Abstract
Background
Lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse (LGBTQ+) individuals face persistent discrimination in healthcare settings, highlighting organizational inclusion efforts to reduce these inequities. While prior research has largely focused on institutional characteristics, the broader policy and sociopolitical context in which healthcare facilities operate remains underexplored. This study makes a novel contribution by using a multilevel approach to examine how state-level factors (e.g., LGBTQ+ laws, political climate, racial and ethnic demographic composition, and Medicaid expansion) are associated with the implementation of LGBTQ+ inclusive policies and practices within diverse healthcare settings across the United States.
Methods
This cross-sectional study used the Healthcare Equality Index (HEI) data collected in 2021 to evaluate LGBTQ+ inclusion in healthcare facilities. We examined 904 American facilities across 48 states that participated in the HEI in 2021. Multilevel modeling was utilized to investigate the association between different state-level factors (LGBTQ+ inclusiveness in laws, political climate, racial and ethnic minority population, and Medicaid expansion status) and HEI scores in the domains of non-discrimination policies, LGBTQ+ inclusive clinical services, inclusive employee benefits, and LGBTQ+ community engagement within different types of healthcare facilities.
Results
In 48 states, 33.3% were Democratic, 22.9% were divided, and 43.8% were Republican; 70.8% had expanded Medicaid. The mean racial and ethnic minority population was 34.9% (SD = 16.2). Among the 904 facilities, 64.7% were short-term acute care hospitals. State-level political climate and racial and ethnic minority population were significant predictors of LGBTQ+ inclusive patient services within healthcare facilities. Compared to acute care hospitals, rehabilitation hospitals, Veterans Affairs (VA) hospitals, and outpatient facilities had lower scores for non-discrimination policies and LGBTQ+ staff training. VA hospitals scored higher for LGBTQ+ inclusive clinical services. Outpatient facilities, psychiatric and behavioral hospitals, and rehabilitation hospitals had lower scores for inclusive employee benefits, while VA hospitals scored higher. Critical access hospitals, psychiatric and behavioral hospitals, and VA hospitals had lower scores for LGBTQ+ community engagement.
Conclusion
Healthcare leaders must be mindful of the influence of state politics on the continued delivery of LGBTQ+ inclusive clinical services. Additionally, system-level interventions are needed to enhance LGBTQ+ inclusion efforts across various types of healthcare facilities.
Keywords: LGBTQ+ inclusion, Health equity, Sexual and gender minorities, Healthcare Equality Index, Multilevel modeling
Introduction
Lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse (LGBTQ+) individuals experience persistent health disparities, including negative healthcare experiences and discrimination [1, 2]. In a 2023 nationwide survey of LGBTQ+ cancer patients and survivors in the United States (U.S.), 37% reported discrimination in healthcare settings [3]. The survey also revealed that 50% reported concerns about anticipated future discrimination within healthcare settings, with 26% of LGBTQ + patients having avoided seeking care [3]. LGBTQ+ cancer patients and survivors from racial and ethnic minority backgrounds, especially Black and Hispanic patients, reported particularly high levels of concern regarding discriminatory treatment, with 72% of Black and 61% of Hispanic respondents expressing such concerns [3]. These disparities are rooted in social and structural inequities and have resulted in healthcare avoidance and worse health outcomes compared to their non-LGBTQ+ peers [1, 4, 5].
A growing body of literature highlights the scope and diversity of these disparities across mental health [6], veteran care [7, 8], adolescent health [9, 10], primary care [11] and rural health settings [12–14]. In recognition of these disparities, efforts have been made to implement LGBTQ+ inclusive policies and practices across healthcare settings, evaluated through the Healthcare Equality Index (HEI). Established in 2007 by the Human Rights Campaign and administered by the Human Rights Campaign Foundation (HRCF), the HEI assesses various aspects of healthcare policies, practices, and services, providing insights into the degree of LGBTQ+ inclusivity within healthcare organizations [15]. Healthcare facilities that achieve the top score of 100 points are designated as LGBTQ+ Healthcare Equality Leaders [15]. Despite its national use, relatively little is known about how different types of facilities perform across different domains of the HEI and what factors influence their performance.
Understanding health disparities among LGBTQ+ populations requires consideration of various policy, social, and demographic characteristics [16–19]. These factors significantly influence the distribution of resources and health outcomes for residents. Therefore, to comprehensively understand population health, it is essential to comprehend the characteristics of the groups or contexts to which individuals belong, including demographics or political climate at the state level [17–19]. Diverse state-level factors can play crucial roles. Medicaid expansion, particularly in states under the Affordable Care Act, profoundly impacts healthcare access and affordability for LGBTQ+ individuals [20]. Political landscapes shape legal protections and resources available to LGBTQ+ communities, impacting healthcare environments and discrimination levels [21]. The intersectionality of race, ethnicity, and LGBTQ+ identity adds complexity to healthcare disparities, necessitating tailored approaches to achieve health equity [22]. Laws at federal or state levels offer legal protections, promote equal rights, and improve healthcare access [23]. Conversely, anti-LGBTQ+ laws exacerbate disparities and foster discrimination [24–28], affecting healthcare access directly [29–31]. Studies suggest that state-level factors may also indirectly influence healthcare organizations’ decisions regarding policy and practice implementation [32, 33].
However, there is limited understanding of the relationship between state-level factors and organizational-level LGBTQ+ inclusion efforts. While previous research has often focused on institutional factors influencing HEI performance [34, 35], few studies have examined how broader contextual factors shape HEI outcomes across diverse facility types. The socioecological model of sexual and gender minority health disparities research framework [36] describes a complex interplay of individual, interpersonal, community, and societal factors that contribute to LGBTQ+ health disparities. Among these multilevel factors, this study aims to assess how broader policy and sociopolitical environments at the state level may constrain or support LGBTQ+ inclusion efforts within healthcare settings.
Methods
Study design and data source
This cross-sectional study used national HEI data collected in 2021 from the HRCF. The HRCF evaluates and assigns scores to healthcare facilities through the HEI biennially, based on their voluntary completion of an online survey and supporting documentation [15].
Study sample
In 2021, 906 healthcare facilities from Washington, D.C., Puerto Rico, and 47 U.S. states participated in the HEI, with no participation from facilities in Alaska, Idaho, or Wyoming. For the purposes of this study, Washington, D.C. was treated as a state. Two facilities in Puerto Rico were excluded due to significant differences in governance, legislation, and healthcare policies compared to mainland U.S. states [37, 38]. The final sample included 904 healthcare facilities from 48 states, with an average of approximately 19 facilities per state, ranging from 1 to 129. This study received an exemption from the Institutional Review Board because the data were publicly available.
Outcome variable
Scores in four domains of the 2022 HEI, collected in 2021, were used as outcomes. These were: (1) Non-Discrimination and Staff Training (score range: 0 to 40), which assesses non-discrimination policies and staff training in LGBTQ+ patient-centered care; (2) Patient Services and Support (score range: 0 to 30), which evaluates the specific services and support available to meet the needs of LGBTQ+ individuals, including transgender-specific clinical services; (3) Employee Benefits and Policies (score range: 0 to 20), which examines the institution’s policies and benefits for LGBTQ+ employees, such as LGBTQ+ inclusive health insurance benefits; and (4) Patient and Community Engagement (score range: 0 to 10), which assesses the institution’s efforts to engage with the LGBTQ+ community through outreach programs, LGBTQ+ related events, or initiatives. Point deductions occur for policies leading to discrimination or due to recent anti-LGBTQ+ incidents. A comprehensive scoring system, criteria, survey questions and methodology for the 2022 HEI are outlined elsewhere [39].
Level 1 predictor (institution-level)
Institution type
Both outpatient and inpatient facilities were included. Outpatient clinics and ambulatory facilities were consolidated into outpatient facilities. Hospitals were categorized based on Definitive Healthcare’s classification, which accounts for different patient populations and care settings [40]. According to their classification, children’s hospitals focus on patients under 18 years old. Critical access hospitals, designated by the Centers for Medicare and Medicaid, aim to improve healthcare access and financial stability in rural areas, with 25 or fewer beds and over 35 miles from another hospital. Long-term acute care hospitals, providing stays of 25 days or more, offer services such as respiratory therapy and pain management. Psychiatric hospitals offer round-the-clock inpatient care for mental illness. Rehabilitation hospitals specialize in restoring functional abilities. Short-term acute care hospitals provide conventional care for short-term medical needs. Veterans Affairs (VA) hospitals, federally funded and administered by the Veteran’s Administration, serve war veterans and retired military personnel. Due to a limited sample size, inpatient addiction treatment facilities were merged with psychiatric hospitals under psychiatric and behavioral hospitals.
Level 2 predictors (state-level)
LGBTQ+ inclusive legal and policy environment
As laws and policies at the state level have had a significant impact on either the improvement or exacerbation of LGBTQ+ disparities [25, 41], the overall LGBTQ+ policy tally for each state, reported by the Movement Advancement Project (MAP) in 2020 [42], served as a level 2 predictor. MAP assesses LGBTQ+ policies across U.S. states, assigning a score based on nearly 40 laws and policies in various areas such as non-discrimination, healthcare access, criminal justice, identity documents, and school-related policies. A full list is available elsewhere [43]. The possible point range for these scores is from − 18.5 to + 38.5 points [23]. We used the 2020 tally to account for the lag between the changes in laws and potential impacts on healthcare practices measured by the 2022 HEI survey [44–46]. Scores were standardized as continuous variables, indicating that positive scores indicate better-than-average LGBTQ+ policy environments, while negative scores suggest worse-than-average environments.
Political party in control of legislative chambers and governorship
Political dynamics significantly influence policy-making processes that may affect LGBTQ+ inclusivity in healthcare organizations [47, 48]. A state control variable was used as a measure of the political landscape in each state in 2021, obtained from the National Conference of State Legislatures [49]. State control is determined by the party holding power in legislative chambers and the governorship. If one party controls all three, it is considered unified; otherwise, it is divided. This variable was categorized into three levels: Republican control, divided control, and Democratic control. Given the absence of legislative chambers, Nebraska was classified as having Republican control due to its Republican governorship. Washington, D.C. was categorized as having Democratic control because the Democratic Party held power in both the city council and the mayorship throughout 2021.
Percentage of the racial and ethnic minority population
The percentage of racial and ethnic minorities at the state level, sourced from the 2021 American Community Survey 1-year estimate, served as a level 2 predictor [50]. Racial and ethnic minorities encompass groups not classified as non-Hispanic White, historically underrepresented or marginalized within a society or region [51]. Healthcare facilities in areas with higher percentages of minorities may encounter distinct socioeconomic and healthcare access challenges compared to those in regions with lower percentages [52]. These challenges impact the implementation of LGBTQ+ inclusive policies and practices. This variable was operationalized as a continuous variable, calculated by subtracting the percentage of non-Hispanic Whites from 100.
Medicaid expansion status
The Medicaid expansion status for each state, sourced from Kaiser Family Foundation [53], was included as a level 2 predictor due to its potential impact on healthcare access, coverage, and resources [54, 55]. States that expanded Medicaid eligibility under the Affordable Care Act may experience changes in healthcare infrastructure compared to non-expansion states. For example, expanded Medicaid could increase insurance coverage among low-income and uninsured individuals, potentially altering the patient population served by healthcare facilities. Additionally, it might affect organizations’ financial stability, reimbursement rates, and ability to invest in resources and initiatives related to HEI participation or high performance. To account for policy implementation lag, we applied the same time lag approach as used for LGBTQ+ policies. Medicaid expansion status was operationalized as a binary variable: 0 for states that had not expanded Medicaid as of January 1, 2020, and 1 for those that had.
Statistical analysis
We first calculated descriptive statistics for institutional and state characteristics. The association between HEI scores in healthcare facilities and state-level factors was examined using multilevel modeling (MLM) [56, 57]. MLM is suitable for this study’s hierarchical data of institutions within states. A two-level model (level 1: institution, level 2: state) was used to assess the impact of both institutional and state-level factors on LGBTQ+ inclusivity in healthcare.
MLM analyses were conducted using Stata BE 17.0, following established guidelines [58, 59]. The intraclass correlation coefficient (ICC), which indicates the proportion of total variability in the outcome attributable to groupings, was examined to confirm the suitability of MLM. MLM was performed using the identity link function and full information maximum likelihood estimation. A random intercept was included at the state level to account for varying intercepts among states, capturing the heterogeneity within the data.
We specified the null model, level 1 model, and level 2 model. Before specifying each model, we calculated generalized variance inflation factors for every independent variable to evaluate multicollinearity. All variables showed low collinearity except for policy tally and political climate, which exhibited moderate collinearity. Residuals were checked for normality and homoscedasticity, with no violations found. Cook’s distance was used to identify influential outliers, with none exceeding a value of 1 [60]. There were no missing data.
Results
Table 1 provides an overview of the characteristics of the 904 healthcare facilities that participated in the HEI in 2021. These healthcare facilities were located across the U.S., with significant clusters in the Northeast and West regions (Fig. 1). Of these facilities, 64.7% were short-term acute care hospitals, 12.4% were VA hospitals, 11.1% were outpatient facilities, 4.1% were children’s hospitals, 3.3% were psychiatric and behavioral hospitals, 2.8% were critical access hospitals, 1.2% were rehabilitation hospitals, and 0.4% were long-term acute care hospitals. The mean HEI scores for all hospitals were as follows: 38.5 (SD 4.6) for Non-Discrimination and Staff Training, 28.3 (SD 5.4) for Patient Services and Support, 18.1 (SD 4.1) for Employee Benefits and Policies, and 8.3 (SD 3.0) for Patient and Community Engagement.
Table 1.
Institution and State Characteristics
| Institution Characteristics | |||||||
|
Institution [N = 904] |
Non-Discrimination and Staff Training [mean (SD)] | Patient Services and Support [mean (SD)] | Employee Benefits and Policies [mean (SD)] |
Patient and Community Engagement [mean (SD)] |
Deduction (mean) |
||
| All Institutions | 904 (100) | 38.5 (4.6) | 28.3 (5.4) | 18.1 (4.1) | 8.3 (3.0) | −0.8 | |
| Institution Type† [n (%)] | |||||||
| Short-term acute care hospital | 585 (64.7) | 39.0 (3.8) | 28.3 (5.6) | 18.5 (3.2) | 8.8 (2.6) | −0.3 | |
| Children’s hospital | 37 (4.1) | 39.9 (0.8) | 29.6 (2.5) | 19.5 (1.6) | 9.5 (1.6) | −0.7 | |
| Critical access hospital | 25 (2.8) | 37.4 (5.8) | 28.2 (5.0) | 17.2 (5.0) | 7.4 (2.9) | −0.2 | |
| Long-term acute care hospital | 4 (0.4) | 40 (0) | 30 (0) | 20 (0) | 10 (0) | 0 | |
| Outpatient facility | 100 (11.1) | 37.2 (6.2) | 27 (6.4) | 15 (7.2) | 8.1 (3.2) | −0.1 | |
| Psychiatric and behavioral hospital | 30 (3.3) | 37.3 (5.5) | 26.5 (6.5) | 16.3 (5.6) | 7 (3.4) | 0 | |
| Rehabilitation hospital | 11 (1.2) | 34.1 (11.6) | 24.5 (10.1) | 15 (7.7) | 8.2 (4.0) | 0 | |
| Veterans Affairs hospital | 112 (12.4) | 37.6 (5.1) | 30 (0) | 19.6 (1.4) | 6.5 (4.0) | −5 | |
| State Characteristics | |||||||
|
States ‡ [N = 48] |
Institution [N = 904] |
Non-Discrimination and Staff Training [mean (SD)] |
Patient Services and Support [mean (SD)] |
Employee Benefits and Policies [mean (SD)] |
Patient and Community Engagement [mean (SD)] |
Deduction (mean) |
|
| Political Party in Control [n (%)] | |||||||
| Democratic | 16 (33.3) | 452 (50) | 39.1 (3.6) | 29.3 (3.5) | 18.7 (3.4) | 8.7 (2.7) | −0.6 |
| Divided | 11 (22.9) | 260 (28.8) | 37.8 (5.3) | 26.8 (7.4) | 17.9 (4.0) | 8.1 (3.0) | −0.6 |
| Republican | 21 (43.8) | 192 (21.2) | 37.9 (5.3) | 28.1 (5.4) | 17.2 (5.4) | 7.7 (3.4) | −1.6 |
| Medicaid Expansion [n (%)] | |||||||
| Expanded | 14 (29.2) | 733 (81.1) | 38.6 (4.5) | 28.3 (5.5) | 18.4 (3.8) | 8.4 (2.9) | −0.7 |
| Not expanded | 34 (70.8) | 171 (18.9) | 38.1 (4.8) | 28.5 (4.8) | 17.1 (5.0) | 7.9 (3.2) | −1.3 |
| LGBTQ+ Policy Tally [mean (SD)] | 14.5 (14.4) | ||||||
| Racial and Ethnic Minority Population [mean (SD)] | 34.9 (16.2) | ||||||
Abbreviation SD standard deviation, LGBTQ+ Lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse individuals
†Children’s hospitals focus on patients under 18 years old. Critical access hospitals, designated by the Centers for Medicare and Medicaid, aim to improve healthcare access and financial stability in rural areas, with 25 or fewer beds and over 35 miles from another hospital. Long-term acute care hospitals, providing stays of 25 days or more, offer services such as respiratory therapy and pain management. Psychiatric hospitals offer round-the-clock inpatient care for mental illness. Rehabilitation hospitals specialize in restoring functional abilities. Short-term acute care hospitals provide conventional care for short-term medical needs. Veterans Affairs hospitals, federally funded and administered by the Veteran’s Administration, serve war veterans and retired military personnel
‡The states included 47 U.S. states and Washington D.C., excluding Alaska, Idaho and Wyoming due to the unavailability of data
Fig. 1.
Geographic Distribution of Healthcare Facilities Participating in the Healthcare Equality Index in 2021. This map displays the 904 healthcare facilities that participated in the 2022 Healthcare Equality Index (HEI), collected in 2021. Short-term acute care hospitals that participated in the HEI were clustered in the Northeast and West regions, whereas participating facilities in the Midwest and South regions were predominantly Veterans Affairs hospitals, albeit in smaller numbers
Table 1 also presents the characteristics of the 48 states in which the 904 healthcare facilities are located. In terms of political party control of legislative chambers and the governorship, 33.3% were Democratic, 22.9% were divided, and 43.8% were Republican. Regarding Medicaid expansion, 70.8% of states had expanded Medicaid as of 2020, while 29.2% had not. The mean LGBTQ+ policy tally among the states was 14.5 (SD = 14.4), ranging from − 6.5 to 34.75. The mean racial and ethnic minority population was 34.9% (SD 16.2). The state-level political climate and the locations of HEI-participating healthcare facilities exhibit a spatial pattern, with states under Democratic or divided control having more HEI-participating facilities compared to states under Republican control (Fig. 2).
Fig. 2.
Political Climate and Participation in the Healthcare Equality Index in 2021. This map illustrates the state-level political climate in 2021, when the 2022 Healthcare Equality Index (HEI) data were collected, alongside healthcare institutions that participated in the 2022 HEI. The state-level political climate and the locations of HEI-participating healthcare facilities exhibit a spatial pattern, with states under Democratic or divided control having more HEI-participating facilities compared to states under Republican control
Non-discrimination and staff training
The multilevel model comprises a fixed effects component, denoted by gamma (γ) coefficients, which includes level 1 and level 2 slope coefficients. Additionally, it includes a random effects component represented by tau (τ) coefficients, signifying variability across state contexts [59].
Null model
The constant term, representing the overall average HEI score for Non-Discrimination and Staff Training across all facilities, assuming no differences between states, was 38.16 (Table 2). The ICC was 0.09. There was significant variability among individual facilities within the same state (τ = 19.43; 95% CI: 17.68 to 21.37) and across states (τ = 1.93; 95% CI: 0.84 to 4.43).
Table 2.
Multilevel Model with Non-Discrimination and Staff Training Scores
| Null Model | ||||
| Parameter | Estimate | Std. error | 95% CI | ICC |
| Constant term | 38.16 | 0.29 | 37.60 to 38.72 | 0.09 |
| Residual | 19.43 | 0.94 | 17.68 to 21.37 | |
| Intercept (State ID) | 1.93 | 0.82 | 0.84 to 4.43 | |
| Level 1 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 38.66 | 0.29 | 38.07 to 39.24 | <0.001 |
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.83 | 0.75 | -0.63 to 2.29 | 0.266 |
| Critical access hospital | -1.56 | 0.91 | -3.34 to 0.21 | 0.084 |
| Long-term acute care hospital | 0.64 | 2.20 | -3.68 to 4.97 | 0.770 |
| Outpatient facility | -1.48 | 0.43 | -2.45 to -0.52 | 0.003 |
| Psychiatric and behavioral hospital | -1.52 | 0.82 | -3.13 to 0.10 | 0.066 |
| Rehabilitation hospital | -4.63 | 1.34 | -7.27 to -2.00 | 0.001 |
| Veterans Affairs hospital | -1.11 | 0.46 | -2.02 to -0.20 | 0.017 |
| Radom-effects parameters† | ||||
| Residual | 18.96 | 0.92 | 17.24 to 20.85 | 0.001 |
| Intercept (State ID) | 1.38 | 0.70 | 0.51 to 3.71 | 0.001 |
| Level 2 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 40.56 | 1.26 | 38.02 to 43.10 | <0.001 |
| Level 1 predictor | ||||
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.82 | 0.75 | -0.64 to 2.29 | 0.271 |
| Critical access hospital | -1.51 | 0.91 | -3.29 to 0.28 | 0.098 |
| Long-term acute care hospital | 0.65 | 2.21 | -3.68 to 4.98 | 0.769 |
| Outpatient facility | -1.50 | 0.49 | -2.46 to -0.53 | 0.002 |
| Psychiatric and behavioral hospital | -1.53 | 0.82 | -3.14 to 0.09 | 0.064 |
| Rehabilitation hospital | -4.58 | 1.34 | -7.22 to -1.94 | 0.001 |
| Veterans Affairs hospital | -1.09 | 0.47 | -2.01 to -0.17 | 0.021 |
| Level 2 predictors | ||||
| LGBTQ+ inclusiveness in laws and policies | -0.01 | 0.37 | -0.74 to 0.71 | 0.969 |
| % of racial and ethnic minority population | -0.02 | 0.02 | -0.06 to 0.02 | 0.318 |
| Medicaid expansion status (reference: no Medicaid expansion) | ||||
| Medicaid expansion | -0.35 | 0.68 | -1.69 to 0.98 | 0.606 |
| Political party in control of legislative chambers and governorship (reference: Democratic) | ||||
| Divided | -1.51 | 0.74 | -2.96 to -0.06 | 0.042 |
| Republican | -1.41 | 0.90 | -3.17 to 0.35 | 0.116 |
| Radom-effects parameters | ||||
| Residual | 19.04 | 0.93 | 17.30 to 20.95 | 0.022 |
| Intercept (State ID) | 0.86 | 0.61 | 0.22 to 3.43 | 0.022 |
Abbreviation ICC intraclass correlation, CI confidence interval, LGBTQ+ lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse individuals
†The statistical significance of the random-effects parameters was determined using the likelihood ratio test
Level 1 model– institution-level effects
Outpatient facilities (γ = −1.48, p = 0.003), rehabilitation hospitals (γ = −4.63, p = 0.001), and VA hospitals (γ = −1.11, p = 0.017) showed significantly lower scores compared to short-term acute care hospitals.
Level 2 model– state-level effects
Rehabilitation hospitals (γ = −4.58, p = 0.001), VA hospitals (γ = −1.09, p = 0.021) and outpatient facilities (γ = −1.50, p = 0.002) showed significantly lower scores compared to short-term acute care hospitals. Additionally, states with divided partisan control of legislative chambers and governorship had significantly lower scores compared to states with Democratic party control (γ = −1.51, p = 0.042).
Patient services and support
Null model
The constant term, representing the overall average HEI score for Patient Services and Support across all facilities, assuming no differences between states, was 28.16 (Table 3). The ICC was 0.18, indicating substantial variability between states. There was significant variability among individual facilities within the same state (τ = 24.71; 95% CI: 22.49 to 27.16) and across states (τ = 5.31; 95% CI: 2.99 to 9.41).
Table 3.
Multilevel Model with Patient Services and Support Scores
| Null Model | ||||
| Parameter | Estimate | Std. error | 95% CI | ICC |
| Constant term | 28.16 | 0.42 | 27.35 to 28.98 | 0.18 |
| Residual | 24.71 | 1.19 | 22.49 to 27.16 | |
| Intercept (State ID) | 5.31 | 1.55 | 2.99 to 9.41 | |
| Level 1 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 27.76 | 0.44 | 26.89 to 28.64 | < 0.001 |
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 1.06 | 0.84 | −0.60 to 2.72 | 0.210 |
| Critical access hospital | 0.04 | 1.03 | −1.99 to 2.06 | 0.972 |
| Long-term acute care hospital | 0.55 | 2.48 | −4.33 to 5.42 | 0.826 |
| Outpatient facility | −0.48 | 0.56 | −1.58 to 0.62 | 0.391 |
| Psychiatric and behavioral hospital | −1.19 | 0.93 | −3.01 to 0.64 | 0.203 |
| Rehabilitation hospital | −2.30 | 1.52 | −5.28 to 0.68 | 0.130 |
| Veterans Affairs hospital | 2.15 | 0.53 | 1.10 to 3.19 | < 0.001 |
| Radom-effects parameters† | ||||
| Residual | 24.09 | 1.16 | 21.92 to 26.47 | < 0.001 |
| Intercept (State ID) | 4.96 | 1.46 | 2.79 to 8.85 | < 0.001 |
| Level 2 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 34.14 | 1.84 | 30.44 to 37.84 | < 0.001 |
| Level 1 predictor | ||||
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 1.04 | 0.84 | −0.61 to 2.70 | 0.216 |
| Critical access hospital | 0.01 | 1.03 | −2.02 to 2.02 | 0.998 |
| Long-term acute care hospital | 0.56 | 2.48 | −4.31 to 5.44 | 0.821 |
| Outpatient facility | −0.50 | 0.56 | −1.60 to 0.60 | 0.371 |
| Psychiatric and behavioral hospital | −1.25 | 0.93 | −3.07 to 0.58 | 0.180 |
| Rehabilitation hospital | −2.29 | 1.52 | −5.27 to 0.68 | 0.131 |
| Veterans Affairs hospital | 2.12 | 0.53 | 1.07 to 3.17 | < 0.001 |
| Level 2 predictors | ||||
| LGBTQ+ inclusiveness in laws and policies | −0.24 | 0.56 | −1.33 to 0.85 | 0.668 |
| % of racial and ethnic minority population | −0.08 | 0.03 | −0.13 to −0.02 | 0.006 |
| Medicaid expansion status (reference: no Medicaid expansion) | ||||
| Medicaid expansion | −1.62 | 1.00 | −3.59 to 0.35 | 0.106 |
| Political party in control of legislative chambers and governorship (reference: Democratic) | ||||
| Divided | −4.12 | 1.11 | −6.30 to −1.93 | < 0.001 |
| Republican | −3.69 | 1.34 | −6.31 to −1.06 | 0.006 |
| Radom-effects parameters | ||||
| Residual | 24.09 | 1.16 | 21.92 to 26.47 | < 0.001 |
| Intercept (State ID) | 3.00 | 1.05 | 1.52 to 5.96 | < 0.001 |
Abbreviation ICC intraclass correlation, CI confidence interval, LGBTQ+ lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse individuals
†The statistical significance of the random-effects parameters was determined using the likelihood ratio test
Level 1 model– institution-level effects
VA hospitals (γ = 2.15, p < 0.001) showed significantly higher scores compared to short-term acute care hospitals.
Level 2 model– state-level effects
VA hospitals (γ = 2.12, p < 0.001) showed significantly higher scores compared to short-term acute care hospitals. Additionally, a higher percentage of racial and ethnic minority population in a state was significantly associated with lower scores (γ = −0.08, p = 0.006). States with divided partisan control of legislative chambers and governorship (γ = −4.12, p < 0.001) and Republican party control (γ = −3.69, p = 0.006) showed significantly lower scores compared to states with Democratic party control.
Employee benefits and policies
Null model
The constant term, representing the overall average HEI score for Employee Benefits and Policies across all facilities, assuming no differences between states, was 17.50 (Table 4). The ICC was 0.17, indicating substantial variability between states. There was significant variability among individual facilities within the same state (τ = 14.66; 95% CI: 13.33 to 16.11) and across states (τ = 2.91; 95% CI: 1.54 to 5.51).
Table 4.
Multilevel Model with Employee Benefits and Policies Scores
| Null Model | ||||
| Parameter | Estimate | Std. error | 95% CI | ICC |
| Constant term | 17.50 | 0.31 | 16.89 to 18.11 | 0.17 |
| Residual | 14.66 | 0.71 | 13.33 to 16.11 | |
| Intercept (State ID) | 2.91 | 0.95 | 1.54 to 5.51 | |
| Level 1 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 17.50 | 0.33 | 16.83 to 18.17 | < 0.001 |
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.92 | 0.62 | −0.30 to 2.13 | 0.139 |
| Critical access hospital | −1.31 | 0.76 | −2.80 to 0.17 | 0.082 |
| Long-term acute care hospital | 0.67 | 1.82 | −2.90 to 4.24 | 0.711 |
| Outpatient facility | −3.06 | 0.41 | −3.87 to −2.25 | < 0.001 |
| Psychiatric and behavioral hospital | −1.90 | 0.68 | −3.24 to −0.56 | 0.005 |
| Rehabilitation hospital | −3.50 | 1.11 | −5.68 to −1.32 | 0.002 |
| Veterans Affairs hospital | 1.91 | 0.39 | 1.14 to 2.67 | < 0.001 |
| Radom-effects parameters† | ||||
| Residual | 12.91 | 0.63 | 11.74 to 14.19 | < 0.001 |
| Intercept (State ID) | 3.06 | 0.99 | 1.62 to 5.77 | < 0.001 |
| Level 2 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p-value |
| Intercept | 17.82 | 1.56 | 14.69 to 20.95 | < 0.001 |
| Level 1 predictor | ||||
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.94 | 0.62 | −0.27 to 2.15 | 0.129 |
| Critical access hospital | −1.31 | 0.76 | −2.79 to 0.17 | 0.083 |
| Long-term acute care hospital | 0.67 | 1.82 | −2.90 to 4.23 | 0.715 |
| Outpatient facility | −3.04 | 0.41 | −3.85 to −2.23 | < 0.001 |
| Psychiatric and behavioral hospital | −1.92 | 0.68 | −3.26 to −0.59 | 0.005 |
| Rehabilitation hospital | −3.48 | 1.11 | −5.66 to −1.30 | 0.002 |
| Veterans Affairs hospital | 2.01 | 0.39 | 1.24 to 2.78 | < 0.001 |
| Level 2 predictors | ||||
| LGBTQ+ inclusiveness in laws and policies | 0.17 | 0.48 | −0.77 to 1.11 | 0.723 |
| % of racial and ethnic minority population | −0.01 | 0.02 | −0.05 to 0.04 | 0.925 |
| Medicaid expansion status (reference: no Medicaid expansion) | ||||
| Medicaid expansion | 0.27 | 0.85 | −1.40 to 1.95 | 0.748 |
| Political party in control of legislative chambers and governorship (reference: Democratic) | ||||
| Divided | 0.16 | 0.96 | −1.73 to 2.04 | 0.869 |
| Republican | −1.13 | 1.15 | −3.38 to 1.13 | 0.327 |
| Radom-effects parameters | ||||
| Residual | 12.89 | 0.62 | 11.73 to 14.18 | < 0.001 |
| Intercept (State ID) | 2.55 | 0.88 | 1.30 to 5.00 | < 0.001 |
Abbreviation ICC = intraclass correlation, CI = confidence interval, LGBTQ+ lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse individuals
†The statistical significance of the random-effects parameters was determined using the likelihood ratio test
Level 1 model– institution-level effects
Outpatient facilities (γ = −3.06, p < 0.001), psychiatric and behavioral hospitals (γ = −1.90, p = 0.005), rehabilitation hospitals (γ = −3.50, p = 0.002) showed significantly lower scores compared to short-term acute care hospitals. VA hospitals (γ = 1.91, p < 0.001) showed significantly higher scores compared to short-term acute care hospitals.
Level 2 model– state-level effects
Outpatient facilities (γ = −3.04, p < 0.001), psychiatric and behavioral hospitals (γ = −1.92, p = 0.005), rehabilitation hospitals (γ = −3.48, p = 0.002) showed significantly lower scores compared to short-term acute care hospitals. VA hospitals (γ = 2.01, p < 0.001) showed significantly higher scores compared to short-term acute care hospitals. No level 2 predictors were significantly associated with the score.
Patient and community engagement
Null model
The constant term, representing the overall average HEI score for Patient and Community Engagement across all facilities, assuming no differences between states, was 7.71 (Table 5). The ICC was 0.24, the highest among the four HEI scores. There was significant variability among individual facilities within the same state (τ = 7.36; 95% CI: 6.70 to 8.09) and across states (τ = 2.31; 95% CI: 1.30 to 4.10).
Table 5.
Multilevel Model with Patient and Community Engagement Scores
| Null Model | ||||
| Parameter | Estimate | Std. error | 95% CI | ICC |
| Constant term | 7.71 | 0.26 | 7.19 to 8.22 | 0.24 |
| Residual | 7.36 | 0.36 | 6.70 to 8.09 | |
| Intercept (State ID) | 2.31 | 0.68 | 1.30 to 4.10 | |
| Level 1 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p -value |
| Intercept | 8.24 | 0.26 | 7.71 to 8.77 | < 0.001 |
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.58 | 0.45 | −0.31 to 1.47 | 0.203 |
| Critical access hospital | −1.30 | 0.55 | −2.39 to −0.21 | 0.019 |
| Long-term acute care hospital | 0.45 | 1.33 | −2.17 to 3.06 | 0.737 |
| Outpatient facility | −0.48 | 0.30 | −1.08 to 0.11 | 0.112 |
| Psychiatric and behavioral hospital | −1.63 | 0.50 | −2.61 to −0.65 | 0.001 |
| Rehabilitation hospital | −0.75 | 0.81 | −2.35 to 0.84 | 0.355 |
| Veterans Affairs hospital | −1.88 | 0.29 | −2.45 to −1.32 | < 0.001 |
| Radom-effects parameters† | ||||
| Residual | 6.92 | 0.34 | 6.29 to 7.61 | < 0.001 |
| Intercept (State ID) | 2.08 | 0.63 | 1.15 to 3.75 | < 0.001 |
| Level 2 Model | ||||
| Parameter | Estimate | Std. error | 95% CI | p -value |
| Intercept | 8.71 | 1.27 | 6.15 to 11.28 | < 0.001 |
| Level 1 predictor | ||||
| Institution type (reference: short-term acute care hospital) | ||||
| Children’s hospital | 0.58 | 0.45 | −0.31 to 1.47 | 0.203 |
| Critical access hospital | −1.31 | 0.56 | −2.40 to −0.22 | 0.019 |
| Long-term acute care hospital | 0.43 | 1.33 | −2.18 to 3.05 | 0.745 |
| Outpatient facility | −0.50 | 0.30 | −1.09 to 0.10 | 0.101 |
| Psychiatric and behavioral hospital | −1.64 | 0.50 | −2.62 to −0.66 | 0.001 |
| Rehabilitation hospital | −0.74 | 0.81 | −2.34 to 0.86 | 0.362 |
| Veterans Affairs hospital | −1.87 | 0.29 | −2.44 to −1.30 | < 0.001 |
| Level 2 predictors | ||||
| LGBTQ+ inclusiveness in laws and policies | 0.55 | 0.40 | −0.23 to 1.32 | 0.169 |
| % of racial and ethnic minority population | −0.01 | 0.02 | −0.04 to 0.04 | 0.946 |
| Medicaid expansion status (reference: no Medicaid expansion) | ||||
| Medicaid expansion | −0.67 | 0.70 | −2.05 to 0.70 | 0.339 |
| Political party in control of legislative chambers and governorship (reference: Democratic) | ||||
| Divided | 0.29 | 0.80 | −1.28 to 1.85 | 0.718 |
| Republican | 0.50 | 0.95 | −1.36 to 2.37 | 0.597 |
| Radom-effects parameters | ||||
| Residual | 6.93 | 0.34 | 6.30 to 7.62 | < 0.001 |
| Intercept (State ID) | 1.89 | 0.60 | 1.01 to 3.53 | < 0.001 |
Abbreviation ICC intraclass correlation, CI confidence interval, LGBTQ+ lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse individuals
†The statistical significance of the random-effects parameters was determined using the likelihood ratio test
Level 1 model– institution-level effects
Critical access hospitals (γ = −1.30, p = 0.019), psychiatric and behavioral hospitals (γ = −1.63, p = 0.001), and VA hospitals (γ = −1.88, p < 0.001) had significantly lower scores compared to short-term acute care hospitals.
Level 2 model– state-level effects
Critical access hospitals (γ = −1.31, p = 0.019), psychiatric and behavioral hospitals (γ = −1.64, p = 0.001), and VA hospitals (γ = −1.87, p < 0.001) had significantly lower scores compared to short-term acute care hospitals. No level 2 predictors were significantly associated with the score.
Discussion
This study’s findings suggest that both institutional factors and state-level geospatial indicators are associated with LGBTQ+ inclusivity within healthcare facilities. The political landscape was significantly linked to the Patient Services and Support domain of the HEI, highlighting disparities in inclusive care and healthcare access across states. Data from the 2022 U.S. Transgender Survey supports this finding, with nearly half of respondents considering relocation due to discriminatory state laws and 5% moving to another location [4]. These results underscore the need to consider political factors when designing strategies to advance LGBTQ+ inclusion in healthcare. In politically restrictive environments and for organizations that rely on state funding, protecting inclusive services requires proactive, multifaceted efforts. Healthcare leaders can strengthen institutional commitment to LGBTQ+ equity by embedding inclusive practices into internal policies, staff training, and care protocols, making them less vulnerable to external policy shifts. Establishing long-term partnerships with trusted community-based organizations can also bolster service delivery and advocacy efforts. Diversifying funding sources through philanthropic or nonprofit partnerships may help reduce overdependence on state-controlled funding. Although balancing political constraints and inclusive care delivery is challenging—as noted by nurse executives in a recent qualitative study [61]—these strategies are vital to sustaining LGBTQ+ services amid rising legislative threats.
There are several reasons why state-level policies in our study may not have reached statistical significance, even though political control emerged as a significant predictor. First, we observed a moderate correlation between political control and state-level policies, indicating that right-leaning state governments often adopt more restrictive policies toward LGBTQ+ populations. This raises the possibility that the observed associations of political control may overlap with or obscure the associations of specific policies. Second, our overall policy tally score encompasses nearly 40 laws across different policy areas. It is possible that certain laws or combinations of policies have a more substantial impact on HEI scores than the overall tally indicates. Future research should consider breaking down these laws and analyzing their individual effects on HEI scores to pinpoint the most impactful policies. Third, although we used policies from the previous year, a one-year gap may not be sufficient to fully observe their impact. The time lag between the enactment of policies and their practical effects on hospital operations or staff training might exceed a single year. Future studies should investigate the effects of policies over a more extended period, potentially examining multiple years of data to capture their full impact. Finally, these policies might directly influence patient-level outcomes rather than affecting hospital-level characteristics. Future research should investigate the impact of implementing LGBTQ+ inclusive policies and practices on patient-level outcomes.
Additionally, higher percentage of racial and ethnic minority populations at the state level was linked to lower scores in this domain. While this may seem counterintuitive—since greater diversity is often assumed to foster inclusivity—our findings suggest that institutional practices may be constrained by adverse state-level political and legal contexts. For example, many facilities in racially and ethnically diverse states such as Florida, Texas, Arizona, and Louisiana demonstrated strong community engagement—an institutional-level strength—yet were located in states with restrictive or anti-LGBTQ+ healthcare laws. These nuances may not have been fully captured in our analysis, as we used an overall LGBTQ+ policy tally that includes a broad range of social policies, not just those related to restrictive clinical services. These broader policy climates may limit institutional capacity to implement inclusive services, regardless of local community need or engagement.
This finding can also be understood through the lens of intersectionality, which examines how overlapping social identities, such as race, ethnicity, and LGBTQ+ status, create unique experiences and challenges [62]. Racial and ethnic minority populations often face systemic challenges such as discrimination, socioeconomic disadvantage, and limited access to culturally responsive care compared to non-Hispanic White populations [63, 64]. These intersecting challenges may further marginalize LGBTQ+ individuals within these populations and complicate efforts by healthcare institutions to meet their needs. As such, even in states with high racial and ethnic diversity and strong community engagement, structural and policy-level barriers may hinder the provision of inclusive and supportive services. These findings underscore the need for targeted strategies that consider both the demographic makeup and the policy environment of a state to ensure that healthcare services are fully inclusive and responsive to LGBTQ+ individuals with intersectional identities.
Alongside state-level factors, variations in HEI scores across different facility types at the institutional level hold significant implications for the health and well-being of LGBTQ+ subpopulations. While VA hospitals scored higher in Patient Services and Support and Employee Benefits and Policies compared to short-term acute care hospitals, they scored lower in Non-Discrimination and Staff Training, as well as Patient and Community Engagement. Moreover, VA hospitals received the highest score deductions due to the VA medical benefits plan’s exclusion of gender-affirming surgeries. This exclusion is an organizational policy beyond the control of individual providers and facilities, highlighting systemic barriers within the VA health system. Addressing these issues within the VA health system is crucial, especially considering the growing recognition of health disparities among LGBTQ+ veterans [7, 8]. Targeted interventions and policy changes are necessary to enhance LGBTQ+ inclusivity within VA healthcare settings. These could include advocating for policy revisions to include gender-affirming surgeries, enhancing effective staff training on LGBTQ+ issues [65], and implementing comprehensive non-discrimination policies.
Psychiatric and behavioral hospitals exhibited underperformance in both Employee Benefits and Policies, as well as Patient and Community Engagement, in comparison to short-term acute care hospitals. This finding is significant considering the well-documented mental health disparities among LGBTQ+ individuals [6, 9] and their heightened tendency to avoid healthcare due to discrimination [66, 67]. One possible contributing factor may be the heavier reliance of psychiatric and behavioral hospitals on state funding [68], which can constrain their ability or willingness to adopt LGBTQ+ inclusive policies—particularly in states with restrictive political climates. To address these disparities, psychiatric and behavioral hospitals should consider implementing targeted interventions to improve LGBTQ+ inclusivity. These could include establishing LGBTQ+ patient advisory councils [69] or LGBTQ+ employee resource groups [61] to promote engagement and trust. Even within constrained financial or political environments, strategic and evidence-informed inclusivity initiatives can play a vital role in mitigating mental health disparities and promoting equitable care delivery.
Additionally, critical access hospitals displayed lower HEI scores in Patient and Community Engagement compared to short-term acute care hospitals. Given the well-documented health and healthcare disparities among LGBTQ+ individuals in rural areas [12–14], there is an urgent need for critical access hospitals to strategically prioritize and actively engage with the LGBTQ+ community. Enhancing community engagement in critical access hospitals demands tailored strategies that consider the unique needs and constraints of rural healthcare settings [70]. This could involve leveraging telehealth technologies to extend outreach efforts and collaborating with local LGBTQ+ organizations to facilitate community events and educational workshops.
Compared to short-term acute care hospitals, outpatient facilities exhibited underperformance in the domains of Non-Discrimination and Staff Training, as well as Employee Benefits and Policies. Given the pivotal role outpatient facilities play in delivering a wide range of healthcare services, often serving as primary points of contact for patients seeking routine care, preventive services, and specialized treatments [11], it is crucial to ensure robust non-discrimination policies and staff training programs within these settings. Additionally, providing comprehensive employee benefits and policies that support LGBTQ+ healthcare providers and staff fosters a more inclusive and supportive work environment, ultimately contributing to better patient care and outcomes.
While rehabilitation hospitals demonstrated underperformance in the HEI compared to short-term acute care hospitals, it is essential to note that inferences may not be robust due to their limited sample size. This underscores the importance of developing more effective strategies to encourage these types of facilities to participate in the HEI, allowing for a more comprehensive assessment of their LGBTQ+ inclusive policies and practices and facilitating improvements in these areas.
Overall, Patient and Community Engagement exhibits the highest variability between states, with many types of facilities demonstrating suboptimal performance in this aspect. Active community engagement denotes the process of actively and meaningfully involving community members in decision-making, problem-solving, and activities that impact their lives and well-being [71–73]. This involvement transcends mere information dissemination or consultation; it emphasizes collaboration, partnership, and empowerment. It entails building relationships, fostering trust, and appreciating the knowledge, experiences, and perspectives of LGBTQ+ community members. LGBTQ+ community engagement should endeavor to ensure that community voices are not only heard but also respected and integrated into the planning, implementation, and evaluation of initiatives, policies, or programs aimed at addressing community needs and fostering positive social change [74, 75].
Several factors must be considered when evaluating this study. Although the utilization of a national sample adds to the study’s robustness and generalizability, it is crucial to acknowledge a potential limitation stemming from the voluntary nature of facilities’ participation in the HEI, which introduces the possibility of selection bias. Another limitation worth noting is the cross-sectional design employed in this study. The use of longitudinal designs would be essential for exploring the temporal relationships between variables, particularly in understanding how changes in state-level factors might influence subsequent HEI scores. Moreover, because the sample includes both inpatient and outpatient healthcare facilities, we did not account for hospital-specific structural characteristics (e.g., size or ownership) which are known to influence organizational capacity and priorities, including the adoption of LGBTQ+ inclusive policies and services. Future research examining how hospital-specific structural characteristics influence the implementation and impact of LGBTQ+ inclusive policies is warranted.
Conclusion
Our study provides insights into the intricate dynamics of LGBTQ+ inclusivity within diverse healthcare settings, considering both institutional and state-level factors. A unique aspect of our research lies in its specific focus on the association between state-level factors and the implementation of LGBTQ+ inclusive policies and practices, employing a multilevel approach. To translate these findings into action, healthcare executives—especially those in politically restrictive states or low-scoring facilities—should prioritize three strategies. First, integrate LGBTQ+ inclusive policies, training, and care protocols to buffer against political shifts. Second, strengthen partnerships with local LGBTQ+ organizations to enhance community engagement and service delivery. Third, diversify funding through philanthropic or nonprofit partnerships to reduce dependence on politically influenced federal or state funding. These system-level efforts are critical to sustaining inclusive care and addressing persistent LGBTQ+ health disparities across facility types and regions.
Acknowledgements
We express our gratitude to the Human Rights Campaign Foundation for generously agreeing to share their data with us.
Abbreviations
- LGBTQ+
Lesbian, gay, bisexual, transgender, queer or questioning, and other sexual and gender diverse persons
- U.S.
United States
- HEI
Healthcare Equality Index
- HRCF
Human Rights Campaign Foundation
- VA
Veterans Affairs
- MAP
Movement Advancement Project
- MLM
Multilevel modeling
- ICC
Intraclass correlation coefficient
- SD
Standard deviation
- CI
Confidence interval
Authors’ contributions
HY, SB, and JB made contributions to the conception and design of this article. HY, TH, SB, and JB contributed to the acquisition, analysis and interpretation of data. HY drafted the manuscript. HY, TH, DDF, SB, SKC, SM, and JB revised the manuscript. All authors approved the final manuscript.
Funding
No funding to report.
Data availability
The research data were provided by a third party, the Human Rights Campaign, under a data use agreement. Permission from the Human Rights Campaign is required to access and utilize the data.
Declarations
Ethics approval and consent to participate
This study received exemption from the University of Pennsylvania Institutional Review Board.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.National Academies of Sciences, Engineering, and Medicine. Understanding the well-being of LGBTQI+ populations 2020. 10.17226/25877 [PubMed]
- 2.Kaiser Family Foundation. LGBT adults’ experiences with discrimination and health care disparities: findings from the KFF survey of racism, discrimination, and health 2024. https://www.kff.org/racial-equity-and-health-policy/poll-finding/lgbt-adults-experiences-with-discrimination-and-health-care-disparities-findings-from-the-kff-survey-of-racism-discrimination-and-health/. Accessed June 1, 2024.
- 3.American Cancer Society Cancer Action Network. Survivor views: discrimination among LGBTQ+ cancer patients 2023. Accessed June 1, 2024. https://www.fightcancer.org/sites/default/files/national_documents/lgbtq_patient_discrimination_0.pdf
- 4.James SE, Herman JL, Durso LE, Heng-Lehtinen R. Early insights: a report of the 2022 US Transgender Survey 2024. https://transequality.org/sites/default/files/2024-02/2022%20USTS%20Early%20Insights%20Report_FINAL.pdf. Accessed June 1, 2024.
- 5.Casey LS, Reisner SL, Findling MG, Blendon RJ, Benson JM, Sayde JM, et al. Discrimination in the United States: experiences of lesbian, gay, bisexual, transgender, and queer Americans. Health Serv Res. 2019. 10.1111/1475-6773.13229 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.King M, Semlyen J, Tai SS, Killaspy H, Osborn D, Popelyuk D, et al. A systematic review of mental disorder, suicide, and deliberate self harm in lesbian, gay and bisexual people. BMC Psychiatry. 2008. 10.1186/1471-244X-8-70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kondo K, Low A, Everson T, Gordon CD, Veazie S, Lozier CC, et al. Health disparities in veterans. Med Care. 2017. 10.1097/MLR.0000000000000756. [DOI] [PubMed] [Google Scholar]
- 8.Carey FR, LeardMann CA, Lehavot K, Jacobson IG, Kolaja CA, Stander VA, et al. Health disparities among lesbian, gay, and bisexual service members and veterans. Am J Prev Med. 2022. 10.1016/j.amepre.2022.04.034. [DOI] [PubMed] [Google Scholar]
- 9.Garcia-Perez J. Lesbian, gay, bisexual, transgender, queer + Latinx youth mental health disparities: a systematic review. J Gay Lesbian Soc Serv. 2020. 10.1080/10538720.2020.1764896. [Google Scholar]
- 10.Chong LS, Kerklaan J, Clarke S, Kohn M, Baumgart A, Guha C, et al. Experiences and perspectives of transgender youths in accessing health care: a systematic review. JAMA Pediatr. 2021. 10.1001/jamapediatrics.2021.2061. [DOI] [PubMed] [Google Scholar]
- 11.Edmiston EK, Donald CA, Sattler AR, Peebles JK, Ehrenfeld JM, Eckstrand KL. Opportunities and gaps in primary care preventative health services for transgender patients: a systematic review. Transgend Health. 2016. 10.1089/trgh.2016.0019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Easpaig BNG, Reynish TD, Hoang H, Bridgman H, Corvinus-Jones SL, Auckland S. A systematic review of the health and health care of rural sexual and gender minorities in the UK, USA, Canada, Australia and New Zealand. Rural Remote Health. 2022. 10.22605/RRH6999 [DOI] [PubMed] [Google Scholar]
- 13.Grundy SA, Brown RC, Jenkins WD. Health and health care of sexual minority individuals in the rural United States: a systematic review. J Health Care Poor Underserved. 2021. 10.1353/hpu.2021.0157 [DOI] [PubMed] [Google Scholar]
- 14.Renner J, Blaszcyk W, Täuber L, Dekker A, Briken P, Nieder TO. Barriers to accessing health care in rural regions by transgender, non-binary, and gender diverse people: a case-based scoping review. Front Endocrinol. 2021. 10.3389/fendo.2021.717821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Human Rights Campaign Foundation. Healthcare Equality Index 2022. 2022. Accessed June 1, 2024. https://hrc-prod-requests.s3-us-west-2.amazonaws.com/HEI-2022-Executive-Summary.pdf
- 16.Bauermeister JA, Connochie D, Eaton L, Demers M, Stephenson R. Geospatial indicators of space and place: a review of multilevel studies of HIV prevention and care outcomes among young men who have sex with men in the United States. J Sex Res. 2017. 10.1080/00224499.2016.1271862 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Diez Roux AV, Mair C. Neighborhoods and health. Ann N Y Acad Sci. 2010. 10.1111/j.1749-6632.2009.05333.x. [DOI] [PubMed] [Google Scholar]
- 18.Schwartz S, Susser E, Susser M. A future for epidemiology? Annu Rev Public Health. 1999. 10.1146/annurev.publhealth.20.1.15. [DOI] [PubMed] [Google Scholar]
- 19.Susser M. The logic in ecological: I. the logic of analysis. Am J Public Health. 1994. 10.2105/AJPH.84.5.825. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Bolibol A, Buchmueller TC, Lewis B, Miller S. Health insurance coverage and access to care among LGBT adults, 2013–19: study examines health insurance and access to care among LGBT adults. Health Aff. 2023. 10.1377/hlthaff.2022.01493. [DOI] [PubMed] [Google Scholar]
- 21.Newcomb ME, Moran K, Li DH, Mustanski B. Demographic, regional, and political influences on the sexual health care experiences of adolescent sexual minority men. LGBT Health. 2020. 10.1089/lgbt.2019.0122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Wesp LM, Malcoe LH, Elliott A, Poteat T. Intersectionality research for transgender health justice: a theory-driven conceptual framework for structural analysis of transgender health inequities. Transgend Health. 2019. 10.1089/trgh.2019.0039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Movement Advancement Project. Mapping LGBTQ equality: 2010 to 2020. 2020. Accessed June 1, 2024. https://www.lgbtmap.org/file/2020-tally-report.pdf
- 24.Bauermeister JA. How statewide LGB policies go from under our skin to into our hearts: fatherhood aspirations and psychological well-being among emerging adult sexual minority men. J Youth Adolesc. 2014. 10.1007/s10964-013-0059-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Hatzenbuehler ML. Structural stigma and the health of lesbian, gay, and bisexual populations. Curr Dir Psychol Sci. 2014. 10.1177/0963721414523775. [Google Scholar]
- 26.Goldberg AE. Impact of HB 1557 (Florida’s Don’t Say Gay Bill) on LGBTQ+ parents in Florida 2023. Accessed June 1, 2024. https://williamsinstitute.law.ucla.edu/wp-content/uploads/Dont-Say-Gay-Impact-Jan-2023.pdf
- 27.Hatzenbuehler ML, Keyes KM, Hasin DS. State-level policies and psychiatric morbidity in lesbian, gay, and bisexual populations. Am J Public Health. 2009. 10.2105/AJPH.2008.153510. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kline NS, Griner SB, Neelamegam M, Webb NJ, Morales JJ, Rhodes SD. Responding to Don’t Say Gay laws in the US: research priorities and considerations for health equity. Sex Res Soc Policy. 2022. 10.1007/s13178-022-00773-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Jackson J, Stewart AM, Fleegler EW. Down but not defeated: clinicians can Harness the power of policy for LGBTQ+ rights. Prev Med. 2023. 10.1016/j.ypmed.2023.107423 [DOI] [PubMed] [Google Scholar]
- 30.Watson RJ, Fish JN, Denary W, Caba A, Cunningham C, Eaton LA. LGBTQ state policies: a lever for reducing SGM youth substance use and bullying. Drug Alcohol Depend. 2021. 10.1016/j.drugalcdep.2021.108659. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Human Rights Campaign. National state of emergency for LGBTQ+ Americans 2023. Accessed June 1, 2024. https://www.hrc.org/campaigns/national-state-of-emergency-for-lgbtq-americans
- 32.Adler-Milstein J, Kvedar J, Bates DW. Telehealth among US hospitals: several factors, including state reimbursement and licensure policies, influence adoption. Health Aff. 2014. 10.1377/hlthaff.2013.1054. [DOI] [PubMed] [Google Scholar]
- 33.Davidoff AJ, LoSasso AT, Bazzoli GJ, Zuckerman S. The effect of changing state health policy on hospital uncompensated care. Inquiry. 2000:253– 67. [PubMed]
- 34.Blackwell CW, Lopez Castillo H, Roque A, Liu Y, Todd A. The relationship between healthcare organizational Magnet® status and scores on the Human Rights Campaign Healthcare Equality Index: a comparative temporal analysis. J Soc Serv Res. 2024;51(1):17–27. 10.1080/01488376.2024.2342958 [Google Scholar]
- 35.Blackwell CW. Demonstrating nursing excellence through equality: the relationship between Magnet® status and organizational LGBTQ client services and support. J Transcult Nurs. 2020;31(2):209–15. 10.1177/1043659619865585. [DOI] [PubMed] [Google Scholar]
- 36.National Institutes of Health Sexual & Gender Minority Research Office. Sexual & gender minority health disparities research framework 2021. https://web.archive.org/web/20240309113829/https://dpcpsi.nih.gov/sites/default/files/NIH-SGM-Health-Disparities-Research-Framework-FINAL_508c.pdf. Accessed June 1, 2024.
- 37.Malavet PA. America’s colony: the political and cultural conflict between the United States and Puerto Rico. NYU. 2004.
- 38.Morris N. Puerto Rico: culture, politics, and identity. Westport (CT): Praeger; 1995.
- 39.Human Rights Campaign Foundation. HEI 2022 scoring system and methodology 2020. https://hrc-prod-requests.s3-us-west-2.amazonaws.com/HEI_2022_Criteria-and-Tier-Desginations.pdf. Accessed June 1, 2024.
- 40.Tieche M. How many hospitals are in the U.S.? 2023. Accessed June 1, 2024. https://www.definitivehc.com/blog/how-many-hospitals-are-in-the-us
- 41.Knauer NJ. Legal consciousness and LGBT research: the role of the law in the everyday lives of LGBT individuals. J Homosex. 2012. 10.1080/00918369.2012.673947. [DOI] [PubMed] [Google Scholar]
- 42.Movement Advancement Project. Mapping LGBTQ equality: 2010 to 2020, United States. Inter-university Consortium Political Social Research. 2020. 10.3886/ICPSR37877.v2 [Google Scholar]
- 43.Movement Advancement Project. Mapping LGBTequality in America 2015. Accessed June 17, 2025. https://www.lgbtmap.org/file/Mapping%20Equality%20for%20LGBT%20Americans%20Post%20SCOTUS.pdf
- 44.McCourt AD, Tormohlen KN, Schmid I, Stone EM, Stuart EA, Davis CS, et al. Effects of opioid prescribing cap laws on opioid and other pain treatments among persons with chronic pain. J Gen Intern Med. 2023. 10.1007/s11606-022-07796-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Stone EM, Tormohlen KN, McCourt AD, Schmid I, Stuart EA, Davis CS, et al. Association between state opioid prescribing cap laws and receipt of opioid prescriptions among children and adolescents. JAMA Health Forum. 2022. 10.1001/jamahealthforum.2022.2461. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Tormohlen KN, McCourt AD, Schmid I, Stone EM, Stuart EA, Davis C, et al. State prescribing cap laws’ association with opioid analgesic prescribing and opioid overdose. Drug Alcohol Depend. 2022. 10.1016/j.drugalcdep.2022.109626. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Michelson MR, Schmitt E. Party politics and LGBT issues in the United States. Oxf Res Encycl Polit. 2020. 10.1093/acrefore/9780190228637.013.1208 [Google Scholar]
- 48.Pomeranz JL, Siddiqi A, Bolanos GJ, Shor JA, Hamad R. Consolidated state political party control and the enactment of obesity-related policies in the United States. Prev Med. 2017. 10.1016/j.ypmed.2017.08.028 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.National Conference of State Legislatures. State partisan composition 2023. https://www.ncsl.org/about-state-legislatures/state-partisan-composition. Accessed June 1, 2024.
- 50.United States Census Bureau. DP05 - ACS demographic and housing estimates: American Community Survey 1-year estimates data profiles 2021. https://data.census.gov/table/ACSDP1Y2021.DP05?q=black+in+each+state+2021. Accessed June 1, 2023.
- 51.National Institute of Minority Health and Health Disparities. Minority health and health disparities: definitions and parameters 2024. https://web.archive.org/web/20250112175430/https://www.nimhd.nih.gov/about/strategic-plan/nih-strategic-plan-definitions-and-parameters.html. Accessed June 1, 2024.
- 52.Tsui J, Hirsch JA, Bayer FJ, Quinn JW, Cahill J, Siscovick D, et al. Patterns in geographic access to health care facilities across neighborhoods in the United States based on data from the National Establishment Time-Series between 2000 and 2014. JAMA Netw Open. 2020. 10.1001/jamanetworkopen.2020.5105 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Kaiser Family Foundation. Status of state Medicaid expansion decisions: interactive map 2023. https://www.kff.org/medicaid/issue-brief/status-of-state-medicaid-expansion-decisions-interactive-map/. Accessed June 1, 2023.
- 54.Miller S, Wherry LR. Health and access to care during the first 2 years of the ACA Medicaid expansions. N Engl J Med. 2017. 10.1056/NEJMsa1612890 [DOI] [PubMed] [Google Scholar]
- 55.Wherry LR, Miller S. Early coverage, access, utilization, and health effects associated with the Affordable Care Act Medicaid expansions: a quasi-experimental study. Ann Intern Med. 2016. 10.7326/M15-2234 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Kreft IG, de Leeuw J. Introducing multilevel modeling. London: SAGE; 1998. 10.4135/9781849209366.
- 57.Subramanian S, Jones K, Duncan C. Multilevel methods for public health research: neighborhoods and health. New York: Oxford University Press; 2003. 10.1093/acprof:oso/9780195138382.003.0004. [Google Scholar]
- 58.Peugh JL. A practical guide to multilevel modeling. J Sch Psychol. 2010. 10.1016/j.jsp.2009.09.002. [DOI] [PubMed] [Google Scholar]
- 59.Khine MS. Methodology for multilevel modeling in educational research: concepts and applications. Singapore: Springer; 2022. 10.1007/978-981-16-9142-3.
- 60.Stevens JP. Outliers and influential data points in regression analysis. Psychol Bull. 1984. 10.1037/0033-2909.95.2.334. [Google Scholar]
- 61.Yu H, Ancheta AJ, Flores DD, Bonett S, Meanley S, Choi SK, et al. Nurse leaders’ recommendations for implementing LGBTQ+ inclusive practices in health systems: a qualitative descriptive study. Int J Nurs Stud Adv. 2024;7:100262. 10.1016/j.ijnsa.2024.100262 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Crenshaw K. Demarginalizing the intersection of race and sex: a Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. 1989. https://chicagounbound.uchicago.edu/cgi/viewcontent.cgi?article=1052&context=uclf. Accessed June 1, 2024.
- 63.Fiscella K, Sanders MR. Racial and ethnic disparities in the quality of health care. Annu Rev Public Health. 2016. 10.1146/annurev-publhealth-032315-021439. [DOI] [PubMed] [Google Scholar]
- 64.Khanijahani A, Iezadi S, Gholipour K, Azami-Aghdash S, Naghibi D. A systematic review of racial/ethnic and socioeconomic disparities in COVID-19. Int J Equity Health. 2021. 10.1186/s12939-021-01582-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Yu H, Flores DD, Bonett S, Bauermeister JA. LGBTQ+ cultural competency training for health professionals: a systematic review. BMC Med Educ. 2023. 10.1186/s12909-023-04373-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Ayhan CHB, Bilgin H, Uluman OT, Sukut O, Yilmaz S, Buzlu S. A systematic review of the discrimination against sexual and gender minority in health care settings. Int J Health Serv. 2020. 10.1177/0020731419885093. [DOI] [PubMed] [Google Scholar]
- 67.Zeeman L, Sherriff N, Browne K, McGlynn N, Mirandola M, Gios L, et al. A review of lesbian, gay, bisexual, trans and intersex (LGBTI) health and healthcare inequalities. Eur J Public Health. 2019. 10.1093/eurpub/cky226. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.American Psychiatric Association. The psychiatric bed crisis in the US: understanding the problem and moving toward solutions 2022. https://www.psychiatry.org/getmedia/81f685f1-036e-4311-8dfc-e13ac425380f/APA-Psychiatric-Bed-Crisis-Report-Full.pdf. Accessed June 17, 2025. [DOI] [PubMed]
- 69.Rosa W, Fullerton C, Keller R. Equality in healthcare: the formation and ongoing legacy of an LGBT advisory council. LGBT Health. 2015;2(4):292–6. 10.1089/lgbt.2014.0068 [DOI] [PubMed] [Google Scholar]
- 70.Rosenkrantz DE, Black WW, Abreu RL, Aleshire ME, Fallin-Bennett K. Health and health care of rural sexual and gender minorities: a systematic review. Stigma Health. 2017. 10.1037/sah0000055. [Google Scholar]
- 71.Attree P, French B, Milton B, Povall S, Whitehead M, Popay J. The experience of community engagement for individuals: a rapid review of evidence. Health Soc Care Community. 2011. 10.1111/j.1365-2524.2010.00976.x. [DOI] [PubMed] [Google Scholar]
- 72.O’Mara-Eves A, Brunton G, McDaid G, Oliver S, Kavanagh J, Jamal F, et al. Community engagement to reduce inequalities in health: a systematic review, meta-analysis and economic analysis. Public Health Res. 2013. 10.3310/phr01040. [PubMed] [Google Scholar]
- 73.Turin TC, Kazi M, Rumana N, Lasker MA, Chowdhury N. Conceptualising community engagement as an infinite game implemented through finite games of ‘research’, ‘community organising’ and ‘knowledge mobilization’. Health Expect. 2023. 10.1111/hex.13801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Agency for Toxic Substances and Disease Registry. Principles of community engagement 2011. https://web.archive.org/web/20240120030901/https://www.atsdr.cdc.gov/communityengagement/pdf/PCE_Report_508_FINAL.pdf. Accessed June 1, 2024.
- 75.National Institutes of Health. About the Community Engagement Alliance (CEAL) 2024. https://ceal.nih.gov/who-we-are. Accessed June 1, 2024.
Associated Data
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Data Availability Statement
The research data were provided by a third party, the Human Rights Campaign, under a data use agreement. Permission from the Human Rights Campaign is required to access and utilize the data.