The Multi-state Learning Collaborative Storyboards: Quality Improvement Lessons Learned from 162 Projects

The Multi-state Learning Collaborative (MLC) brought health departments in 16 states together with public health system partners to prepare for national voluntary accreditation and to implement quality-improvement (QI) practices. Data from each of the MLC participating states were collected through a comprehensive process over three years. An Excel database of several hundred pages was derived, categorized by individual target area, and organized into thematic domains for further study. Available data were culled and compiled for each MLC project and synthesized across MLC target areas. Two-hundred thirty-four health departments participated in 162 mini-collaboratives in nine of ten target areas. Public health QI projects generally made substantial progress toward achievement of stated objectives. Well-developed aim statements were the lynchpins of successful QI projects. Basic QI tools were utilized consistently and proficiently. Application of best and promising practices was limited. There were no appreciable differences in the QI results according to state public health structure, nor were outcomes related to differences in mini-collaborative leadership. Hundreds of health department staff members were introduced to QI tools and the opportunity to apply them immediately to public health problems

Sharing Local Public Health Services Across Jurisdictions: Comparing Practice in 2012 and 2014

Objective: Describe cross-jurisdiction service sharing (CJS) by local and tribal health departments (LHD) in Wisconsin in 2014 compared to 2012. Design: An online survey of 91 LHD directors in Wisconsin was conducted. Results were compared to the results of a 2012 survey. Characteristics of CJS arrangements and differences in results by population size, geographic region, and governance type were described. Standardized proportion differences (h) were estimated using the arcsin transformation. Confidence intervals were estimated using unconditional exact confidence intervals for the difference of proportions.8 A forest plot of the estimates and confidence intervals was generated to visualize change in CJS for each population category. Results: Seventy-eight percent of respondents in 2014 reported currently sharing services compared to 71% of respondents in 2012. Positive effect sizes indicate increased sharing in year 2014 relative to 2012. CJS was more frequent for LHD serving smaller jurisdictions, consistent with both 2012 survey results and national findings. All governance types continue to engage in sharing public health services. Implications: Cross jurisdictional service sharing is widespread and increasing in Wisconsin, implying that it is a useful strategy for providing public health services under some circumstances. Educating public health practitioners and students about CJS strategies in public health is recommended

Turnover, COVID-19, and Reasons for Leaving and Staying Within Governmental Public Health

Background and Objectives: Public health workforce recruitment and retention continue to challenge public health agencies. This study aims to describe the trends in intention to leave and retire and analyze factors associated with intentions to leave and intentions to stay. Design: Using national-level data from the 2017 and 2021 Public Health Workforce Interests and Needs Surveys, bivariate analyses of intent to leave were conducted using a Rao-Scott adjusted chi-square and multivariate analysis using logistic regression models. Results: In 2021, 20% of employees planned to retire and 30% were considering leaving. In contrast, 23% of employees planned to retire and 28% considered leaving in 2017. The factors associated with intentions to leave included job dissatisfaction, with adjusted odds ratio (AOR) of 3.8 (95% CI, 3.52-4.22) for individuals who were very dissatisfied or dissatisfied. Odds of intending to leave were significantly high for employees with pay dissatisfaction (AOR = 1.83; 95% CI, 1.59-2.11), those younger than 36 years (AOR = 1.58; 95% CI, 1.44-1.73) or 65+ years of age (AOR = 2.80; 95% CI, 2.36-3.33), those with a graduate degree (AOR = 1.14; 95% CI, 1.03-1.26), those hired for COVID-19 response (AOR = 1.74; 95% CI, 1.49-2.03), and for the BIPOC (Black, Indigenous, and people of color) (vs White) staff (AOR = 1.07; 95% CI, 1.01-1.15). The leading reasons for employees\u27 intention to stay included benefits such as retirement, job stability, flexibility (eg, flex hours/telework), and satisfaction with one\u27s supervisor. Conclusions: Given the cost of employee recruitment, training, and retention of competent employees, government public health agencies need to address factors such as job satisfaction, job skill development, and other predictors of employee retention and turnover. Implications: Public health agencies may consider activities for improving retention by prioritizing improvements in the work environment, job and pay satisfaction, and understanding the needs of subgroups of employees such as those in younger and older age groups, those with cultural differences, and those with skills that are highly sought-after by other industries

Centering Communities of Color in the Modernization of a Public Health Survey System: Lessons from Oregon

Context: Public health survey systems are tools for informing public health programming and policy at the national, state, and local levels. Among the challenges states face with these kinds of surveys include concerns about the representativeness of communities of color and lack of community engagement in survey design, analysis, and interpretation of results or dissemination, which raises questions about their integrity and relevance. Approach: Using a data equity framework (rooted in antiracism and intersectionality), the purpose of this project was to describe a formative participatory assessment approach to address challenges in Oregon Behavioral Risk Factor Surveillance System (BRFSS) and Student Health Survey (SHS) data system by centering community partnership and leadership in (1) understanding and interpreting data; (2) identifying strengths, gaps, and limitations of data and methodologies; (3) facilitating community-led data collection on community-identified gaps in the data; and (4) developing recommendations. Results: Project team members’ concerns, observations, and critiques are organized into six themes. Throughout this engagement process, community partners, including members of the project teams, shared a common concern: that these surveys reproduced the assumptions, norms, and methodologies of the dominant (White, individual centered) scientific approach and, in so doing, created further harm by excluding community knowledges and misrepresenting communities of color. Conclusions: Meaningful community leadership is needed for public health survey systems to provide more actionable pathways toward improving population health outcomes. A data equity approach means centering communities of color throughout survey cycles, which can strengthen the scientific integrity and relevance of these data to inform community health efforts

A study of rowing and steering by local health agencies.

A study of rowing and steering by local health agencies

Minimum relevant features to obtain AI explainable system for predicting breast cancer in WDBC

The potential to explain why a machine learning model produces a certain prediction in incomprehensible terms is becoming increasingly crucial, as it provides accountability and confidence in the algorithm's decision-making process. The interpretation of complex models is difficult. Various approaches to dealing with this issue are being offered. These problems are typically handled in tree ensemble methods by assigning priority levels to input features globally or for a specific prediction.  We show that current feature attribution approaches are inconclusive, and develop solutions using SHAP (SHapley Additive Explanation) values, LIME (Local Interpretable Model-Agnostic Explanations), and the Skope Rules package. We employ feature selection methods from SHAP and LIME in this work, which uses the Breast cancer Wisconsin data sets. In the suggested method, features are chosen at the first level of feature selection using Decision tree entropy values. Based on the SHAP and LIME reports, level 2 features are chosen from fewer options. The features are tested on a Decision Tree (DT) model and a DT and Support Vector Machine (SVM) ensemble. Experiments suggest that the ensemble works better as compared to DT. We have also used the Skope Rules package to generate global rules for generalization

Knowing Where Public Health Is Going: Levels and Determinants of Workforce Awareness of National Public Health Trends

Context: Several recent developments are trending in public health, providing an important window into the future of policy and practice in the field. The extent to which public health workforce is aware of these trends has not been assessed. Objective: This research examined the extent to which the public health workforce is familiar with 8 important developments and trends in public health and explored factors associated with variation in awareness levels. Design: This study characterizes an observational cross-sectional design, based on analysis of secondary data collected by the Association of State and Territorial Health Officials through the Public Health Workforce Interests and Needs Survey (PH WINS). Setting: Our study used data from those states for which representative samples for the local health department (LHD) employees were also available. Participants: We included survey responses from employees of state health agencies\u27 central offices and LHDs. Main Outcome Measure: The primary outcome variable for the analysis was the level of awareness about emerging public health trends in the public health workforce. Results: Awareness of emerging trends was lowest for Public Health Systems and Services Research; roughly 1 in 4 employees were aware of this trend. The second least heard of trends were Health in All Policies, and cross-jurisdictional sharing. The public health trends about which the highest proportion of public health employees had heard were implementation of the Patient Protection and Affordable Care Act and evidence-based public health practice. Awareness about public health trends was generally higher among state health agency employees than among LHD employees. Work environment, supervisory status, employee education, and female gender were significantly associated with higher awareness levels for both state health agency and LHD employees. Conclusions: Public health trends that are important for health agencies should be brought to the spotlight in national dialogue in order to increase practitioner involvement in those initiatives

Addressing Psychological, Mental Health and Other Behavioral Health Care Needs of the Underserved Populations in the U.S.: Role of Local Health Departments

Aims: (1) To assess the extent to which local health departments (LHDs) implement and evaluate strategies to target the behavioural healthcare needs for the underserved populations and (2) to identify factors that are associated with these undertakings. Methods: Data for this study were drawn from the 2013 National Profile of Local Health Departments Study conducted by National Association of County and City Health Officials. A total of 505 LHDs completed the Module 2 questionnaire of the Profile Study, in which LHDs were asked whether they implemented strategies and evaluated strategies to target the behavioural healthcare needs of the underserved populations. To assess LHDs’ level of engagement in assuring access to behavioural healthcare services, descriptive statistics were computed, whereas the factors associated with assuring access to these services were examined by using logistic regression analyses. To account for complex survey design, we used SVY routine in Stata 11. Results: Only about 24.9% of LHDs in small jurisdiction ( Conclusions: The extent to which the LHDs implemented or evaluated strategies to target the behavioural healthcare needs of the underserved population varied by geographic regions and jurisdiction types. Different community needs or different state Medicaid programmes may have accounted for these variations. LHDs could play an important role in improving equity in access to care, including behavioural healthcare services in the communities