample was n = 9630 in tier 1, n = 4829 in tier 2, and n = 714 in tier 3 staff. Main Outcome Measure: Three factors were identified within the skills portion of PH WINS, using exploratory factor analysis. To interpret retained factors, the following parameters were used: factor loadings greater than 0.4, factor cross-loadings less than 0.4 or higher than loadings on other factors, and communalities greater than 0.5. Results: Factors included (1) data and systems thinking, (2) planning and management, and (3) community collaboration, with slight variation in item loadings between tier 1 and tier 2 and 3 staff analyses. Conclusion: This study was the first known factor analysis of the training needs and workforce skills portion of PH WINS in the published literature. This study advances our conceptualization of public health workforce skills and has the potential to shape future critical workforce training development.

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“…Given this mix of interest in the data, along with barriers to participation, we strongly recommend that UCOA data providers (ie, local and state health departments) be assured easy access to and use of the data that they and their peers provide. This should include user-centered visualization features that support meaningful data-driven decision-making 18. Such accessibility would also support improved financial management practices among practitioners—an area of high need for improved public health workforce competencies and related tools 24…”

Section: Discussionmentioning

confidence: 99%

“…This should include user-centered visualization features that support meaningful data-driven decision-making. 18 Such accessibility would also support improved financial management practices among practitioners-an area of high need for improved public health workforce competencies and related tools. 24…”

Section: Ensure Data Accessibility and Usability For Those Providing ...mentioning

confidence: 99%

A Uniform Chart of Accounts: Strengthening Public Health Practice and Research Through Standardized Financial Data

Bekemeier

Heitkemper²,

Zaichkin³

et al. 2022

Journal of Public Health Management and Practice

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Context:The COVID-19 pandemic made the long-standing need for a national uniform financial reporting standard for governmental public health agencies clear, as little information was available to quantify state and local public health agencies' financial needs during the pandemic response. Such a uniform system would also inform resource allocation to underresourced communities and for specific services, while filling other gaps in practice, research, and policy making. This article describes lessons learned and recommendations for ensuring broad adoption of a national Uniform Chart of Accounts (UCOA) for public health departments. Program: Leveraging previous efforts, the UCOA for public health systems was developed through collaboration with public health leaders. The UCOA allows state and local public health agencies to report spending on activities and funding sources, along with practice-defined program areas and capabilities. Implementation: To date, 78 jurisdictions have utilized the UCOA to crosswalk financial information at the program level, enabling comparisons with peers. Evaluation: Jurisdictions participating in the UCOA report perceptions of substantial up-front time investment to crosswalk their charts of accounts to the UCOA standard but derive a sense of valuable potential for benchmarking against peers, ability to engage in resource allocation, use of data for accountability, and general net positive value of engagement with the UCOA. Implications for Policy and Practice:The UCOA is considered a need among practice partners. Implementing the UCOA at scale will require government involvement, a reporting requirement and/or incentives, technical assistance, financial support for agencies to participate, and a means of visualizing the data.

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Supporting rural public health practice to address local-level social determinants of health across Northwest states: Development of an interactive visualization dashboard

Cited by 16 publications

References 53 publications

The DASH model: Data for addressing social determinants of health in local health departments

The DASH model: Data for addressing social determinants of health in local health departments

Grouping Public Health Skills to Facilitate Workforce Development: A Factor Analysis of PH WINS

A Uniform Chart of Accounts: Strengthening Public Health Practice and Research Through Standardized Financial Data

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