New Prescriptions? Nonprofit Hospital and Health System Charitable Spending on Housing as a Social Determinant of Health
by Carl Hedman
B.A. Economics Reed College, 2013
SUBMITTED TO THE DEPARTMENT OF URBAN STUDIES AND PLANNING IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER IN CITY PLANNING AT THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY
MAY 2020
©2020 Carl Hedman. All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created.
Signature of Author:______Department of Urban Studies and Planning May 19, 2020
Certified by:______Justin Steil Associate Professor of Law and Urban Planning Department of Urban Studies and Planning
Accepted by:______Ceasar McDowell Professor of the Practice Chair, MCP Committee Thesis Supervisor Department of Urban Studies and Planning
2 New Prescriptions? Nonprofit Hospital and Health System Charitable Spending on Housing as a Social Determinant of Health
by Carl Hedman
Submitted to the Department of Urban Studies and Planning on May 19, 2020 in Partial Fulfillment of the Requirements for the Degree of Master in City Planning
ABSTRACT
There is an emerging consensus that socioeconomic, environmental, and structural factors—known as the social determinants of health (SDOH)—are stronger drivers of health outcomes than genetics or clinical care. In particular, health researchers have elevated housing stability, quality, and affordability as critical SDOH. As focus in public health shifts towards addressing SDOH, attention has turned to the role of hospitals—particularly those with nonprofit status—in improving local housing conditions. To maintain federal tax exemption, nonprofit hospitals and health systems must annually report charitable practices, known as “community benefits,” to the Internal Revenue Service (IRS). Recent changes in IRS reporting requirements, coinciding with federal and state healthcare overhauls, encourage hospitals to make local charitable investments to address SDOH, including housing.
Following the regulatory changes and increased recognition of the SDOH, this thesis has two primary aims. First, utilizing processed IRS Form 990 Schedule H annual hospital filings from 2010-2017, I conduct a descriptive analysis to assess geographic and temporal variations in charitable practices across the United States. Second, relying on demographic data summarized at the ZIP Code level, I employ regression techniques to analyze whether the socioeconomic characteristics of an institution’s immediate vicinity explain variations in charitable spending on housing and other SDOH activities.
I do not find evidence of widespread shifts in community benefit practices to address SDOH. These expenses were minimal and declined relative to other charitable practices from 2010-2017. Results indicate that local characteristics do explain differences in charitable spending: institutions located in communities with higher poverty and less affordable housing options are more likely to report spending on housing and other SDOH activities. However, stronger unobserved factors are likely driving variations in this spending. These findings suggest limitations of the current community benefits standard for increasing charitable expenditures on housing and other SDOH activities.
Thesis Supervisor: Justin Steil Title: Associate Professor of Law and Urban Planning
3 Acknowledgements
This work would not be possible without the dedication and generous guidance of my advisor, Justin Steil, who remained steadfast in his commitment to this project throughout a semester defined by unprecedented challenges and, thankfully, glimmers of hope. Welcome to the world, Camilo!
I want to extend my sincerest gratitude to my reader, Megan Sandel, whose comments and wisdom were instrumental in shaping this thesis. Your commitment to bridging housing and health justice remains a continuing source of inspiration.
Thank you to Dr. Thea James, Alyia Gaskins, Eva Allen, Casey Brock, and Dr. Giridhar Mallya for generously offering your time and insights to help inform this research.
I am deeply indebted to Jessica Boatright for her unwavering mentorship, support, and encouragement this last year. Thank you, Jessica, Chris, Gail and the rest of the NHD family, for making DND feel like a second home.
Dina, thank you for the late-night edits, the Polar, the ragù, the support, the Hulu, and, generally, for helping me stay sane these last few months.
Thank you to my DUSP family for the conversations after class, the late nights in CRON, the Friday hangs, and, more recently, the Zoom backgrounds. I have learned and grown so much these past two years. I can’t wait to see you all again IRL.
Finally, thank you to my family—Mom, Dad, and Ian—for your unwavering love and support throughout the years. None of this would have been possible without you.
4 Table of Contents
1. Executive Summary ...... 7 2. Health, Housing, and Hospital Investment ...... 11 2.1 The Social and Structural Determinants of Health ...... 11 2.2 Health and Housing...... 12 2.3 Hospital Investment in Housing ...... 14 2.4 Motivations, Barriers, and Support ...... 17 2.5 Conclusion ...... 20 3. Hospital Ownership, Taxes and Community Benefits ...... 21 3.1 Hospital Ownership ...... 21 3.2 Federal Tax Exemption and Community Benefits ...... 23 3.3 ACA, CHNA and CHIP ...... 31 3.4 State and Local Tax Exemption ...... 33 3.5 Community Benefit and Community Building Activities Analysis ...... 36 3.6 Conclusion ...... 37 4. Data description ...... 38 4.1 IRS Form 990 and Schedule H ...... 38 4.2 American Community Survey Data ...... 42 4.3 State Hospital Regulations ...... 43 4.4 Rural-Urban Continuum Classification ...... 43 5. Analysis: Spatial and Temporal Descriptive Results ...... 45 5.1 Revenue and Profit ...... 45 5.2 Community Benefits ...... 46 5.3 Community Building Activities ...... 49 5.4 Community Building Activities: Physical Improvements and Housing ...... 55 6. Analysis: Community Characteristics and Chartable Spending ...... 60 6.1 Analysis Approach ...... 60 6.2 Decile Analysis ...... 61 6.3 Linear Regression ...... 66 7. Discussion ...... 74 7.1 Community Benefit and Community Building Activity Spending Trends ...... 74
5 7.2 Spatial Characteristics and Charitable Spending ...... 76 7.3 Limitations and Future Research ...... 80 7.4 Implications and Recommendations ...... 81 8. Conclusion ...... 84 9. Appendix ...... 86 10. Work Cited ...... 89
6 1. Executive Summary
Over the past 25 years, public health and clinical researchers have generated a substantial body of evidence demonstrating that the conditions where people live, learn, work, grow, and age impact a wide range of health risks and outcomes (Braveman and Gottlieb 2014). There is an emerging consensus that socioeconomic, environmental, and structural factors are stronger drivers of health outcomes than genetics or clinical care. These factors have dramatic and tragic implications: in Boston, Massachusetts the average life expectancy at birth for a resident of the Roxbury neighborhood, 59 years, is two and a half decades shorter than a resident of the adjacent more-affluent South End, 84 years (Zimmerman et al. 2012). This research has prompted an increased shift in healthcare focus from acute clinical care to a framework that addresses the “social determinants of health” (SDOH), which include institutionalized racism, economic stability, housing, neighborhood and physical environment, education, food, community and social context, and healthcare access. Housing has emerged as a critical SDOH, with studies evaluating the role of stable, decent, and affordable housing in affecting a variety of mental and physical health outcomes (Sandel and Desmond 2017; Viveiros, Ault, and Maqbool 2015). In addition to the direct health impact, research in public health and health policy have documented the cost implications of housing insecurity on hospitals and public insurance systems, providing evidence of cost savings associated with funding for rapid rehousing and supportive housing programs (Rosenbaum et al. 2015; Cunningham and Batko 2018). The evidence is emerging as communities across the United States are experiencing an escalating housing affordability crisis and declining or stagnant federal support for affordable rental housing (Marcuse and Madden 2016). The growing consensus on the SDOH and the pressures of the housing crisis has brought attention to the role of nonprofit hospitals and health systems—both as healthcare providers and as “anchor institutions” with political and economic capital—in addressing housing quality and instability. Nonprofit hospitals and health systems, which account for a majority of community hospitals in the United States, are heterogenous institutions that vary in size, mission, capacity, and affiliations. However, these institutions share a common federal regulatory framework as tax- exempt entities monitored by the Internal Revenue Service (IRS). Tax exemption offers nonprofit
7 hospitals and health systems significant financial relief (the value of nonprofit hospital tax exemption was estimated to be $24.6 billion per year in 2011), but also subjects their practices and management to additional public scrutiny as federally designated charitable institutions (Rosenbaum et al. 2015). To maintain federal tax exemption, nonprofit hospitals and health systems must annually report organizational financial information and charitable practices, known as “community benefits,” to IRS through a Form 990 tax filing. While eligible community benefits were originally limited to free or reduced patient care for those unable to pay for treatment (i.e., “charity care”) or other specified activities pertinent to patient services and research, advocates and industry representatives lobbied the IRS to recognize external spending targeting SDOH as a charitable practice eligible under the community benefit standard. Beginning in 2009, the IRS implemented a new community benefits reporting standard (captured through the supplemental IRS form “Schedule H”) that allows nonprofit hospitals and health systems to declare external community health improvement services and community building activities designed to address SDOH as charitable expenses. This IRS regulatory change coincided with the implementation of the Affordable Care Act, which included a requirement for nonprofit hospitals and health systems to conduct a Community Health Needs Assessment (CHNA) and target community benefit spending to address identified needs. Over the last decade, there has been a series of well-documented nonprofit hospital investments in local activities designed to improve housing quality and reduce residential instability. Additionally, there is limited, but growing, professional literature that provides guidance on how hospitals should approach community benefits spending on housing. This literature details what kinds of housing activities satisfy new community benefits requirements and how hospital investments can have the greatest impact in the housing space. Based on the reporting and advocacy, there appears to be an emerging trend of hospitals committing to housing investments. Following the regulatory changes, increased recognition of the SDOH, and advocacy, this thesis seeks to answer two primary question. First, what are the spatial patterns and temporal variations of nonprofit hospitals’ and health systems’ charitable practices across the United States?
8 Second, how do the socioeconomic characteristics of an institution’s immediate vicinity explain variations in charitable spending on housing and other SDOH activities? To address these questions, I relied on two primary analysis methods. The first is a descriptive analysis of national temporal trends and geographic patterns of nonprofit hospital and health system charitable practices across the United States. This analysis utilizes a processed dataset of IRS Form 990 Schedule H annual hospital tax filing records in United States between 2010 and 2017. The second employs linear regression techniques to 1) analyze how the socioeconomic characteristics of an institution’s immediate vicinity affect the likelihood of a hospital or health system reporting spending on community building activities, as a measurement of SDOH activities, and physical improvements and housing expenses, as a measurement of housing specific activities; and 2) how these local socioeconomic characteristics affect the amount of spending on community building activities and physical improvements and housing. The regression models include additional explanatory variables to control for variations in state policy, metropolitan context, and hospital profitability. This analysis relies on IRS Form 990 Schedule H annual hospital tax filing summarized at the hospital level between 2010 and 2017, 2013-17 American Community Survey data summarized at the ZIP Code level, state regulatory policy governing community benefits spending, and county-level data on urbanization and development (e.g., rural or large metropolitan area). Consistent with earlier research, this thesis does not find evidence of widespread shifts in nonprofit hospital community benefit practices to address SDOH from 2010 to 2017. While total community benefit expenses increased over the period, it appears that the growth in spending was largely driven by increases in direct patient financial assistance for treatment and reimbursements for means-tested government programs. These expenditures increased by $12 billion over the period and became a more dominant share of hospital community benefit expenditures. Reported expenditures on practices designed to address SDOH (i.e., community building activities) and housing activities (i.e., physical improvements and housing expenses) were minimal—less than 1 percent of community benefits spending—and declined both in total aggregate dollars and as a share of spending normalized to hospital revenue over the period.
9 The analysis of how an institution’s immediate context influences charitable spending produced mixed results. Results indicate that local characteristics do explain differences in the likelihood and amount of charitable spending reported by hospitals and health systems over the period. Specifically, institutions located in communities with higher poverty rate and less affordable housing options are more likely to report spending community benefit activities and community benefit activities related to housing. However, among those who do report community building activities and activities related to housing, these same explanatory variables have the opposite directional impact on the proportion of spending (e.g., for hospitals that report spending on community building activities, the amount of spending is lower in communities with higher poverty rates than those located in communities with lower poverty rates). However, the explanatory strength of both models is low, suggesting that unobserved factors are likely driving most of the variation in this spending. Despite the regulatory changes and growing research on the SDOH, the findings indicate that hospitals and health systems have not, by-in-large, reoriented charitable practices to address housing and other upstream community health interventions. These results speak to the limitations of relying on the current community benefits standard alone to increase hospital and health system spending on activities designed to address SDOH. However, despite the limitations, the regression analysis offers early evidence that hospitals’ and health systems’ charitable expenditures on housing and other SDOH activities are not random and are, at least partially, shaped by the local socioeconomic factors. When complemented with the CHNA process, the standard recognizes and supports hospitals and health systems engaging in innovative activities designed to improve community health and combat disparities. As pressure builds for a reorientation of the healthcare sector from a fee-for-service model towards a value-based care framework focused on population health, the community benefits standard and CHNA have the potential to be critical complementary tools in directing activities to address the social and structural factors that perpetuate health disparities.
10 2. Health, Housing, and Hospital Investment
2.1 The Social and Structural Determinants of Health
There is an emerging consensus that socioeconomic and structural factors—more than genetics or clinical care—drive health outcomes. Researcher have found that only 10 to 20 percent of the variations in health outcomes can be attributed to factors associated with clinical care. The remaining 80 to 90 percent of determinant factors affecting health outcomes are attributable to health behaviors and socioeconomic conditions (Hood et al. 2015). While there is no current consensus on the relative share of health outcomes that can directly be attributed to health behavior or socioeconomic conditions—as many socioeconomic or structural factors can influence health behaviors (e.g., smoking, diet, and exercise)—recent research suggests that up to 50 percent of health outcomes can be attributed to socioeconomic conditions (Sandel and Desmond 2017; Artiga and Hinton 2018). These factors, referred to as the “social determinants of health” (SDOH), include economic stability, housing, neighborhood and physical environment, education, food, community and social context, and healthcare system access. The evidence has placed heighted pressures on the public health field to address nonmedical factors as a critical means of improving individual and population health. As the understanding of SDOH evolves, there is a growing demand for research to evaluate the efficacy of interventions designed to address SDOH and to assess their cost implications. Generally, these interventions are framed as “upstream” investments or programs designed to address specific socioeconomic conditions that will result in improved “downstream” health outcomes (Artiga and Hinton 2018). The shifting focus from health service as the primarily driver to a broader socioeconomic and, in some cases, structural lens requires a significant reorientation for healthcare institutions and policymakers. There is a growing number of federal and state policy initiatives aimed at incentivizing and encouraging healthcare providers—particularly through Medicaid delivery system and payment reform initiatives—to invest in activities aimed at addressing SDOH (Artiga and Hinton 2018). These initiatives tie into the broader prospective transformation in the paradigm of healthcare in the United States from a fee-for-service model towards a value-based
11 care framework that focuses on population health. The perceptions around this looming shift create additional financial incentives for hospitals and health systems to address these upstream factors (Burrill and Thomas 2017).
2.2 Health and Housing
There is a growing body of SDOH research documenting the importance of stable, decent, and affordable housing on a wide range of mental and physical health outcomes (Sandel and Desmond 2017; Viveiros, Ault, and Maqbool 2015). Research evaluating housing as a health determinant broadly falls into four categories: stability, quality, affordability, and location (Taylor 2018). Fletcher, Andreyeva, and Busch (2009) find that increases in rental housing costs are associated with increases in food insecurity among low-income families with children. Families that are severely burdened by housing costs (paying over 50 percent of income on rent) spend less on food and healthcare than families spending 30 percent or less of their income on rent (Joint Center for Housing Studies 2014). Pollack, Griffin, and Lynch (2010) report that compared to people living in affordable housing, people in unaffordable housing situations were more likely to: not adhere to health treatment plans and avoid filling prescriptions due to issues of cost; have higher rates of certain chronic health conditions; and have lower self-reported health assessments. Another substantive body of research is focused on the role of housing quality on an individual’s health, with research documenting the impact of poor housing quality on a resident’s exposure to lead, asthma rates, and accidental injury rates (Braubach and Fairburn 2010). In addition to shelter, a home ties a person to a neighborhood. The patterns of residential segregation, environmental racism, transit access, and disinvestment produce neighborhoods of varying environmental quality, investment, and economic opportunity that are highly stratified by race and income. Research has documented a range of positive mental and physical health outcomes associated with improvements to a neighborhood’s physical environment—including access to parks and green space, walkability and recreation access, and blight reduction—and, conversely, negative health outcomes associated with proximity to environmental contamination sites and chronic pollution sources, such as high-volume roads (Taylor 2018). Additionally, researchers have emphasized racial segregation’s complex health implications. A 2009 assessment
12 of the literature found that acute residential segregation is associated with poor pregnancy outcomes and increased mortality for African Americans. This same report, however, cites several studies documenting the health-protective effects of living in clustered African American neighborhoods net of social and economic isolation (Kramer and Hogue 2009). Increased attention is turning to the impact of acute residential instability—particularly chronic homelessness—on health outcomes for adults and children. In the United States, people who experience chronic homelessness are three to six times more likely to become ill; have four times higher rates of hospitalization; and are three to four times more likely to die at a younger age compared with the national average (Maness and Khan 2014). Cutts et al. (2011) document that housing insecurity is associated with poorer health, lower weight, and increased developmental risk among children three to seven years old. In a summary of literature on the topic, Kyle and Dunn (2008) identify that homeless children are more vulnerable to mental health issues and suggest that lasting housing stability is strongly associated with improvements in mental health outcomes. Within public health and policy research, there is evidence documenting the significant treatment costs associated with providing health services to individuals who experience chronic homelessness. One study estimating that the top five percent of hospital users—overwhelmingly poor and housing insecure—account for 50 percent of healthcare spending (Blumenthal and Abrams 2016). Culhane, Metraux, and Hadley (2002) find that persons placed in supportive housing experienced reductions in: shelter use, hospitalizations, length of stay per hospitalization, and time incarcerated and also point to how offering supportive housing to these individuals was associated with a net cost saving of $995 per individual per year. Additionally, recent evidence has suggested that rapid rehousing and Housing First programs may be an effective way to reduce homelessness and costs across a range of public services (Cunningham and Batko 2018). (Brown, Bains, and Escobar's (2018) assessment of Better Health Through Housing, a program run in partnership between the University of Illinois Chicago Hospital and the Chicago Center for Housing and Health to provide rental assistance for people in need permanent supportive housing, found that the intervention reduced overall healthcare costs by 21 percent and
13 emergency department utilization rates by 57 percent for program participants over the course of the study. 2.3 Hospital Investment in Housing
There is increased attention to the role of hospitals and health systems—as both medical care facilities and “anchor institutions” imbedded in communities with economic and political power—in improving residential stability and housing quality for their patient base. Over the last decade, there have been a handful of well-documented investments made by hospitals and health systems to address the housing-related needs of their local community. These investments ranged from direct rental assistance, funding for supportive housing services, legal aid, grants for new affordable housing construction, rapid rehousing programs, repair grants to improve home conditions, donation of surplus property for affordable housing development, and more (Reynolds et al. 2019; Enterprise Community Partners 2018). The scale of investments, the target populations, partnerships and practitioner organizations, and the timelines vary significantly by activity type and community housing need. For example, a hospital located in a high-cost city may prioritize capital grants to help facilitate the development of affordable housing, while a hospital located in a disinvested community experiencing population decline may support home repair programs designed to address blight and housing quality concerns. Figure 2.1 provides a table of various actions and programs hospitals and health systems have funded to address issues related community housing needs. The actions are divided into the following categories: production and preservation; medical, legal, and supportive services; cash assistance; home quality repairs and goods; and policy, advocacy, and research. The table is not a comprehensive list of activities that hospitals can or have supported, but is intended to represent the range in activities hospitals and health systems are participating in. The following section presents two brief cases that profile nonprofit hospital-led housing investment efforts.
14 Figure 2.1: Documented Hospital- or Health System-Sponsored Housing Activity Medical, legal, Home quality Policy, Production and and supportive repairs and advocacy, and preservation services Cash assistance goods research • “Gap • Funding for • Direct rental • Home repair • Grants for financing” on-site assistance grants to tenant (grants and supportive • Emergency increase advocacy low interest service cash accessibility organizations loans) to coordinators assistance and support • Research on support • Medical for families residents health and affordable respite facing aging in housing housing programs for eviction place initiatives development homeless • Lead paint • Political and rehab individuals abatement advocacy for • Operating • Support for programs renter subsidies to on-site • Home protection stabilize medical care repairs to and stability affordable providers Asthma legislation housing • Legal aid prevention properties services • Unit • Operations • Hospital- improvement grants for staffed grants for affordable service and public housing housing housing developers coordinators agencies • Land donation Sources: Author’s review of literature
Columbus, Ohio
The Healthy Neighborhoods Healthy Family (HNHF) initiative—launched by the large nonprofit pediatric research hospital Nationwide Children’s Hospital—is a broad place-based program targeting the hospital’s immediate community of South Side Columbus, Ohio. HNHF is a partnership between Nationwide Children’s Hospital and Community Development for All People, a faith-based community development corporation based in the South Side. The initiative
15 was launched in 2008, at a time when the neighborhood—which has long struggled with high unemployment, poverty rates, and vacancy—was experiencing an acute foreclosure crisis and heightened job loss spurred by the Great Recession (Scally, Waxman, and Gourevitch 2017). The hospital was also undergoing a significant expansion during this period and faced pressure from city officials and local residents to direct community investments to the South Side. Rather than focus on a specific population of need (e.g., children, homeless individuals, elderly), the initiative adopts a wholistic strategy that focuses on affordable housing, education, health and wellness, safe and accessible neighborhoods, and workforce development. The largest component of the strategy is housing. HNHF provides homeowners with small grants for home renovation and operates a development program that purchases abandon homes and vacant lots in the South Side for renovation as affordable homeownership and rental opportunities. The initiative was founded through an initial $3-5 million 3-year grant by Nationwide Children’s Hospital. Since the program’s launch, the hospital has increased program funding and attracted a variety of public and private investors to support and expand program activity. Over the last decade, the initiative has invested over $30 million in the improvement of nearly 300 homes and, through other housing partnerships and initiatives, attracted nearly $80 million in housing investments in South Side (Edgar 2018; Nationwide Children’s Hospital 2018). HNHF has been widely hailed as a success and model for placed-based hospital investment in housing. However, there are growing concerns around gentrification and displacement in the South Side, which has caused the initiative to partially reorient its focus towards preservation and stabilization activities (Edgar 2018).
Boston, Massachusetts
In 2017, Boston Medical Center (BMC)—a nonprofit safety net hospital located in central Boston, Massachusetts—announced a five-year $6.5 million investment in affordable housing and stabilization programs. Rather than commit to one specific housing intervention or population, the fund supports a range of activities, including $800,000 to create permanent supportive housing for individuals with mental illness or ambulatory disabilities, $1 million towards a partnership with a homeless service and shelter provide to create a stabilization program for
16 medically complex individuals, $1 million towards a stabilization fund to support renters facing eviction, and nearly $1 million in funding for on-site service coordinators (BMC 2017). While the action steps are diverse, a core focus of the fund is preventing family homelessness and providing shelter and supportive services to those who experience chronic homelessness. Approximately 25 percent of the patients admitted to BMC are homeless and BMC is under tremendous financial pressure to reduce readmissions from rates, particularly among its chronical homeless patients (BMC 2018). In 2019, BMC, along with the two prominent Boston-based nonprofit hospitals Brigham and Women’s Hospital and Boston Children’s Hospital, launched the Innovative Stable Housing Initiative (ISHI). The $3 million initiative targets resident housing instability: offering emergency grants for families facing eviction and grants to support policy and systems change to promote housing affordability and stability. The financial contribution for ISHI is structured to satisfy each hospital’s Determination of Need requirements—a unique Massachusetts program that, in addition to other regulatory requirements, mandates that nonprofit hospitals and health systems in the state who are undergoing expansion or large capital investment projects to contribute at least 5 percent of total capital expenditures on population health initiatives (Ropes & Gray 2016; Massachusetts Department of Public Health 2020). Unlike federal community benefit requirements, which are ongoing charitable contributions that nonprofit hospitals are required to track and report annually (detailed in Chapter 3), these expenditures are one-time payments that correspond to a hospital’s capital projects. For BMC, these two initiatives represent the first time that a Massachusetts hospital dedicate all Determination of Need spending on housing programs (BMC 2018).
2.4 Motivations, Barriers, and Support
What are the motivations driving hospitals to make these investments in housing and other upstream factor to address the social determinants of health? Are they spurred by shifts in research on SDOH, changing federal and state regulatory requirements, community relations and concerns around the hospital’s image, fulfillment of hospital mission, pressure from local political forces, or as a means to drive down patient treatment costs? While the answer is likely a
17 combination of multiple factors and certainly varies by hospital or health system—as well as among staff within a hospital or health system—there is emerging research seeking to understand these motivations and barriers to hospitals making investments in housing and other SDOH. Researchers at the Urban Institute conducted a survey of 45 nonprofit hospital administrators to understand the prevalence of housing-related community benefit initiative, organizational motivations, and interests in particular housing strategies. Their study found that while hospital respondents were generally aware of the local housing needs and the importance of housing as a platform for addressing social determinants of health, there was concern about the time and resources associated with housing programs and limited understanding about the housing development process and what funding would be most effective. Among study participants, the authors found that vast majority identified reducing unnecessary hospitalizations and emergency room visits as their primary motivation for housing investments. Their research found that hospitals who make commitments to housing initiatives are more likely to do so in the form of collocating supportive services in housing, medical respite programs, and policy advocacy rather than direct financial investment in housing. Those that did invest often did so through a financial intermediary (e.g., community development financial institution). Most reported hospital invested were modest, with a third reporting less than $250,000 invested in one or two development projects (Reynolds et al. 2019). Hacke and Deane (2017) led an in-depth qualitative study of 12 hospitals and health systems currently making investments in affordable housing and other community development efforts to understand their practices, motivations, and experience with the investments. Their study revealed a range of motivations that differed across institutions—and, in some cases, differed among staff within an institution—but were not necessarily conflicting. For some respondents, particularly those from religious-affiliated institutions, the investments decisions were seen as a means of advancing their mission to improve community health. Other respondents cited a sense of “shared fate” between the hospital and their surrounding community. These respondents saw revitalization efforts as a way to not only address SDOH, but improve the institution’s image, attract patients, recruit staff, and increase property values for the institution. For some, there was a sense of strategic imperative as hospitals and health systems were looking
18 to address SDOH in preparation for a projected change in federal or state regulatory environment that prioritized paying for wellness rather than volume of procedures. Many referenced an interest in quantifying the cost saving related to upstream investments targeting SDOH, although few respondents had an evaluation system in place to measure impact (Hacke and Deane 2017). When making these investments, hospital and health systems enter into an often well- established and sophisticated housing landscape of advocates, government official, developers, practitioners, financing institutions, and local community organizations. Navigating these arrangements, potential legal and regulatory barriers, and understanding where their spending would be the most impactful can be daunting for these institutions. Over the last three years, national nonprofit research, advocacy and trade organizations—including the American Hospital Association (2017), Enterprise Community Partners (2018), The Catholic Health Association (2018), and The Urban Institute (2019)—have released guidance to support hospital and health systems invest in affordable housing (American Hospital Association 2017; Enterprise Community Partners 2018; Ayala and Trocchio 2018; Reynolds et al. 2019). Broadly, these reports appear targeted at a hospital administrator and housing practitioner audience, commonly including a description of successful hospital housing investment cases, detailed explanation of regulatory requirements, share lessons for the field, and strategies for building local partnerships. In 2018, the Center for Community Investment, with funding from the Robert Wood Johnson Foundation, launched the Accelerating Investments for Healthy Communities initiative, a two-phased strategy which aims to increase health system investment in SDOH, particularly affordable housing. A core focus of the initiative is to support hospitals utilizing their exist assets (e.g., financial resources, land, expertise, and political capital) to invest in affordable housing and other community development efforts. Eight health systems, including BMC and Nationwide Children’s Hospital, participated in phase one of the program. This phase prioritized connecting staff within a participating hospital or health system to understand institutional goals, the local community investment landscape, potential partnership, and where their capital investment could be most effectively leveraged. In 2019, six health systems continued on to phase two of the initiative, which expanded the initiative to include local government officials, affordable housing developers, community groups representatives, and local financial intermediaries. The goal of the
19 second phase is to support the participants in developing and executing an affordable housing investment pipeline (Center for Community Investment 2019).
2.5 Conclusion
The nonprofit advocacy, research, and press attention surrounding hospital spending on housing activities point to the potential for a nationwide trend. However, without systemic analysis, it remains unclear whether these signals reflect a broader shift in spending by hospitals and health systems on housing to address SDOH. While the hospitals and health systems that engage in housing activities differ in location, size, and institutional affiliation, they largely share a common organizational characteristic: nonprofit ownership. Nonprofit status offers hospitals and health systems federal and state tax exemption, but subjects these institutions to additional regulatory restrictions and oversight. As detailed in the next chapter, recent regulatory changes related to nonprofit hospitals’ and health systems’ charitable practices create conditions favorable to increased spending on housing and other SDOH.
20 3. Hospital Ownership, Taxes and Community Benefits
3.1 Hospital Ownership
In the United States, ownership of community hospitals—defined as nonfederal short- term hospitals—largely falls into three classifications: private, for-profit hospitals that operate in a similar manor private corporations with are shareholders and investors; public hospitals that are owned by state or local governments and have a mandate to treat underserved populations; and private, nonprofit hospitals, which are tax-exempt institutions that are obligated to operate as a charitable entity in order to retain their tax status. Nationally, 57 percent of hospitals are owned and managed by nonprofit organization, 25 percent are for-profit, and 19 percent are state and local government managed (Kaiser Family Foundation 2020). Over the last two decades, the national share of hospitals owned by nonprofit organizations has declined modestly, falling from 61 percent of community hospitals in 1999 to 57 percent in 2018 (Figure 3.1). Similarly, the share of hospitals owned by a state or local government fell from 24 percent in 1999 to 19 percent in 2018. Much of this change has been driven by a growth in for-profit hospitals, which increased in facilities from 747 in 1999 to 1,296 in 2018 (the share grew from 15 percent to 25 percent over the period).
21 Figure 3.1: Hospital Ownership in the United States, 1999-2018 3,500
3,000
2,500
2,000
1,500
1,000
500
-
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
State/Local Government Non-Profit For-Profit
Source: Author’s analysis of Kaiser Family Foundation data on hospital ownership, 1999-2018
While there are nonprofit hospitals operating in all 50 states and the District of Columbia, the share of community hospitals that are owned by nonprofit entities varies by region. As Figure 3.2 demonstrates, states in the Northeast and upper-Midwest tend to have higher proportion of community hospitals owned by nonprofit organizations. For example, all community hospitals in Vermont are nonprofit. In Maryland, Connecticut, North Dakota, Manie and Wisconsin, over 90 percent of community hospitals in the state are owned by nonprofit entities. States with lower rate of nonprofit hospital ownership tend to be in the South and Great Plains. In Oklahoma, Louisiana, and Texas, nonprofits account for less than a third of hospital in the state. Wyoming (14%) has the lowest nonprofit hospital rate (66% of hospitals in Wyoming are owned by state or a local government).
22 Figure 3.2: Share of Community Hospitals in a State Owned by Nonprofit Organizations, 2018
Source: Author’s analysis of Kaiser Family Foundation data on hospital ownership, 1999-2018
3.2 Federal Tax Exemption and Community Benefits
Unlike religious institution and governmental organizations, nonprofit hospitals have never been categorically exempted from federal income tax. As with other 501 (c)(3) organizations, nonprofit hospitals and health systems are granted federal tax-exempt status by qualifying as charitable organizations. The rationale for the exemption is that the organization is providing a service that would have otherwise been paid for by the public and that the organization is providing services in promotion of general welfare (Steinwald 2008). The Internal Revenue Service (IRS) and federal courts have recognized the promotion of health benefits for the community—including charity care and medical research—as a charitable purpose under the guidelines of U.S. federal tax law. Organizationally, nonprofit hospitals and health systems must be structured and operated exclusively for the promotion of general health and not the enrichment of a private individual or shareholder.
23 The IRS has issued a series of revenue rulings dictating how nonprofit hospitals can meet the requirement for tax exempt status. Early guidelines mandated that if hospitals generate any surplus funds, the excess revenue should be used to provide charity care to the extent of their financial abilities. In 1969, the IRS released the “community benefits standard”, which revised the ruling to allow excess funds to be spent on activities that broadly benefit the community to meet the standard for qualifying as a charitable organization, rather than exclusively charity care. The ruling recognized five factors that would support a nonprofit hospital’s tax-exempt status: 1. “the operation of an emergency room open to all members of the community without regard to ability to pay; 2. a governance board composed of community members; 3. the use of surplus revenue for facilities improvement, patient care, and medical training, education, and research; 4. the provision of inpatient hospital care for all persons in the community able to pay, including those covered by Medicare and Medicaid; and 5. an open medical staff with privileges available to all qualifying physicians.” (GAO 2008) The IRS provides for flexibility in determining if the facility meets the community benefit standard, allowing that “the Service will weigh all of the relevant facts and circumstances in each case…” and that the “…absence of particular factors set forth above or the presence of other factors will not necessary be determinative” (IRS 1969). The community benefit standard has been widely interpreted as providing hospitals with broad latitude in meeting the charitable standard and qualifying for tax exemption (Steinwald 2008). The ruling does not include a specific requirement for the total amount or proportion of revenue in excess of costs the hospital must spend on these community benefits retain their 501 (c)(3) status. Since the implementation of the community benefit standard, there has been a consistent policy debate about nonprofit hospitals’ and health systems’ tax-exempt status and the efficacy of the standard in delivering meaningful community benefits (Young et al. 2013). Due to the size of many of these organizations, the cost of the foregone federal tax is significant. Rosenbaum et al. (2015) estimate that the value of the tax exemption for nonprofit hospitals—which includes foregone taxes, public contributions, and the value of tax-exempt bond financing—reached $24.6 billion in 2011, up from $12.6 billion in 2002. Additionally, despite their label, many nonprofit hospitals and health systems take in revenues that far exceed operating costs, thus generating
24 “profit.” Although for-profit hospitals on average tend to be more profitable than nonprofit hospitals, in 2013 seven of the ten most profitable hospitals were nonprofit (Bai and Anderson 2016). These seven hospitals each earned more than $160 million in profit from patient care service. Additionally, nonprofit hospitals and health systems often have sizable and growing endowments. A survey of 56 nonprofit health care institutions reported an average of 13.2 percent return net-of-fees on investable assets for 2017, a increase from 6.2 percent return, on average, for 2016. The surveyed funds managed $2.1 billion on average, with a nearly $1 billion median pool of investable assets (McElhaney 2018). There is also mixed evidence as to whether the activities nonprofit and for-profit hospitals are substantively different in their management practices, pricing, executive remuneration, or community orientation, with empirical economics and health policy research yielding inconclusive findings (Principe et al. 2011). Research and public debates spurred national political action in the late-2000s for greater oversight of nonprofit hospital and health system finances and a reassessment of how these institutions qualify for the tax exemption. Following a 2007 Senate Finance Committee hearings on the subject, in 2008 the IRS released final instructions for the redesign of the Form 990, the tax form that all charitable entities—including nonprofit hospitals and health systems—are required to file annually detailing the finances, mission, structure and other pertinent information about the organization (IRS 2020b). The action was the first major redesign of Form 990 since 1979, and included in the revision was the addition of 16 schedules for specific organization types, including “Schedule H” designed exclusively for nonprofit hospitals and health systems (CHA 2008). Completion of Schedule H, in addition to Form 990, became a requirement for all tax- exempt nonprofit hospitals and health systems beginning in tax year 2009. The goal of the new Schedule was to increase transparency into nonprofit hospitals’ and health systems’ charitable practices and provide additional guidance as to what activities count towards meeting the community benefit standard. Schedule H directs filers to account for separate charitable expenses on “community benefits” from supplemental expense on “community building activities”, “unreimbursed Medicare”, and “bad debt expenses”. Further descriptions of these categories are included below. While there was consideration of setting a federal minimum community benefit standard when the updated guidance was being produced, the final 2008 requirement did not set a
25 minimum community benefit contribution requirement or provide specific guidance on how proportionally charitable expenses should be divided across these categories (Principe et al. 2011).
Community Benefits
Schedule H requires that community benefit expenses are tracked across eight IRS itemized expense categories. These categories, which are detailed below, are separated between “financial assistance and means-tested government programs”, expenses related to direct patient care, and five specified activities that qualify as “other benefits”. For each category, the IRS provides a worksheet to assist organization in calculating community benefit expenditures and offers detailed guidance on which expenses qualify for accounting purposes (IRS 2019b; CHA 2015). The categories of community benefit are as follows: • Financial Assistance and Means-Tested Government Programs: o Charity care: also called “financial assistance at cost” is free or discounted health services provided by a hospital to a person who cannot afford to pay for treatment and meets certain hospital-determined eligibility requirement for assistance. o Unreimbursed Medicaid: unpaid costs associated with the treatment of patients receiving Medicaid. This calculation is intended to be the difference what the hospital receives for treatment and the cost of caring for the patient. o Unreimbursed costs: unpaid costs associated with the treatment of patients on state and local programs other than Medicaid (e.g., State Children’s Health Insurance Program and state medical programs for low-income or indigent patients not covered by Medicaid). • Other Benefits: o Community health improvement services and community benefit operations: activities carried out that respond to an identified community health need and are designed to meet a community health objective. These activities extend beyond patient care and are subsidized by the hospital. These activities could include community health education, support groups, self-help programs, community based clinical services, mobile units, clinics for uninsured persons, social and environmental
26 improvement activities (e.g., violence prevention, removal of asbestos or other harmful materials from housing, nutrition programs). o Health professions education: costs related to educational programs for physicians, residents, interns, medical students, nurses and nursing students, and other health professionals who are pursuing a degree or training required by state law, accrediting body or health profession society. o Subsidized health services: clinical programs that are provided despite a financial loss, but meets an identified community need that, if no longer offered, would no longer be available or fall to a government or another tax-exempt organization to provide. o Research: direct and indirect costs associated with clinical or community health research where findings are generalizable and publicly shared. o Cash and in-kind contributions to community groups: direct cash or in-kind donations to community organizations or the community at-large to support a community benefit activity, such as event sponsorship, technical assistance for a local health initiative, or food donation.
Community Building Activities
Community building activities—introduced for the first time as a charitable expense category in the 2008 revision to the Form 990 Schedule H—are generally understood to be hospital activities intended to benefit population health, but are not related to the direct provision of patient care. Drawing from the research on SDOH, these activities are designed to address the root cause of poor health outcomes, such as housing, employment, environment, community safety, education, social support networks, and income (Somerville et al. 2012). Similar to community benefit expenses, the IRS directs filers to itemize community building activities on Schedule H across eight defined activity categories and one catch-all “other” category. These expenses are not required, but must be reported if they exist. Community building activities are separated into the following categories (IRS 2019b): • Physical improvements and housing: costs include provision or rehabilitation of housing for vulnerable populations, improvement of housing to remove materials that may be harmful
27 to health of residents (e.g., lead, asbestos, mold), provision of housing for vulnerable patients after discharge, housing for seniors, and payments to improve park, streets and playgrounds, among others. • Economic development: supporting new employment opportunity in community with high rates of unemployment or assisting small business development in low-income communities. • Community support: programs to improve community support networks, violence prevention programs, disaster preparedness programs, child care, and mentoring programs. • Environmental improvements: programs to address environmental hazards that impact community health (e.g., air pollution, garbage removal) as well as activities aim at reducing the environmental impact caused by the hospital (e.g., purchasing clean energy, eliminating the use of toxic materials such as mercury). • Leadership development and training for community members: trainings around conflict resolution, civic skills, language skills, or medical interpreter skills for community members. • Coalition building: support for community organization efforts to address health, safety, housing, or other pressing issues related to community health. • Community health improvement advocacy: support for policies and programs at the local, state or national level to support issues to improve public health, access to health care services, housing, the environment, and transportation. • Workforce development: training and recruitment of health professional to work in communities currently underserved. • Other: activities to protect or improve community health that are not identified in the other categories.
Housing: Community Benefit or Community Building Activity?
Efforts to create a revised community benefit reporting standard were largely led by the Catholic Health Association of the United States (CHA). The CHA is a ministry of the Catholic
28 Church and, with over 2,2000 health operating health facilities, represents the largest collection of nonprofit health providers in the United States (Flex Monitoring Team 2009; CHA 2020). The reporting requirement ultimately included in the Schedule H is consistent with the community benefits reporting framework developed by CHA in 2006. However, the final version of the Schedule H does not include a “community building” category within the community benefits section, but instead requires hospitals to itemize these types of expenses in the “community building activities” section of the form (Somerville et al. 2012). Initial drafts of the reporting requirement included community building activities as a community benefits category. However, there was not consensus at the IRS that external investments intended to address upstream SDOH should meet the definition “community benefit”. Ultimately, the addition of the separate “community building activities” category as a means of tracking these expenses, but not including them with the “community benefit” category was adopted as a compromise (Salinsky 2009). This separation created confusion as to whether community building activities counted towards the charitable activities the hospitals report as a means of qualifying as a tax exemption organization (Enterprise Community Partners 2018). Additionally, in several cases the distinction between whether an activity qualifies as a community benefit or community building activity is murky. In particular, the guidance provided for the “community health improvement services and community benefit operations” category of community benefits could be understood to overlap with community building activities. For example, if hospital organization who identifies heightened rates of childhood lead poisoning in their community and creates a grant program to remove lead paint from homes, it is not clear whether that expense should be reported as a “community health improvement services and community benefit operation” or a “community building activity: physical improvements and housing” action. In response to the uncertainty and potential issues of double counting, the IRS promulgated revised Schedule H instructions in 2011 to advise that “[s]ome community building activities may meet the definition of community benefit” and that if these expenses that are reported as community benefits they should not be additionally reported as community building activities (i.e., these activities should not be reported twice) (Enterprise Comunity Partners 2018).
29 In December 2015, the guidance was further clarified to specifically address inquiries related to hospital charitable expenditures on housing: “…some housing improvements and other spending on social determinants of health that meet a documented community need may qualify as community benefit for the purposes of meeting the community benefit standard. If a hospital chooses to report, such a community benefit in Part I (Financial Assistance and Certain Other Community Benefits at Cost) of Schedule H, then the Instructions say: "Do not report in Part II community building costs that are reported on Part I, line 7 as community benefit."” (IRS 2020a).
In 2018, Enterprise Community Partners, in partnership with the CHA, released guidance for nonprofit hospitals and health systems on what housing activities met the updated IRS guidelines. The report provides specific guidelines on which housing activities meet the community benefit standard and how to classify that spending on the Form 990 Schedule H filing. The report directs filers to report legal aid, housing quality improvements (e.g., lead mitigation, remedying housing-based asthma triggers, weatherization), direct housing subsidies, short-term rental assistance, screening for housing related needs (e.g., housing instability, exposure to toxins), as “community health improvement services and community benefit operations.” The report advises that placing medical professional in supportive or low-income housing if the training is part of a certification require could qualify for “health professional education.” Funding for research to assess housing and health outcomes could meet the community benefit “research” guideline. Finally, direct cash grants or in-kind assistance to homeless shelters or housing organizations, donation of surplus property for affordable housing development, capital grants to affordable housing, and administrative and operational capacity support to affordable housing organizations could meet the “cash and in-kind contributions” guidelines (Enterprise Comunity Partners 2018). The report also lists specific housing activities that would not meet the community benefits standard. These housing activities include temporary housing to facilitate patient discharge to reduce hospital costs, post-acute respite care, housing activities that would facilitate general economic development and not specific address a community health concern, and affordable housing investments or loans where hospitals expect a return. In general, community benefit activities cannot be declared for expenditures where a hospital and health system expects a
30 financial return or in cases where the hospital intends to recoup the expenses (e.g., a loan). This condition restricts nonprofit hospital and health system capital subsidies declared as “community benefits” on affordable projects to grants, which—due to the complexities of affordable housing finance and taxation—can be financially less impactful than a low-interest or forgivable loan. Therefore, most of the investment strategies promoted by the Accelerating Investments for Healthy Communities program and others seeking to leverage nonprofit hospital endowments for impact investing would not be captured as a “community benefit” (Center for Community Investment n.d.). It remains unclear as to how, if at all, nonprofit hospitals have shifted their reporting on housing activities from community building activities to community benefits in response to the 2015 updated IRS guidance and the 2018 Enterprise report. Moreover, it is unclear if the updated guidance has encouraged nonprofit hospitals and health systems to commit to housing activities for the first time. While it is still early, it appears that confusion about how to classify and report housing expenses remains. The Urban Institute’s 2019 study found that many respondents did “not have a good understanding of federal opportunities that may spur investments in housing, including IRS rules about which housing activities may qualify as meeting the community benefit obligation” (Reynolds et al. 2019).
3.3 ACA, CHNA and CHIP
The passage and implementation of the federal 2010 Patient Protection and Affordable Care Act (ACA) has broad implications for the healthcare system in the United States. While the ACA’s impact on nonprofit healthcare organizations is sweeping and detailing full effect is beyond the scope of this work, the law has many direct impacts on community benefits, IRS tax compliance, and the orientation of nonprofit hospitals and health systems towards their community. A particularly important factor was the ACA’s expansion of health insurance coverage and the expected decrease in demand for free and reduced care. It was predicted that the reduction in the demand for charity care would free up community benefit resources for hospitals to increase contributions for other community-oriented health activities (e.g., community health improvement services, community building activities) (Somerville 2014). Additionally, the ACA
31 places greater financial pressure on nonprofit hospitals to reduce certain readmissions and this may incentivize institutions to invest in upstream actions to mitigate readmissions. However, early evidence suggests that while community benefit spending did increase following the ACA implementation, much of that spending was attributed to increased spending on subsidized health services and Medicaid shortfalls rather than community health improvement and cash/in-kind contributions (Alberti, Sutton, and Baker 2018). A significant new regulatory component of the ACA for nonprofit hospitals and health systems was the implementation of Community Health Needs Assessment (CHNA) process. The CHNA is designed as a mechanism for nonprofit hospitals and health systems to identify and analyze community health needs and assets through systematic data collection and analysis (Rosenbaum 2013). The CHNA requirement—which went into effect March 2012—is enforced by the IRS and to maintain compliance a nonprofit hospital or health system must conduct a CHNA process once every three years. To meet the requirements, a hospital must complete the following steps: 1) “Define the community it serves [which can be defined by geography—e.g., neighborhood,
ZIP code, city—or by population with special needs—e.g., children, elderly]; 2) Assess the health needs of that community; 3) In assessing the community’s health needs, solicit and take into account input received from persons who represent the broad interests of that community, including those with special knowledge of or expertise in public health; document the CHNA in a written report that is adopted for the hospital facility by an authorized body of the hospital facility; and 4) Make the CHNA report widely available to the public” (IRS 2019c).
Following the CHNA’s release, a hospital organization is required to develop an Implementation Strategy to specify how the hospital or health system plans to direct its community benefits, community building activities, and other hospital resources to address the community health needs identified through the CHNA over the next three years. If there is a community need identified through the CHNA process that the hospital intends not to address, the institution must describe why it chose not to do so in the Implementation Strategy narrative.
32 Hospitals that fail to meet the CHNA guidelines risk losing their 501 (c)(3) status and being assessed penalties of up to $50,000 each year the hospital is out of compliance (IRS 2019c). The CHNA timelines for institutions vary, but, at most, a facility operating through the period would have produced three CHNA reports as of 2020 (IRS 2011). As a comprehensive assessment of community health conditions, the CHNA process has the potential to elevate specific community socioeconomic conditions as public health concerns and prompt hospitals and health systems to invest in “upstream” preventative measure. A 2017 review of 97 Implementation Strategies by the Association of American Medical Colleges found that 92 percent of the strategies included action to address SDOH. With those report, the top nine reported social determinants of health were, in order: food access, social support, poverty, crime, education, transportation, housing, built environment, and racism. Among those who listed actions to address SDOH, 17 percent addressed housing (compared with 52 percent for food access and 45 percent for social support). Select implementation strategies to address housing described in the report include medical respite programs to provide recuperative care for homeless men and women and hiring a housing retention specialist to work with patients to assess potential barriers to maintaining stable housing (AAMC 2017).
3.4 State and Local Tax Exemption
In addition to qualifying from federal income tax exemption, most nonprofit hospitals also receive exemption from state and local taxes (e.g., property, sales, payroll, and state income). These exemptions are granted by state statue and, in a few cases, nonprofit hospitals and health systems are not excluded from specific state or local taxes. All states grant nonprofit hospitals and health systems property tax exemption, all but two states (Washington and Alaska) grant these institutions state income tax exemption, and all but eight states (Alabama, California, Louisiana, North Carolina, Oklahoma, Rhode Island, Washington, West Virginia) grant these institutions sales tax exemption (The Hilltop Institute 2020). As with federal taxes, the value of the exemption from state and local taxes is significant. In 2011, the value of the state and local tax exemption was estimated to be worth nearly $12 billion (Rosenbaum et al. 2015).
33 These exemptions have triggered debates at the state and local level as to whether these benefits are justified and calls for greater oversight into how hospitals spend their community benefits. In 2013, the City of Pittsburgh filed a lawsuit against UPMC, a prominent nonprofit research hospital system, to remove the organization’s tax-exempt status and collect the estimated $20 million in taxes the institution would owe the city annually (Zullo 2014). The lawsuit was an escalation in a high-profile conflict between the city’s mayor and UPMC following a series of closures of medical facilities in poor communities, the perceived as retaliation of the hospital against unionization attempts by staff, and claims of excessive compensation for hospital executives (the lawsuit was dropped by the subsequent mayor). UPMC faced additional legal action in 2019 from the Pennsylvania’s Attorney General claiming that the institution’s healthcare access and billing practices were “not fulfilling its obligation as a public charity” (the lawsuit was also dropped) (Pennsylvania Office of Attorney General 2019). In 2015, a New Jersey state judge removed the property tax exemption of the nonprofit Morristown Medical Center—noting that “for purposes of the property tax exemption, modern nonprofit hospitals are essentially legal fictions”—and ordered the institution to pay several years of back taxes (Meiksins 2015). While nearly all states grant nonprofit hospitals tax exempt status, state regulations governing nonprofit hospitals’ financial assistance policies, billing practices, Medicaid reimbursement, community health need assessment processes, and community benefit spending vary considerably. The Hilltop Institute, a research organization based at the University of Maryland, Baltimore County, maintains a comprehensive database of state requirements that apply to nonprofit hospitals. Drawing from this analysis, half of the states impose additional statutory requirements on nonprofit hospitals’ community benefit practices that exceed the federal baseline regulations. While the text of each state statute differs, the Hilltop Institute separates the mandates between unconditional community benefit requirements (i.e., an explicit requirement that nonprofit hospitals provide charity care and participate in the state’s Medicaid program) and conditional community benefit requirements (i.e., providing charity care and/or participating in the state’s Medicaid program is required to receive state tax exemptions or licensing). Using this framework, nine states have unconditional requirements and 16 have conditional requirements (see Figure 3.3 below) (The Hilltop Institute 2020).
34
Figure 3.3: State Community Benefit Regulations
Source: Author’s analysis of data from The Hilltop Institute 2020
Additionally, five states—Illinois, Nevada, Pennsylvania, Texas, and Utah—impose minimum community benefit expenditure requirements. As with other community benefit guidelines, the text of the statue varies by state. However, most direct nonprofit hospitals to provide community benefits at least commensurate with the value of a local or state tax exemption. For example, a 2012 Illinois statue requires that nonprofit hospitals seeking “property tax exemption provide charity care or other specified services or activities at levels at least equivalent to what the hospital otherwise would be required to pay in property taxes” (The Hilltop Institute 2020). Among the statues that impose additional regulations on community benefit practices or minimum payments, nearly all direct hospitals to target the community benefit expenses on charity care and other direct patient services. While this direction is understandable as free care and other direct medical provisions are the most tangible charitable practices, it is
35 uncertain whether these directives discourage investments in upstream preventative activities (i.e., community building activities).
3.5 Community Benefit and Community Building Activities Analysis
After the filing are reviewed by the IRS, Form 990 and supplemental Schedule H filings become public record. Despite the relatively recent change in requirement, quantitative research has emerged to evaluate nonprofit hospitals’ and health systems’ community benefit practices. Singh et al. (2015) analyzed 2009 data from hospital tax filing and 2010 Count Health Rankings to examine the relationship between community health needs and the types and levels of hospitals’ community benefit expenditures. Their analysis found that there were some patterns between community health needs and spending on community benefit, but no relationship between community health improvement spending and community health needs. Rosenbaum, Byrnes, and Rieke (2013) compare Schedule H community benefits reporting across a selection of 24 states and found that state law largely lacks the clarity of IRS guidance and considerably variable in how it treats community benefits. Young et al. (2013), analyzing a national subsample of hospital tax filing for 2009, found that hospitals spent, on average, 7.5 percent of operating expenses on community benefits and that a majority of these expenses went towards charity care and other patient services. Their analysis found a wide range in reported community benefit spending across hospitals and did not find evidence that this variety was associated with indictors of community need. Alberti, Sutton, and Baker (2018) compare Form 990 filings from a sample of nonprofit teaching hospitals in 2012 and 2015 to assess the impact of ACA’s insurance expansion on community benefit expenses. Their analysis found that the sample of hospitals increased overall community benefit expenditures by 20 percent over the period despite spending 16 percent less on charity care. The authors also found that hospitals in Medicaid expansion states increased spending on subsidized health services and Medicaid shortfalls at a higher rate relative to hospitals in non-expansion states.
36 3.6 Conclusion
The 2008 revision to the community benefits standard increased transparency around reporting of nonprofit hospitals’ and health systems’ charitable practices. Additionally, the inclusion of the community building activities category and subsequent clarifications around how to report spending on activities to address SDOH—such as housing instability and quality— signaled an acceptance on the part of federal regulators that nonprofit hospitals’ and health systems’ charitable practices to address these upstream SDOH. However, it remains unclear how nonprofit hospitals have systematically responded to these changes. While these studies document the recent trends in community benefit spending, there does not appear to be a quantitative study of community building activities and housing activities, specifically. The quantitative analysis in thesis building on this previous research work to explore how spending on community benefits, community building activities, and community benefit activities related to housing have changed over the last decade. Additionally, building off the research by Singh et al. (2015), it seeks to assess how neighborhood socioeconomic conditions explain variations in the amount of spending reported by nonprofit hospitals and health systems to SDOH, generally, and in housing, specifically.
37 4. Data description
4.1 IRS Form 990 and Schedule H
Unless the entity is categorically exempted (e.g., religious institution or governmental agency), all 501 (c)(3) tax-exempt organizations must annually file a Form 990 with the IRS. The Form 990 is the IRS’s primarily resource for gathering information about tax-exempt organizations, informing organizations about tax law requirements, and for monitoring compliance (IRS 2020b). In June 2016, the IRS released all electronically filed Forms 990 and supplemental schedules for the first time in a machine-readable format through Amazon Web Services (Amazon Web Services 2020). While the returns are public records, previous electronic Form 990 filings were only available as static image files, which limited the ability for researchers to systematically analyze filings. The IRS data release includes yearly records from 2010 through 2017. In addition to the standard Form 990, nonprofit hospitals and health systems are required to file a supplemental Schedule H form that details the institution’s charitable practices and other pertinent hospital activities. The electronic dataset is limited to nonprofit organizations who electronically file their taxes, which the IRS estimates to include over 60% of all Form 990s filed by 501 (c)(3) tax-exempt organizations (Amazon Web Services 2020). For nonprofit hospitals and health system, the electronic filing rate is likely higher. In 2016, for example, among the estimated 2,849 nonprofit hospitals in the United States, the final processed dataset contained records for 2,003 hospitals (70% of potential filers) (Kaiser Family Foundation 2020). Community Benefit Insight, an online data resource developed and maintained by the research organization RTI International with support from the Robert Wood Johnson Foundation and Public Health Institute, provides national and state-level summary data on nonprofit hospital charitable activity as well as a searchable database for individual nonprofit hospital tax filings (Community Benefit Insights 2020). The tool draws primarily on the IRS’s electronic release of nonprofit hospital Form 990 and supplemental Schedule H filings, which detail community benefits and community building activity expenditures (further described below). The resource also provides general hospital and health system financial reporting (e.g., revenue, total functional expenses, and hospital address) collected on the Form 990.
38 Community Benefit Insight maintains an Application Programming Interface (API) for researchers to access the underlying data supporting their online platform, including the detailed 990 Schedule H filings records for single hospital. These hospital-level yearly tax filings are stored on their servers as a JavaScript Object Notation (JSON) records (Community Benefit Insights 2020). Using R statistical programming software, I wrote a script to individually scrape the detailed tax filing records from Community Benefit Insight’s API and produce a single comma- separated values (CSV) dataset of all records. This program was run January 14, 2020 and produced 22,958 raw records. I then worked to standardize and process this raw output to address issues of duplicate filing records, typos and inconsistencies in hospital and health system names, missing entries, and faulty data (i.e., nonnumeric values in numeric columns). I created a hospital-level unique identification to ensure duplicate records were not included in the dataset and utilized unique identifications to aggregate hospital-level spending on community benefits and community building activities across the sample period. This process yielded a dataset containing 16,199 records and 2,882 unique hospitals across the eight years of tax filings. Table 1 provides a breakdown of the filings per year in the dataset. The IRS releases a majority of tax returns from organizations that operate nonprofit hospitals 16 months after the end of their tax reporting period. Due to this delay IRS return processing—as well as variation in organizational tax return submissions deadlines—2017 has fewer records (1,321) than the other tax years (Community Benefit Insights 2020).
Figure 4.1: Yearly Form 990 Records Year Form 990 Records 2010 2,208 2011 2,201 2012 2,187 2013 2,153 2014 2,096 2015 2,030 2016 2,003 2017 1,321 Total 16,199 Source: Author’s analysis of IRS Form 990 filings, 2010-17
39 From this processed set, I create two final datasets for analysis. The first includes all 16,199 individual yearly tax filing records, which allows for temporal comparisons in spending on community benefits and community building activities. The second set summarizes financial reporting information at the hospital-level across all years where filings are available to create 2,882 records. Due to issues of IRS processing delays, electronic filing rates, and hospital closures and openings, only about a third of hospitals have returns for all eight years. Over half have returns for at least seven years.
Figure 4.2: Cumulative Annual Filings by Hospital Cumulative filings Number of hospitals Percent 1 315 11% 2 196 7% 3 201 7% 4 207 7% 5 195 7% 6 211 7% 7 642 22% 8 915 32% Total 2,882 100% Source: Author’s analysis of IRS Form 990 filings, 2010-17
Hospital Financial Reporting and Geospatial Information
The Form 990 records provide yearly financial and administrative information for nonprofit hospitals. The financial records include total revenue and total functional expenses, from which I am able to estimate a hospital’s annual net profit (revenue minus total functional expenses) and gross profit rate (profit divided by revenue). The administrative records include hospital name, filing year, and hospital address (street address, city, state, and ZIP Code). The hospital addresses allow me to join the filing records to geospatial data (e.g., ACS summary demographic data, state-level regulations).
Community Benefits
Community benefit expenses are tracked across eight IRS designated expense categories (rows H through I in Figure 4.3 below, detailed in the previous chapter). For each category, the
40 IRS provides a worksheet to assist organization in calculating community benefit expenditures and provides guidance on which expenses qualify for community benefits accounting purposes. For the purposes of this analysis, I utilize the total expenses reported across the eight categories (column c) and the summarized total community benefit spending (row k).
Figure 4.3: IRS Form 990 Schedule H: Community Benefits Table Reporting Table
Source: Internal Revenue Service (IRS 2019a)
Community Building Activities
Similar to community benefit expenses, the IRS directs filers to itemize expenses on community building activities across eight defined activity categories and one catch-all “other” category (Figure 4.4). The IRS does not provide worksheets to assist filers with calculating these expenses, but includes descriptions of what costs qualify for which categories (detailed in previous chapter). For the purposes of this analysis, I utilize the total expenses reported across the nine categories (column c) and the summarized total community building activity spending (row 10).
41 Figure 4.4: IRS Form 990 Schedule H: Community Building Activities Reporting Table
Source: Internal Revenue Service (IRS 2019a)
4.2 American Community Survey Data
To assess the social, economic, and housing conditions of the hospital’s immediate vicinity, I drew on 2013-17 American Community Survey (ACS) 5-year estimates of local housing and socioeconomic characteristics. The housing characteristics including home owner-occupancy rate, residential occupancy rate, median home value, median gross rent, and share of renters paying more than 35 percent of household income on rent (as a measurement of housing cost burden. The socioeconomic characteristics include unemployment rate, share of persons 65 years old or higher, share of persons without health insurance, median household income, and poverty rate. The analysis utilizes ACS estimates summarized at the ZIP Code Tabulation Areas, which is a Census Bureau areal representations of United States Postal Service ZIP Code service areas. This data is joined to the hospital-level dataset by the ZIP Code reported on the hospital’s tax filing records. Among the 2,882 hospitals, there were 184 cases where there are no ACS estimates for the listed ZIP Code. Often this is the case when the hospital’s address is listed as a Post Office (P.O.) Box in a ZIP Code that does not have a defined geographic area. Additionally, in certain geographies with lower populations, the Census Bureau suppresses the estimate due to limited data. These missing rates vary by ACS variable, from 184 missing in the estimate of housing units
42 to 224 missing in the median value of an owner-occupied housing unit. The records with missing ACS values were excluded from the final regression analysis models.
4.3 State Hospital Regulations
As detailed in the previous chapter, the state regulatory landscape for nonprofit hospitals is varied. The Hilltop Institute, a research organization based at the University of Maryland, Baltimore County, maintains a comprehensive database of state community benefit requirement and tax emptions for nonprofit hospitals. The database includes descriptions of the various state statutes dictating financial assistance policy, community benefits, billing protocols, community health need assessment processes, tax exemption, and other nonprofit hospital regulations (The Hilltop Institute 2020). For the purposes of this analysis, I focus on the 25 states with laws regulating nonprofit hospital community benefit activity. While the text of each state statute differs, the Hilltop Institute defines the mandates between unconditional community benefit requirements (i.e., an explicit requirement that nonprofit hospitals provide charity care and participate in the state’s Medicaid program) and conditional community benefit requirements (i.e., providing charity care and/or participating in the state’s Medicaid program is required to receive state tax exemptions or licensing). Using this framework, nine states have unconditional requirements and 16 have conditional requirements. Additionally, five states—Illinois, Nevada, Pennsylvania, Texas, and Utah—impose minimum community benefit expenditure requirements. At the state level, I created a dataset of three indicator variables to designate whether the state has an unconditional community benefit requirement, a conditional community benefit requirement, and a minimum community benefit requirement. This dataset was merged to the hospital dataset by state.
4.4 Rural-Urban Continuum Classification
Within a state, housing markets and local housing needs vary based on regional development and urbanization. In particular, renters living in rural and non-metropolitan areas are more likely to reside in manufactured housing, live in older housing, and report housing
43 quality issues than their urban rent counterparts (Scally et al. 2018). Additionally, nonmetropolitan areas may have less sophisticated affordable and supportive housing developers, advocates, and practitioners. To account for these factors, I utilize a nine-point classification scheme created by The United States Department of Agriculture’s (USDA) Economic Research Service to categorize metropolitan and non-metropolitan counties by population and degree of urbanization. The 2013 designation creates three classifications for metropolitan status based on regional population (outlined below). For non-metropolitan counties, there is a six-degree classification based on regional population and proximity to a metropolitan area (USDA 2019).
Metropolitan Counties: 1. Counties in metro areas of 1 million population or more 2. Counties in metro areas of 250,000 to 1 million population 3. Counties in metro areas of fewer than 250,000 population Nonmetropolitan Counties: 4. Urban population of 20,000 or more, adjacent to a metro area 5. Urban population of 20,000 or more, not adjacent to a metro area 6. Urban population of 2,500 to 19,999, adjacent to a metro area 7. Urban population of 2,500 to 19,999, not adjacent to a metro area 8. Completely rural or less than 2,500 urban population, adjacent to a metro area 9. Completely rural or less than 2,500 urban population, not adjacent to a metro area
44 5. Analysis: Spatial and Temporal Descriptive Results
5.1 Revenue and Profit
The financial characteristics of nonprofit hospitals and health systems in United States vary considerably. As Figure 5.1 demonstrates, while the median revenue across the sample period is $121 million, the mean is over 2.5 times larger ($336 million). This range is driven by a handful of very large health systems with revenues in excess of $1 billion annually. From 2010 to 2017, median hospital revenues grew by 11 percent (from $113.6 million to $126.6 million), with revenue peaking in 2017. The gulf separating the largest hospitals from the rest accelerated over the period. The third quartile of hospitals grew by 29 percent (from $304 million to $393 million), while revenue among the first quartile of hospital increased by 6 percent (from $35 million to $37 million). To account for this variation in size, subsequent analysis of hospital charitable expenditures and other hospital financial characteristics are normalized by revenue.
Figure 5.1: Revenue Summary Figures by Year 1st Quartile 3rd Quartile Year Count Revenue Median Revenue Mean Revenue Revenue 2010 2,208 $35,215,384 $113,625,331 $285,021,387 $304,775,504 2011 2,201 $36,381,951 $111,786,727 $296,814,851 $313,463,997 2012 2,187 $35,421,345 $114,194,403 $306,201,188 $319,702,364 2013 2,153 $36,989,691 $117,059,080 $321,848,916 $331,721,078 2014 2,096 $37,893,383 $122,810,955 $346,601,858 $351,626,559 2015 2,030 $41,046,849 $128,802,938 $369,688,858 $373,042,920 2016 2,003 $41,101,331 $131,902,023 $390,094,105 $390,125,331 2017 1,321 $37,492,135 $126,622,756 $411,998,136 $393,412,076 Total 16,199 $37,306,436 $120,577,451 $336,303,064 $341,990,601 Source: Author’s analysis of IRS Form 990 filings, 2010-17
Overall, most nonprofit hospital and health systems recorded a modest profit. The median gross profit margin (defined as the revenue minus total function expenses divided by revenue) across the sample period was 3.91% (Figure 5.2). From 2010-17, the median profit margin fluctuated mildly, peaking in 2014 at 4.94% then declining to 3.32% in 2017. However, the variation between the most profitable and least profitable hospital and health systems accelerated,
45 with the gap between the first quartile and the third quartile increased from 6.88% in 2010 to 9.42% in 2017. Overall, nearly a quarter of filers reported negative profit, and this proportion remained generally consistent over the period.
Figure 5.2: Profit Margin Summary Figures by Year 1st Quar. 3rd Quar. Median Year Margin Median Margin Mean Margin Margin Profit Mean Profit 2010 0.50% 3.78% 3.58% 7.38% $3,113,447 $16,716,436
2011 0.22% 3.80% 3.59% 7.42% $3,071,678 $17,092,134
2012 -0.07% 3.72% 3.64% 7.91% $3,073,168 $17,618,210
2013 -0.23% 3.73% 3.19% 8.07% $3,270,601 $20,055,533
2014 0.71% 4.94% 4.95% 9.40% $4,694,035 $24,967,983
2015 0.13% 4.24% 3.94% 8.66% $4,040,531 $21,158,454
2016 -0.41% 3.77% 3.57% 8.11% $3,263,697 $20,467,811
2017 -0.70% 3.32% 3.80% 8.72% $3,112,689 $23,692,506 Total 0.08% 3.91% 3.78% 8.12% $3,400,302 $19,990,101 Source: Author’s analysis of IRS Form 990 filings, 2010-17
5.2 Community Benefits
Community benefits were a significant expense for most nonprofit hospitals and health systems in the sample. The median community benefit expense was over $8 million (7.12 percent of revenue). Hospital community benefit spending as a function of income varied, with the first quartile of hospitals spending less than 4.67% and third quartile of spending at 10.28%. Over the period, community benefit expenditures grew both as a share of hospital revenue and in absolute dollars, with the median share of increasing by 0.8 percentage point and the median contribution growing by over $2 million (Figure 5.3).
Figure 5.3: Community Benefit Expenditures Summary Statistics by Year 1st Quar. Median Mean Year Share Median Share Mean Share 3rd Quar. Share expense expense
46 2010 4.24% 6.57% 7.70% 9.48% $7,149,470 $24,712,697 2011 4.70% 7.01% 8.32% 10.07% $7,757,564 $27,342,846 2012 4.84% 7.30% 8.43% 10.28% $8,214,239 $28,491,907 2013 4.79% 7.24% 8.38% 10.43% $8,268,778 $27,622,868 2014 4.55% 7.06% 8.21% 10.33% $8,546,311 $28,399,067 2015 4.64% 7.17% 8.48% 10.38% $9,277,498 $30,975,423 2016 4.81% 7.46% 8.72% 10.75% $9,638,467 $33,545,427 2017 4.85% 7.37% 8.89% 10.83% $9,424,101 $34,919,201 Total 4.67% 7.12% 8.36% 10.28% $8,366,718 $29,153,366 Source: Author’s analysis of IRS Form 990 filings, 2010-17
Within the community benefit subcategories, the largest reported expense was unreimbursed Medicaid (3.23% of revenue), followed by charity care (1.86%), health professions education (1.34%), subsidized health services (0.79%), research (0.69%), community health improvement services and community benefit operations (0.36%), cash and in-kind contributions to community groups (0.24%), and unreimbursed costs (0.16%). As Figure5.4 demonstrates, shifts in subcategory community benefit spending were largely limited to a few categories. In particular, spending on charity care reduced in 2013-14, while unreimbursed Medicaid expenditures increased. This shift likely corresponds with the expansion of Medicaid eligibility and opening of health care exchanges following the Affordable Care Act. Additionally, the decline in research spending observed between 2012 and 2013 is likely due to a reporting requirement change implemented in 2013 that removed restricted research grant funding from Schedule H reporting (Alberti, Sutton, and Baker 2018).
47 Figure 5.4: Total Spending on Community Benefits Subcategories as Share of Total Hospital
Revenue, 2010-17
10.00%
0.23% 9.00% 0.28%
0.20% 1.18% 0.23% 0.24% 1.15% 0.24% 0.29% 0.44% 0.44% 0.26% 0.36% 8.00% 1.17% 0.43% 0.43% 0.79% 0.79% 0.81% 0.76% 0.78% 0.86% 0.78% 7.00% 0.72%
1.34% 1.33% 1.36% 1.34% 1.35% 1.38% 1.32% 6.00% 1.29% 0.36% 0.39% 0.39% 0.35% 0.18% 0.36% 0.14% 0.34% 0.20% 0.20% 0.35% 0.13% 0.09% 5.00% 0.38% 0.14% 0.18%
4.00% 2.84% 2.90% 3.13% 2.64% 3.26% 3.60% 3.72% 3.65% 3.00%
2.00%
1.00% 2.10% 2.25% 2.27% 2.12% 1.66% 1.50% 1.53% 1.51%
0.00% 2010 2011 2012 2013 2014 2015 2016 2017
Charity care Unreimbursed Medicaid Unreimbursed costs: Community health improvement services… Health professions education: Subsidized health services Research Cash and in-kind contributions to community groups
Source: Author’s analysis of IRS Form 990 filings, 2010-17
At the state level, there is significant variation in community benefits spending (Figure 5.5). Tennessee had the highest rate of community benefit over the period (14% of revenue), followed by a cluster in the Northeast (Vermont, Connecticut, New Hampshire, and New York) where community benefit expenses exceeded 11 percent of total revenue. In four states—Utah, Mississippi, Louisiana, and Alaska—community benefits expenses were less than 4 percent of total revenue.
48
Figure 5.5: Total Community Benefits Spending as Share of Nonprofit Hospital Revenue (2010-
17) by State
Source: Author’s analysis of IRS Form 990 filings, 2010-17
5.3 Community Building Activities
Compared with community benefits, spending on community building activity expenses were minimal. Over the period, the median reported community building activity expense was just $3,656 (0.04% of median community benefits expenses). From 2010-17, spending on community building activities declined both in dollar terms and as a share of revenue (Figure 5.6). The median reported community building activities expense peaked in 2012 at $5,046, but then declined by nearly half to $2,794 in 2017.
Figure 5.6: Community Building Activities Expenditures Summary Statistics by Year 1st Quar. Median Mean Year Share Median Share Mean Share 3rd Quar. Share expense expense
49 2010 0.000% 0.004% 0.100% 0.051% $3,812 $205,995 2011 0.000% 0.004% 0.250% 0.054% $4,361 $218,819 2012 0.000% 0.005% 0.090% 0.053% $5,046 $220,481 2013 0.000% 0.004% 0.087% 0.052% $4,870 $204,865 2014 0.000% 0.003% 0.100% 0.048% $2,667 $203,006 2015 0.000% 0.003% 0.086% 0.044% $3,250 $204,267 2016 0.000% 0.002% 0.077% 0.045% $2,500 $209,146 2017 0.000% 0.003% 0.084% 0.043% $2,794 $198,033 Total 0.000% 0.003% 0.111% 0.050% $3,656 $208,680 Source: Author’s analysis of IRS Form 990 filings, 2010-17
While nearly all hospitals report community benefit spending, there is tremendous variation in spending on community building activities. Among the 16,199 filings across the sample period, 44 percent reported no community building activities (Figure 5.7). This proportion remained relatively constant across the period, with 44% of organizations reporting no community building activity expenses in 2010 compared with 46% in 2017. For the filings that did report community building activity expenses, 61 percent were less than $100,000. However, in 4% of filings the community building activity expenses exceeded $1,00,000. Figure 5.7 provides descriptive statistics on community building activity by year limited to institutions with reported spending.
Figure 5.7: Community Building Activities Expenditures Summary Statistics by Year for Institutions with Reported Spending Share 1st Quar. Median 3rd Quar. Median Mean Year Count of total Share Share Mean Share Share expense expense 2010 1234 55.9% 0.01% 0.04% 0.18% 0.14% $57,718 $368,588 2011 1234 56.1% 0.01% 0.04% 0.45% 0.16% $62,064 $390,292 2012 1255 57.4% 0.01% 0.04% 0.16% 0.13% $60,456 $384,217 2013 1221 56.7% 0.01% 0.04% 0.15% 0.12% $58,730 $361,240 2014 1142 54.5% 0.01% 0.04% 0.18% 0.12% $56,495 $372,592 2015 1125 55.4% 0.01% 0.03% 0.15% 0.12% $56,338 $368,588 2016 1100 54.9% 0.01% 0.04% 0.14% 0.11% $62,347 $380,836 2017 716 54.2% 0.01% 0.03% 0.15% 0.11% $66,053 $365,365 Total 9027 55.7% 0.01% 0.04% 0.20% 0.12% $59,861 $374,477
50 Source: Author’s analysis of IRS Form 990 filings, 2010-17
While nearly all subcategories of community building activity expenses experienced declines, the drop was more pronounced in certain spending categories (Figure 5.8). Spending on community support expenses and physical improvements and housing declined by half and economic development declined by a third from 2010-17. Spending on the remaining community building activity categories remained relatively steady, with workforce development, the category that captures training and recruitment of health professional to work in communities currently underserved, remaining the largest expense category over the period.
51 Figure 5.8: Community Building Activity Spending by Subcategories as Share of Total Hospital Revenue, 2010-17
0.080%
0.005% 0.070% 0.004% 0.004%
0.005% 0.018% 0.060% 0.017% 0.017% 0.004%
0.004% 0.004% 0.050% 0.017%
0.016% 0.003% 0.011% 0.011% 0.014% 0.016% 0.015% 0.040% 0.005% 0.004% 0.015% 0.013% 0.002% 0.001% 0.005% 0.001% 0.001% 0.010% 0.001% 0.009% 0.008% 0.030% 0.002%
0.004% 0.004% 0.003% 0.009% 0.015% 0.016% 0.001% 0.003% 0.001% 0.001% 0.001% 0.002% 0.001% 0.001% 0.016% 0.001% 0.020% 0.004% 0.001% 0.012% 0.013% 0.014% 0.001% 0.014% 0.007% 0.008% 0.010% 0.006% 0.010% 0.005% 0.005% 0.004% 0.004% 0.010% 0.002% 0.009% 0.008% 0.004% 0.005% 0.004% 0.004% 0.004% 0.000% 2010 2011 2012 2013 2014 2015 2016 2017
Physical improvements and housing Economic development
Community support Environmental improvements
Leadership development and training for community members Coalition building
Community health improvement advocacy Workforce development
Other
Source: Author’s analysis of IRS Form 990 filings, 2010-17
Although reported community building activities were generally low, there was variation in spending at the state level (Figure 5.9). Wyoming, at 0.34%, had the high rate of spending on
52 community building activities as a function of total hospital revenue from 2010-17. However, the state had the fewest nonprofit hospitals and this high relative rate is a function of Wyoming’s low overall hospital revenue. There are no evident regional patterns of states with a higher or lower proportional spending on community building activities. After Wyoming, the states with the highest rates were Delaware, Oklahoma, Florida, and Maryland, with spending ranging from 0.265% to 0.145% of revenue. California had the highest aggregate spending on community building activities with $501 million, but the state is also by far the largest in terms of hospital revenue and this spending reflected 0.078% of total revenue over the period. All 50 states and D.C. had reported community building activities from 2010-17. However, in two states, Alaska and Rhode Island, reported spending was below $1 million.
Figure 5.9: Total Community Building Activities Spending as Share of Nonprofit Hospital Revenue (2010-17) by State
Source: Author’s analysis of IRS Form 990 filings, 2010-17
While community building activities were a minor expense for the vast majority of nonprofit hospitals, for a handful of hospitals this expense was substantial. Figure 5.10 provides
53 the top ten spenders on community building activities over the period proportional to revenue. The facilities range in terms of location and urbanization, with the share split evenly between hospitals in non-metropolitan counties with less than 20,000 people and those in metropolitan centers. Powell County Memorial Hospital—located in Deer Lodge, Montana—reported $18.2 million in spending over the period, which represented 23 percent of hospital revenue. The hospital is a 16-bed critical access facility service non-metropolitan Dodge County and the outlying rural communities. Nearly all (99 percent) of that spending was reported in 2011, the year the facility opened, as an economic development expense. A local newspaper article announcing the opening of the facility at the time makes no reference to external economic development activities. However, the article cites the facilities development cost at $19 million, which suggests that the facility may have inappropriately listed the development cost of the hospital project itself as an economic development activity (Hansen 2011). Powell County Memorial Hospital appears to be an outlier in this respect, with the other top facilities generally reporting their community building activity expenses across multiple years and categories. A table of top spenders on community building activities not normalized to revenue is included in the Appendix (Figure 9.1). Boston Medical Center reports the highest overall spending ($127,770,246), which is 1.6 percent of revenue over the period.
Figure 5.10: Hospital or Health Systems with the Highest Reported Spending on Community Building Improvements as a Function of Revenue, 2010-17 Community Community Building Phys. Building Community Activities Improv. & Organization Name Location Region Revenue Activities Benefits (%) (%) Housing (%) n Deer Powell County Lodge, Non- Memorial Hospital MT metro $79,339,645 $18,276,829 1% 23% 0% 8 Motion Picture and Woodland Metro Television Fund Hills, CA (1M+) $626,308,939 $84,991,774 19% 14% 12% 8 Hot Fall River Health Springs, Non- Services SD metro $123,163,885 $7,227,565 8% 6% 6% 8 Glenwood Valley View Hospital Springs, Non- Association CO metro $844,804,045 $37,524,280 12% 4% 0% 5
54 Metro Emanuel Medical Turlock, (250K- Center Inc CA 1M) $898,751,769 $22,944,000 16% 3% 0% 4 Uintah Basin Roosevelt, Non- Medical Center UT metro $541,522,032 $13,360,241 3% 2% 2% 7 Leesburg Regional Leesburg, Metro Medical Center Inc FL (1M+) $1,943,218,378 $46,473,352 5% 2% 2% 8 Community Hospital Metro of The Monterey Monterey, (250K- Peninsula CA 1M) $3,924,731,140 $90,410,213 14% 2% 0% 8 The Villages Tri- The county Medical Villages, Metro Center Inc FL (1M+) $1,318,002,423 $29,489,353 5% 2% 2% 8 Northwest Medical Foundation Tillamook, Non- Tillamook OR metro $436,347,532 $9,292,926 8% 2% 0% 7 Source: Author’s analysis of IRS Form 990 filings, 2010-17
5.4 Community Building Activities: Physical Improvements and Housing
Physical improvements and housing—the category the encompasses all community building activity spending on housing and built environment investments—was an uncommon expense for most hospitals. Among the 16,199 returns analyzed, only 8.6% percent report community building expenses on physical improvements and housing. The limited reported expenditures resulted in a $0 median expenditure and mean of $19,420 (0.018% of revenue, Figure 5.11). Over the period average spending on physical improvement and housing declined, with the mean expense falling from $27,158 in 2010 to $15,496 in 2017. In aggregate, reported spending on this category fell from nearly $60 million in 2010 to just over $34 million in 2016.
Figure 5.11: Community Building Activities: Physical Improvements and Housing Summary Statistics by Year 1st Quar. Median Mean Year Share Median Share Mean Share 3rd Quar. Share expense expense 2010 0.000% 0.000% 0.016% 0.000% $0 $27,158 2011 0.000% 0.000% 0.021% 0.000% $0 $26,039 2012 0.000% 0.000% 0.014% 0.000% $0 $23,167 2013 0.000% 0.000% 0.013% 0.000% $0 $13,039 2014 0.000% 0.000% 0.031% 0.000% $0 $17,218 2015 0.000% 0.000% 0.017% 0.000% $0 $13,662 2016 0.000% 0.000% 0.014% 0.000% $0 $17,125
55 2017 0.000% 0.000% 0.023% 0.000% $0 $15,469 Total 0.000% 0.000% 0.018% 0.000% $0 $19,420 Source: Author’s analysis of IRS Form 990 filings, 2010-17
Figure 5.12 provides summary statistics limited to hospitals and health systems that report community building expenses on physical improvements and housing. Over the period, that share declined modestly from 9.7% reporting expenditures in 2010 to 8.3% in 2017. Even when restricted to this subsample, the median expense is just $6,981 (0.003% of revenue), which indicates that half of hospitals who report this expense report less than $7,000. However, the mean expense is significantly higher $225,665, which reflects a long upper-tail in this spending. Accordingly, 51 filings (0.3% of the sample) report expense on physical improvements and housing that exceed $1,000,000 during a tax year. However, there was an overall decline in amount of spending on physical improvements and housing over the period, with the mean expense falling from $278,911 in 2010 to $185,763 in 2017.
Figure 5.12: Community Building Activities: Physical Improvements and Housing Summary Statistics by Year for Institutions with Reported Spending Share 1st Quar. Median 3rd Quar. Median Mean Year Count of total Share Share Mean Share Share expense expense 2010 215 9.7% $5,757 0.003% 0.169% 0.012% $5,757 $278,911 2011 210 9.5% $6,382 0.003% 0.219% 0.011% $6,382 $272,917 2012 194 8.9% $6,279 0.003% 0.155% 0.013% $6,279 $261,162 2013 165 7.7% $8,062 0.003% 0.170% 0.012% $8,062 $170,145 2014 155 7.4% $7,418 0.002% 0.425% 0.014% $7,418 $232,831 2015 171 8.4% $8,500 0.003% 0.197% 0.016% $8,500 $162,191 2016 174 8.7% $9,417 0.002% 0.161% 0.015% $9,417 $197,133 2017* 110 8.3% $5,927 0.002% 0.276% 0.011% $5,927 $185,763 Total 1394 8.6% $6,981 0.003% 0.214% 0.013% $6,981 $225,665 Source: Author’s analysis of IRS Form 990 filings, 2010-17
At the state level, spending on community building activities related to physical improvements and housing were largely concentrated in a handful of states (Figure 5.13). Florida, Utah, and South Dakota had the highest proportional spending on this expense, but the amount was minimal compared with overall revenue (0.035%, 0.033%, and 0.032%, respectively). California had the highest aggregate reported spending on physical improvements and housing, $89 million, followed by Florida with $86 million. In 25 states and D.C., aggregated spending on
56 physical improvement and housing over the period fell below $1 million. In four states—Alaska, Hawaii, Nevada, and Rhode Island—there was no reported spending on physical improvements and housing activities.
Figure 5.13: Total Community Building Activities Spending on Physical Improvements and Housing as Share of Nonprofit Hospital Revenue (2010-17) by State
Source: Author’s analysis of IRS Form 990 filings, 2010-17
While the vast majority of hospital systems reported very minimal or no community building expenses related to physical improvements and housing, for a few hospitals this expense was significant. Figure 5.14 provides the top ten hospitals in terms of spending on physical improvements and housing relative to revenue. The Motion Picture and Television Fund hospital, a nonprofit hospital affiliated with the larger Motion Picture and Television Fund charity that serves workers in the entertainment industries, reported, by far, the higher expenses. Over the period, the hospital reported $77,782,108 in community building expenses related to physical improvements and housing, 12.4% of revenue. The hospital facility, which is located in suburban
57 Woodland Hills, CA, near Los Angeles, is collocated with a residential retirement community for entertainment industry retirees and their spouses (MPTF 2020). Leesburg Regional Medical Center and The Villages Tri-County Medical Center, the next largest spenders on physical improvement and housing in terms of total dollar investment, both border “The Villages”, a census-designated place in central Florida home to nearly 125,000 resident, 80 percent of whom are over 65 years old. The Villages are notable for being the largest and “most famous” retirement community in the United States (Woolington and Barnes 2020). Among the remaining seven hospitals, six are small hospitals (with annual revenues below $100 million) located in rural or nonmetropolitan communities. Bon Secours Hospital, located in Baltimore, Maryland, is notable for supporting their own community development corporation and the hospital is a member of the Accelerating Investments for Healthy Communities collaborative (Center for Community Investment n.d.). A table of top spenders on physical improvements and housing not normalized to revenue is included in the Appendix (Figure 9.2). Motion Picture and Television Fund remains the highest overall spender on physical improvements and housing; Nationwide Children's Hospital—with $6,840,537 reported spending—is the 10th highest on the list.
Figure 5.14: Hospital or Health Systems with the Highest Reported Spending on Physical Improvements and Housing as a Function of Revenue, 2010-17 Community Phys. Phys. Building Improv. & Organization Improv. & Community Activities Housing Name Location Region Revenue ($) Housing ($) Benefits (%) (%) (%) n Motion Picture and Television Woodland Metro Fund Hills, CA (1M+) $626,308,939 $77,782,108 19% 14% 12% 8 Hot Fall River Springs, Non- Health Services SD metro $123,163,885 $ 6,964,084 8% 6% 6% 8 Uintah Basin Roosevelt, Non- Medical Center UT metro $541,522,032 $13,360,241 3% 2% 2% 7 Leesburg Regional Medical Center Leesburg, Metro Inc FL (1M+) $1,943,218,378 $46,473,352 5% 2% 2% 8 The The Villages Villages, Metro Tri-county FL (1M+) $1,318,002,423 $29,489,353 5% 2% 2% 8
58 Medical Center Inc Cavalier County Memorial Non- Hospital Langdon, metro Association ND (Rural) $69,394,449 $1,312,936 2% 2% 2% 8 Artesia General Metro Hospital Plano, TX (1M+) $191,221,341 $1,991,270 8% 1% 1% 4 Bon Secours Hospital Baltimore, Metro Baltimore Inc MD (1M+) $902,635,782 $9,330,657 13% 2% 1% 7 Arkansas Valley Regional La Junta, Non- Medical Center CO metro $328,558,860 $3,021,063 18% 1% 1% 8 Bemidji, Non- Sanford MN metro $83,349,809 $609,600 6% 1% 1% 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17
59 6. Analysis: Community Characteristics and Chartable Spending
6.1 Analysis Approach
Following the descriptive analysis, an explanatory analysis method was developed to address the second research question: how socioeconomic characteristics of an institution’s immediate vicinity explain variations in charitable spending on housing and other SDOH activities? The analysis approach assesses the variation across three charitable spending categories: community benefits, community building activities, and community building activities related to housing and physical environment. This approach uses Form 990 Schedule H tax returns summarized at the hospital-level across the sample period (2010-17). To normalize for variation in hospital and health system size, the dependent variables of analysis are all divided by the aggregate revenue over the sample period. The housing and socioeconomic characteristics of the hospital’s immediate vicinity, the analysis utilizes American Community Survey 2013-17 estimates of owner-occupancy rates, home vacancy rates, median home value, median rent, share of renters who are housing cost burdened (paying more than 30 percent of household income on rent), unemployment rate, share of persons 65 years old or higher, share of persons without health insurance, median household income, and poverty rate summarized at the ZIP code level. Given the additional regulatory requirements imposed by certain states, the analysis includes indicators for state-level community benefits regulatory requirements. Additionally, to account for variations in housing characteristics between large metropolitan areas and rural communities, I include the USDA urban-rural continuum classifications. Finally, to account for the range in size and financial performance of the nonprofit hospitals, I include Form 990 data on revenue and gross profit margin. This section utilizes two analysis approaches. First, a cohort analysis to compare the hospital financial characteristics, housing and socio-economic characteristics of the neighboring community, state regulatory context, and metropolitan urban context amongst hospitals who report similar spending rates on community benefits, community building activities, and
60 community building activities related to housing. The second approach employs linear regression techniques to analyze how the socioeconomic characteristics of an institution’s immediate vicinity effect the likelihood of a hospital or health system to report spending on community building activities (as a measurement of SDOH activities) and physical improvements and housing expenses (as a measurement of housing specific activities), and the amount of that spending normalized by hospital revenue.
6.2 Decile Analysis
Given the range of hospital reported charitable activities, the first approach analyzes whether there are shared organizational or spatial characteristics among nonprofit hospitals who report similar normalized spending community-oriented activities over the period. To do this, I create decile grouping based on the total spending on community benefits, community building activities, and community benefits activities on physical environment and housing (all normalized to total revenue). To create the groupings, the sample is ordered based on the normalized spending value across the three categories, sectioned into ten equally proportioned groups based on the spending, and assigns a score of 1 to 10 based on relative spending. For example, hospitals who reported bottom 10 percent spending on community benefits as a function of revenue receive a score of 1 and nonprofit health organizations in the top 10 percent of spending on community benefits as a function of revenue receive a score of 10. For community building activities, 951 hospitals (33% of the sample) reported no community benefit activities across the sample period. Rather than spilt this subset randomly, these hospitals are all assigned to the lowest category (score 1). The remaining 67% are assigned based on the initial decline classification parameters to create a total of eight categories, with hospitals receiving a score of 8 having the highest spending on community building activities across the period as a function of total revenue. For the physical improvements and housing, 2,388 hospital (83% of the sample) report no spending on this category across the period. Those hospitals are assigned a score of 1 and the remaining hospitals with this spending are ordered and split into two final categories (with hospitals receiving a score of 3 being the top spenders).
61 The following tables (Figure 6.1-6.6) report the median revenue, median share community benefit, median share community building activities, median share physical improvements, median gross profit margin, median owner occupied, median home value, median rent, median share cost burdened for each decile category across the three charitable spending categories. A detailed discussion of the decile analysis results is included in the next chapter.
62
63
64 65 6.3 Linear Regression
Building off the analysis approach developed by Singh et al. (2015), I developed a series of regression models to estimate how the socioeconomic conditions of a hospital’s immediate vicinity, a hospital’s financial performance, and state regulatory factors explain normalized spending on community benefits, community building activities, and community building activities expenses on physical improvements and housing across the sample period. This analysis utilizes the explanatory variable set included in the decile analysis. However, to mitigate issues of multicollinearity, particularly among the socioeconomic variables, I created a correlation matrix and excluded explanatory variables with correlation coefficients that exceed .5. Motivated by interests to address SDOH, it is predicted that hospitals located in communities with lower socioeconomic status and limited affordable housing options would spend a greater proportion on community building activities and, specifically, community building activities on physical improvements and housing. To assess this hypothesis, the following an Ordinary Least Squares (OLS) regression model is utilized to evaluate normalized spending across the three dependent variables (community benefits, community building activities, and physical improvements and housing):
� = � + � � + � � + � � + � � +∈
Where � represents neighborhood housing characteristics (residential vacancy, the proportion of units renting for less than $500, the share of renters with residential costs exceeding 35 percent of income), � represents socioeconomic characteristics (poverty rate, the share of person without health insurance, and the share of person over 65 years), � state-level regulatory requirements around community benefits (unconditional community benefit requirement, conditional community benefit requirement, and minimum community benefit expenditure requirement),
� regional population characteristics (large metro, nonmetro), � the gross profit margin for the hospital, and ∈ is the error term.
66 Community Benefits Figure 6.7: Community Benefits OLS Regression
Estimate t-statistic Constant 0.12511 6.19489 *** Share occupied housing units -0.00039 -2.25675 * Share of rental units with gross rent less than $500 -0.00047 -3.44464 *** Share cost burdened renter (>35% income on rent) -0.00007 -0.41345 Poverty rate 0.00036 1.65424 . Share of residents without health insurance 0.00074 2.64245 ** Share of residents over 65 years -0.00097 -3.31076 *** Unconditional state community benefit requirement 0.00356 0.95863 Conditional state community benefit requirement 0.00254 0.78171 State minimum community benefit requirement 0.00637 1.54581 Non-metropolitan or rural county 0.00584 1.62967 metropolitan county of 1 million or more people 0.01080 3.27004 ** Gross profit margin -0.00070 -7.43938 *** Observations 2,659 Adjusted R2 0.05036 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17; ACS 2013-17
Figure 6.7 provides the summary output of the linear model evaluating community benefit spending as a share of revenue. Among the ZIP Code demographic and housing explanatory variables, occupied housing rate, the share of units renting for $500 or less, and the share of residents over 65 years all have a statistically significant negative effect on community benefits spending relative to revenue. The share of residents over 65 years has the largest explanatory effect. The share of resident without health insurance has a large, positive, and statistically significant effect on the community benefits spending rate. State-level regulations on community benefits, while all positive, does not have a statistically significant effect on community benefit spending. Location in a metropolitan area of a million or more people has a positive and statistically significant impact on community benefits spending. Finally, the gross profit margin has a large and statistically significant negative impact on community benefit expenditures, suggesting that more profitable hospitals are spending less on community benefits. However,
67 overall the model has relatively low explanatory strength. The adjusted R-squared value is 5%, indicating that variation in community benefit spending is likely explained by factors not included in this model.
Community Building Activities and Physical Improvements and Housing Among the 2,659 hospital and health systems in the regression sample, 894 (34%) did not report any community building activities and 2,221 (84%) did not report any expenses on physical improvements or housing. This high proportion of zero values violates the normality assumption of the ordinary least squares regression model, as the dependent variable is “limited” by being restricted at the left-end (zero) of the distribution. This issue can be mitigated through the use of the Cragg (1971) two-set estimation—or “double hurdle”—procedure. In the first stage of the process, a Probit model is used to estimate the effect of the explanatory variables on the binary likelihood that the dependent variable is equal to zero or is great than zero. In this example, cases with no reported spending on community building activities or those who do report spending. In the second stage, the model is truncated and restricted to only the cases with positive values for the dependent variable. Restricting to these values introduces some bias into the model as the dependent variable is no longer a random sample. However, the truncated regression model works to correct for omitted values in the dependent variable. Generally, the two-stage process allows for greater interpretability by producing two separate estimates to assess the explanatory factors associated with whether or not reports spending and, for those who do report spending, which explanatory factors explain differences in the reported spending amount. An alternative approach to address the limited dependent variable is the Tobit model. The Tobit approach combines the Probit and truncated regression models in one step. This model takes the assumption that the discrete decision and the continuous decision are the same and produces one set of coefficient estimates. To assess which analysis approach to use, I perform a log likelihood test on both dependent variable models (share community benefit activity and share physical improvement and housing) to assess the Tobit model’s null hypothesis that the coefficient values for the discrete and continuous variables are the same. In each case, the Tobit model is
68 rejected in favor of Cragg’s model. The results of the Tobit regression models and test statistics are included in the Appendix (Figures 9.3-9.4). The following tables present the regression model result for the two dependent variables: share community benefit activity and share physical improvement and housing. Each model utilizes the same independent variable set included in OLS regression model described above. For both dependent variables, I included the OLS regression results (for descriptive and comparative purposes), the Probit regression result, and the Truncated regression results.
Figure 6.8: Community Building Activities Regression Output OLS Regression Probit Regression Truncated Regression Estimate t-statistic Estimate t-statistic Estimate t-statistic Constant -3.50E-04 -0.19992 0.06102 0.15034 -4.1728 -5.1220 *** Share occupied housing units (%) 7.09E-06 0.46839 0.01035 2.95416 ** 0.0094 1.9500 . Share of rental units with gross rent less than $500 (%) 5.61E-06 0.47292 -0.01086 -3.93142 *** 0.0118 3.3672 *** Share cost burdened renter (>35% income on rent) (%) -4.46E-06 -0.31906 -0.00351 -1.06499 0.0018 0.3945 Poverty rate (%) -4.12E-06 -0.21853 0.01221 2.75688 ** -0.0228 -3.0374 ** Share of residents without health insurance (%) -1.12E-06 -0.04645 -0.01834 -3.21868 ** 0.0124 1.3719 Share of residents over 65 years (%) 2.16E-05 0.84970 -0.00415 -0.70117 0.0277 4.0983 *** Unconditional community benefit requirement (0/1) 1.11E-03 3.45561 *** 0.21804 2.74290 ** 1.0035 6.3117 *** Conditional community benefit requirement (0/1) -3.84E-05 -0.13659 -0.35378 -5.43101 *** 0.0909 0.6934 State minimum community benefit requirement (0/1) -1.62E-04 -0.45417 -0.12450 -1.53961 -0.3916 -1.8571 . Non-metropolitan or rural county (0/1) 4.53E-04 1.45875 0.00971 0.13254 1.0336 5.1849 *** Metropolitan county of 1,000,000+ (0/1) 1.69E-04 0.59018 -0.16001 -2.35442 * 0.6358 3.7743 ** Gross profit margin (%) 1.82E-06 0.22239 0.01111 4.87855 *** -0.0117 -3.1873 **
69 Sigma NA NA NA NA 0.14028 0.00000 *** Observations 2,659 2,659 1,765 AIC: 3245.6 Test Statistics Adjusted R2: 0.04378 Pseudo- R2: 0.0518 Pseudo- R2: 0.0102 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17; ACS 2013-17
Figure 6.8 provides the summary results for the three regression models assessing community building activities. For the OLS model, the only explanatory variable that is statistically significant at the 95% confidence level or higher is the indicator for whether the state has an unconditional community benefit spending requirement. That coefficient estimate is positive and relatively large. While not statistically significant, it is notable that poverty rate and housing cost burden rate coefficient values are negative, suggesting that an increase in poverty and rates of cost burden is associated with a reduction in spending on community building activities. However, the adjusted R-square value for this model is very low (0.00438). The Probit model—which assesses the discrete probably of a hospital having any community building activity spending—produced several statistically significant coefficient estimates. Among the local socioeconomic characteristics, share occupied housing and poverty rate have a positive and statistically significant effect on the likelihood of a hospital or health system reporting a community building expense, while the share of rental units with gross rent less than $500 and the share of residents without health insurance have statistically significant negative effect. With the state regulatory indicator variables, hospital located in unconditional community benefit reporting requirements are more likely to report these expenses and hospitals located in states with conditional community benefit requirements are less likely to record any community building activities. Finally, profit margin has a large and statistically significant positive effect on the likelihood of a hospital or health system reporting these expenses. The truncated model, which restricts the sample to only hospitals with positive community building expenses, similarly produces several statistically significant coefficient estimates. The share of rental units with gross rent less than $500 and share of residents over 65 years have a statistically significant and positive effect, along with the indicator variables for unconditional state community benefit requirement, non-metropolitan or rural county and metropolitan county of 1 million or more people. Poverty rate and gross profit margin have a
70 large and statistically negative effect on reported community building expenses relative to income. In eight cases, the direction of the effect switched, including in four cases where the estimate is statistically significant in both models (share of rental units with gross rent less than $500, poverty rate, county in metropolitan area of 1 million or more people, and gross profit margin). The results are counterintuitive, as it suggests that, for example, a hospital or health system located in ZIP Codes with higher poverty rates are more likely report any community building expenses, but, among those that do report, the higher poverty rates are associated with lower share of spending reported on community building activities. This finding is discussed in greater detail in the next chapter.
Figure 6.9: Community Building Activities: Physical Improvements and Housing Regression Output OLS Regression Probit Regression Truncated Regression Estimate t-statistic Estimate t-statistic Estimate t-statistic Constant -6.41E-04 -0.73310 -0.45772 -0.93100 -11.7204 -3.8061 *** Share occupied housing units (%) 4.95E-07 0.06546 0.00162 0.37500 0.0062 0.9743 . Share of rental units with gross rent less than $500 (%) -1.93E-06 -0.32525 -0.01289 -3.76727 *** 0.0162 1.5986 . Share cost burdened renter (>35% income on rent) (%) 6.33E-06 0.90630 -0.01022 -2.63299 ** 0.0061 0.9214 Poverty rate (%) -2.74E-06 -0.29060 0.02065 4.00248 *** -0.0971 -3.4831 *** Share of residents without health insurance (%) 3.48E-06 0.28839 -0.01403 -2.09163 * 0.0524 2.9707 *** Share of residents over 65 years (%) 2.56E-05 2.01396 * -0.00622 -0.89332 0.0298 3.8451 *** Unconditional community benefit requirement (0/1) 2.48E-04 1.54106 0.09334 1.14326 0.3795 1.8452 . Conditional community benefit requirement (0/1) -1.22E-04 -0.87045 -0.40708 -5.10370 *** -4.9937 -3.0008 ** State minimum community benefit requirement (0/1) 8.03E-05 0.45037 -0.08642 -0.79261 5.4084 3.1098 ** Non-metropolitan or rural county (0/1) 5.70E-05 0.36699 -0.10762 -1.26398 9.3567 3.6560 ***
71 Metropolitan county of 1,000,000+ (0/1) 1.97E-04 1.37874 -0.10071 -1.32631 9.7765 3.6755 *** Gross profit margin (%) -1.49E-06 -0.36370 . 0.01326 4.23705 *** -0.0711 -3.7807 *** Constant NA NA NA NA 0.0362 7.8779 *** Observations 2,659 2,659 438 AIC: 2288.1 Test Statistics Adjusted R2: 0.01366 Pseudo- R2: 0.049 Pseudo- R2: 0.0106 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17; ACS 2013-17
Figure 6.9 provides the summary results for the three regression models for community building activities on physical improvements and housing. The first column provides the regression output for OLS model evaluating share of spending on physical improvement and housing relative to reported revenue. Similar to the community building model, this model has very weak explanatory value, with an adjusted R-squared value of 0.01366. Only one variable, share of residents over 65 years, has a statistically significant coefficient at the 95 percent confidence level. That estimate is positive, suggesting that hospitals located in communities with a greater proportion of senior residents are likely to spend more on physical improvement and housing expenses. The Probit regression results—which assesses the discrete probably of a hospital having any physical improvements and housing spending—are reported in the second column of Figure 6.9. The socioeconomic and housing independent variables produce somewhat counterintuitive findings. Hospitals located in ZIP Codes with higher poverty rates are more likely to report spending on physical improvements and housing and hospitals located in ZIP codes with more affordable units (units renting for less than $500) are less likely to report this spending. However, hospital located in ZIP Codes with higher housing cost burden rates and a higher proportion of uninsured residents are less likely to report spending on physical improvements and housing. The only state regulatory or urbanization indicator variable that has statistical significance is the conditional state community benefit requirement, which, as in the community building activities model, has a large negative effect on the likelihood that a hospital will report physical improvement and housing expenses. Hospitals with higher gross profit rates are more likely to report this spending.
72 The truncated regression results, which restricts the sample to only hospitals with positive physical improvements and housing expenses, are included in the last column of Figure 6.9. The share of residents without health insurance along with the indicator for state minimum community benefit requirement, metropolitan county of 1 million or more people, and non- metropolitan or rural county have a statistically significant positive effect on physical improvement and housing spending. Poverty rate, gross profit margin, and the indicator for conditional state community benefit requirement have a negative impact on this spending. Similar to the community building activity model, in nine coefficients the direction of the sign flipped between the Probit and truncated coefficients. For four of the explanatory variables that flip signs— poverty rate, gross profit margin, share of residents without health insurance, and state minimum community benefit requirement—the estimates were statistically significant in each model.
73 7. Discussion
7.1 Community Benefit and Community Building Activity Spending Trends
The descriptive analysis provides no evidence of broad increases in spending by nonprofit hospitals and health systems on charitable activities designed to address SDOH from 2010 to 2017, including housing. While community benefit expenditures grew both in aggregate dollars and as a share of hospital revenue, the expenditure were still primarily attributed to subsidized patient care and hospital operations. Notably, the declines in charity care expenses—likely related to health insurance expansion following the implementation of the ACA—appear entirely captured by the increase in unreimbursed Medicaid expenses. Charity care reported expenses declined from 24% in 2010 to 18% in 2017, while unreimbursed Medicaid increased from 30% to 43% of reported community benefit over the period, respectively. In aggregate dollars, in 2016, the latest year of complete data, over $29.1 billion of unreimbursed Medicaid costs were reported (up from $16.6 billion in 2010) a 75 percent increase. Charity care expenses, by contrast, declined from $13.2 billion in 2010 to $11.9 billion in 2016 (a 10 percent reduction). Overall, direct patient financial assistance for treatment and reimbursements for means-tested government programs grew by $12 billion and became a more dominant share of hospital community benefit expenditures (increasing from 57 percent of community benefits spending in 2010 to 63 percent in 2016). Among the community benefit expense categories that have the potential to have a SDOH or upstream-investment orientation, community health improvement services and community benefit operations and cash and in-kind contributions to community groups, spending remained relatively steady over the period. Expenses on community health improvement services and community benefit operations remained flat at 4% of community benefits and cash and in-kind contributions to community groups increased modestly from 2% to 3% of community benefit expenditures. Consistent with the growth in revenue and total community spending, the aggregate dollars spending on community health improvement services and community benefit operations increased from $2.4 billion in 2010 to $2.7 billion in 2016. Similarly, cash and in-kind contributions to community groups increased from $1.2 billion in 2010 to $1.8 billion in 2016.
74 These results are largely consistent with Alberti, Sutton, and Baker’s (2018) findings that much of the reduction in charity care following the ACA insurance expansion appear to be captured by other health service reimbursements. Additionally, that there is not a significant increase in spending on community health improvement services and community benefit operations and cash and in-kind contributions to community groups. Community building activities—the expenses which are designed to explicitly capture SDOH activities—were miniscule compared with community benefit expenses. In 2010, aggregate spending on community building activities was $455 million, less than 1% of community benefit spending that same year ($54.6 billion) and well below any individual community benefit category. Spending on community building activities peaked in 2012 at $482 million but then declined—both in share of revenue and in terms of aggregate dollars—over the period to $419 million, while aggregate revenue and spending on community benefits increased. The decline in the hospitals reporting community building expenses was more modest. It does not appear that the reduction in spending was driven by fewer hospitals reporting community building activities—in 2010 55.9% of hospitals reported community benefits and in 2016 that share dropped modestly to 54.9%. Additionally, the median reported community benefit activity remained steady over the period. Spending on physical improvements and housing declined by nearly half, from $60 million in 2010 to $34 million 2016. Similar to the community building activity category, the share of hospital reporting this expense remained fairly consistent (peaking in 2010 at 9.7% of filer and bottoming-out at 7.4% in 2014, but increasing modestly in the subsequent two years). Over the period, the median reported physical improvement and housing category for filers who reported that expense was very low ($6,981). However, the median expense increased over the period (from $5,757 in 2010 to $9,417 in 2016), but the mean expense fell (from $278,911 in 2010 to $197,133 in 2016). This divergence suggests that the overall decline in spending in this category was primary due to reductions in spending at the upper extreme, but a modest increase in general across those reporting these expenses. However, the median value is so low that difficult to imagine the spending have any tangible impact on a hospital’s local built environment or community housing stability.
75 While it is possible that the decline within the physical improvements and housing category could be attributed—at least partially—to the 2015 changes in IRS guidance on how to classify community-oriented housing activities, the findings do not seem to support it. Between 2015 and 2016, the number of filers reporting spending on physical improvements and housing increased modestly (from 8.4% of sample to 8.7%, respectively) and the median reported expense increased from $8,500 to $9,417. Although these descriptive findings cannot offer causal evidence on the impact of the IRS guidance, the findings suggest that nonprofit hospitals and health systems did not reclassify their spending en masse.
7.2 Spatial Characteristics and Charitable Spending
While the descriptive analysis suggests that there were not broad shifts in spending to address SDOH, there were hospitals and health systems who reported significant expenses. Section two of the analysis offers early evidence to understand the variation in this spending, specifically how the socioeconomic and housing conditions of a hospital’s or health system’s immediate context influences these spending decisions.
Socioeconomic and Housing Conditions For community benefit expenses, there is evidence that the socioeconomic and housing conditions of the ZIP Code effect the spending level normalized to revenue. Comparing the ZIP Codes of hospitals in the top decile of community benefit spending to the bottom decline, the top decile had lower home owner occupancy rates, higher rents, higher cost housing cost burden rates, higher insurance rates, and higher poverty rates. These results largely held in the OLS regression analysis. Share occupied housing units, share of rental units with gross rent less than $500 (as a measure of affordable housing units), and share of residents over 65 years have a statistically significant negative effect on normalized community benefits spending. Additionally, share of residents without health insurance has a statistically significant and positive effect on spending. However, the 5% adjusted R-squared value of the OLS model suggests that the model has weak explanatory value and additional unobserved factors are likely contributing to majority of differences in spending.
76 For community building activities and expenditures on physical improvements and housing, the effect of a hospital’s immediate socio-economic context is less certain. The decile analysis—while limited due to the heightened proportion hospitals who report no expenses—does not offer a clear pattern relationship among hospitals who share similar proportional levels of spending community building activities or physical improvements and housing. The Probit regression analysis offers evidence on how the explanatory influence whether or not a hospital reports any spending on these charitable expenses across the period. The results suggest that hospitals located in communities with higher poverty rates, a lower proportion of units renting for $500 or less, lower vacancy rates, and a lower share uninsured people are more likely to report spending on community building activities. The Probit results are largely similar for physical improvements and housing model: hospitals and health systems located in communities with higher poverty rates, a lower proportion of units renting for under $500, and a lower rate of uninsured residents are more likely to report physical improvement and housing expenditures. Surprisingly, hospitals located in communities with higher housing cost burden rates are statistically less likely to report this spending. Results seem to suggest that hospitals located in ZIP Codes with high poverty rates, but stronger housing markets (i.e., low vacancy and higher rents) tend to spend more on community building activities and physical improvements and housing. The negative coefficient value for renter housing cost burden—particularly for the physical improvements and housing expense—is counterinitiative. It could suggest that a greater proportion of residents in these ZIP Codes are homeowners or live in deed-restricted affordable housing, but there is little additional evidence to support this speculation. The truncated regression model is used to assess variation within hospital and health systems that report spending on community benefit activities and physical improvements and housing. In both dependent variable specifications, the regression model produced several statistically significant results that show an opposite relationship to what was produced in the Probit specification. A value in Cragg’s two-step estimate approach is that it allows the explanatory variables to differ in magnitude, size, and significant between a binary outcome and the continuous outcome. In the gross profit margin explanatory variable, it makes intuitive sense
77 that hospitals with higher profit margins are likely to report spending on community benefit activities or physical improvements and housing than those with low-to-no profit who may not have the resources for any charitable spending. However, limited to only hospitals with reported spending, a higher profit margin would be associated with a lower normalized spending on these charitable activities as they would increase hospital expenditures and reduce profit. However, the change of sign in the poverty rate explanatory variable in the truncated model, indicating that hotels located in higher poverty neighborhoods spend less on community building activities and physical improvements and housing, is difficult to interpret. In general, the coefficient values for the ZIP Code socioeconomic factors are low in both truncation models, suggesting they have lower magnitude in explaining the variation in spending than the other explanatory variables. While higher rates of uninsured residents might generally reflect lower socioeconomic status and be a motivating factor for hospitals and health systems to engage in activities designed to address SDOH, in both Probit models assessing community benefit activities and physical improvement and housing spending higher uninsured residents is negatively associated with spending. It seems likely that this finding is due to the hospital dedicating more of their charitable spending to subsidized patient care rather than community building activities or housing. Notably, the decile analysis suggests that hospitals who report the highest rates of community benefit spending relative to income tend to report lower levels of community building activities. The relationship does not appear to be linear—as hospitals with very low rates of community benefit expenditures tend to have very low rates of community benefit activities. Reviewing the Figure 6.1, median community benefit expense increases modestly across deciles of community benefit spending until it maxes in decile 8 at 0.0144% of revenue before falling by half to 0.0069% in the top decile of community benefit expenditures. Among the 10 hospital who report the highest rate of spending on community benefits relative to income, eight do not report any community building activities. However, the lack of community building activities does not necessarily reflect a lack of spending on activities designed to address SDOH. Among the eight cases without community building activities, in three over half of community benefit spending were classified as community health improvement services or cash and in-kind contributions to community groups.
78
Other Characteristics Among the state regulatory variables, being located in a state with a conditional community benefit requirement (i.e., providing charity care and/or participating in the state’s Medicaid program is required to receive state tax exemptions or licensing) is strongly negatively associated with a hospital’s likelihood of reporting community building activities or physical improvements and housing expenses. While the conditional community benefit requirement is positively associated with community benefits spending, the estimate is not statistically significant nor is it large. Unconditional state community benefit requirement (i.e., an explicit requirement that nonprofit hospitals provide charity care and participate in the state’s Medicaid program) is a statistically significant and positive predictor of community building activities across the three regression models, but, while positive, is not statistically significant or large in any of the physical improvements and housing regression models. While positively associated, it is notable that neither of these indicators, which govern hospital community benefit spending in the state, are statistically significant or large in the community benefits OLS model. It is likely that the results observed in the community building activities or physical improvements and housing models are attributable to other conditions in the state other than the regulatory restrictions around community benefit spending. Hospital gross profit margin is negatively associated with reported charitable spending in the OLS community benefits regression and the two truncated models. The coefficients were statistically significant and generally had a large magnitude in each model. Additionally, the metropolitan and urbanization characteristics of the hospital had some measurable effects on reported hospital charitable activities. Hospital located in metropolitan areas with 1 million or more people tend to spend more on community benefits, but were less likely to report community building activities or physical improvement and housing expenses (although physical improvement and housing was not statistically significant).
79 7.3 Limitations and Future Research
While the regression analysis offers early evidence into how socio-spatial factors may influence hospital charitable practices, there are modeling limitations that discount the interpretability of the results. In particular, the high proportion of nonprofit hospitals and health systems reporting no community building activity and, in particular, no spending on physical improvement and housing expenses introduces sampling bias into the regression analysis. While Cragg’s two-step model seeks to correct for this bias, there remains unobserved error that limits its interpretability. Broadly, the limited explanatory strength of the regression analysis models (as demonstrated by the low R2 and pseudo-R2 values) suggest that variations in hospital and health system charitable practices, particularly those related to social determinants of health, are influence by factors beyond neighborhood socioeconomic context, profitability, state regulations, and regional urban development. Additionally, there are likely issues in the models stemming from omitted variable bias that would affect the estimates and reduce the validity of the findings. Despite their widespread use in social research and policy analysis, ZIP Codes—which are standardized geographies introduced by the U.S. Postal Service as a means of maximizing postal processing and delivery efficiency—are an imprecise means of understanding the immediate neighborhood context of a hospital or health system (U.S. Postal Service Office of Inspector General 2013). It seems almost certain that most hospitals and health systems do not look to their ZIP Code boundaries when seeking to understand their patient-base and where to make targeted interventions to address SDOH. Future research might seek to align the community boundaries determined by a hospital’s CHNA process as a more precise method of analyzing community context for a hospital or health system. However, given the decentralized and hospital-led nature of the CHNA process, determining a systematic approach to find and analyze a CHNA geography would be challenging. The uncertainty around how nonprofit hospitals and health systems classify charitable spending on housing and other upstream activities designed to address social determinants of health is an important caveat to this work. While the descriptive findings do no suggest that there were widespread reductions in reported spending on physical improvements and housing and corresponding increase in community benefits expenses that could have a SDOH focus (i.e.,
80 “community health improvement services and community benefit operations” and “cash and in- kind contributions to community groups”) following the 2015 change in IRS guidance, it is impossible to know how an individual hospital or health system classifies these expenses through Form 990 reporting alone. As long as IRS retains the same charitable expenses reporting framework, future research would benefit from a qualitative study of how nonprofit hospital and health system accountants and tax professionals itemize charitable expenditures and interpret IRS guidance on the subject. The quantitative analysis in thesis is restricted to nonprofit hospital and health system spending on housing as reported as a charitable expense. However, the activities hospitals and health systems engage in and fund in this space extend beyond those that reported annually to the IRS. In particular, investments in housing where there is an expectation that capital could return to the institution (e.g., low- or no-interest loans) are current ineligible to be reported as community benefits or community building activities. These components are important factors in the ecosystem of affordable housing that are missing from the Form 990 filing records. Additionally, more research is needed to assess how these expenses are itemized and tracked within a hospital system and which expenses are ultimately reported each year. Given the history of community benefits reporting and regulations, it seems likely that hospitals are better suited organizationally to track and quantify expenses related to direct patient care than those with an external community orientation (e.g., housing investments). Research in this field would benefit from an in-depth qualitative study involving interviews with nonprofit hospital and health system accountants, tax professionals, and managers.
7.4 Implications and Recommendations
It is notable that total community building activities declined from 2010-17 both in aggregate dollar figures and as a share of total revenue, despite the comparative rise in revenue and community benefits spending. While additional research is needed to understand the causal factors driving this trend, insight from the Urban Institute (2019) survey suggest that confusion remains as to what counts as a community building activity versus a community benefit and how to classify housing, specifically. Although it is unknown whether the uncertainty around
81 regulations impact hospital investment decision, the research suggest there may be hesitation to report these expenses or limited understanding that these programs could count as a charitable expense. To address the uncertainty, the IRS’s charitable expense reporting framework would benefit from combining community benefits and community building activities into a single standard to avoid confusion around whether activities such as housing “counts” towards meeting their charitable activities. This action would further reinforce the policy of recognizing actions to address the SDOH on equal footage to direct patient care, research, and staff professional development. However, the detailed reporting categories that the community building activities section includes (e.g., physical improvements and housing, economic development) does provide researchers, advocates, and government officials with a unique window to see which charitable activities these institutions engage in. The IRS should consider retaining the specificity of the reporting categories under the larger single umbrella of community benefits. It is striking that despite the expansion of insurance coverage following the implementation of the ACA, the proportion of community benefits expenses reported as subsidized patient care increase both in aggregate dollars and as a share of overall community benefit expenses. This growth was largely driven by increases in reported unreimbursed Medicaid costs, which far eclipsed reductions in charity care expenses following insurance expansion. While the primary goal of the ACA was not to reorient hospital chartable practices towards community health investments, the perceived reduction in the demand for charity care—along with the implementation of the CHNA requirement—was viewed by many as a way of incentivizing hospitals to invest in targeted community health measures. These descriptive finding suggest there are limitations to using IRS’s charitable spending regulations as a primary means of driving nonprofit hospital and health systems to invest in SDOH, particularly housing. The potential shift in the healthcare sector from fee-for-service model towards a population-health-focused value- based care framework, as well as new financial penalties for readmittance, are likely to be the larger drivers of change in orientation for nonprofit hospitals and health systems towards community health (Burrill and Thomas 2017).
82 Despite the limitations, the regression analysis offers early evidence that hospital spending on community benefits, community building activities, and physical improvements and housing is not random and is, at least partially, shaped by the local socioeconomic factors. This research suggests that these institutions are responding to local needs and that if the incentives and penalties change to place additional priority on these upstream investments, hospitals and health system could be well-position to make effective investments and program decisions to address the SDOH. However, significant questions remain about the capacity of these heterogenous institutions to reorient their charitable practices en masse towards community health. Additionally, given the scale and impact of the interventions, there are serious concerns around governance, process, and community participation for hospitals and health systems in making these investment and program decisions which have life-and-death consequences. An effective and just transition in a hospital’s community orientation cannot occur through shifting financial incentives alone.
83 8. Conclusion
Between 2008 and 2017, a confluence of factors—including increased research on SDOH, federal and state regulatory changes, nonprofit technical assistance, and high-profile hospital success stories—have coincided to create favorable conditions for nonprofit hospitals and health systems to make charitable investments to address SDOH. However, this analysis found that, by- in-large, the charitable practices of hospitals and health systems did not respond in kind. Reported community building activities declined both in aggregate dollar figures and as a share of total revenue from 2010 to 2017, despite a rise in revenue and community benefits spending. Additionally, the community benefit expense categories with a potential SDOH orientation— “community health improvement services and community benefit operations” and “cash and in- kind contributions to community groups”—remained flat over the period. These findings suggest that impediments remain which are discouraging hospitals and health systems from making these investments. Further research is needed to understand the contributing factors. While the findings do not indicate widespread investment in activities designed to address SDOH, several hospitals did report substantial spending on community building activities and on housing, specifically. The regression analysis suggests that differences in the likelihood of reporting these investments and the amount of spending are at least partially explained by variations in the socioeconomic characteristics of hospital’s immediate community. While these findings suggest that hospital and health systems are responding to local conditions, the low explanatory strength of the models indicate that other factors are likely the primary motivation for this spending. The limited explanatory strength is understandable. Nonprofit hospitals and health systems are heterogeneous institutions and the motivations influencing their decisions to invest in efforts to improve local housing and address other social determinants of health are dynamic and varied. While further research is needed, this analysis offers a first step for understanding how charitable spending on activities designed to address SDOH reflect local conditions. The community benefit standard is a blunt instrument for directing hospitals and health systems’ charitable practices. Absent a minimum community building activity requirement, it appears unlikely that the standard alone will lead to increased nonprofit hospital and health
84 system spending on activities to address the social determinants of health. However, when complemented with the CHNA process, the community benefits framework recognizes and supports hospitals and health systems engaging in innovative activities designed to improve community health and combat disparities. Additionally, the framework remains a critical tool for promoting transparency in nonprofit hospital and health system charitable practices. As pressure builds for a reorientation of the healthcare sector from a fee-for-service model towards a value- based care framework that focuses on population health, the community benefits standard and CHNA process have the potential to be critical complementary tools in directing activities to address the social and structural factors that perpetuate health disparities. The unfolding tragedy of the COVID-19 pandemic has renewed the public conversation on racial health disparities and the urgent need to address the social and structural determinants of health. As of this writing, reports indicate that communities of color are suffering disproportionately higher rates of illness and mortality from the virus and it is likely the trend will continue (CDC 2020). These discrepancies reflect deeply-rooted economic, social, and environments injustices that persist in the United States. While nonprofit hospitals and health systems alone cannot solve the structural factors that contribute to economic and racial health disparities, these institutions as a whole command significant economic and political power. It is my hope that the crisis will spur government and healthcare leaders to take decisive action to address these root issues.
85 9. Appendix
Figure 9.1: Hospitals or Health Systems with the Highest Aggregate Reported Spending Community Building Activities, 2010-17 Communit Phys. Community Communit y Building Improv. & Regio Building y Benefits Activities Housing Organization Name Location n Revenue Activities (%) (%) (%) n Boston Medical Boston, Metro $127,770,24 Center MA (1M+) $7,974,989,756 6 12.56% 1.60% 0.01% 7 Altamont Adventist Health e Springs, Metro $24,462,837,46 $113,017,50 System Sunbelt Inc FL (1M+) 3 1 11.67% 0.46% 0.00% 7 Multicare Health Tacoma, Metro $11,912,442,71 $109,502,13 System WA (1M+) 3 9 9.88% 0.92% 0.05% 7 Community Metro Hospital Of The Monterey (250K Monterey Peninsula , CA -1M) $3,924,731,140 $90,410,213 13.79% 2.30% 0.00% 8 Metro Lakeland Regional Lakeland, (250K Medical Center Inc FL -1M) $5,118,348,248 $89,205,636 12.88% 1.74% 0.00% 7 Woodlan Motion Picture And d Hills, Metro Television Fund CA (1M+) $626,308,939 $84,991,774 19.18% 13.57% 12.42% 8 Children's Hospital & Research Center Oakland, Metro At Oakland CA (1M+) $3,732,419,373 $54,965,774 19.67% 1.47% 0.00% 7 Leesburg Regional Leesburg, Metro Medical Center Inc FL (1M+) $1,943,218,378 $46,473,352 5.43% 2.39% 2.39% 8 Metro Saint Francis (250K Hospital Inc Tulsa, OK -1M) $7,743,160,050 $44,844,434 8.13% 0.58% 0.02% 8 Mount Sinai Medical Center of Miami Metro Florida Inc Beach, FL (1M+) $4,759,933,754 $44,356,569 9.74% 0.93% 0.13% 8 Source: Author’s analysis of IRS Form 990 filings, 2010-17
Figure 9.2: Hospital or Health Systems with the Highest Aggregate Reported Spending on Physical Improvements and Housing, 2010-17 Phys. Community Improv. Phys. Building & Organization Improv. & Community Activities Housing Name Location Region Revenue Housing Benefits (%) (%) (%) n Motion Picture and Woodland Metro Television Fund Hills, CA (1M+) $626,308,939 $77,782,108 19% 14% 12% 8
86 Leesburg Regional Leesburg, Metro Medical Center Inc FL (1M+) $1,943,218,378 $46,473,352 5% 2% 2% 8 The Villages Tri- county Medical The Metro Center Inc Villages, FL (1M+) $1,318,002,423 $29,489,353 5% 2% 2% 8 Uintah Basin Roosevelt, Non- Medical Center UT metro $541,522,032 $13,360,241 3% 2% 2% 7 Bon Secours Hospital Baltimore Baltimore, Metro Inc MD (1M+) $902,635,782 $9,330,657 13% 2% 1% 7 Ochsner Clinic New Metro Foundation Orleans, LA (1M+) $47,412,566,092 $8,153,967 1% 0% 0% 8 San Francisco, Metro Dignity Health CA (1M+) $68,168,364,185 $7,941,245 10% 0% 0% 7 Connecticut Childrens Medical Hartford, Metro Center CT (1M+) $2,031,004,157 $7,363,136 25% 1% 0% 7 Fall River Health Hot Springs, Non- Services SD metro $123,163,885 $6,964,084 8% 6% 6% 8 Nationwide Children's Hospital Columbus, Metro Group Return OH (1M+) $11,811,168,350 $6,840,537 9% 0% 0% 8 Source: Author’s analysis of IRS Form 990 filings, 2010-17
Figure 9.3: Community Building Activities Tobit Regression Output Tobit Regression Estimate t-statistic Constant -3.724e-03 -1.537 Share occupied housing units (%) 3.507e-05 1.671 Share of rental units with gross rent less than $500 (%) -2.06E-05 -1.261 . Share cost burdened renter (>35% income on rent) (%) -1.37E-05 -0.716 Poverty rate (%) 2.50E-05 0.983 Share of residents without health insurance (%) -4.47E-05 -1.361 Share of residents over 65 years (%) 1.59E-05 0.463 Unconditional community benefit requirement (0/1) 1.64E-03 3.862 *** Conditional community benefit requirement (0/1) -9.76E-04 -2.534 * State minimum community benefit requirement (0/1) -5.70E-04 -1.135 Non-metropolitan or rural county (0/1) 5.52E-04 1.311 Metropolitan county of 1,000,000+ (0/1) -1.83E-04 -0.473
87 Gross profit margin (%) 3.85E-05 2.829 ** logSigma -4.95E+00 -290.175 *** Observations 2,659 Test Statistics 5697.134 on 14 Df Log likelihood comparative test statistic 5510.16 on 13 DF Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17; ACS 2013-17
Figure 9.4: Community Building Activities: Physical Improvements and Housing Tobit Regression Output Tobit Regression Estimate t-statistic Constant -7.195e-03 -2.014 *
Share occupied housing units (%) 9.646e-06 0.311 Share of rental units with gross rent less than $500 (%) -7.885e-05 -3.105 ** Share cost burdened renter (>35% income on rent) (%) -4.036e-05 -1.422 Poverty rate (%) 1.084e-04 2.886 ** Share of residents without health insurance (%) 6.901e-05 -1.398 Share of residents over 65 years (%) 2.327e-05 0.474 Unconditional community benefit requirement (0/1) 9.372e-04 1.577 Conditional community benefit requirement (0/1) -2.654e-03 -4.405 *** State minimum community benefit requirement (0/1) -2.390e-04 -0.293 Non-metropolitan or rural county (0/1) -4.793e-04 -0.757 Metropolitan county of 1,000,000+ (0/1) -1.322e-04 -0.236 Gross profit margin (%) 7.107e-05 2.948 ** logSigma -4.906e+00 - 140.201 *** Observations 2,659 Test Statistics 948.349 on 14 Df Log likelihood comparative test statistic 1903.114 on 13 Df Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Author’s analysis of IRS Form 990 filings, 2010-17; ACS 2013-17
88 10. Work Cited
AAMC. 2017. “Teaching Hospitals’ Commitment to Addressing the Social Determinants of Health.” Association of American Medical Colleges. https://www.aamc.org/data- reports/faculty-institutions/report/teaching-hospitals-commitment-addressing-social- determinants-health. Alberti, Philip, Karey Sutton, and Matthew Baker. 2018. “Changes in Teaching Hospitals’ Community Benefit Spending After Implementation of the Affordable Care Act.” Academic Medicine 93 (May): 1. https://doi.org/10.1097/ACM.0000000000002293. Amazon Web Services. 2020. “IRS 990 Filings - Registry of Open Data on AWS.” Amazon Web Services. 2020. https://registry.opendata.aws/irs990/. American Hospital Association. 2017. “Housing and the Role of Hospitals.” American Hospital Association. https://www.aha.org/system/files/hpoe/Reports-HPOE/2017/housing-role- of-hospitals.pdf. Artiga, Samantha, and Elizabeth Hinton. 2018. “Beyond Health Care: The Role of Social Determinants in Promoting Health and Health Equity.” Disparities Policy. KFF. https://www.kff.org/disparities-policy/issue-brief/beyond-health-care-the-role-of- social-determinants-in-promoting-health-and-health-equity/. Ayala, Mary, and Julie Trocchio. 2018. “Housing and Community Benefits: What Counts?” Catholic Health Association of the United States. https://www.chausa.org/docs/default- source/health-progress/community-benefit-housing-and-community-benefit-what- counts.pdf?sfvrsn=0. Bai, Ge, and Gerard F. Anderson. 2016. “A More Detailed Understanding Of Factors Associated With Hospital Profitability.” Health Affairs 35 (5): 889–97. https://doi.org/10.1377/hlthaff.2015.1193. Blumenthal, David, and Melinda K. Abrams. 2016. “Tailoring Complex Care Management for High-Need, High-Cost Patients.” JAMA 316 (16): 1657–58. https://doi.org/10.1001/jama.2016.12388. BMC. 2017. “Boston Medical Center to Invest $6.5 Million in Affordable Housing to Improve Community Health and Patient Outcomes, Reduce Medical Costs.” Boston Medical Center. December 7, 2017. https://www.bmc.org/news/press- releases/2017/12/07/boston-medical-center-invest-65-million-affordable-housing- improve. ———. 2018. “BMC Invests $6.5 Million to Help Combat Homelessness.” Boston Medical Center. March 5, 2018. https://www.bmc.org/about-us/stories/bmc-invests-65-million-help- combat-homelessness. Braubach, Matthias, and Jon Fairburn. 2010. “Social Inequities in Environmental Risks Associated with Housing and Residential Location—a Review of Evidence.” European Journal of Public Health 20 (1): 36–42. https://doi.org/10.1093/eurpub/ckp221.
89 Braveman, Paula, and Laura Gottlieb. 2014. “The Social Determinants of Health: It’s Time to Consider the Causes of the Causes.” Public Health Reports 129 (1_suppl2): 19–31. https://doi.org/10.1177/00333549141291S206. Brown, S., S. Bains, and S. Escobar. 2018. “302 The Better Health Through Housing Program: Applying the Housing First Model in an Urban Emergency Department.” Annals of Emergency Medicine 72 (4): S119. https://doi.org/10.1016/j.annemergmed.2018.08.307. Burrill, Steve, and Sarah Thomas. 2017. “Population Health Management Models and Value- Based Care.” Deloitte US. https://www2.deloitte.com/us/en/pages/life-sciences-and- health-care/articles/population-health-based-model.html. CDC. 2020. “Coronavirus Disease 2019 (COVID-19).” Centers for Disease Control and Prevention. April 22, 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra- precautions/racial-ethnic-minorities.html. Center for Community Investment. 2019. “Announcing AIHC Participants: Six Hospitals and Health Systems Step Up Efforts to Increase Affordable Housing in Their Regions | Center for Community Investment.” Center for Community Investment. February 20, 2019. https://centerforcommunityinvestment.org/blog/announcing-aihc-participants-six- hospitals-and-health-systems-step-efforts-increase-affordable. ———. n.d. “Accelerating Investments for Healthy Communities | Center for Community Investment.” Center for Community Investment. Accessed May 10, 2020. https://centerforcommunityinvestment.org/accelerating-investments-healthy- communities. CHA. 2008. “Press Conference - Explaining the New Rules for Measuring Community Benefit.” Health Progress: Journal of the Catholic Health Association of the United States. October 2008. https://www.chausa.org/publications/health-progress/article/september-october- 2008/press-conference---explaining-the-new-rules-for-measuring-community-benefit. ———. 2015. “Community Benefit Categories and Definitions.” Catholic Health Association of the United States. https://www.chausa.org/communitybenefit/what-counts. ———. 2020. “About.” Catholic Health Association of the United States. 2020. https://www.chausa.org/about/about. Community Benefit Insights. 2020. “Data Sources.” Community Benefit Insight: RTI International. 2020. http://www.communitybenefitinsight.org/?page=info.data_sources. Culhane, Dennis P, Stephen Metraux, and Trevor Hadley. 2002. “Public Service Reductions Associated with Placement of Homeless Persons with Severe Mental Illness in Supportive Housing.” Housing Policy Debate 13 (1): 107–63. https://doi.org/10.1080/10511482.2002.9521437. Cunningham, Mary, and Samantha Batko. 2018. “Rapid Re-Housing’s Role in Responding to Homelessness.” The Urban Institute. Cutts, Diana Becker, Alan F. Meyers, Maureen M. Black, Patrick H. Casey, Mariana Chilton, John T. Cook, Joni Geppert, et al. 2011. “US Housing Insecurity and the Health of Very Young
90 Children.” American Journal of Public Health 101 (8): 1508–14. https://doi.org/10.2105/AJPH.2011.300139. Edgar, John. 2018. “Getting Ahead of Gentrification in the South Side of Columbus.” Shelterforce (blog). May 7, 2018. https://shelterforce.org/2018/05/07/building-a-sustainable-mixed- income-community-in-south-side-columbus/. Enterprise Community Partners. 2018. “Housing and Community Benefit: What Counts?” Enterprise Community Partners. https://www.enterprisecommunity.org/resources/housing-and-community-benefit- what-counts-6230. Fletcher, Jason M., Tatiana Andreyeva, and Susan H. Busch. 2009. “Assessing the Effect of Increasing Housing Costs on Food Insecurity.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1503043. Flex Monitoring Team. 2009. “A Community Benefit Reporting Toolkit for Critical Access Hospitals.” Flex Monitoring Team: University of Minnesota, University of North Carolina at Chapel Hill, University of Southern Maine. https://www.ruralcenter.org/resource- library/a-community-benefit-reporting-toolkit-for-critical-access-hospitals. Hacke, Robin, and Katie Deane. 2017. “Improving Community Health by Strengthening Community Investment.” Center for Community Investment. https://www.rwjf.org/en/library/research/2017/03/improving-community-health-by- strengthening-community-investment.html. Hansen, Pat. 2011. “New Medical Center Opens.” Montana Standard, September 25, 2011. https://mtstandard.com/business/local/new-medical-center-opens/article_a8f5130a- e71b-11e0-a722-001cc4c002e0.html. Hood, Carlyn, Keith Gennuso, Geoffrey Swain, and Bridget Catlin. 2015. “County Health Rankings: Relationships Between Determinant Factors and Health Outcomes.” American Journal of Preventive Medicine 50 (November). https://doi.org/10.1016/j.amepre.2015.08.024. IRS. 1969. “Rev. Rul. 69-545, 1969-2 C.B. 117.” Internal Revenue Service. https://www.irs.gov/pub/irs-tege/rr69-545.pdf. ———. 2011. “Notice and Request for Comments Regarding the Community Health Needs Assessment Requirements for Tax-Exempt Hospitals.” Notice 2011-52. Part III - Administrative, Procedural, and Miscellaneous. Internal Revenue Service. https://www.irs.gov/pub/irs-drop/n-11-52.pdf. ———. 2019a. “Schedule H (Form 990): Hospitals.” Internal Revenue Service. Cat. No. 50192T. https://www.irs.gov/pub/irs-pdf/f990sh.pdf. ———. 2019b. “2019 Instructions for Schedule H (Form 990).” Internal Revenue Service. https://www.irs.gov/pub/irs-pdf/i990sh.pdf. ———. 2019c. “Community Health Needs Assessment for Charitable Hospital Organizations - Section 501(r)(3).” Internal Revenue Service. September 20, 2019.
91 https://www.irs.gov/charities-non-profits/community-health-needs-assessment-for- charitable-hospital-organizations-section-501r3. ———. 2020a. “Exempt Organizations Update Archive.” Internal Revenue Service. January 31, 2020. https://www.irs.gov/charities-non-profits/exempt-organizations-update-archive. ———. 2020b. “Form 990 Resources and Tools.” Internal Revenue Service. March 19, 2020. https://www.irs.gov/charities-non-profits/form-990-resources-and-tools. Joint Center for Housing Studies. 2014. “The State of the Nation’s Housing 2014.” Text. Joint Center for Housing Studies of Harvard University. https://www.jchs.harvard.edu/research-areas/reports/state-nations-housing-2014. Kaiser Family Foundation. 2020. “State Health Facts: Hospitals by Ownership Type.” The Henry J. Kaiser Family Foundation. February 21, 2020. https://www.kff.org/other/state- indicator/hospitals-by-ownership/. Kramer, Michael R., and Carol R. Hogue. 2009. “Is Segregation Bad for Your Health?” Epidemiologic Reviews 31 (1): 178–94. https://doi.org/10.1093/epirev/mxp001. Kyle, Tania, and James R. Dunn. 2008. “Effects of Housing Circumstances on Health, Quality of Life and Healthcare Use for People with Severe Mental Illness: A Review.” Health & Social Care in the Community 16 (1): 1–15. https://doi.org/10.1111/j.1365-2524.2007.00723.x. Maness, David L, and Muneeza Khan. 2014. “Care of the Homeless: An Overview.” Edited by David L Maness. American Family Physician 89 (8): 634–40. Marcuse, Peter, and David J. Madden. 2016. In Defense of Housing : The Politics of Crisis. Politics of Crisis. London: Verso. Massachusetts Department of Public Health. 2020. “Determination of Need (DoN).” Commonwealth of Massachusetts Department of Public Health. 2020. https://www.mass.gov/determination-of-need-don. McElhaney, Alicia. 2018. “Big Returns for Health Care Nonprofits in 2017.” Institutional Investor (blog). September 11, 2018. https://www.institutionalinvestor.com/article/b19xcxqqqdklvz/Big-Returns-for-Health- Care-Nonprofits-in-2017. Meiksins, Rob. 2015. “Judge Terms Modern Nonprofit Hospitals a ‘Legal Fiction.’” Non Profit News | Nonprofit Quarterly (blog). July 7, 2015. https://nonprofitquarterly.org/judge-terms- modern-nonprofit-hospitals-a-legal-fiction/. MPTF. 2020. “Living & Thriving on Campus.” MPTF. 2020. https://mptf.com/campus/. Nationwide Children’s Hospital. 2018. “The South Side Renaissance Fund Expanding Healthy Homes and South Side Renaissance Homes.” Nationwide Children’s Hospital. July 20, 2018. https://www.nationwidechildrens.org/newsroom/news-releases/2018/07/the- south-side-renaissance-fund-expanding-healthy-homes-and-south-side-renaissance- homes. Pennsylvania Office of Attorney General. 2019. “Press Release: Attorney General Josh Shapiro Announces Legal Action Against UPMC for Violating Pennsylvania’s Charities Laws.”
92 Pennsylvania Office of Attorney General (blog). February 7, 2019. https://www.attorneygeneral.gov/taking-action/press-releases/attorney-general-josh- shapiro-announces-legal-action-against-upmc-for-violating-pennsylvanias-charities- laws/. Pollack, Craig Evan, Beth Ann Griffin, and Julia Lynch. 2010. “Housing Affordability and Health Among Homeowners and Renters.” American Journal of Preventive Medicine 39 (6): 515–21. https://doi.org/10.1016/j.amepre.2010.08.002. Principe, Kristine, E. Kathleen Adams, Jenifer Maynard, and Edmund R. Becker. 2011. “The Impact of the Individual Mandate and Internal Revenue Service Form 990 Schedule H on Community Benefits From Nonprofit Hospitals.” American Journal of Public Health 102 (2): 229–37. https://doi.org/10.2105/AJPH.2011.300339. Reynolds, Kathryn, Eva Allen, Martha Fedorowicz, and Joycelyn Ovalle. 2019. “Affordable Housing Investment: A Guide for Nonprofit Hospitals and Health Systems.” The Urban Institute. Ropes & Gray. 2016. “Massachusetts Determination of Need Proposed Regulations.” Ropes & Gray. September 30, 2016. http://www.ropesgray.com/en/newsroom/alerts/2016/September/Massachusetts- Determination-of-Need-Proposed-Regulations. Rosenbaum, Sara. 2013. “Principles to Consider for the Implementation of a Community Health Needs Assessment Process.” The George Washington University. https://nnphi.org/wp- content/uploads/2015/08/PrinciplesToConsiderForTheImplementationOfACHNAProce ss_GWU_20130604.pdf. Rosenbaum, Sara, Maureen Byrnes, and Amber M Rieke. 2013. “Hospital Tax-Exempt Policy: A Comparison of Schedule H and State Community Benefit Reporting Systems.” Frontiers in Public Health Services and Systems Research 2 (1). https://doi.org/10.13023/FPHSSR.0201.03. Rosenbaum, Sara, David A. Kindig, Jie Bao, Maureen K. Byrnes, and Colin O’Laughlin. 2015. “The Value Of The Nonprofit Hospital Tax Exemption Was $24.6 Billion In 2011.” Health Affairs 34 (7): 1225–33. https://doi.org/10.1377/hlthaff.2014.1424. Salinsky, Eileen. 2009. “Schedule H: New Community Benefit Reporting Requirements for Hospitals.” National Health Policy Forum: The George Washington University. http://www.nhpf.org/library/background-papers/BP67_ScheduleH_04-21-09.pdf. Sandel, Megan, and Matthew Desmond. 2017. “Investing in Housing for Health Improves Both Mission and Margin.” JAMA 318 (23): 2291–92. https://doi.org/10.1001/jama.2017.15771. Scally, Corianne, Brandi Gilbert, Carl Hedman, Amanda Gold, and Lily Posey. 2018. “Rental Housing for a 21st Century Rural America.” The Urban Institute. https://www.urban.org/sites/default/files/publication/99045/rental_housing_for_a_21st _century_rural_america.pdf. Scally, Corianne, Elaine Waxman, and Ruth Gourevitch. 2017. “Good Neighbors Make Better Partners: Emerging Strategies for Integrating Health and Housing.” The Urban Institute.
93 Singh, Simone R., Gary J. Young, Shoou-Yih Daniel Lee, Paula H. Song, and Jeffrey A. Alexander. 2015. “Analysis of Hospital Community Benefit Expenditures’ Alignment With Community Health Needs: Evidence From a National Investigation of Tax-Exempt Hospitals.” American Journal of Public Health 105 (5): 914–21. https://doi.org/10.2105/AJPH.2014.302436. Somerville, Martha. 2014. “Hospital Community Benefits: Opportunities for Healthy Homes.” National Center for Healthy Housing. https://nchh.org/resource/technical- brief_hospital-community-benefits_opportunities-for-healthy-homes/. Somerville, Martha, Gayle Nelson, Carl Mueller, Cynthia Boddie-Willis, and Donna Folkemer. 2012. “Hospital Community Benefits after the ACA: Community Building and the Root Causes of Poor Health.” The Hilltop Institute - University of Maryland, Baltimore County. https://www.hilltopinstitute.org/publication/hospital-community-benefits-after-the-aca- community-building-and-the-root-causes-of-poor-health/. Steinwald, A. 2008. “Nonprofit Hospitals: Variation in Standards and Guidance Limits Comparison of How Hospitals Meet Community Benefit Requirements.” United States Government Accountability Office. Taylor, Lauren. 2018. “Housing And Health: An Overview Of The Literature.” Health Affairs Health Policy Brief, June. https://doi.org/10.1377/hpb20180313.396577. The Hilltop Institute. 2020. “Community Benefit State Law Profiles Comparison: State Community Benefit Requirements and Tax Exemptions for Nonprofit Hospitals.” The Hilltop Institute: UMBC. 2020. https://hilltopinstitute.org/our-work/hospital- community-benefit/hcbp-state-comparison/. U.S. Postal Service Office of Inspector General. 2013. “The Untold Story of the ZIP Code.” RARC- WP-13-006. United States Postal Service. https://www.uspsoig.gov/sites/default/files/document-library-files/2015/rarc-wp-13- 006_0.pdf. USDA. 2019. “Rural-Urban Continuum Codes.” United States Department of Agriculture: Economic Research Service. October 25, 2019. https://www.ers.usda.gov/data- products/rural-urban-continuum-codes.aspx. Viveiros, Janet, Mindy Ault, and Nabihah Maqbool. 2015. “The Impacts of Affordable Housing on Health: A Research Summary.” National Housing Conference. https://www.nhc.org/publication/the-impacts-of-affordable-housing-on-health-a- research-summary/. Woolington, Rebecca, and Bethany Barnes. 2020. “For Seniors in Florida’s Villages, Coronavirus Dangers Stack Up.” FRONTLINE: Public Broadcasting Service, April 4, 2020. https://www.pbs.org/wgbh/frontline/article/seniors-in-floridas-villages-coronavirus- covid-19-dangers/.
94 Young, Gary J, Chia-Hung Chou, Jeffrey Alexander, Shoou-Yih Daniel Lee, and Eli Raver. 2013. “Provision of Community Benefits by Tax-Exempt U.S. Hospitals.” The New England Journal of Medicine 368 (16): 1519–27. https://doi.org/10.1056/NEJMsa1210239. Zimmerman, Emily, Benjamin Evans, Steven Woolf, and Amber Haley. 2012. “Social Capital and Health Outcomes in Boston.” Virginia Commonwealth University Center on Human Needs. Zullo, Robert. 2014. “UPMC, City Drop Legal Fight over Taxes.” Pittsburgh Post-Gazette, July 29, 2014. https://www.post-gazette.com/local/city/2014/07/29/UPMC-city-drop-legal- fight-over-taxes/stories/201407290183.
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