Startseite The Role of Healthcare Conversion Foundations in Investing in Population Health
Artikel Open Access

The Role of Healthcare Conversion Foundations in Investing in Population Health

  • Casey P. Balio ORCID logo EMAIL logo , Nicole Galler und Michael B. Meit
Veröffentlicht/Copyright: 20. November 2024
Nonprofit Policy Forum
Aus der Zeitschrift Nonprofit Policy Forum

Abstract

Healthcare conversion foundations (CF) are charitable entities with endowments of varying sizes that are created as the result of a sale of a hospital or health system. Limited current research focuses on the impacts of CF grant-making and philanthropy within the communities they serve. In this study, we use a panel analysis of CF financial information from 2011 to 2021 to characterize CF investments by geography, and as compared to required tax-exempt hospital community benefit spending. Of the 51 foundations included in the analysis, CFs invested over $382 million into the communities they served through contributions, gifts, and grants in fiscal year 2021 alone. On average, CFs invested $20.21 per-capita on contributions, gifts, and grants in their communities, with CFs that serve non-metropolitan areas investing significantly more per-capita than those that serve only metropolitan areas ($32.97 vs $10.09, respectively), although non-metropolitan CFs may represent a larger proportion of overall community charitable investment as compared to metropolitan CFs within a given community. In conjunction with prior evidence, findings from the current study suggest that CF investments in the communities they serve appear to be on a similar scale as community benefit spending of tax-exempt hospitals, although there is significant heterogeneity in spending across both CFs and tax-exempt hospitals. Further understanding of the impacts of conversion foundations within the communities they serve and how they may change over time in response to changing communities, health care context, and regulations is important to understanding the scope and impact of philanthropic funding for population health.

1 Introduction

In recent years, there has been substantial effort in the United States to invest in population health to improve health and control health care costs. Many types of organizations are making such investments, including tax-exempt, nonprofit hospitals and health systems, public health agencies, and philanthropic organizations. Healthcare conversion foundations (CFs), also known as health legacy foundations, are one type of charitable organization making these investments. CFs are generally created from the sale or conversion of a nonprofit healthcare organization to a for-profit entity. Nonprofit hospitals, specifically, are required to provide community benefits to maintain tax-exempt status. The resulting sale of a nonprofit health organization to a for-profit entity can face laws and regulations at both the federal and state level, but primarily occur at the state level (Treanor and Khanna 2021). The assets from the sale of the nonprofit entity are used to form the CF, which then focus on health-related issues from a social determinants perspective including topics such as disease prevention, access to care, and behavioral health (Treanor and Khanna 2021). These new CF organizations become separate charitable entities with their own boards and mission, but typically serve the same area or population as the previous healthcare organization (Treanor and Khanna 2021). CFs can be classified as 501(c)(3) organizations or 501(c)(4) organizations. Under the 501(c)(3) exemption, CFs can either be private foundations or public charities. Private foundations are required by law to distribute at least 5 % of their total assets each year, while public charities do not have this requirement. Further, private foundations complete IRS Form 990-PF, requiring different reporting information.

Highlighting the recent policy interest in the idea of community benefit, nonprofit hospitals, specifically, have seen increased scrutiny for the growing value of their tax-exempt status and the limited increase in community benefit spending to compensate for this valuable status (United States House Committee on Ways & Means 2023). While CFs are expected to continue the charitable mission, or community benefit, of the former organization as it relates to improving health and wellbeing of their service area, the specific ways in which CFs do this may differ substantially from the former health care organization. For example, a significant portion of non-profit community benefit spending is often on uncompensated or charity care, while CFs often focus on social determinants of health or population health efforts (Singh et al. 2016; Young et al. 2018). As of 2021, 303 health care CFs currently exist in the United States with assets ranging from about $200,000 to $3.8 billion (Treanor and Khanna 2021). Most CFs operate at regional or local levels, while some operate at state or multi-state levels, which is typically reflective of the former service area of the non-profit health organization (Treanor and Khanna 2021).

Literature that offers insight into the important role CFs play through specific programs, initiatives, evaluations has been published as many community-based initiatives and partnerships have been implemented through the decades that CFs have been in operation. These articles offer specific examples of the unique approaches and successful grantmaking, organizing, and programmatic roles that CFs play in communities. For example, programs that have been initiated or funded by CFs have had successes in strengthening community building for issues such as domestic violence, children’s health, and investing in post-secondary education (Cao et al. 2016; Eggen et al. 2020; Meehan et al. 2009). Further, CFs have published internal evaluations and recommendations on organizational frameworks and capacity building that can promote sustainable work for the organizations they serve (Baker and Constantine 2019; McCracken and Firesheets 2010).

Healthcare CFs began forming in the 1980s and 1990s (Treanor and Khanna 2021; Williams and Brelvi 2000). During this time, many large for-profit health systems acquired non-profit community hospitals, medical centers and health systems, with 155 hospitals and hospital systems converting between 1994 and 1996 (Treanor and Khanna 2021). These conversions created an unprecedented number of new philanthropic organizations (i.e. conversion foundations), with millions of dollars in assets (Treanor and Khanna 2021; Williams and Brelvi 2000). Early research during this time was focused on understanding the conversion process. Studies found that the sale of a non-profit hospital to create a for-profit hospital and conversion foundation is typically regulated at the state level, with no federal level oversight (Gray 1997; Sackett 1999). During this time, researchers suggested that more formal processes of oversight and greater public awareness of the transactions should be established to ensure that communities do not lose resources in the conversion process (Butle 1997; Claxton et al. 1997; Gray 1997; Sackett 1999). More recently, Niggel and Brandon have noted that there has been limited research in recent years that goes beyond the conversion process, some research has focused on case studies or legal review (Niggel and Brandon 2014).

Many states now have specific laws pertaining to the sale of a nonprofit health organization to ensure the sales are regulated and resources are set aside for the benefit of the communities impacted. An important example was the creation of the California Wellness Foundation, which is a conversion foundation established in 1992 after one of the biggest sales of a nonprofit healthcare entity occurred in the state (Yates and David 2000). Advocates called for increased scrutiny of these sales, and established law in the state code of regulations, Section 999.5(h)(1) of Title 11, that dictates the actions that must be taken for the sale of a nonprofit healthcare entity (Legal Information Institute 2021). However, state policy surrounding the sale of nonprofit health organizations vary greatly, with some states requiring, for example, attorney general involvement, public hearings, and monitoring of the conversion and post-conversion process with reporting, while other states may have no official policy (Orlando and Dube 2014).

CFs have been highlighted as “exciting players in health philanthropy” as they offer funds to areas that are often underfunded such as disease prevention and public health (Garigan 2004). The distribution of grants and funds typically occurs in local communities where the previous non-profit hospital existed, which can create a driving force in addressing health disparities. An interview with the president and CEO of the California Endowment, a CF, discussed how this particular CF has used strategic planning and community involvement to shift from primarily providing direct service grants to more advocacy and policy change grants, where they have seen significant victories in improving population health (Ferris 2013). A recent study of 33 CFs that found CFs were addressing a variety of social determinants of health in their communities (Easterling and McDuffee 2018). Another study found that as philanthropic entities, CFs have the ability to improve population health through collaboration with partners and the generation of innovative ways to solve population health issues (Heinze et al. 2016). Since the CFs began emerging in the 1980s, several important policy challenges have been imparted, including ensuring that charitable assets are not lost to the public, developing strategies to help CFs become effective grant making organizations, and verifying that CF funds are used appropriately (Gray 1997).Since the CFs began emerging in the 1980s, several important policy challenges have been imparted, including ensuring that charitable assets are not lost to the public, developing strategies to help CFs become effective grant making organizations, and verifying that CF funds are used appropriately (Gray 1997).

While literature exists on the positive impacts of specific programs, grantmaking initiatives, or supportive roles CFs can play in community-based work, gaps still exist in our understanding of how the roles of CF and community investments vary across different geographies, populations, or by state-level policy differences. With the billions of dollars in assets held in these foundations, it is important to better understand the scale of investments from CF that contribute to community level health.

The purpose of this research note is to quantify the financial investment, as measured by per capita expenditures, of CFs that were created from hospitals or health systems in the communities they serve. Using the 2021 Grantmakers In Health (GIH) report of healthcare CFs, financial records, and information about the communities CFs served, this study used a panel design to characterize a subset of CF investment by characteristics of the CF and the community served. Findings from this study shed light on healthcare CF investments in population health, as compared to other organization types, including their former non-profit organizations. These findings can be utilized to better understand the scale of investments CFs make in population health and set the stage for additional research into the outcomes of these financial investments. Findings from this study will be of interest to policymakers involved in population health, organizational decision makers in non-profit institutions investing in population health, and grant making organizations interested in population health investments.

2 Methods

2.1 Study Design and Population

This study uses a panel analysis of CF financial information from 2011 to 2021 to characterize CF investments in their communities served, with a focus on investments through contributions, gifts, and grants in alignment with their charitable missions. Our sample was derived from the GIH 2021 Conversion Foundation Directory which identifies 303 CFs (Treanor and Khanna 2021). Our sample of CFs was then restricted based on three criteria. First, we limit our sample to CFs created from the conversion of hospitals or health systems. CFs can also be established from other legacy organizations, such as health plans and clinical organizations such as nursing homes. We limit to only those created from hospitals or health systems as the non-profit expectations on such organizations are well-defined. These also represent a significant portion of CFs identified in the GIH directory (83 %) (Treanor and Khanna 2021). Second, we include only CFs that are classified as private foundations. In general, CFs may be classified as either private foundations or public charities. For the purpose of this study, we only include those who are characterized as private foundations as the IRS rules and reporting are different for each. Private foundations are required to distribute a minimum of 5 % of their total assets each year and submit IRS Forms 990-PF, as compared to public charities which submit a different Form 990 to report their financial information annually. A total of 105 CFs in the Grantmakers in Health directory meet these two criteria. Lastly, our sample is limited to those for which the population served (counties in which the CF works) could be identified through CF websites or publicly available media sources. Altogether, our sample represents approximately half of CFs that are private foundations and derived from a hospital or health system. Our sample primarily includes CFs that serve one or several contiguous counties within a given state. There are CFs that serve a full state or region of multiple states, however these CF are more likely to be formed as a result of the sale of a health plan, for example.

2.2 Data Sources

The list of CFs and information about the organizations was extracted from the GIH 2021 Directory. Areas served by county were identified by CF websites and available media sources. Financial information for CFs was obtained through forms 990-PF. Depending on the year, these were obtained from GuideStar and the Internal Revenue Service (IRS). At the time of analysis, forms 990-PF were not downloadable from the IRS website for those filed in 2017–2019. As such, we relied on GuideStar data for these years. Neither IRS nor GuideStar have consistent data available for tax year 2016 for private foundations, so 2016 was omitted from the analysis. Additional county-level population information was obtained from American Community Survey (ACS) and United States Department of Agriculture.

2.3 Financial Measures

Financial measures were defined based on the IRS definitions in form 990-PF. Measures include total assets; exempt spending; exempt spending on contributions, gifts, and grants; and exempt administrative spending. Exempt spending is defined by form 990-PF Part I, column d, “Dispersements for charitable purposes.” These expenses are divided into the categories of “total operating and administrative expenses” and “Contributions, gifts, grants paid.” Operating and administrative expenses includes 11 categories, including items such as compensation of officers, directors, trustees, etc.; other employee salaries and wages; pension plans, employee benefits; legal, accounting, and other professional fees; occupancy; conferences, travel, and meetings; and printing and publications. We include per-capita estimates of all measures. Per-capita amounts were calculated using ACS population estimates from counties served by the CF as identified by CF websites. Population estimates for all counties served were added for the per capita denominator. Given the focus of the study on the role of CFs in supporting community health and well-being, we focus on the exempt spending of CFs, especially the exempt spending on contributions, gifts, and grants. Further, we estimated the percent of exempt spending on each total operating and administrative expenses as compared to contributions, gifts, and grants paid. Lastly, we estimated the percent of total assets spent on contributions, gifts, and grants paid, and compare that to the IRS threshold of distributing at least 5 % annually. Of note, the IRS requirement does not require this full 5 % to be contributed through contributions, gifts, and grants, but can also include “reasonable and necessary administrative expenses” and amounts paid to purchase assets that are “directly to carry out the charitable or other public purpose” (IRS 2024). As such, our measure is not a direct assessment of meeting this requirement, but rather assessing the portion of CFs in our sample at least meeting this requirement by contributions, gifts, and grants alone. All financial measures were calculated for each tax year and adjusted for inflation to 2023 USD.

2.4 Organization & Population Measures

Several characteristics of the CF and the population served were also included in the analyses. Selection of these measures are those that are potentially related to organizational operations and scale, demographic and economic characteristics of the community served, especially those relevant to health equity and population need which may align with the population health mission of CFs. Organizational characteristics of the CF include: asset size (small [up $50 million], medium [greater than $50 million to $100 million], and large [greater than $100 million]), year of conversion (before 2000, 2000–2009, and 2010-current), and a binary indicator for whether the CF serves a single county. The year of conversion categories were designed to capture changes in both the CF and larger health policy landscape. The majority of CFs were formed in the 1990s. During this time, state policies were also being enacted regarding conversions. 2000 through 2009 reflect a time with increasing CFs and them becoming more prominent. The last period beginning in 2010 through current is designed to mark the substantial change in health policy brought on by the passage of the Affordable Care Act. Not only did this have widespread implications for health policy generally, but also had tremendous implications for hospital finance and non-profit hospital requirements.

Population characteristics include: percent of the population that is non-white, percent of the population that is Hispanic or Latino, median household income, and a binary indicator for the CF serves at least one non-metropolitan county as compared to only metropolitan counties. Metropolitan and non-metropolitan status was identified using 2013 Rural-Urban Classification Codes (RUCCs) categories 1–3 and 4–9, respectively. Population characteristics were all estimated from ACS 5-year estimates data by aggregating all counties served by the CF and calculating percentages of the total population.

2.5 Analyses

First, descriptive statistics of CFs and the populations served were provided for the full sample and by serving any non-metropolitan counties compared to only metropolitan counties, conducted using Pearson’s Chi-Squared tests (categorical measures) and T-tests (continuous measures). Next, descriptive statistics of financial measures were conducted overall, by year (2011, 2017, and 2021), Next, bivariate analyses of financial measures for all years by CF serving any non-metropolitan counties compared to only metropolitan counties using t-tests. Finally, panel linear and logistic regressions of various financial measures as a function of CF and population characteristics were conducted. These models include state and year fixed effects and standard errors clustered at the CF level to account for repeated observations. We include state fixed effects because of the variation in state policies regarding mergers or acquisitions of hospitals and health systems and specific policies regarding the conversion or the CF itself (Niggel and Brandon 2014; Orlando and Dube 2014).

3 Results

In total, 51 private foundation CFs were included in the analysis, with varying numbers of CFs by year resulting in 431 CF-year observations. Approximately 45 % of CFs in the sample were from CFs serving any non-metropolitan counties, while the remaining 55 % served all metropolitan counties (Table 1). Two CFs served entire states and 26 CFs served only one county. The mean number of counties served was 5.96 and median of 1. There were some significant differences in characteristics of CFs and the communities they serve by metropolitan status, with CFs that serve any non-metropolitan counties tending to have lower median incomes and smaller portions of the populations they serve that are non-White. In 2021, total assets of CFs ranged from $5.4 million to $3.1 billion with a mean of $281.5 million and a median of $94.5 million (in 2023 USD, Table 2). In 2021, organizations spent a total of $382,268,854 on contributions, grants, and gifts in the communities they serve. This is inherently a significant underestimate of the total CF investments as it captures only half of private foundation CFs from hospitals and health systems, and about 17 % of all known CFs.

Table 1:

Descriptive characteristics of CFs in the sample.

Serve all metro Serve any non-metro Total p-Value
N = 28 N = 23 N = 51
Asset size 0.61
 Small, ≤50 mil 10 (35.7 %) 9 (40.9 %) 19 (38.0 %)
 Medium, 50–100  7 (25.0 %) 3 (13.6 %) 10 (20.0 %)
 Large, >100 mil 11 (39.3 %) 10 (45.5 %) 21 (42.0 %)
Year CF established 0.69
 Before 2000 19 (67.9 %) 13 (56.5 %) 32 (62.7 %)
 2000–2009 5 (17.9 %) 6 (26.1 %) 11 (21.6 %)
 2010-current 4 (14.3 %) 4 (17.4 %) 8 (15.7 %)
Serves single county 23 (82.1 %) 3 (13.0 %) 26 (51.0 %) <0.001
Percent of Pop. Served non-white 28.5 (14.2) 18.9 (14.4) 24.2 (14.9) 0.021
Percent of Pop. Served Hispanic or Latino 11.6 (13.7) 12.9 (22.4) 12.2 (18.0) 0.80
Median household income quartiles 0.004
 Quartile 1 3 (10.7 %) 12 (52.2 %) 15 (29.4 %)
 Quartile 2 7 (25.0 %) 6 (26.1 %) 13 (25.5 %)
 Quartile 3 9 (32.1 %) 4 (17.4 %) 13 (25.5 %)
 Quartile 4 9 (32.1 %) 1 (4.3 %) 10 (19.6 %)
  1. p-Values for comparisons of categorical variables were conducted using Pearson’s Chi-Square tests while those for continuous, numeric variables were conducted using T-tests. This table represents each CF-year observation.

Table 2:

Financial measures by year.

All Years (2023 USD) 2011 Sample (2023 USD) 2017 Sample (2023 USD) 2021 Sample (2023 USD)
Mean Median Mean Median Mean Median Mean Median
Total assets 170,360,491 72,701,586 106,247,810 61,950,616 220,292,394 106,036,888 281,504,218 94,546,743
Total assets per capita 524.18 192.10 480.59 183.69 566.57 247.84 598.27 176.70
Total exempt spending per capita 25.09 10.41 24.21 10.45 27.12 11.34 24.53 10.10
Exempt spending on contributions per capita 20.21 7.42 19.77 7.27 21.87 8.47 19.69 6.09
Exempt spending on admin per capita 5.03 1.63 4.44 1.27 5.89 1.98 4.84 1.34
Percent exempt spending on contributions 75.53 80.51 78.31 83.65 72.14 78.50 77.63 80.62
Percent exempt spending on admin 24.47 19.49 21.69 16.35 27.86 21.50 22.37 19.38
Percent of assets spent on contributions 4.10 3.94 4.41 4.48 3.72 3.56 4.13 3.66

In bivariate comparisons, CFs that serve any non-metropolitan counties spent significantly more on total exempt costs, exempt administrative costs, and contributions, gifts, and grants (p < 0.001, Figure 1). On average, CFs that serve any non-metropolitan counties spent $32.97 per-capita on contributions, gifts, and grants as compared to $10.09 among CFs that serve all metropolitan counties (p < 0.001). Further, CFs that serve any non-metropolitan counties also spent a significantly greater share of their total assets on contributions, gifts, and grants compared to those that serve all metropolitan counties on average (4.57 % vs. 3.73 %).

Figure 1: 
CF exempt spending per-capita by metropolitan status of area served (2011–2021 pooled). Note: *p < 0.05; **p < 0.01; ***p < 0.001. T-tests were used to compare mean spending values by metropolitan status.
Figure 1:

CF exempt spending per-capita by metropolitan status of area served (2011–2021 pooled). Note: *p < 0.05; **p < 0.01; ***p < 0.001. T-tests were used to compare mean spending values by metropolitan status.

Regression results suggest that year of conversion and serving any nonmetropolitan counties are significantly associated with most financial measures (Table 3). CFs established since 2010 are associated with greater total assets per capita (coef.: 854.66, p-value: 0.004), compared to those formed before 2000. CFs serving any non-metropolitan counties were at over six times greater odds spending at least 5 % on contributions, gifts, and grants (p = 0.042) and had significantly greater total assets per capita (coef.: 744.51, p-value: 0.017), and contributions, gifts, and grants per capita (coef.: 3.24, p-value: 0.021) compared to those that serve only metropolitan counties. Medium sized CFs (with total assets between $50–100 million) had higher exempt spending per capita (coef.: 4.60, p-value: <0.001), and higher contributions, gifts, and grants per capita as compared to small foundations (coef.: 3.46, p-value: 0.032). In contrast, large CFs (with total assets greater than $100 million) had lower contributions, gifts, and grants per capita as compared to small foundations (coef.: −2.82 p-value: 0.040). Lastly, total assets per capita were positively associated with exempt spending per capita (coef.: 0.04, p-value: <0.001), administrative and operational spending per capita (coef.: 0.01, p-value: <0.001), contributions, gifts, and grants per capita (coef.: 0.04, p-value: <0.001), and increased odds of spending at least 5 % on contributions, gifts, and grants (OR.: 1.001, p-value: 0.002).

Table 3:

Regression results of CF financial measures as a function of CF and population characteristics.

total assets per capita Exempt spending per capita Admin spending per capita Contribution spending per capita Contributions at least 5 %
Coef. p-Value Coef. p-Value Coef. p-Value Coef. p-Value OR p-Value
Asset size
 Small, ≤50 mil ref ref ref ref ref ref ref ref ref ref
 Medium, 50–100 mil −17.26 0.367 4.60 0.001 1.19 0.186 3.46 0.032 1.43 0.534
 Large, >100 mil −28.55 0.314 −1.83 0.265 1.22 0.052 −2.82 0.040 0.23 0.065
Total assets 0.04 <0.001 0.01 <0.001 0.04 <0.001 1.001 0.002
Year CF established
 Before 2000 ref ref ref ref ref ref ref ref ref ref
 2000–2009 416.16 0.285 1.68 0.630 −2.34 0.370 4.67 0.046 3.72 0.027
 2010-Current 854.66 0.004 −4.58 0.297 0.76 0.675 −4.79 0.231 2.01 0.401
Serves single county 159.2 0.638 1.57 0.423 0.04 0.974 1.19 0.484 0.84 0.869
Percent of Pop. Served non-white −0.21 0.936 −0.04 0.506 −0.06 0.363 0.02 0.701 1.04 0.037
Percent of Pop. Served Hispanic or Latino 1.36 0.327 −0.02 0.710 −0.04 0.077 0.01 0.876 0.997 0.863
Median household income
 Quartile 1 ref ref ref ref ref ref ref ref ref ref
 Quartile 2 −29.37 0.318 −5.48 0.122 −0.73 0.548 −5.05 0.100 0.68 0.703
 Quartile 3 −57.63 0.138 −5.43 0.077 −1.21 0.445 −5.24 0.084 0.93 0.937
 Quartile 4 −63.68 0.238 −4.33 0.103 −2.05 0.394 −3.03 0.374 3.31 0.157
Serve any non-metro counties 744.51 0.017 3.11 0.066 −0.25 0.756 3.24 0.021 6.34 0.042
Constant −105.08 0.810 4.38 0.274 5.98 0.188 0.37 0.945 0.02 0.051
N 430 430 425 425 346
Clusters 51 51 51 51 41
R-Squared overall 0.68 0.91 0.68 0.86
Pseudo R2 0.26
  1. Panel regression results with state and year fixed effects and standard errors clustered at the CF level. Note that each set of Coef. And p-value columns represents a different regression model. The first four models are linear regressions while the final model is a logistic regression with odds ratios presented. Diagnostic criteria of the regression analyses are at the bottom of the table.

4 Discussion

CFs are one of the many organizations that invest in population health at the community level, along with tax exempt, non-profit hospitals and health systems. However, CFs and the resulting impacts that the conversion process and foundations have on communities are often overlooked. The conversion process of a non-profit hospital or health system and the resulting CF may become increasingly relevant in future years as health systems and hospitals face financial pressure because of the COVID-19 pandemic. These pressures are being seen throughout the U.S. as COVID-19 relief funding that was keeping hospitals solvent has been discontinued, but are most commonly found in rural communities as hospitals face financial and staffing difficulties (Levinson et al. 2023). As hospitals convert from non-profit to for-profit institutions, the structure, composition, and requirements for investing in population health by the established CF may also shift. The current study describes the size and amount of spending by CFs that are private foundations, including the amount spent on contributions, gifts, and grants. While investments via contributions, gifts, and grants are an important mechanism for investing in population health, they are an intermediate measure, and do not capture the impact CFs are having on their communities. Further work is needed in this area, requiring substantial data collection efforts based on the specific contributions, activities, and intended audience and goals of each CF and each investment made.

First, we find that this sample of CFs invested over $382 million in the communities that they serve in 2021 alone. Within their capacity as private foundations investing in community and population health, they spent a mean of $77 and median of $81 per capita on contributions, gifts, and grants. Each of these measures is an underestimate of the full investment of CFs, given the limited inclusion criteria and limited sample. Some of the largest CFs are the product of health plans, and are therefore not included in this study. For example, the California Endowment was established in 1992 when WellPoint Health Networks was acquired by Blue Cross of California (The California Endowment 2024). Their current assets are over $3 billion and they have invested nearly the same amount through grants since their establishment (The California Endowment 2024). In looking at tax-exempt non-profit hospital spending on “community health improvement” activities (the most similar comparison to CF spending on contributions, gifts, and grants), previous evidence suggests that these organizations spent a median of $130 per capita on community benefit activities, but that a relatively small proportion of that spending is actually on community health improvement activities (as opposed to charity care or other types of exempt spending) (Singh et al. 2016; Young et al. 2018). One study estimates that tax exempt spending on direct population health efforts is approximately $11 per person, but with significant heterogeneity (Singh et al. 2016). In some states, average per-capita spending of this type ranged from below $1 to greater than $25 (Singh et al. 2016). Another study suggests that mean community benefit spending at the hospital referral region was $164 per capita, but less than 5 % of that spending is on community health improvement activities (Leider et al. 2017). Altogether, this suggests that these CF investments in population health are generally on the same scale as their tax-exempt hospital counterparts, especially when we consider the role of individual hospitals, health systems, or conversion foundations rather than all of the organizations investing within a given geographic area. We also note that there is great heterogeneity in the amount invested by both non-profit hospitals and health systems as well as CFs. The lack of associations between CF exempt spending and most CF and community characteristics suggests more research is needed to better understand this variation among CFs.

Existing evidence suggests that CFs vary greatly in many important ways, are subject to both federal and state political environments, and may face regulatory and contextual changes over time. We also identify variation in the amount distributed directly through contributions, gifts, and grants alone by year of CF conversion and serving any nonmetropolitan counties, and some differences in operational and administrative spending by CF size. Larger CFs may be performing different types of roles and activities compared to smaller CFs, which may contribute to this difference in operational and administrative spending. For example, larger CFs are likely managing more and larger grants, and may be more likely to be conducting more foundational work to affect population health and promote change at a systems level, rather than being more solely focused on contributions gifts and grants. However, we are not able to assess this within this data.

Notably, there are significant differences in the state-level policies surrounding CF formation, as some states have specific laws that outline formal procedures for the sale of a nonprofit health organizations while others do not. Differences in state level policies may also affect how CFs are formed and how they function, which may, in turn, create variation in investments and benefits to the communities they serve. Adding to the complexity, Grantmakers in Health estimates that about a third of CFs are still engaged with their formation organization, which may also lead to CF operational differences. It is possible that policy differences could be influencing the presence and activity of CFs, however to our knowledge, there is not conclusive evidence on the impact of state-level policy differences on CF formation, investment, and community-level health benefits. CFs that were formed in the 1990s as compared to those formed more recently, including those before or after the Affordable Care Act and/or the COVID-19 pandemic, may undertake different types of activities, approaches, or spending. Importantly, these changes over time, by potential changing community context and age of the CF formation, and health outcomes related to the investments of CFs and how they differ based on state policies are unknown. Because of the lack of readily available, comprehensive information regarding the policies CFs face at the state level and the small sample size in the current study, we were unable to account for this in our analyses. Understanding and quantifying the community benefit offered by CFs, and how this may be influenced by state policies is an important area for future research as both the health care and policy landscape vary greatly across the U.S. Research of this nature would be important to policymakers who could change state-level policies related to the sale of nonprofit health related organizations.

We also find in both bivariate and multivariate comparisons that total exempt spending per capita and spending on contributions, gifts, and grants per capita are greater among CFs that serve any non-metropolitan areas as compared to those that serve only metropolitan areas. While this may suggest that CFs serving more rural areas play a larger role in investing in population health than in urban areas, this is likely a function of there being a smaller number of total hospitals or health systems and CFs in rural areas doing this type of investing. Conversely, in more urban areas where there are more entities investing in community health, the spending by an individual CF may represent a smaller share of the overall community investment in population health. Regression results also show that CFs that serve any non-metropolitan areas are at greater odds of spending at least 5 % of their assets towards contributions, gifts, and grants alone. Together, this suggests that CFs are important investors in their communities, particularly those that serve non-metropolitan areas.

Lastly, we find that exempt spending is largely a function of the per-capita total assets, which are a function of the original sale price, even when also adjusting for rurality. Understanding what drives the conversions and the sale price, and how this may differ by geography, will be key for interpreting the implications for this finding. Future research is warranted in this area.

5 Limitations

While this study is among the first to assess the role CFs play in investing in population health in recent years, it is not without limitations. First, our sample is limited to those that are private foundations created from hospitals or health systems and that had their geographic service area in counties clearly articulated on their websites. This sample may not be representative of all CFs or generalizable due to the small sample size and inclusion criteria. Many CFs with potentially large endowments have been formed from large health insurance plans, classified as public charitable entities, or have limited information available on their website as to the geographic area served. Additionally, the 990-PF provides a direct measure of spending for charitable purposes, facilitating the analysis but limiting our sample to private foundations only and limiting the generalizability to other types of foundations. While our sample represents about 50 % of private foundation CFs that are derived from hospitals or health systems, this is an underestimate of the full financial role of CFs and is not generalizable to all CFs. Previous work also suggests that CFs that derive from health plans may differ in significant ways from others, including having greater assets and greater service areas (Niggel and Brandon 2014). As such, there is a notable margin of error and findings should be interpreted with care. However, this study expands the evidence of the financial role of CFs, which has been noted to be limited historically to studies focused on the process of conversion and case studies, rather than a more comprehensive view. Second, we estimate per-capita investments based on the theoretical geographic area served. CFs may not actually invest in all of these counties, or equally across them. Theoretically serving these areas does not imply that investments are actually reaching each of these counties each year. In addition, CFs may also make investments at the state or national level, or outside of the local geography. Next, we describe the contributions, gifts, and grants as being related to population health. While this is the primary giving objective of CFs, we cannot assess how much of this spending category is related to population health. Additionally, the current study does not account for other CFs, hospitals, or health systems that may also be investing in population health efforts in the same geographic area. Therefore, we are only capturing a proportion of the population health investments occurring from CFs and not all investments. This is likely a greater limitation in metropolitan areas that are more likely to be served by more than one CF, as well as remaining non-profit hospitals and systems. Next, CFs may make important investments towards population health outside of those that are categorized directly as “contributions, gifts, and grants paid.” Select operational and administrative spending may indirectly, but invaluably, affect population health. For example, travel, conferences, and meeting spending may be used to train and educate staff with the most current evidence and practices to support health and wellbeing, therefore potentially improving the impact of the CFs work. In addition, much of the work of the officers, directors, trustees, and employees is to facilitate funding to improve the health and wellbeing of their communities. Funding for their salaries is an indirect investment in population health. Lastly, for the purposes of this study, we have dichotomized CFs into those that serve only metropolitan counties compared to those that serve at least one nonmetropolitan county. This is a coarse measure of rurality and does not capture some of the unique spending patterns and differences of organizations that may be at a county, state, or regional level. However, half of the sample are CFs that serve only 1 county, providing some justification for using this measure across CFs that serve only 1 county to those that serve entire states.

These limitations identify important areas for future research such as understanding public and private CFs and how they differ, CFs formed by different types of legacy organizations, how CF activities and roles have changed over time, variation in and the role of state policy in CF spending and activities. Further, research should seek to generate an understanding of geographical areas served by CF, more comprehensive understanding of what CFs are investing in, and community level differences in CF grantmaking and outcomes. Additionally, research that offers comparisons of CF grant-making to prior non-profit hospital expenditures for community benefit would be beneficial to understanding the impacts to the communities served.

6 Conclusions

As the US continues to emphasize population health through policy and financial investments, it is increasingly important to understand the full variety of charitable organizations operating within this space. We find that CFs are considerable investors in this area, yet we lack comprehensive understanding of differences in investment activities and population health outcomes, the effect of policy differences on CF giving and outcomes, how they are addressing health disparities, and how their work compares to the community benefit activities to their former non-profit institutions warrants further research.


Corresponding author: Casey P. Balio, Center for Rural Health and Research, East Tennessee State University, 2109 W Market St #116, Johnson City, 37614-0661, Tennessee, USA, E-mail:

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Balio led the study design, data acquisition, data cleaning, analysis, interpretation of results, writing, and editing of the manuscript. Galler supported data acquisition, writing, and editing of the manuscript. Meit supported study design, interpretation of results, and editing of the manuscript.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Competing interests: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

Baker, S. M., and M. D. Constantine. 2019. “Making Health Equity Real: Implementing a Commitment to Engage the Community through Fellowships.” The Foundation Review 11 (4). https://doi.org/10.9707/1944-5660.1493.Suche in Google Scholar

Butle, Patricia A. 1997. “State Policy Issues in Nonprofit Conversions.” Health Affairs 16 (2): 69–84. https://doi.org/10.1377/hlthaff.16.2.69.Suche in Google Scholar

Cao Yu, H., J. Henderson-Frakes, and L. Corral Peña. 2016. “Building a Field: Blue Shield of California Foundation’s Strong Field Project Leaves a Legacy and Valuable Lessons.” The Foundation Review 8 (2). https://doi.org/10.9707/1944-5660.1294.Suche in Google Scholar

Claxton, Gary, Judith Feder, David Shactman, and Stuart Altman. 1997. “Public Policy Issues in Nonprofit Conversions: An Overview.” Health Affairs 16 (2): 9–28. https://doi.org/10.1377/hlthaff.16.2.9.Suche in Google Scholar

Easterling, D., and L. McDuffee. 2018. “Social Determinants of Health: How Are Health Conversion Foundations Using Their Resources to Create Change?” Health Affairs Blog 2018. https://doi.org/10.1377/forefront.20180313.6738.Suche in Google Scholar

Eggen, M. B., J. C. Jennings, M. O’Keefe, B. N. Kelly Pryor, and L. Clements. 2020. “Advancing Social Determinants of Health through Investments in Postsecondary Attainment and Sustaining Employment.” The Foundation Review 12 (3). https://doi.org/10.9707/1944-5660.1528.Suche in Google Scholar

Ferris, James. 2013. “An Interview with Robert K. Ross, M.D” Nonprofit Policy Forum 4 (1).10.1515/npf-2013-0011Suche in Google Scholar

Garigan, Margaret. 2004. “Health Conversion Foundations.” In The Center for Public & Nonprofit Leadership. Washington DC: Georgetown Public Policy Institute. https://core.ac.uk/download/pdf/75778459.pdf.Suche in Google Scholar

Gray, Bradford H. 1997. “Conversion of HMOs and Hospitals: What’s at Stake?” Health Affairs 16 (2): 29–47. https://doi.org/10.1377/hlthaff.16.2.29.Suche in Google Scholar

Heinze, Kathryn, Jane Banaszak-Holl, and Kathy Babiak. 2016. “Social Entreprenurial in Communities, Examining the Collaborative Processes of Health Conversion Foundations.” Nonprofit Management and Leadership 26 (3): 313–330, https://doi.org/10.1002/nml.21198.Suche in Google Scholar

IRS. 2024. Private Foundations: Treatment of Qualifying Distributions IRC 4942(h). https://www.irs.gov/charities-non-profits/private-foundations-treatment-of-qualifying-distributions-irc-4942h.Suche in Google Scholar

Legal Information Institute. 2021. Cal. Code Regs. Tit. 11, § 999.5 – Attorney General Review of Proposals to Transfer Health Facilities Under Corporations Code Sections 5914 et seq. and 5920 et seq. Cornell Law School. https://www.law.cornell.edu/regulations/california/11-CCR-999.5.Suche in Google Scholar

Leider, Jonathon P., Greg J. Tung, Richard C. Lindrooth, Emily K. Johnson, Rose Hardy, and Brian C. Castrucci. 2017. “Establishing a Baseline: Community Benefit Spending by Notfor-Profit Hospitals Prior to Implementation of the Affordable Care Act.” Journal of Public Health Management and Practice: JPHMP 23 (6): e1–9. https://doi.org/10.1097/PHH.0000000000000493.Suche in Google Scholar

Levinson, Zachary, Jamie Godwin, and Scott Hulver. 2023. Rural Hospitals Face Renewed Financial Challenges, Especially in States that Have Not Expanded Medicaid. KFF. https://www.kff.org/health-costs/issue-brief/rural-hospitals-face-renewed-financial-challenges-especially-in-states-that-have-not-expanded-medicaid/.Suche in Google Scholar

McCracken, A. L., and K. Firesheets. 2010. “Sustainability Is Made, Not Born: Enhancing Program Sustainability through Reflective Grantmaking.” The Foundation Review 2 (2). https://doi.org/10.4087/FOUNDATIONREVIEW-D-10-00012.Suche in Google Scholar

Meehan, D., K. Hebbeler, S. Cherner, and D. Petersen. 2009. “Community Building for Children’s Health: Lessons from Community Partnerships for Healthy Children.” The Foundation Review 1 (1). https://doi.org/10.4087/FOUNDATIONREVIEW-D-09-00003.Suche in Google Scholar

Niggel, Sabrina Jones, and William P. Brandon. 2014. “Health Legacy Foundations: A New Census.” Health Affairs 33 (1). https://doi.org/10.1377/hlthaff.2013.0868.Suche in Google Scholar

Orlando, J., and N. Dube. 2014. “Nonprofit Hospital Conversion Laws in Other States.” OLR Research Report, https://www.cga.ct.gov/2014/rpt/2014-R-0229.htm (accessed May 2022).Suche in Google Scholar

Sackett, S. 1999. “Conversion of Not-For-Profit Health Care Providers: A Proposal for Federal Guidelines on Mandated Charitable Foundations.” Stanford Law and Policy Review 10: 247.Suche in Google Scholar

Singh, Simone R., Erik Bakken, David A. Kindig, and Gary J. Young. 2016. “Hospital Community Benefit in the Context of the Larger Public Health System: A State-Level Analysis of Hospital and Governmental Public Health Spending across the United States.” Journal of Public Health Management and Practice: JPHMP 22 (2): 164–74. https://doi.org/10.1097/PHH.0000000000000253.Suche in Google Scholar

The California, Endowment. 2024. “Our Story. Health Does Not Only Happen in a Doctor’s Office – it Also Happens.” Our Homes, Our Schools, and Our Communities, https://www.calendow.org/our-story/ (accessed May 2022).Suche in Google Scholar

Treanor, K., and N. Khanna. 2021. “Updates from the Field: Results of Grantmakers in Health’s 2021 Review of Health Care Conversion Foundations.” Grantmakers In Health, https://www.gih.org/restricted/?redirect_to=%2Fpublication%2F2021-conversion-foundations-report%2F (accessed May 2022).Suche in Google Scholar

United States House Committee on Ways & Means. 2023. Top Four Takeaways from Ways and Means Oversight Hearing on Non-Profit Hospitals. https://waysandmeans.house.gov/2023/04/28/top-four-takeaways-from-ways-and-means-oversight-hearing-on-non-profit-hospitals/.Suche in Google Scholar

Williams, M. V., and S. S. Brelvi. 2000. “A Closer Look: Profiling Foundations Created by Health Care Conversions.” Health Affairs: 257–9. https://doi.org/10.1377/hlthaff.19.2.257.Suche in Google Scholar

Yates, Gary, and Thomas David. 2000. “Don’t Call Us “Conversion Foundations.” Please.” In Grant Makers in Health. Views from the field. https://www.gih.org/files/usrdoc/53190.pdf.Suche in Google Scholar

Young, Gary J., Stephen Flaherty, E. David Zepeda, Simone Rauscher Singh, and Geri Rosen Cramer. 2018. “Community Benefit Spending by Tax-Exempt Hospitals Changed Little after ACA.” Health Affairs 37 (1): 121–4. https://doi.org/10.1377/hlthaff.2017.1028.Suche in Google Scholar

Received: 2023-05-12
Accepted: 2024-11-01
Published Online: 2024-11-20

© 2024 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Heruntergeladen am 14.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/npf-2023-0041/html
Button zum nach oben scrollen