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. Author manuscript; available in PMC: 2024 Jan 1.
Published in final edited form as: Circ Heart Fail. 2022 Oct 19;16(1):e009745. doi: 10.1161/CIRCHEARTFAILURE.122.009745

Racial inequities in access to VAD and transplant persist after consideration for preferences for care: A report from the Registry Evaluation for Vital Information for VADs in Ambulatory Life (REVIVAL)

Thomas M Cascino a, Monica Colvin a, David E Lanfear b, Blair Richards c, Shokoufeh Khalatbari c, Douglas L Mann d, Wendy C Taddei-Peters e, Neal Jeffries e, Daphne C Watkins f, Garrick C Stewart g, Keith D Aaronson a, REVIVAL Investigators
PMCID: PMC9851944  NIHMSID: NIHMS1837892  PMID: 36259388

Abstract

Background:

Racial disparities in access to advanced therapies for heart failure (HF) patients are well documented, although the reasons remain uncertain. We sought to determine the association of race on utilization of ventricular assist device (VAD) and transplant among patients with access to care at VAD centers and if patient preferences impact the effect.

Methods:

We performed an observational cohort study of ambulatory chronic systolic HF patients with high-risk features and no contraindication to VAD enrolled at 21 VAD centers and followed for two years in the REVIVAL study. We used competing events cause-specific proportional hazard methodology with multiple imputation for missing data. The primary outcomes were (1) VAD/transplant and (2) death. The exposures of interest included race (Black or White), additional demographics, captured social determinants of health (SDoH), clinician-assessed HF severity, patient-reported quality of life (QOL), preference for VAD, and desire for therapies.

Results:

The study included 377 participants, of whom 100 (26.5%) identified as Black. VAD or transplant was performed in 11 (11%) Black and 62 (22%) White participants, while death occurred in 18 (18%) Black and 36 (13%) White participants. Black race was associated with reduced utilization of VAD and transplant (adjusted hazard ratio, 95% CI; 0.45, 0.23-0.85) without an increase in death. Preferences for VAD or life-sustaining therapies were similar by race and did not explain racial disparities.

Conclusions:

Among patients receiving care by advanced HF cardiologists at VAD centers, there is less utilization of VAD and transplant for Black patients even after adjusting for HF severity, QOL, and SDoH, despite similar care preferences. This residual inequity may be a consequence of structural racism and discrimination or provider bias impacting decision-making.

Clinical Trial Registration:

ClinicalTrials.gov Identifier: NCT01369407

Introduction

Heart failure (HF) disproportionately affects racial and ethnic minorities and those impacted negatively by the social determinants of health (SDoH).1-4 HF is not only more common among Black adults, with up to a 20x higher incidence before age 50 years,5 but is also associated with a 2-fold higher rate of hospitalizations2 and death3 than for White patients. In end-stage HF, advanced therapies, including ventricular assist devices (VADs) and heart transplants, extend life and improve its quality and are treatments of choice for those who qualify.6, 7 Inequities in the use of VAD and transplant among underserved patients are well documented.8-13

The reasons for inequities in access to advanced therapies for underserved groups remain uncertain. Potential explanations have included systemic differences in access to care, patient preference, and provider decision-making, with work primarily focused on differences in access to care and provider decision-making, often with mixed findings. For instance, Medicaid expansion through the Affordable Care Act was associated with increased listing of Black patients for transplant without increasing White patient access11 but did not impact VAD utilization.14 Meanwhile, several SDoH, including socioeconomic status and insurance status, have been associated with VAD utilization and outcomes.10 Implicit biases favoring White patients among HF clinicians can impact decision-making for both VAD and transplant.15, 16 Research on the intersection of SDoH and physician biases is beginning to elucidate the mechanisms contributing to inequities in access. Since much of this work has used claims data, a significant limitation has been the challenge of identifying a HF population at risk for advanced HF therapies outside of single-center studies.17 Furthermore, a complete understanding of the relationship between SDoH and biases in decision-making must also account for care preferences expressed by those patients with HF with high-risk features who could be considered for VAD or transplant. As such, understanding the effects of SDoH and whether patient preferences for care impact subsequent utilization of advanced therapies is a necessary and critical step toward understanding the causes of inequities in advanced therapy utilization.

We have previously shown that increased patient preference for VAD is associated with higher NYHA class, worse quality of life, lower education level, and reduced income, but not with race.18 Herein, we build on this work by exploring the associations between (1) race and SDoH and (2) preference for VAD and life-sustaining therapies and outcomes, including (1) VAD and transplant and (2) death, in an ambulatory cohort of HF patients with high-risk features receiving care at VAD centers by HF/transplant specialists. We hypothesized that underserved populations and those negatively impacted by the SDoH, such as Black HF patients, would receive less advanced therapies despite access to advanced HF care and that patient preferences would not affect the association of race and the SDoH and outcomes.

Methods

Data Source

The Registry Evaluation of Vital Information for VADs in Ambulatory Life (REVIVAL) study was a prospective, observational cohort study of ambulatory chronic systolic HF patients. Full details of the rationale and design have been described previously.19 Funded by the National Institutes of Health, REVIVAL was a 2-year study of 400 ambulatory systolic HF patients recruited from 21 US VAD centers from all major geographic regions of the county representing 16 different states between July 2015 and June 2016 that sought to gain a better understanding of the clinical trajectory of patients with HF with high-risk features. An independent Observational Study Monitoring Board oversaw the conduct of the REVIVAL study. The Institutional Review Board at each clinical site and the Data Coordinating Center at the University of Michigan approved the study. All subjects were provided written informed consent before study participation. The data for REVIVAL have been uploaded to National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) and are available per National Institutes of Health policy.

Study Cohort

The registry was designed to include patients with high-risk criteria for death in the absence of advanced therapies to achieve a predicted 25% 1-year event rate of the primary composite outcome of death, urgent transplant, or VAD. Entry criteria excluded patients with obvious medical contraindications to advanced HF therapies (Table S1). The REVIVAL dataset was selected because of the inclusion of comprehensive and detailed serial evaluations including clinical data, physician assessments, and patient-reported outcomes including preferences for care, with study visits occurring at enrollment, 2, 6, 12, 18, and 24 months or until death, heart transplant, or VAD.

Self-reported race and ethnicity were collected as required by the National Institutes of Health, the funding agency for REVIVAL, adhering to its policy for the inclusion of women and minorities in research involving human subjects.20, 21 Of the 400 participants, 23 who selected race other than Black or White were excluded due to the small sample size. The final cohort included 377 patients who identified as either Black race or White race.

Outcomes

The outcomes of interest for the study were (1) VAD or urgent heart transplant (UNOS Status 1A or 1B transplant, using the allocation system in effect at the time of this study) and all-cause death at two years.

Race, social determinants of health, clinical covariates, and preferences for care

The primary independent estimators were race and several SDoH. Given that race is a sociopolitical framework and not a biological one,22 race was selected to further understand sociocultural environmental and health care system influences on described disparities in access to advanced therapies.13, 23 The SDoH are “conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.”24 The SDoH are generally grouped into domains, including health care access and quality, social and community context, education, economic stability, and neighborhood and built environment.24 The REVIVAL registry included detailed patient history that could be mapped to the Healthy People 2030 SDoH.24 Demographic SDoH included sex and age.25 Body mass index was also included given the increased risk of higher BMIs in racial and ethnic minoritized groups26 and the influence of BMI on VAD and transplant provider decisions.27 Additional SDoH included education, income, insurance type, and caregiver status (married, domestic partner, or completed caregiver survey). HF illness severity and burden were evaluated by physicians using the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) Profiles,28 which are associated with HF burden over several dimensions and outcomes.29 The EuroQol visual analog scale (EQ-VAS) was used to determine patient-reported health-related quality of life as it has previously been shown to be associated with outcomes and is recommended to be considered as part of the shared decision-making process for advanced therapies.30, 31 To determine preference for VAD, patients received standardized information about VAD therapy written at an 8th-grade level, including an illustration of a VAD, description of how a VAD works, and anticipated outcomes after VAD implantation (Figure S1).18, 32 After reviewing this, patients were asked, “Based on how you feel right now, how would you feel about having a VAD placed to treat your heart failure?” with responses on a 5 point Likert Scale (from “1-definitely want” to “5-definitely do not want.” Participants were also asked to express their preference for life-staining therapy by responding “yes” or “no” to, “At this time, would you want any and all life-sustaining therapies available”; listed therapies included “kidney dialysis, being placed on a breathing machine, a feeding tube if unable to eat, chest compressions” and “transfer to the Intensive Care Unit.” INTERMACS patient profile, EQ-VAS, VAD preference, and preference for life-sustaining therapies, assessed at each study visit, were included as time-varying covariates, with assessment at baseline, and at the 8-week, 6-month, 12-month, 18-month, and 24-month visits.

Statistical Analysis

Continuous variables are displayed as mean (± SD) or median [25th, 75th percentile] for normal and non-normally distributed data, respectively. Univariable comparisons were performed using the Fisher exact test for categorical variables, Wilcoxon rank sum test for continuous variables, and zero-inflated Poisson regression as appropriate. Time to event outcomes by race were evaluated with the Kaplan-Meier method. We performed a competing-events, cause-specific proportional hazards analysis in which the primary outcomes were (1) VAD or urgent UNOS Status 1A or 1B transplant (using the pre-October 2018 US heart allocation policy then in effect) and (2) death to assess the association between the SDoH and outcomes. Explanatory variables included in the initial analysis were SDoH (race, sex, age, education, income, insurance type, caregiver), body mass index (BMI), clinician-assessed HF severity (INTERMACS patient profile), and patient-reported quality of life (EQ-VAS). INTERMACS patient profile, EQ-VAS, VAD preference, and preference for life-sustaining therapies, assessed at each study visit, were included as time-varying covariates. Hazard ratios (HR) for INTERMACS patient profiles were reported to show the effect of moving from a better to a worse profile (e.g., from profile 7 to 6). As a result of the low number of events relative to the number of SDoH measures, SDoH were selected for inclusion into the multivariable analysis from the univariable analysis. Explanatory variables with a prespecified p-value <0.20 in univariable analyses were included as candidate variables in the multivariable analyses, except for race which was included a priori (model 1). After completion of the multivariable model, the preference for VAD given current health (transformed to a 3-point Likert scale) (model 2) and “want for any and all life-sustaining therapies” (yes/no) (model 3) as time-varying factors were each separately added to model 1. Multiple imputation with 40 replications was performed for missing variables measured at the baseline visit. The last recorded value was carried forward for missing variables measured at every completed study visit. Missingness was overall low (<10%) for all variables with the exception of preference for VAD (12%), want of all life-sustaining therapies (14%), household education (20% missing ) and income (39% missing), levels of missingness for which multiple imputation with 40 replications has been shown to perform well.33-35 Additional details of the multiple imputation are in the online supplement (Methods S1). Sensitivity analyses were performed, including 1. complete cases (cases with no missing values for the predictors selected from the univariable analysis) in the multivariable models; 2. inclusion of all explanatory variables without selection; 3. repeating the multivariable models including REVIVAL sites as a random effect to account for variability across sites; 4. repeating the multivariable models for the outcome of receipt of VAD alone. Testing was performed at a 5% significance level with 2-sided tests. Analyses were performed using SAS version 9.4 (SAS Institute, Cary, N.C.)

Results

Among the 400 REVIVAL patients, 377 participants were included after 23 individuals who self-identified as other than Black or White race were excluded. Table 1 presents the characteristics of the participants by race. Of the 377 participants included, 100 (27%) identified as Black and 93 (25%) were female; the mean age was 60.3 (± 11.3) years. Compared to White participants, Black participants were younger and less likely to have a caregiver. There were no differences in preference for VAD or life-sustaining therapies by race at baseline. The primary outcome of VAD or UNOS Status 1A or 1B transplant was performed in 11 (11.0%) Black patients, of whom 8 (8.0%) received a VAD and 3 (3.0%) a transplant, and 62 (22.3%) White participants, of whom 43 (15.5%) received a VAD and 19 (6.9%) a transplant. Death occurred in 18 (18%) Black participants and 36 (13%) White participants. The competing outcome curves for these events are shown in Figure 1.

Table 1.

Patient characteristics at enrollment

Characteristic Overall
n=377		 Black
n=100		 White
n=277		 p-value
Age, years 60.3 (11.3) 58.0 (11.2) 61.1 (11.2) 0.020
Female 93 (25) 36 (36) 57 (21) 0.003
Ethnicity (n=370) 0.002
Hispanic/Latino 22 (6) 0 (0) 22 (8)
Non-Hispanic/Non-Latino 348 (94) 99 (100) 249 (92)
NYHA Class 0.318
I 6 (2) 3 (3) 3 (1)
II 104 (28) 30 (30) 74 (27)
III 257 (68) 66 (66) 191 (69)
IV 10 (3) 1 (1) 9 (3)
INTERMACS Patient Profile 0.050
4 33 (9) 10 (10) 23 (8)
5 76 (20) 13 (13) 63 (23)
6 144 (38) 48 (48) 96 (35)
7 124 (33) 29 (29) 95 (34)
BMI, kg/m2 (n=375) 30.3 (6.35) 31.0 (6.61) 30.0 (6.25) 0.190
Heart rate, beats per minute (n=372) 74.9 (12.34) 78.3 (12.70) 73.7 (12.01) 0.002
Systolic BP, mmHg (n=375) 108.6 (15.90) 115.5 (17.20) 106.2 (14.68) <0.001
Diastolic BP, mmHg (n=374) 66.9 (10.17) 70.5 (11.30) 65.7 (9.44) <0.001
Ischemic etiology 0.001
213 (56) 71 (71) 142 (51)
164 (44) 29 (29) 135 (49)
Left ventricular ejection fraction (%) 20.0 (15.0 to 25.0) 20.0 (15.0 to 25.0) 20.0 (16.0 to 25.0) 0.862
KCCQ - overall score (n=351) 63.0 (20.73) 65.6 (19.72) 62.2 (21.03) 0.183
EQ-VAS, (n=346) 62.7 (19.36) 64.5 (21.02) 62.1 (18.77) 0.314
HF Hospitalizations in last year (#) 0.103
0 172 (46) 36 (36) 136 (49)
1 90 (24) 30 (30) 60 (22)
2 65 (17) 17 (17) 48 (17)
3 28 (7) 5 (5) 23 (8)
≥4 22 (6) 12 (12) 10 (4)
Sodium, mg/dL 138.1 (3.81) 139.0 (3.66) 137.7 (3.81) 0.003
Creatinine, mg/dL 1.30 (1.09 to 1.63) 1.40 (1.14 to 1.70) 1.30 (1.04 to 1.61) 0.040
Prior DT VAD evaluation: 55 (15) 17 (17) 38 (14) 0.414
Heart transplant waitlist status 0.742
2 59 (16) 18 (18) 41 (15)
7 2 (1) 0 (0) 2 (1)
Not listed 316 (84) 82 (82) 234 (84)
Caregiver (n=369) 258 (70) 51(53) 207 (76) <0.001
Education Level (n=301) 0.377
≤12th grade 98 (33) 28 (41) 70 (30)
Attended college/tech school 98 (33) 19 (28) 79 (34)
Associate/Bachelor degree 74 (25) 17 (25) 57 (25)
Post Grad degree 31 (10) 5 (7) 26 (11)
Household Income, dollars (n=231) 0.497
<40k 124 (54) 32 (62) 92 (51)
40k-80k 60 (26) 11 (21) 49 (27)
>80k 47 (20) 9 (17) 38 (21)
Medical Insurance Groups (n=373) 0.098
Medicare/Medicaid/Tricare 161 (43) 50 (50) 111 (41)
Private/commercial/WC/other 152 (41) 40 (40) 112 (41)
Both Groups 60 (16) 10 (10) 50 (18)
VAD Preference (n=332) 0.923
Definitely/Probably 94 (28) 22 (27) 72 (29)
Not Sure 100 (30) 26 (31) 74 (30)
Definitely/Probably not 138 (42) 35 (42) 103 (41)
Want any and all life-sustaining therapies (n=325) 218 (67) 63 (74) 155 (65) 0.139
CRT+D 183 (49) 36 (36) 147 (53) 0.004
Beta-blocker 359 (95) 96 (96) 263 (95) 0.790
ACE, ARB, or ARNI 316 (84) 78 (78) 238 (86) 0.081
MRA 278 (74) 66 (66) 212 (77) 0.047
Hydralazine 69 (18) 39 (39) 30 (11) <0.001
Nitrate 96 (25) 40 (40) 56 (20) <0.001
Loop diuretic 347 (92) 93 (93) 254 (92) 0.83
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Continuous characteristics: mean (SD) or median (25th percentile, 75th percentile) for measures with non-normal distributions. Categorical characteristics: n (%). Characteristics missing data have the n stated (n=). Continuous characteristics: mean (SD) or median (25th percentile, 75th percentile) for measures with non-normal distributions. Categorical characteristics: n (%). Characteristics missing data have the n stated (n=). Abbreviations: NYHA, New York Heart Association; INTERMACS, Interagency Registry for Mechanically Assisted Circulatory Support; BMI, body mass index; KCCQ, Kansas City Cardiomyopathy Questionnaire; EQ-VAS, EuroQol visual analog scale; HF, heart failure, DT, destination therapy; VAD, ventricular assist device; WC, workers compensation; CRT+D, cardiac resynchronization therapy defibrillator; ACE, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blockers; ARNI, angiotensin receptor-neprilysin inhibitor.

Figure 1. Cumulative incidence for VAD or transplant (1A) and death (1B) by race.

Figure 1.

Figure 1.

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Compared to white patients, Black patients were less likely to receive a VAD and transplant without a significant increase in death.

The univariable and multivariable relationships between the explanatory variables and 2-year outcomes are shown in Table 2 for VAD and transplant and Table 3 for death. Recipient race, age, INTERMACS patient profile, EQ-VAS score, and level of education were selected for inclusion into the multivariable cause-specific model with VAD and transplant as the outcome. Black participants had a 55% decreased relative rate of VAD or transplant compared to white participants (HR, 95% CI; 0.45, (0.23 – 0.85)) (model 1). Participants with worse INTERMACS patient profile, lower EQ-VAS, and higher education were more likely to receive a VAD or transplant. The addition of care preferences had no impact on any associations (models 2 & 3).

Table 2.

Univariable and multivariable associations for VAD and transplant using multiple imputation

Univariable Multivariable
Model 1 Model 2 Model 3
Clinical/SDoH VAD preference Life-sustaining therapy
HR (95% CI) HR (95% CI) HR (95% CI) HR (95% CI)
Demographics
  Black race (Ref: White) 0.46 (0.24 – 0.87)* 0.45 (0.23 – 0.85)* 0.46 (0.24 – 0.87)* 0.42 (0.22 – 0.80)§
  Female (Ref: male) 0.74 (0.42 – 1.30) --- --- ---
  Age (years) 0.99 (0.97 – 1.00)‡ 0.98 (0.96 – 1.00) 0.98 (0.96 – 1.00) 0.98 (0.96 – 1.00)
  BMI (per kg/m2) 0.99 (0.96 – 1.03) --- ---
Illness severity
  INTERMACS PP (per status change) 2.09 (1.75 – 2.50)† 1.96 (1.62 – 2.38)† 1.98 (1.63 – 2.40)† 1.96 (1.62 – 2.37)†
HRQoL
  EQ-VAS (per 10-unit change) 0.76 (0.69 – 0.84)† 0.86 (0.78 – 0.96)§ 0.87 (0.79 – 0.97)* 0.86 (0.78 – 0.96)§
SDoH
  Education (Ref: ≤12th grade) Overall effect‡ Overall effect* Overall effectns Overall effect*
  - Attended college/Tech School 0.81 (0.42 – 1.54) 0.98 (0.51 – 1.89) 0.96 (0.50 – 1.86) 1.02 (0.53 – 1.97)
  - Associate/Bachelor Degree 1.06 (0.55 – 2.06) 1.32 (0.68 – 2.57) 1.29 (0.66 – 2.52) 1.42 (0.73 – 2.80)
  - PostGrad Degree 1.93 (0.92 – 4.07)‡ 2.70 (1.27 – 5.70)§ 2.61 (1.20 – 5.67)* 2.77 (1.31 – 5.84)§
  Income (Ref: <40k) --- --- ---
  - 40-80 0.70 (0.34 – 1.45)
  - >80k 1.09 (0.58 – 2.07)
  Insurance (Ref: Both) --- --- ---
  - Medicare/Medicaid/Tricare 0.92 (0.46 – 1.85)
  - Private/Commercial/WC/Other 1.20 (0.61 – 2.38)
  Caregiver (Ref: No) 1.11 (0.66 – 1.88) --- --- ---
Preference for LVAD --- ---
 (Ref: Definitely/Probably Not) Overall effect‡ Overall effectns
- Definitely/Probably 1.18 (0.70 – 1.99) 1.10 (0.63 – 1.92)
- Not Sure 0.64 (0.33 – 1.21) 0.63 (0.33 – 1.22)
Preference for life-sustaining therapy (Ref: No) 1.20 (0.72 – 2.01) --- --- 1.35 (0.79 – 2.30)
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‡

P<0.20 (for Univariable only)

*

P<0.05

§

P<0.01

†

P<0.001

ns

p>0.05 (included for categorical variables overall effect only)

variables with a p-value <0.20 in univariable analyses were included in the multivariable analyses, except for race which was included a priori. Abbreviations: SDoH, social determinants of health; VAD, ventricular assist device; HR, hazard ratio; CI, confidence interval; BMI, body mass index; INTERMACS PP, Interagency Registry for Mechanically Assisted Circulatory Support, Patient Profile; HRQoL, health-related quality of life; EQ-VAS, EuroQol visual analog scale; WC, workers compensation.

Table 3.

Univariable and multivariable associations for death using multiple imputation

Univariable Multivariable
Model 1 Model 2 Model 3
Clinical/SDoH VAD preference Life-sustaining therapy
HR (95% CI) HR (95% CI) HR (95% CI) HR (95% CI)
Demographics
  Black race (Ref: White) 1.26 (0.71 – 2.21) 1.23 (0.67 – 2.25) 1.23 (0.67 – 2.26) 1.10 (0.59 – 2.04)
  Female (Ref: male) 0.79 (0.42 – 1.51) --- --- ---
  Age (years) 1.03 (1.00 – 1.06)* 1.03 (1.00 – 1.06) 1.03 (1.00 – 1.06) 1.03 (1.00 – 1.06)*
  BMI (per kg/m2) 0.93 (0.88 – 0.97)§ 0.94 (0.89 – 0.99)* 0.94 (0.90 – 0.99)* 0.93 (0.88 – 0.98)§
Illness severity
  INTERMACS PP (per status change) 1.90 (1.57 – 2.30)† 1.95 (1.58 – 2.39)† 1.98 (1.60 – 2.44)† 1.94 (1.58 – 2.37)†
HRQoL
  EQ-VAS (per 10-unit change) 0.93 (0.82 – 1.06) --- --- ---
SDoH
  Education (Ref: ≤12th grade) Overall effect‡ Overall effectns Overall effect* Overall effect§
  - attended college/tech school 2.33 (1.08 – 5.04)* 3.21 (1.42 – 7.25)§ 3.12 (1.36 – 7.15)§ 3.52 (1.56 – 7.95)§
  - Associate/Bachelor degree 1.23 (0.47 – 3.20) 1.35 (0.51 – 3.58) 1.32 (0.50 – 3.51) 1.51 (0.57 – 4.04)
  - PostGrad degree 1.24 (0.32 – 4.89) 2.09 (0.52 – 8.36) 1.91 (0.47 – 7.79) 2.25 (0.56 – 9.12)
  Income (Ref: <40k) --- --- ---
  - 40-80 0.96 (0.49 – 1.90)
  - >80k 0.47 (0.16 – 1.34)
  Insurance (Ref: Both) --- --- ---
  - Medicare/Medicaid/Tricare 1.08 (0.51 – 2.31)
  - Private/commercial/WC/other 0.88 (0.40 – 1.95)
  Caregiver (Ref: No) 0.47 (0.27 – 0.81)§ 0.41 (0.22 – 0.76)§ 0.41 (0.22 – 0.75)§ 0.38 (0.21 – 0.71)§
Preference for LVAD --- ---
 (Ref: definitely/probably not) Overall effectns
- Definitely/Probably 0.69 (0.36 – 1.33) 0.74 (0.37 – 1.50)
- Not Sure 0.77 (0.39 – 1.51) 0.70 (0.35 – 1.40)
Preference for life-sustaining therapy (Ref: No) 1.28 (0.69 – 2.36) --- --- 1.86 (0.96 – 3.60)
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‡

P<0.20 (for Univariable only)

*

P<0.05

§

P<0.01

†

P<0.001

ns

p>0.05 (included for categorical variables overall effect only)

variables with a p-value <0.20 in univariable analyses were included in the multivariable analyses, except for race which was included a priori. Abbreviations: SDoH, social determinants of health; VAD, ventricular assist device; HR, hazard ratio; CI, confidence interval; BMI, body mass index; INTERMACS PP, Interagency Registry for Mechanically Assisted Circulatory Support, Patient Profile; HRQoL, health-related quality of life; EQ-VAS, EuroQol visual analog scale; WC, workers compensation.

For the multivariable cause-specific model with death as the outcome, age, BMI, education, absence of a caregiver, and INTERMACS patient profile were selected for inclusion Table 3). The rate of death among Black participants compared to White participants was similar (HR, 95% CI; 1.23, 0.67 – 2.25) (Table 3). Worse INTERMACS patient profile (1.95, 1.58 – 2.39) was associated with increased 2-year death while higher BMI (0.938, 0.893 – 0.985) and presence of a caregiver (0.41, 0.22 – 0.76) was protective. Increasing age and attending college or tech school compared to those who completed ≤12th grade were associated with increased death when care preferences were considered (models 2 & 3). Associations were verified to be consistent by comparing HRs and 95% confidence intervals in sensitivity analyses, including the participants with complete cases for the multivariable analysis (Tables S2 & S3), all explanatory variables (Table S4 & S5), including center as a random effect (Table S6 & S7), and for the outcome of VAD alone (Table S8).

Discussion

In this prospective study of ambulatory HF patients with high-risk features, Black race was associated with decreased utilization of VAD and transplant. Patient preferences for either VAD or want to pursue all life-sustaining therapies did not impact the findings. SDoH were associated with both utilization of advanced therapies and survival, with education being associated with receipt of VAD or transplant and the presence of a caregiver being associated with decreased death. Collectively, these findings suggest 1) that racial inequity in VAD and transplant exists despite access to care at VAD centers by experienced providers (i.e., advanced HF/transplant cardiologists) and 2) that this inequity is not the result of differences in patient-expressed preference for care.

Prior work has revealed convincingly that racial inequities in access to HF care exist and impact outcomes.8, 10, 11, 36 While the reasons for inequality may be complex, the historical roots and the structure of our current health system has facilitated disparities.37 Black Americans are more likely to develop HF,1-4 less likely to be on evidenced-based treatments36 or receive care from a cardiologist,38, 39 and more likely to die from HF.3 Utilization of advanced therapies among Black patients has been growing.8, 40 However, it is uncertain if advanced therapies are offered or provided at the appropriate rates.36 As the advanced HF community looks to understand why such inequities exist, explanations have included access to care, provider biases, or patient preference. The current study builds on this work by demonstrating reduced utilization of VAD and transplant among Black patients receiving care at expert VAD centers by advanced HF cardiology teams. This relationship persisted after adjusting for the two primary reasons to get a VAD or transplant, reduced quality of life and HF severity. While access to care is critical, as demonstrated in studies showing worse outcomes when HF patients are not treated by cardiologists,39 this work suggests that receiving care at advanced HF centers does not ensure equitable access to VAD and transplant.

A novel finding in our study is the continued racial inequities in access to VAD and transplant after considering patient preferences for VAD and overall life-sustaining therapies. Neither patient preference for receiving a VAD nor a patient’s want to pursue “all life-sustaining therapies” impacted the reduced utilization. In trying to understand how and among whom inequities occur, prior work has demonstrated provider biases in the utilization of advanced therapies for Black candidates,15, 16 and decreased utilization for VAD among “less ideal” candidates either because patients are too sick (e.g., more comorbidities) or potentially less ill.13 Racial differences in treatment preferences have also been proposed as an explanation for disparities in healthcare;8 however, the current study demonstrates that in a real-world sample of patients with access to highly specialized care, there is differential utilization of VAD therapy despite similar patient preferences. Taken together, our results suggest that there are factors extrinsic to measurable determinants of VAD candidacy studied (e.g., presence of payor, caregiver, and treatment preference) that are impacting utilization and that are likely occurring at the decision-making level. Potential explanations include unobserved patient factors influencing patient or provider decision-making, implicit provider biases, or overt racism.

These findings are complementary and fill an important gap in knowledge when taken into consideration with the results of an analysis looking at the SDoH and VAD access among participants in the multicenter Decision Support Intervention for Patients and their Caregivers Offered Destination Therapy for End-Stage Heart Failure (DECIDE-LVAD) trial. Participants were enrolled in DECIDE-LVAD after either a request was made for insurance authorization for VAD or a request was made for patient education about VAD.41 Among the 212 patients included in an analysis focusing on the impact of SDoH, 73.1% underwent VAD, and there was no difference in utilization by race among the 29 Black participants.42 This could have resulted either because the DECIDE-LVAD study was underpowered to detect a meaningful difference, as the authors acknowledge (n = 29 for Black participants),42 or because there are no disparities in access to care once a patient is actively referred for VAD. There is a need for future work to understand where in the pipeline from the development of advanced heart failure to VAD placement disparities are occurring. The hypothesis from the combined DECIDE-LVAD and REVIVAL results is that there may be differential decision making in the referral for formal evaluation for VAD or transplant.

These findings have implications for the many stakeholders in VAD and transplant, including policymakers, transplant centers, and physicians. For policymakers, recent events have laid bare that structural racism and discrimination (SRD) is the primary cause of health inequity in America.25, 43 SRD is defined as the macro-level conditions such as institutional policies that limit the opportunities, resources, and well-being of people based on status such as race/ethnicity, sex, or socioeconomic status.44 There is an immediate need for policies to identify and address these inequities.45 A necessary first step is adopting methods to track health inequities across the spectrum of the SDoH fully. While analysis of currently collected information on advanced therapies, including VAD and transplant, through STS INTERMACS and United Network for Organ Sharing contain information on patients who receive a VAD or have a transplant evaluation opened, neither of these databases include all patients referred or considered for either therapy. Tracking underserved patients with inclusion of basic demographics, quality checking the accuracy of the documentation of race and the SDOH,46, 47 and increased specificity for the reasons why they do not receive a VAD or become listed for transplant would be a start toward improving equity in access.

It is not enough to identify disparities; the onus is on those who participate in its perpetuation to find ways to engender change. For transplant centers and staff, including physicians, practice must change immediately. This change can begin with gaining an understanding of the impact of SDoH25 and SRD45, 48, 49 on health inequities. Initial steps should include mandatory implicit bias training for all team members involved in the transplant process given prior observed biases15, 16 and some evidence that it can change behavior.50 Inclusion of psychosocial components into decision-making about advanced therapy candidacy likely impacts minoritized racial and ethnic groups disproportionately.51, 52 While parts of the psychosocial evaluation, such as social support, have been associated with outcomes after receipt of advanced therapies,51, 53 the lack of an agreed-upon standard about how to perform and interpret this critical part of the evaluation likely leads to observed biases.15, 16 Performing a stepwise psychosocial assessment with evolving best practices and using it as an opportunity to identify intervenable barriers has the potential to improve equity while awaiting additional research aimed at equitably understanding and addressing the psychosocial risk stratification process.53 These measures, however, may not be effective on their own. Programs where there are considerable issues or poor representation (e.g., staff demographics that are not reflective of population demographics) should consider the inclusion of disparity experts in their meetings and decision-making to help identify biases and barriers in real-time, to help promote equity, and to provide hands-on learning.

The results of this study should be interpreted after considering several limitations. The study is observational, and as such, there is always the possibility of unobserved heterogeneity and unmeasured confounding. However, we have demonstrated inequity among a highly selected group of patients enrolled in a clinical registry and receiving care through advanced HF programs. Thus, we have eliminated access to care, an important component of disparities; nevertheless, these disparities still exist. Given what is known about the impact of race on health inequities,48 the true disparity may very well be greater than we observed in this study, as many underserved patients are very likely not being evaluated by advanced HF cardiologists. Next, the finding of no association between sex and the use of advanced therapies or death merits discussion. There is ample evidence of inequities in the use of VAD and transplant among women.9, 54, 55 In the present study, we did not observe sex differences in utilization among patients with HF being cared for at VAD centers. The lack of an association may be due to limited power to detect a meaningful difference. The future steps should include an improved understanding of the incidence of women who qualify for VADs and transplant42 and of barriers to access of care at VAD centers. Third, the consistent results when using complete cases reduces concerns that the findings are the result of poorly specified multiple imputation, although when using multiple imputation there is always the possibility that variables are not missing at random and the imputed results may be biased. Last, we cannot be certain that an expressed preference for receiving a VAD in a research questionnaire accurately reflected patients' real-world choices if offered a VAD or predicts whether they would only want a heart transplant. The primary combined outcome of VAD or transplant was selected as it represents the failure of medical therapy. Only ~2% of patients within STS Intermacs who receive a VAD do not want a transplant, suggesting willingness for VAD would be very strongly associated with acceptance of transplant.56 The combined outcome of VAD and transplant was chosen before performing analyses and is reported as the primary outcome as such. The VAD-only sensitivity analysis was performed subsequently and showed a similar point estimate for the impact of race on VAD alone that is consistent, albeit underpowered to detect a meaningful difference. Both VAD and transplant were performed at a ratio of 2:1 for White compared to Black patients, suggesting that neither therapy alone explains the findings.

In conclusion, among HF patients with high-risk features receiving care from advanced HF cardiologists at VAD centers, there is less utilization of VAD and transplant among Black patients even after adjusting for HF severity, SDoH, patient-reported QOL, and care preferences. While unmeasured patient factors influencing VAD and TXP candidacy cannot be excluded, this residual inequity in VAD and TXP may result from SRD or provider biases impacting clinician decision-making.

Supplementary Material

Disparities Checklist
Supplemental Publication Material

What is new?

  • Black people with high-risk heart failure are less likely to receive ventricular assist devices and transplants than White people despite access to care by experienced providers.

  • Patient preferences for care are not the reason for inequities in access to ventricular assist devices.

What are the clinical implications?

  • There is an urgent need for providers to acknowledge our role in perpetuating current inequities and our future role in engendering change.

  • Steps to consider now include mandatory implicit bias training for all involved in the care of heart failure patients, standardizing the evaluation for ventricular assist devices and transplants, and inclusion of disparity experts in meetings to decide on therapies.

Acknowledgements:

The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.

Sources of Funding:

Supported by funding from the National Institutes of Health, National Heart, Lung, and Blood Institute (NHLBI Contract Number: HHSN268201100026C; K12 HL138039-02 to Dr. Cascino), the National Center for Advancing Translational Sciences (NCATS Grant Number: UL1TR002240) for the Michigan Institute for Clinical and Health Research (MICHR), and an Amplifier Grant Award from the Samuel and Jean Frankel Cardiovascular Center.

Non-standard Abbreviations and Acronyms

BMI

Body mass index

DECIDE-LVAD

Decision Support Intervention for Patients and their Caregivers Offered Destination Therapy for End-Stage Heart Failure

EQ-VAS

EuroQol visual analog scale

HR

Hazard ratios

HF

Heart failure

INTERMACS

Interagency Registry for Mechanically Assisted Circulatory Support

REVIVAL

Registry Evaluation of Vital Information for VADs in Ambulatory Life

SdoH

Social determinants of health

SRD

Structural racism and discrimination

VAD

Ventricular assist device

Footnotes

Disclosures: Keith Aaronson reports serving as a consultant and contracted clinical research from Medtronic; consultant and contracted clinical research from Abbott; Scientific Advisory Board at Procyrion; and consultant for NuPulse CV. Monica Colvin reports serving on Advisory Board CareDx; Advisory Board Medscape. David E. Lanfear has received research grants from Amgen, Bayer, Astra Zeneca, Lilly, Critical Diagnostics, Somalogic, and Janssen; he has acted as a consultant for Amgen, Janssen, Ortho Diagnostics, Cytokinetics, Illumina, ACI (Abbott Laboratories), Martin Pharmaceuticals and DCRI (Novartis). Garrick Stewart reports serving as a consultant for Abbott Laboratories and Procyrion, Inc. All other authors report no conflicts.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Disparities Checklist
NIHMS1837892-supplement-Disparities_Checklist.pdf (54.1KB, pdf)
Supplemental Publication Material
NIHMS1837892-supplement-Supplemental_Publication_Material.pdf (1.8MB, pdf)

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