Utilizing public health core competencies to share data effectively with community organizations to promote health equity

Edmonton's Race-based Data Table: A municipal approach to addressing systemic racism through the collection and use of disaggregated, race-based data

Recent events, such as the COVID-19 pandemic, have drawn nationwide attention to systemic racism as a serious threat to public health in Canada. One promising approach to address such racism is through developing and implementing standardized procedures for collecting and using disaggregated, race-based data. In this commentary, we summarize why this approach is necessary to address systemic racism in Canada, and highlight municipal actions being taken in Edmonton, Alberta, to move this approach forward. In 2021, a Race-based Data Table, comprising 24 institutions and organizations affiliated with health, education, and policing systems, was formed in Edmonton. It aimed to engage practitioners, systems representatives, academics, and community members in collective advocacy around accessing race-based data to better understand and address disparate health outcomes associated with COVID-19 for racialized communities. Further, the Table intends to co-create a charter and toolkit outlining best practices for ethical, race-based data collection and use with local stakeholders and knowledge users. In documenting the beginning stages of the Table, and in evaluating its ongoing progress, we contribute to national conversations regarding the need for government institutions and other organizations to consistently collect and use race-based data as a means of increasing transparency and accountability in their actions.

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

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.

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

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.

Factors related to complex care needs of older adults in community-based integrated care centers in Japan: A cross-sectional study

AIM

This study aimed to identify the factors related to complex care needs of older adults in community-based integrated care centers.

METHODS

We sent 936 self-reported questionnaires to community-based integrated care center directors in the Kinki region of Japan. These questionnaires included questions not only about the directors' demographic data, but also regarding the sociodemographic, psychosocial, and family-related dimensions of the older adults in the community centers. The directors divided their cases into two categories: "Complex cases" and "Straightforward cases." We compared the intergroup differences and examined the factors related to complex care needs in older adults.

RESULTS

A total of 232 directors responded. Complex cases were significantly associated with younger age, poor health conditions, and having a family member who needs care, as compared to straightforward cases where these associations were not present. Logistic regression showed that in older adults, factors of refusing support or social services, social isolation, and trouble with neighbors were associated with their complexities. Additionally, family members with a high likelihood of refusing social services, older adults without a key family member, and difficulties in forming their consensus regarding care were associated with older adults' complexities.

CONCLUSION

Older adults with complex care needs could have the risk of self-neglect, and their families faced difficulties in supporting them as family members. Healthcare professions should carefully assess these factors and develop needs-oriented services for them without their family support as an upstream intervention.

Self-reported competences of public health nurses for developing needs-oriented local healthcare plans: A nationwide cross-sectional survey

AIM

To identify self-reported competencies of public health nurses for reflecting community healthcare needs in local healthcare plans.

DESIGN

We conducted a nationwide cross-sectional survey in Japan from October 7-November 30, 2019.

METHODS

We sent 2,185 self-reported questionnaires to public health nurses in Japan who had developed a local healthcare plan since 2013. Self-reported questionnaires included questions regarding demographic data and the reflection of community healthcare needs in local healthcare plans, and the involvement in local healthcare planning.

RESULTS

We analysed 1,042 questionnaires: 651 (62.5%) were from public health nurses who reported that they elicited and shared community views to be reflected for purposes of local healthcare planning (the reflecting group), and 391 (37.5%) of the remaining public health nurses who reported that they did not do so (the non-reflecting group). The logistic regression analysis revealed that public health nurses in the reflecting group were more likely to be in a managerial position, have colleagues who played an active role in healthcare planning, conduct a questionnaire survey, engage in group work, participate in a municipal healthcare planning committee with community-dwelling people, and identify the opinions of the professional organizations.

CONCLUSIONS

Identifying community healthcare needs through collaboration with community-dwelling people and professional organizations should be essential competencies for public health nurses (the reflecting group) in developing needs-oriented local healthcare plans.

IMPACT

Identification of their related competencies for developing a needs-oriented local healthcare plan as an upstream strategy to mitigate the prevalence of health inequities in each community.