Non-profit Hospital Targeted Health Priorities and Collaboration With Local Health Departments in the First Round Post-ACA: A National Descriptive Study

An action research partnership in an urban Texas county to explore barriers and opportunities for collaborative community health needs assessments

Background

The Affordable Care Act mandated triennial community health needs assessments (CHNAs) for greater nonprofit hospital accountability in responding to community health needs. Over 10 years later, hospital spending on community benefits remains largely unchanged. While greater collaboration in CHNA implementation can increase hospital investment in community-based initiatives, nonprofit hospitals in conservative states are subject to policy, political, and economic factors that inhibit public health partnerships and magnify existing disparities in health care access. This participatory action research study explores the decision-making environment of collaborative CHNA implementation within a group of nonprofit hospitals in a north Texas urban county.

Methods

In 2017 faculty from an urban anchor institution initiated an academic-community partnership with a coalition of nonprofit hospitals, public health departments, and academic institutions. An interdisciplinary research team engaged in multi-method document review and qualitative data collection to describe historical barriers for local CHNA processes and develop practical strategies for joint CHNA initiatives. Local CHNA documents were first reviewed through team-based content analysis and results applied to develop a qualitative study protocol. Key informants were recruited from county-based nonprofit hospitals, community-based nonprofit organizations, and public health systems. Seventeen senior- and mid-level professionals participated in semi-structured research interviews to describe their perspectives relating to CHNA-related planning and implementation decisions. Through iterative data collection and analysis, the research team explored CHNA-related knowledge, experiences, and processes. A constructivist lens was subsequently applied to examine historical barriers and future opportunities for local collaboration.

Results

Findings reveal CHNA implementation is a multi-stage cyclical process in organizational environments with accountability to a wide range of public and private stakeholders. This promotes varied levels of inclusivity and conservatism in data collection and community benefit implementation. Decisions to collaborate are hindered by competing priorities, including compliance with existing guidelines, administrative simplicity, alignment with health care service delivery, and efficient resource use. Efforts to promote greater CHNA collaboration may be facilitated through intentional alignment with organizational priorities and clearly communicated benefits of participation for leaders in both public and private nonprofit health systems.

Discussion

We consider implications for policymakers and health systems in restrictive political environments and advance a conceptual framework for greater CHNA collaboration.

Association between non-profit hospital community benefit spending and health outcomes

OBJECTIVE

To determine if greater non-profit hospital spending for community benefits is associated with better health outcomes in the county where they are located.

DATA SOURCES AND STUDY SETTING

Community benefit data from IRS Form 990/Schedule H was linked to health outcome data from Area Health Resource Files, Map the Meal Gap, and Medicare claims from the Center for Medicare and Medicaid Services at the county level. Counties with at least one non-profit hospital in the United States from 2015 to 2019 (N = 5469 across the 5 years) were included.

STUDY DESIGN

We ran multiple regressions on community benefit expenditures linked with the number of health professionals, food insecurity, and adherence to diabetes and hypertension medication for each county.

DATA COLLECTION

The three outcomes were chosen based on prior studies of community benefit and a recent survey sent to 12 health care executives across four regions of the U.S. Data on community benefit expenditures and health outcomes were aggregated at the county level.

PRINCIPAL FINDINGS

Average hospital community benefit spending in 2019 was $63.6 million per county ($255 per capita). Multivariable regression results did not demonstrate significant associations of total community benefit spending with food insecurity or medication adherence for diabetes. Statistically significant associations with the number of health professionals per 1000 (coefficient, 12.10; SE, 0.32; p < 0.001) and medication adherence for hypertension (marginal effect, 0.27; SE, 0.09; p = 0.003) were identified, but both would require very large increases in community benefit spending to meaningfully improve outcomes.

CONCLUSIONS

Despite varying levels of non-profit hospital community benefit investment across counties, higher community benefit expenditures are not associated with an improvement in the selected health outcomes at the county level. Hospitals can use this information to reassess community benefit strategies, while federal, state, and local governments can use these findings to redefine the measures of community benefit they use to monitor and grant tax exemption.

Using adverse childhood experiences to explore the usefulness of community health needs assessments to monitor complex determinants of health at the local level

BACKGROUND

Hospital led community health needs assessments (CHNAs) are intended to help medical care organizations assess determinants of health within the communities they serve. This study demonstrates the utility of data from non-profit hospital CHNAs to monitor complex health issues such as adverse childhood events (ACEs) at the local-level.

METHODS

CHNA data were collected from August to November 2019 and analyzed July 2021. A series of logistic regressions were used to analyze associations between ACEs, mental health conditions, and self-rated health from a convenience sample of 2831 adults from two regional hospitals that service five counties located in central Appalachia.

RESULTS

ACEs were associated with increased odds of experiencing all metal health conditions after adjusting for other exposures and demographics, including: bipolar disorder (AOR: 2.42, CL: 1.78, 3.30), chronic pain (AOR: 1.61, CL: 1.438, 1.87), depression (AOR: 2.05, CL: 1.76, 2.36), PTSD (AOR: 3.83, CL: 2.95, 4.98), and poor self-rated health (AOR: 1.88, CL: 1.65, 2.15).

CONCLUSION

Findings suggest hospital CHNAs are a useful way to assess local data and should include factors known to antecede disease including associated risks and outcomes. CHNAs may provide an opportunity to fill important gaps in community surveillance and inform local prevention and treatment strategies.

Racial And Ethnic Inequities In Children's Neighborhoods: Evidence From The New Child Opportunity Index 2.0

Neighborhoods influence children's health, so it is important to have measures of children's neighborhood environments. Using the Child Opportunity Index 2.0, a composite metric of the neighborhood conditions that children experience today across the US, we present new evidence of vast geographic and racial/ethnic inequities in neighborhood conditions in the 100 largest metropolitan areas in the US. Child Opportunity Scores range from 20 in Fresno, California, to 83 in Madison, Wisconsin. However, more than 90 percent of the variation in neighborhood opportunity happens within metropolitan areas. In 35 percent of these areas the Child Opportunity Gap (the difference between Child Opportunity Scores in very low- and very high-opportunity neighborhoods) is higher than across the entire national neighborhood distribution. Nationally, the Child Opportunity Score for White children (73) is much higher than for Black (24) and Hispanic (33) children. To improve children's health and well-being, the health sector must move beyond a focus on treating disease or modifying individual behavior to a broader focus on neighborhood conditions. This will require the health sector to both implement place-based interventions and collaborate with other sectors such as housing to execute mobility-based interventions.