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Article

Organizational Characteristics Associated with Addressing Community Social Determinants of Health in U.S. Hospitals: A National Perspective

1
Department of Healthcare Administration, School of Public Health, University of Nevada at Las Vegas, Las Vegas, NV 89119, USA
2
Department of Orthodontics, Roseman University, 4 Sunset Way, Bldg. C., Henderson, NV 89014, USA
3
Center for Health Disparities Research, School of Public Health, University of Nevada at Las Vegas, Las Vegas, NV 89119, USA
*
Author to whom correspondence should be addressed.
Hospitals 2025, 2(1), 8; https://doi.org/10.3390/hospitals2010008
Submission received: 8 December 2024 / Revised: 12 March 2025 / Accepted: 13 March 2025 / Published: 18 March 2025

Abstract

:
Background: With so much emphasis currently on Social Determinants of Health (SDOH), we examined the characteristics of U.S. hospitals making commitments to SDOH and engagement with community social determinant programs and activities (CSDPAs). Methods: This cross-sectional study used the 2021 American Hospital Association (AHA) Annual Survey with a total of 5992 hospitals included. The dependent variables were the community social determinants composite score, community partnership composite score, and the use of CSPDAs to assess outcomes. Results: Hospitals most influenced by payment policies and regulations were most likely to engage in CSDPAs. Hospitals with ACOs implement 3.38 more CSPDAs and hospitals participating in bundled payments are 41% more likely to address SDOH (OR = 1.41, 95% CI = [1.14, 1.75]). Hospitals in competitive markets and hospitals with ≥400 beds are positively associated with both SDOH activities and partnerships. Teaching hospitals, not-for-profit hospitals, Medicare mix, and rural hospitals, as well as market competition, were positively associated with higher levels of CSDPAs. Conclusion: Reimbursement requirements, organizational size and resources, and external pressures were shown as drivers for hospitals to implement CSDPAs.

1. Introduction

In 2023, a Call to Action from The Department of Health and Human Services (HHS) was issued with the goal of integrating health and social care systems to improve health for all Americans by addressing the social needs of communities through partnerships [1]. Healthy People 2030 defines Social Determinants of Health (SDOH) as “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risk” [2]. SDOH account for significant variation in health outcomes due to factors such as financial strain, food and housing insecurity, pollution, inadequate access to healthy foods, transportation limitations, and limited English language proficiency [1]. These barriers to social support and healthy living impact health outcomes and contribute to health disparities. The HHS has called for collaboration between healthcare organizations and community partners to address SDOH as a means of reducing health disparity [1]. The integration of social services into healthcare delivery is important for facilitating better health outcomes and health equity.
The American Hospital Association (AHA) Population Health Survey chronicles the degree to which U.S. hospitals report being aligned with population health goals and in providing programs related to SDOH. The survey asks hospitals to report on what social needs (housing, food insecurity, utility, interpersonal violence, transportation, employment, income, education, social isolation, health behaviors, or others) that the hospitals have programs to address [3]. The survey also asks whether the hospitals screen patients for social needs and record those needs in the electronic health record (EHR) [3]. The survey inquires as to whether the hospitals utilize outcome measures to assess the effectiveness of interventions to address patients’ social needs and, if so, have those programs resulted in any of the following: better health outcomes, decreased hospital utilization, decreased healthcare costs, and improved community health status [3]. Additionally, the survey asks the hospitals to identify who is accountable for meeting equity goals, whether it is the CEO or some other individual, and whether the hospital uses diversity, equity, and inclusion information to inform a health equity strategic plan [3]. With regard to collaboration, the survey asks the extent of the hospitals’ current external partnerships and whether they work together to meet patient social needs regarding referral or case management, participate in the community health needs assessment process, or work together to implement community initiatives to address SDOH and with what organizations they collaborate with in those initiatives [3]. Given the scope of this study, we did not assess the outcomes of programs or have the complete demographic compositions that the hospitals serve with the exception of self-reported patient mix, so that was not the focus of this paper. Instead, we focused on examining the characteristics of hospitals that were making commitments to SDOH screenings or interventions, whether they were internally motivated, and whether they partnered with community organizations for SDOH initiatives or community social determinant programs and activities (CSDPAs).
Health outcomes cannot be attributed solely to the quality of healthcare delivery; certain types of determinants might exert more influence on health than previously proposed [4]. According to the World Health Organization (WHO), “In countries at all levels of income, health and illness follow a social gradient: the lower the socioeconomic position, the worse the health” [5]. The concept of health promotion through community partnership is not a new concept. As early as 1988, the WHO recognized the importance of the Health Promoting Hospital Initiative and the WHO has also initiated programs focused directly on addressing SDOH [5]. The WHO has recognized the importance of advancing health equity by promoting Health in All Policies (HiAPs) that encourage capacity building, training resources, transforming education, improved intersectional planning, and supporting government policymakers [5]. The WHO has the goal of improving SDOH for at least 20 million disadvantaged people in 12 countries by 2028 [5]. Although the U.S. is not one of the countries targeted by the WHO, both Healthy People 2030 and HHS have emphasized the need for such initiatives to curtail health inequity in the U.S. through healthcare collaboration with community partners.
Link and Phelan (1995) posited that disparities persist because, even with scientific or medical advances, disadvantaged communities persistently lack resources that enable them to protect and enhance their health and many policies perpetuate those inequalities [6]. Collaborating across both healthcare and community partnerships in activities that address these social and financial limitations may in turn improve health outcomes for those disadvantaged communities. Collaboration comes with challenges. Without financial incentives or reimbursement contingent on addressing social needs, it may be difficult for hospitals to invest resources in SDOH initiatives. Our study helps identify what characteristics might drive a hospital to invest time and resources in SDOH initiatives. It is important to also recognize that there is a difference between factors impacting an individual’s health and factors impacting population health. Historical and systemic racism for instance has had a longstanding impact on population health. The role of ongoing and historical racism in shaping SDOH is critical to address given the implications it has for differential resource allocation, healthcare utilization, and structural barriers to health [7]. Health equity is a multidimensional concept that includes dimensions like neighborhood, race or ethnicity, level of education, occupation, and economic status [8]. In order to best impact health disparity, cross-organizational and cross-sector collaboration should be certain to include a significant representation of people with lived experience regarding unmet social needs [2]. Healthy People 2030 promotes creating a “social, physical, and economic environment that promotes attaining the full potential for health and well-being for all” [3].
McGinnis et al. (2002) stated that early deaths in the United States can be attributed to genetic predisposition (30 %), social circumstances (15 %), environmental exposures (5 %), behavioral patterns (40 %), and shortfalls in medical care (10 %) [9]. A criticism of these approaches is that these studies often conflate causation because they neglect to account for confounding and synergistic relationships between these factors [10]. Patients with one social risk are likely to have multiple [7].
Changes in federal government policy, such as various efforts to reward value-based services, and the Accountable Health Communities Model program of the Centers for Medicare & Medicaid Services (CMS) are drivers in providing screening and interventions related to SDOH in hospitals [11]. There are programs that encourage health providers to screen for and attempt to curtail the negative impacts of SDOH through healthcare pathways or community partnerships and data standardization such as Medicaid Section 1115 demonstrations, Medicaid managed care, supplemental benefits in Medicare Advantage, the Merit-Based Incentive Payment System, the Medicare Shared Savings Program, grants from the Centers for Disease Control and Prevention (CDC), an SDOH module for the Behavioral Risk Factor Surveillance System inclusion from the CDC, and inclusion of SDOH data in the United States Core Data for Interoperability (USCDI) [1]. As of 2024, hospitals participating in the Inpatient Quality Reporting Program must report quality measures related to Screening for Social Drivers of Health and Hospital Commitment to Health Equity and Medicare will pay for SDOH risk assessments, which identify unmet social needs that may affect the diagnosis and treatment of medical problems [1]. Additionally, for non-profit hospitals, Section 4959 of the Affordable Care Act makes it a requirement that hospitals conduct community health needs assessments every three years to qualify for nonprofit status [12].
It is therefore not surprising that Begun and Potthoff (2017) found hospitals that were more likely to accept responsibility for the health of populations were significantly more likely to be large, not-for-profit, metropolitan, teaching-affiliated hospitals and more likely to be members of larger hospital systems [11]. There are multiple factors that may drive whether a hospital wants to invest in initiatives to target SDOH. Deciding to invest in SDOH can be difficult given the fact that outcome impacts are unclear. Larger hospitals and health systems are more able to achieve economies of scale from population health activities because of their wider market areas, making those activities more affordable and therefore easier to justify in their strategic mission [11]. Given the alignment with the strategic mission, Begun and Potthoff (2017) also found that those hospitals investing in population health interventions were more likely to organize their population health activities with strong executive-level involvement and full-time-equivalent support, and had coordination at the system level [11].
The strategic focus of a hospital will depend on the decision-makers or dominant coalition [13]. The strategic goals can be internally or externally focused and will link the organization to its environment [14]. Research by Ford-Eickhoff et al. (2011) found that when the board of directors is involved earlier in the strategic decision-making process, the focus is more likely to be on external issues [15]. Hospitals with an external issue focus may more readily engage in initiatives to address social needs and form community partnerships to address those needs. Additional studies have found that community orientation [16] and an equity mission [17] are two characteristics that increase hospitals’ likelihood to engage in programs related to social needs. A study by Lemont et al. (2023) examined the extent to which Critical Access Hospitals (CAHs) (rurally located small hospitals typically receiving government financial support) engaged in community health improvement, particularly upstream SDOH initiatives [17]. The study found that CAHs fell behind their urban and non-CAH counterparts unless they had an equity mission [17]. When the researchers stratified hospitals according to whether they emphasized an equity-focused approach as an organization, CAHs with an equity approach did better than non-CAH hospitals in the number of SDOH screenings, strategies, and community partnerships [17]. If an equity approach is what drives CAHs to engage in SDOH initiatives, maybe an equity approach is the underlying driver for all hospitals or is it reimbursement or legitimacy-driven? Understanding what drives hospitals is important for facilitating these collaborative SDOH initiatives.
A recent scoping review of the literature since 2020 found that non-safety-net hospitals compared to safety-net hospitals were more likely to engage in initiatives to address SDOH; the initiatives addressed two or more SDOH concurrently, and most initiatives were designed as clinical trials that used electronic health record (EHR)-independent technologies to collect and report the SDOH data collected [18]. Rangachari et al. (2024) recommended enhancing the scope of value-based payment models to include the reduction in health disparities because they found that most upstream initiatives were undertaken by large teaching hospitals that participated in value-based payment arrangements [18]. And despite the connection between SDOH and disparity in health outcomes, they found few initiatives sought to reduce health disparities or promote health equity, and only three programs incorporated EHR-based automated support based on SDOH data, which is a significant missed opportunity [18]. Additionally, if we consider hospitals’ likelihood to offer diversity plans as an indication of their willingness to address social needs that impact health, we can look at the results of a 2011 study by Moseley et al. that found resource availability, urban location, less dependence on Medicaid reimbursement, capitation arrangements, managed care, and an external orientation had some effect on hospital’s willingness to offer a diversity plan [19]. If we translate those same factors to the likelihood of SDOH initiatives, we would expect similar hospital characteristics.
The scoping review of the literature since 2020 suggested future research could be aimed at addressing the gaps identified in the adequacy and distribution of hospital initiatives to address SDOH, including the use of EHRs to integrate SDOH into care practices and the development of hospital–community partnerships, especially among safety-net hospitals [18]. Our study addresses that gap by examining the characteristics of hospitals that are associated with their engagement in SDOH initiatives, forming external partnerships for community health initiatives, and whether they utilize outcome measures to assess the effectiveness of interventions that address social needs. Our main research questions were as follows: (1) What hospital characteristics are associated with hospital behavior and actions addressing SDOH with an external approach by partnerships with community organizations? (2) Do hospitals with greater institutional pressures tend to have programs focused on SDOH? (3) Are market competition and geographic locations (rural vs. urban) associated with hospital behavior and actions in providing services focused on SDOH? Independent of the community composition the hospitals serve, understanding the organizational and environmental characteristics of hospitals that define those engaged in social needs initiatives could help drive effective policy for greater SDOH community partnerships going forward.

2. Conceptual Framework

Institutional theory provides a framework to understand why hospitals are addressing social determinants of health (SDOH) and engaging in CSDPAs. Key concepts from Institutional Theory are based on the social constructs of legitimacy and isomorphism (the tendency to mimic other organizations). Institutional Theory recognizes that hospitals do not operate in isolation but rather are influenced by societal pressures and expectations. Institutional Theory provides a robust framework for examining how external pressures influence hospital engagement with social determinants of health (SDOH). This theoretical lens emphasizes the roles of coercive, mimetic, and normative isomorphism in shaping organizational behavior, highlighting how hospitals conform to societal, regulatory, and peer-driven expectations to maintain legitimacy [20,21].

2.1. Coercive Isomorphism: Regulatory and Policy Pressures

Hospitals face coercive pressures from regulatory bodies, payers, and policies that mandate or incentivize community social determinant programs and activities. For instance, non-profit hospitals are required to conduct community health needs assessments every three years under the Affordable Care Act to maintain their tax-exempt status [12]. Since for-profit hospitals are not subject to the requirement to conduct community health needs assessments every three years to qualify for nonprofit status, they may be less likely to be externally motivated to address SDOH and form community partnerships [22]. Similarly, the Centers for Medicare & Medicaid Services (CMS) now requires hospitals to report quality measures related to health equity and SDOH screenings as part of the Inpatient Quality Reporting Program [1]. These regulatory mechanisms compel hospitals to address SDOH, particularly those reliant on Medicare or Medicaid funding. Regulatory compliance (e.g., community health needs assessments mandated by the Affordable Care Act) and financial pressures drive hospitals to adopt SDOH initiatives and engage in community social determinant programs and activities to secure funding and tax-exempt status. Other payers may also place pressure on hospitals to engage in SDOH initiatives and community partnerships with ACO, managed care, bundled payment, and other value-based payment models [23,24]. A 2006 study found evidence of both coercive and mimetic isomorphism with regard to offering community orientation activities but not with regard to health promotion services [25].

2.2. Normative Isomorphism: Professional and Community Expectations

Normative isomorphism results from pressures from community and competitors’ expectations and values that influence hospital behavior. Hospitals with strong equity missions or affiliations with academic institutions are more likely to engage in upstream SDOH initiatives, as these align with broader societal values and professional standards [17]. Additionally, hospitals serving diverse or underserved populations face normative pressures to address health disparities through partnerships with community organizations, reflecting their commitment to community health improvement [21,25].

2.3. Mimetic Isomorphism: Organizational Responses to Uncertainty

Mimetic isomorphism occurs as hospitals emulate successful peers to navigate uncertainties in the healthcare environment. Hospitals in competitive markets often adopt innovations related to SDOH to maintain legitimacy and secure a competitive edge. For example, large teaching hospitals participating in value-based payment models are more likely to implement comprehensive SDOH initiatives, as they serve as examples for smaller institutions [18]. Mimetic behaviors are amplified in competitive markets where legitimacy is linked to innovation and community involvement. The imitation of successful models ensures that hospitals align with perceived best practices, particularly in response to funding uncertainties and market dynamics [26]. Mimetic isomorphism explains how hospitals may adopt innovations and programs that may be considered necessary to stay competitive, especially in highly saturated and competitive markets [27].

2.4. Institutional Legitimacy and SDOH Engagement

Engagement in SDOH initiatives allows hospitals to secure institutional legitimacy by demonstrating alignment with societal values and addressing disparities in population health. Larger, metropolitan hospitals with greater resource availability and executive involvement are more likely to implement robust SDOH programs, as these institutions can achieve economies of scale and justify such activities within their strategic missions [11]. For smaller hospitals, partnerships with community organizations can bolster legitimacy and enhance the effectiveness of SDOH interventions. Normative isomorphism results from pressures from communities and competitors’ expectations and values.
With so much emphasis currently on SDOH, hospitals may be feeling pressure to conform. Institutional Theory underscores the importance of external pressures in shaping hospital strategies for addressing SDOH. Coercive policies, mimetic adoption of peer practices, and normative alignment with community expectations collectively drive hospital engagement with SDOH.
Our research has formulated three hypotheses related to coercive, normative, and mimetic isomorphism and a hospital’s propensity to engage in SDOH initiatives and community social determinant programs.
Our hypotheses:
(1)
Driven by coercive isomorphism, as evidenced through reimbursement mechanisms (bundled payment, ACO membership, and capitation), federally tax-incentivized hospitals (not-for-profit) were positively associated with a hospital’s propensity to engage in SDOH initiatives.
(2)
Being driven by normative isomorphism, critical access hospitals and teaching hospitals were positively associated with a hospital’s propensity to engage in SDOH initiatives due to the need and pressure to gain legitimacy in the community.
(3)
Driven by mimetic isomorphism, hospitals with large sizes, in centralized health systems, or in the competitive marketplace were more likely to engage in community social determinant programs and activities due to a desire to seek competitive advantage and gain legitimacy in their communities.

3. Methods

3.1. Data and Study Design

This was a cross-sectional study using the 2021 American Hospital Association (AHA) Annual Survey data. It represents various types of hospitals, healthcare networks, patients, and communities. The AHA Annual Survey is a valuable resource for identifying hospital programs and activities in relation to community social determinants of health services [3]. This survey contains information on whether hospitals self-report screening of patients for their social needs, programs offered to address patient social needs, and hospital–community partnerships, which is included in Section F of the survey, Addressing Patient Social Needs and Social Determinants of Health [3]. After missing values in some variables were deleted, a total of 5992 hospitals were included in the analysis.

3.2. Measures

Response variables: We identified three dependent variables that reflect hospital community social determinants and health equity programs and activities. The first dependent variable was a composite measure and continuous variable, based on four questions in the AHA survey. Two of the questions ask “which social needs of patients/social determinants of health in communities does your hospital or health system have programs or strategies to address?” and “If yes, please indicate which social needs are assessed?” Each of these two questions has 10 choices covering aspects such as housing instability/quality/financing, food insecurity or hunger, utility needs, interpersonal violence, transportation, employment and income, education, social isolation/lack of family and social support, health behaviors, and other, respectively, and hospitals can check all that apply. A value of “1” was assigned if any of the choices were checked; otherwise, a value of “0” was assigned. The remaining four questions ask about screening patients for social needs, recording the screening results in electronic health records, and being able to gather data indicating that the social determinant activities result in better patient, economic, and community outcomes, which was assigned a value of “0” or “1”, respectively. As a result, the total summarizing score of the four questions ranged from 0 to 28.
The second dependent variable was a composite measure and continuous variable “indicating the extent of the hospital’s current partnerships with external partners for population and/or community health initiatives programs” with 16 types of hospital–community partnership organizations to address patient social needs. Those organizations included (1) other healthcare providers; (2) insurance providers; (3) local/state public health agencies; (4) social service agencies; (5) faith-based organizations; (6) local organizations addressing food insecurity; (7) local organizations addressing transportation needs; (8) local organizations addressing housing insecurity; (9) local organizations providing legal assistance for individuals; (10) other non-profit organizations; (11) local schools; (12) colleges or universities; (13) local businesses; (14) law enforcement and safety services; (15) area behavioral health service providers; and (16) area agencies on aging. For the hospital’s activities with each of the 16 types of community organizations, they were categorized as “not involved”, “work together to meeting patient social needs (e.g., referral arrangement or case management)”, “participates in AHA’s community health needs assessment process”, and “work together to implement community-level initiatives to address social determinants of health”. A value of “1” was assigned if a hospital checked any of the four categories and “check all that apply” was allowed. Therefore, the range of this composite variable was 0–64.
The third dependent variable was a binary variable (yes/no) as to whether the hospital or health system utilizes outcome measures (for example, cost of care or readmission rates) to assess the effectiveness of the interventions to address patients’ social needs. This variable is equal to 1 if a hospital answered “yes” and if they answered “no” or did not respond to the question, their value for this variable is equal to 0.
Independent variables: The Institutional Theory framework not only contextualizes hospital actions but also provides measurable variables in real-world data to assess the drivers and outcomes of SDOH engagement. We arranged our independent variables based on the Institutional Theory that three types of isomorphism (i.e., coercive isomorphism, mimetic isomorphism, and normative isomorphism) drive and shape organizational behavior and actions of hospitals; some of them have been widely used in hospital care research [11,16]. Coercive isomorphism was measured by five variables. Hospital ownership type was defined as non-federal public hospital, not-for-profit private hospital that tended to behave as coercive isomorphism (served as the reference group in comparison), investor-owned private hospital, and federal hospital. We also used four more variables to measure coercive isomorphism, such as whether the hospital had contracts with commercial payers, whether the hospital or healthcare system established an accountable care organization (ACO) [22], and whether the hospital had bundled payment arrangement [22] and percentage participation in Medicaid [16], respectively. Previous research found ownership type, ACO member, and acceptance of bundled payment to be associated with coercive isomorphism [22].
Normative isomorphism was measured by two variables. The critical access hospital (CAH) status was also selected from the AHA survey. Teaching hospital affiliation was defined in the AHA data as major (Member of Council of Teaching Hospital of the Association of American Medical Colleges (COTH)) or minor (participating site recognized for one or more Accreditation Council for Graduate Medical Education accredited programs or medical school affiliation reported to the American Medical Association) and non-teaching (reference). CAHs have been reported to provide less social determinant services [17]. Academic medical centers and CAHs have been found to be associated with normative isomorphism with regard to a hospital’s propensity to form community partnerships [22].
Mimetic isomorphism was measured by three variables. Hospital size was considered at three levels: <100 beds, 100–399 beds, and ≥400 beds. Hospital system types were grouped as centralized health system, centralized physician/health insurance system, moderately centralized health system, decentralized health system (reference), and independent health system. Market competition was a constructed degree of hospital care competition in a local market (by county) calculated by a Herfindahl–Hirschman Index (HHI) that was calculated based on the outpatient care adjusted total annual inpatient admissions per hospital and was then converted to a categorical variable with three levels (competitive market (HHI < 1000), mild concentrated market (1000 ≤ HHI < 1800), and concentrated market (HHI ≥ 1800), (reference)) [28]. Prior studies have shown associations between the level of market competition with hospital strategic responses and behavior [16,22].

3.3. Statistical Analysis and Control Variables

A descriptive analysis was conducted first. Then, multiple linear regression was conducted for the two continuous response variables and multiple logistic regression was employed to examine the relationship between the independent variables and the binary response variable. Several factors were included as control variables that included the hospital management model (i.e., hospital managed by contract or not); hospital type grouped as short-term acute general hospital, mental health hospital, children hospital, specialty hospital, and long-term care hospital; hospital location as rural hospital or non-rural hospital; the percentage of Medicare inpatient days as total inpatient days (Medicare mix); the percentage of Medicaid inpatient days as total inpatient days (Medicaid mix); and the Census Division (i.e., Divisions 1–9) where the hospital is located. During the analysis, major and minor teaching hospitals were combined since only about four percent of hospitals were major teaching hospitals. Finally, over 30% of hospitals had unknown system affiliations; those hospitals were included in the data analysis to maintain the sample size, but their results were not interpreted. SAS 9.14 was used for data analysis and the statistically significant level was set at p < 0.05.

4. Results

Hospital characteristics are displayed in Table 1. For the three dependent variables, the average composite scores of community social determinant activities and community partnership activities were 7.6 and 12.9, respectively, whereas 36.9% of the hospitals used outcome metrics to assess the effects of community social determinant programs and activities.
As shown in Table 1, 8.4% of hospitals were large hospitals with 400 or more beds, 73.0% of the hospitals were acute short-term general hospitals, over half of the hospitals were not-for-profit private hospitals (53.0%), 41.7% of the hospitals were either major or minor teaching hospitals, 16.6.0% of hospitals belonged to decentralized health systems, and 8.9% of the hospitals belonged to centralized health systems. The percentages of Medicare and Medicaid inpatient days as total inpatient days were 47.6% and 18.7%, respectively. A total of 10.3% of the hospitals had capitation arrangements, 6.4% were contract-managed, 33.3% had contracts with commercial insurance payers, 18.8% had ACOs, 15.0% used bundled payment mechanisms, 25.3% were located in rural areas, 22.5% were critical access hospitals, and, finally, over two-thirds of the hospitals (74.7%) were in concentrated markets.

4.1. Factors Associated with Hospital Community Social Determinant Programs and Activities

Table 2 shows the results of associations of hospital factors with their community social determinant programs and activities (CSDPAs). In regard to coercive isomorphism, investor-owned hospitals offered 2.61 (p < 0.001) fewer CSDPAs than their not-for-profit counterparts; hospitals with ACO membership implemented 3.38 (p < 0.001) more community social determinant programs than hospitals without; hospitals participating in bundled payment programs also implemented 2.24 (p < 0.001) more CSDPAs than hospitals not participating; hospitals with capitation arrangement offered 1.60 (p < 0.001) more CSPDAs than those without; and hospitals contracting with commercial insurance offered 4.91 more CSDPAs than those without.
With regard to normative isomorphism, CAHs had 1.27 (p < 0.001) fewer CSDPAs than non-CAHs, whereas teaching hospitals, on average, had 1.03 (p < 0.001) more CSDPAs than their non-teaching counterparts (p < 0.001). In the aspect of mimetic isomorphism, 0.48 more CSPDAs were implemented as hospital bed size moved up by one level; hospitals in any of the non-centralized health systems offered fewer CSDPAs than hospitals in centralized health systems; and hospitals in competitive markets or mild concentrated markets implement 0.59 (p = 0.0036) or 0.73 (p = 0.001) additional SDOH-related activities compared to those in concentrated markets (Table 2).

4.2. Factors Associated with Hospital External Community Partnership

Table 3 displays the results of associations of hospital factors with hospital external partnerships for developing and implementing population and/or community health programs (EPPCHPs). In terms of coercive isomorphism, compared with not-for-profit hospitals, investor-owned hospitals and public hospitals offered 3.10 (p < 0.001) and 2.48 (p < 0.001) fewer EPPCHPs; hospitals with ACO membership had 5.92 (p < 0.001) more EPPCHPs than non-ACO hospitals; hospitals participating in bundled payment programs had 4.87 (p < 0.001) more EPPCHPs than hospitals not participating; hospitals with capitation arrangements offered 2.09 (p < 0.001) more EPPCHPs than those without the arrangements; and hospitals contracting with commercial insurance had 8.51 more EPPCHPs than hospitals without the contracts.
With regard to normative isomorphism, critical access hospitals had 1.40 fewer EPPCHPs than other hospitals (p = 0.007), whereas teaching hospitals, on average, had 1.25 (p < 0.001) more EPPCHPs than their non-teaching counterparts. As for mimetic isomorphism, hospital bed size was positively associated with EPPCHPs, with hospital bed size moving up one level resulting in 0.65 (p < 0.001) more EPPCHPs being implemented, and hospitals in competitive markets had 0.82 more EPPCHPs than their counterparts in concentrated markets. Compared to hospitals in centralized health systems, hospitals in centralized physician/insurance health systems had 1.60 (p < 0.001) more EPPCHPs, whereas hospitals in any of the non-centralized health systems offered fewer EPPCHPs (Table 3).

4.3. Factors Associated with Use of Outcome Measures Assessing Effectiveness of Addressing SDOH in Hospitals

Table 4 lists the results of associations of hospital factors with whether hospitals used outcome metrics assessing the effectiveness of interventions to address patients’ needs. In regard to coercive isomorphism, compared to not-for-profit hospitals, both public hospitals and investor-owned hospitals were less likely to use outcome metrics (OR = 0.78, CI = [0.64, 0.96] for public hospitals, and OR = 0.69, CI = [0.56, 0.85] for investor-owned). Hospitals having ACO membership were more likely to use outcome metrics than their counterparts without ACO membership status (OR = 1.47, CI = [1.19, 1.83]); hospitals participating in bundled payment programs had a higher odds of using outcome metrics than hospitals not participating (OR = 1.41, CI = [1.14, 1.75]); hospitals having capitation reimbursement arrangement had 40% of higher odds of using outcome metrics than those without capitation (OR = 1.40, CI = [1.10, 1.79]); and hospitals contracting with commercial insurance had 186% higher odds of using outcome metrics than those not contracting with commercial insurance (OR = 2.86, CI = [2.40, 3.41]).
With regard to normative isomorphism, critical access hospitals were less likely to use outcome metrics than non-critical access hospitals to conduct assessments (OR = 0.71, CI = [0.57, 0.88]), and teaching and non-teaching hospitals had comparable odds of using outcome metrics (OR = 1.106, CI = [0.93, 1.31]). As for mimetic isomorphism, hospitals at different bed size levels had comparable odds of using outcome metrics. Compared with hospitals in centralized health systems, hospitals in any of the other health systems were less likely to use outcome metrics. Hospitals in competitive markets or mild concentrated markets were more likely to use outcome metrics than hospitals in concentrated markets (OR = 1.27, CI = [1.05, 1.52] for hospitals in competitive markets, (OR = 1.28, CI = [1.04, 1.56] for hospitals in mild concentrated markets) (Table 4).

5. Discussion

This study is a cross-sectional study that explores the organizational factors influencing hospital engagement with social determinants of health (SDOH) initiatives, revealing how organizational characteristics and external pressures shape such efforts. This study highlights characteristics of hospitals that may influence their propensity to engage in activities and community partnerships directed towards SDOH; it identifies associations, but it cannot establish causation. Guided by Institutional Theory, which identifies coercive, mimetic, and normative isomorphic pressures [20,21], our findings suggest that hospitals’ structural attributes and regulatory contexts play significant roles in determining their capacity and willingness to address SDOH. The results across coercive, mimetic, and normative isomorphic forces reveal interconnected dynamics that may be driving hospital engagement in SDOH activities. The constructs of the theory are interconnected, with coercive isomorphism often acting as the initial driver for hospitals to address SDOH, mimetic isomorphism influencing the adoption of peer practices, and normative isomorphism reinforcing sustained engagement through professional and community expectations.
Institutional legitimacy serves as the overarching goal, motivating hospitals to demonstrate their commitment to equity and population health through robust SDOH initiatives. These connections are critical for understanding the systemic nature of hospital engagement with SDOH and the multifaceted pathways influencing organizational behavior. Engagement in SDOH initiatives allows hospitals to secure institutional legitimacy by demonstrating alignment with societal values and addressing disparities in population health.

5.1. SDOH Related to Coercive Isomorphism Among Hospitals

Hypothesis 1, focusing on coercive isomorphism, was strongly supported by our study findings of all five measures for all three dependent variables. Coercive forces are evident in not-for-profit hospitals prioritizing equity missions, community partnerships, and benefits. Nonprofit hospitals, bound by requirements such as the IRS-mandated Community Health Needs Assessment (CHNA), demonstrate greater engagement with social determinants of health compared to for-profit counterparts, who face fewer coercive pressures to prioritize community-oriented goals [22]. Empirical evidence has consistently shown that not-for-profit hospitals are incentivized and motivated to provide more community benefits, including addressing community social determinants and health equity, and engaging community organizations to maintain their legitimacy (as not-for-profit) in communities and strengthen their strategic posture in the marketplace than investor-owned hospitals [29].
Consistent with the existing literature, our findings show that hospitals with federal tax incentives and regulatory incentives like bundled payments, ACO membership, capitation, and CHNAs align with coercive pressures with regard to programs, forming partnerships, and utilizing outcome measures to assess the effectiveness of interventions [18,23,24]. Hospitals may also need to engage in community health initiatives that address social determinants of health to manage their resource dependency on managed-care sources of payment. Policies may force their hand by offering more rewards or penalties for hospitals failing to address social needs. Trying to gain a competitive advantage or maintain legitimacy may also be the driver. Hospitals’ engagement with social determinants of health initiatives is strongly influenced by regulatory mandates and financial models that align incentives with health outcomes. Additionally, value-based payment models like bundled payments and ACOs incentivize investment in upstream interventions to address social needs, reinforcing hospitals’ focus on long-term population health improvements [18,23]. These findings highlight how regulatory frameworks can drive institutional behavior, ensuring alignment with public health priorities.

5.2. SDOH Related to Normative Isomorphism Among Hospitals

Hypothesis 2, focusing on normative isomorphism, was partially supported by the mixed findings of our study. Driven by normative isomorphism, our findings indicate that teaching hospitals are positively associated with a propensity to engage in SDOH initiatives but that was not found to be true for critical access hospitals. Normative pressures, stemming from societal expectations and professional norms, also shape hospitals’ SDOH engagement. Institutions with strong equity missions or affiliations with academic centers are particularly proactive, aligning their activities with community needs and professional standards [30].
Our findings indicate that critical access hospitals were less likely to have SDOH initiatives and programs than non-critical access hospitals, which is in contrast to our hypothesis but is consistent with the existing literature [17]. Critical access hospitals, some of them in rural areas, often face unique constraints, such as limited funding and workforce shortages, which necessitate innovative partnerships to meet community demands [17,31]. These partnerships illustrate how normative pressures compel hospitals to address disparities, even in resource-limited settings.

5.3. SDOH Related to Mimetic Isomorphism Among Hospitals

Hypothesis 3, focusing on mimetic isomorphism, was generally and largely supported by our findings. Driven by mimetic isomorphism, our research found larger hospitals and hospitals in centralized health systems or in competitive markets were more likely to engage in community social determinant programs and create partnerships as found in the existing literature [11,18]. This propensity to engage in social determinants of health activities may be due to a desire to seek competitive advantage and gain legitimacy in the community. Competitive markets and peer-driven norms significantly influence hospitals’ adoption of social determinants of health initiatives and programs. This dynamic reflects mimetic isomorphism, where organizations emulate successful models to maintain legitimacy and competitiveness within their markets [27]. Larger, metropolitan hospitals with greater resource availability and executive involvement are more likely to implement robust social determinants of health programs, as these institutions can achieve economies of scale and justify such activities within their strategic missions [11]. For smaller hospitals, partnerships with community organizations can bolster legitimacy and enhance the effectiveness of social determinants of health interventions. Hospitals in highly competitive markets are more likely to innovate and adopt community health strategies, responding to external pressures to demonstrate leadership in health equity. Consistent with the existing literature, our findings demonstrate that hospitals in competitive markets tend to emulate best practices due to mimetic forces [16] and, while serving as examples for smaller institutions, large teaching hospitals participating in value-based payment models are more likely to implement comprehensive social determinants of health initiatives [18].

5.4. Limitations

This study has several limitations. First, the reliance on self-reported data from the American Hospital Association (AHA) survey may introduce response biases, as hospitals may overstate their involvement in SDOH activities to align with perceived best practices. This social desirability bias is an issue that is difficult to mitigate with a written survey, but there is some degree of anonymity associated with the AHA survey that may curtail overstating. Triangulation of data would be very important especially if we were to examine the outcomes of the programs, but that is not the focus of this study. We recommend future research focuses on connections between SDOH and the outcome or performance of healthcare delivery systems including hospitals. Second, the absence of detailed demographic and socioeconomic data for hospital service areas limits the ability to contextualize findings. Since SDOH impacts individuals and communities differently, it would be useful to know the patient demographic composition and predominant socioeconomic status of the communities each hospital serves. For example, hospitals serving predominantly low-income or minority populations may face unique challenges and opportunities that are not captured in this analysis. Third, the cross-sectional design of this study precludes causal inferences about the relationship between organizational factors and SDOH engagement. Fourth, the absence of standardized reporting guidelines for such interventions may result in inconsistencies across hospitals in how they measure and report their SDOH activities. This variability can limit the comparability of findings and reduce the generalizability of results to other contexts or institutions not included in this study. This study does not analyze the effectiveness of SDOH programs; the survey only asks whether the hospitals gather outcome measures. Without outcome or organizational effectiveness data, determining whether hospitals’ engagement in SDOH activities translates into meaningful improvements in community health is not possible, which merits future research. We would have liked to study more revenue indicators, but the data were insufficient in those areas.

5.5. Policy, Practice, and Research Implications

Policy Implications: Policymakers should consider expanding value-based payment models to incentivize broader participation in SDOH initiatives, especially among smaller and resource-limited hospitals. Programs like Medicare Advantage could incorporate additional rewards for addressing SDOH in underrepresented regions or hospital types. Additionally, strengthening hospital–community partnerships, particularly for rural and safety-net hospitals, could enhance their capacity to address social needs. Rural and safety-net hospitals face financial barriers that partnerships and incentive programs may help alleviate. This could involve grants, philanthropy, innovative care coordination, leveraging value-based payment models, technical assistance, or facilitated collaborations with non-profit organizations.
Practice Implications: Hospitals should prioritize incorporating SDOH findings into Electronic Health Records (EHRs) to streamline data collection and enable automated interventions [32]. Furthermore, increasing board-level involvement in strategic decision-making could foster greater alignment with community health priorities, as previous research has shown external orientation correlates with higher SDOH engagement [15,16,17].
Research implications: Future longitudinal studies could provide more robust insights into the dynamics of hospital–community partnerships and the sustainability of SDOH initiatives. Since some have suggested that the emphasis on SDOH interventions may fade with time, it would be useful to study the hospitals’ commitment to SDOH interventions over the long term. Future research should aim to incorporate regional and policy-level data to provide a more nuanced understanding of the factors shaping hospital-level SDOH interventions. Future research should explore factors such as the involvement of the BOD in defining the strategic mission, whether programs directed at SDOH are impacting health outcomes and patients’ perspectives of SDOH programs. Patient populations served by the hospitals, cost–benefit, equity, appropriateness, and effectiveness of implementation should all be studied. Future research could explore how these forces interact to influence long-term commitment to health equity and the sustainability of SDOH programs.
In conclusion, institutional legitimacy emerges as a key driver, motivating hospitals to actively demonstrate their commitment to equity and population health through comprehensive Social Determinants of Health (SDOH) initiatives. These efforts are crucial for understanding the systemic nature of hospital engagement with SDOH and the complex factors influencing organizational behavior. By engaging in SDOH initiatives, hospitals can enhance their legitimacy, aligning with societal values while addressing health disparities. Our study highlights the systemic dynamics of SDOH initiatives and the diverse pressures shaping hospital decision-making. Despite notable progress, significant gaps remain in the use of outcome metrics to assess SDOH initiatives. Only 36.9% of hospitals reported utilizing outcome measures, emphasizing the need for more robust evaluation frameworks to demonstrate the impact of these programs. Addressing these gaps and strategically leveraging isomorphic forces can enhance hospitals’ capacity to drive health equity and improve community health outcomes. Expanding value-based payment models to include health equity metrics, for instance, could foster wider adoption of outcome-based evaluations, ensuring that SDOH efforts are both effective and sustainable.

Author Contributions

Conceptualization, methodology, software, validation, formal analysis, J.J.S. and K.J.-R.; data curation, J.J.S. and L.H.; writing—original draft preparation, K.J.-R. and W.L.; writing—review and editing, K.J.-R. and J.J.S.; supervision, J.J.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable. This is a non-human subject study.

Informed Consent Statement

Not applicable. This is a non-human subject study.

Data Availability Statement

Data are not available due to the data purchasing agreement with the American Hospital Association.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Social determinant activities and organizational characteristics of U.S. hospitals, 2021 (n = 5992).
Table 1. Social determinant activities and organizational characteristics of U.S. hospitals, 2021 (n = 5992).
VariableFrequencyPercent
Community social determinants and partnership
 Social determinant activities, mean, std7.68.0
 Community partner activities, mean, std12.913.6
 Use of assessment outcomes of community social determinants221136.9
Organizational structure
 Hospital bed size level
   <100 beds340556.8
   100–399 beds208234.8
   ≥400 beds 5058.4
 Hospital type
  General hospital437173.0
  Mental health62210.4
  Children1412.4
  Specialty5108.5
  Long-term care3445.7
 Ownership
  Not for profit 316453.0
  Public120620.1
  Investor-owned162227.1
 Teaching hospital
  Non-teaching 349258.3
  Teaching250041.7
 Health system
  Centralized health system 5328.9
  Centralized physician/insurance health system1893.2
  Moderately centralized health system105317.8
  Decentralized health system 99216.6
  Independent hospital118819.8
  Other or unknown203834.0
Reimbursement and managerial payment model
  % Medicare inpatient days as total inpatient days, mean, std47.621.4
  % Medicaid inpatient days as total inpatient days, mean, std18.715.9
 Capitation
  Yes61710.3
  No537589.7
 Contract Management
  Yes3856.4
  No560793.6
 Contract Commercial
  Yes199333.3
  No399966.7
 ACO
  Yes112718.8
  No486581.2
 Bundled payment
  Yes89915.0
  No509385.0
Geographic location and market environment
 Rural hospital
  Yes151725.3
  No447574.7
 Critical access
   Yes134722.5
  No464577.5
 Market competitiveness
  Concentrated market447874.7
  Competitive market86914.5
  Moderately concentrated market64510.8
Note: std: standard deviation; ACO: accountable care organization.
Table 2. Organizational factors associated with community social determinant programs and activities in U.S. hospitals (n = 5992).
Table 2. Organizational factors associated with community social determinant programs and activities in U.S. hospitals (n = 5992).
VariableParameter EstimateStandard Errorp-Value
Coercive isomorphism
 Ownership type0.480.160.0023
  Private, not for profit (reference)
  Investor-owned−2.610.23<0.0010
  Public−0.970.22<0.0001
 ACO membership3.380.25<0.0001
 Bundled payment2.240.24<0.0001
 Capitation1.600.27<0.0001
 Contract with commercial insurance4.910.21<0.0001
Normative isomorphism
 Critical access hospital−1.270.24<0.0001
 Teaching hospital1.030.19<0.0001
Mimetic isomorphism
 Hospital bed size level0.480.160.0023
 Health system type
  Centralized system (reference)
  Centralized physician insurance0.840.460.0644
  Moderately centralized system−0.630.230.0054
  Decentralized system−0.20.230.0015
  Independent system−0.710.220.0015
 Market competition
  Concentrated market (reference)
  Competitive market0.590.200.0036
  Mild concentrated market0.730.220.001
Note: ACO: accountable care organization. The multivariable anaylis was controlled for hospital contract management, hospital type, Medicare mix, Medicaid mix, rural location, and Census Division.
Table 3. Organizational factors associated with community partnerships with external partners for population and/or community health initiative programs in U.S. hospitals (n = 5992).
Table 3. Organizational factors associated with community partnerships with external partners for population and/or community health initiative programs in U.S. hospitals (n = 5992).
VariableParameter EstimateStandard Errorp-Value
Coercive isomorphism
 Ownership type
  Private, not for profit (reference)
  Investor-owned−3.100.38<0.0001
  Public−2.480.39<0.0001
 ACO membership5.920.42<0.0001
 Bundled payment4.870.42<0.0001
 Capitation 2.090.48<0.0001
 Contract with commercial insurance8.510.37<0.0001
Normative isomorphism
 Critical access hospital−1.400.420.0007
 Teaching hospital0.970.33<0.0001
Mimetic isomorphism
 Hospital bed size level0.650.270.0168
 Health system type
  Centralized system (reference)
  Centralized physician insurance1.370.790.0824
  Moderately centralized system−2.180.39<0.0001
  Decentralized system −1.230.40.0021
  Independent system−1.760.39<0.0001
 Market competition
  Concentrated market (reference)
  Competitive market0.790.350.0248
  Mild concentrated market0.960.380.0125
Note: ACO: accountable care organization. The multivariable anaylis was controlled for hospital contract management, hospital type, Medicare mix, Medicaid mix, rural location, and Census Division.
Table 4. Organizational factors associated with using outcome measures assessing the effectiveness of addressing patients’ social needs (n = 5992).
Table 4. Organizational factors associated with using outcome measures assessing the effectiveness of addressing patients’ social needs (n = 5992).
VariableOdds Ratio95% CIp–Value
Coercive isomorphism
 Ownership type
  Private, not for profit (reference)
  Investor-owned0.69[0.56, 0.85]0.0005
  Public0.78[0.64, 0.96]0.0180
 ACO membership1.47[1.19, 1.83]0.0004
 Bundled payment1.41[1.14, 1.75]0.0016
 Capitation1.40[1.10, 1.79]0.0067
 Contract with commercial insurance2.86[2.40, 3.41]<0.0001
Normative isomorphism
 Critical access hospital0.71[0.57, 0.88]0.0020
 Teaching hospital1.11[0.93, 1.79]0.2511
Mimetic isomorphism
 Hospital bed size level
  <100 beds0.85[0.63, 1.15]0.3042
  100–399 beds0.88[0.67, 1.14]0.3260
  ≥400 beds (reference)
 Health system type
  Centralized system (reference)
  Centralized physician/insurance system 0.61[0.39, 0.95]0.0297
  Moderately centralized system0.43[0.31, 0.58]<0.0001
  Decentralized system0.52[0.39, 0.71]<0.0001
  Independent hospital0.34[0.24, 0.47]<0.0001
 Market competition
  Concentrated market (reference)
  Competitive market1.26[1.05, 1.52]0.0138
  Mild concentrated market1.28[1.04, 1.56]0.0188
Note: CI: confidence interval; ACO: accountable care organization. The multivariable anaylis was controlled for hospital contract management, hospital type, Medicare mix, Medicaid mix, rural location, and Census Division.
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Jones-Rudolph, K.; Lacro, W.; Hurst, L.; Shen, J.J. Organizational Characteristics Associated with Addressing Community Social Determinants of Health in U.S. Hospitals: A National Perspective. Hospitals 2025, 2, 8. https://doi.org/10.3390/hospitals2010008

AMA Style

Jones-Rudolph K, Lacro W, Hurst L, Shen JJ. Organizational Characteristics Associated with Addressing Community Social Determinants of Health in U.S. Hospitals: A National Perspective. Hospitals. 2025; 2(1):8. https://doi.org/10.3390/hospitals2010008

Chicago/Turabian Style

Jones-Rudolph, Kimberly, Wilfredo Lacro, Larry Hurst, and Jay J. Shen. 2025. "Organizational Characteristics Associated with Addressing Community Social Determinants of Health in U.S. Hospitals: A National Perspective" Hospitals 2, no. 1: 8. https://doi.org/10.3390/hospitals2010008

APA Style

Jones-Rudolph, K., Lacro, W., Hurst, L., & Shen, J. J. (2025). Organizational Characteristics Associated with Addressing Community Social Determinants of Health in U.S. Hospitals: A National Perspective. Hospitals, 2(1), 8. https://doi.org/10.3390/hospitals2010008

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