INTRODUCTION
Racial and ethnic disparities in healthcare remain significant challenges in the USA.1 Considerable differences persist in barriers to care and patient outcomes.2,3 The All of Us (AoU) Research Program was established by the National Institutes of Health with the goal of recruiting one million socially diverse participants.4 We aim to further understand self-reported cost- and non-cost associated barriers to care and medications that racial and ethnic minorities face in the USA.
METHOD
This cross-sectional study analyzed survey data from AoU (2017–2022), with a focus on questions related to barriers to accessing medical care and medications. Patients of multiple races/ethnicities were not included in this study due to lack of granular information. Data analyses were conducted in the AoU Researcher Workbench using Jupyter Notebook software and Python (version 3.12.1). A two-sided P < 0.05 was considered statistically significant. Multivariable logistic regression was adjusted for a priori covariates including sex, foreign born, and income.
RESULTS
Our study included 393,043 participants, of which 20% were Black, 19% were Hispanic, 4% were Asian, and 4% reported more than one race (Table 1). Compared to White participants, Black and Hispanic participants had lower household income, less likely to be married, have private insurance, or college degrees, all p < 0.001.
Table 1.
Demographics and Characteristics of the Study Population
| White | % or St Dev | Black | % or St Dev | P value | Hispanic | % or St Dev | P value | Asian | % or St Dev | P value | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | 226,615 | 57.7% | 78,321 | 19.9% | 73,945 | 18.8% | 14,162 | 3.6% | |||
| Age | 53.3 | 17.1 | 49.0 | 14.7 | 44.0 | 15.8 | 42.1 | 16.8 | |||
| Sex | |||||||||||
| Female | 138,258 | 61.0% | 45,147 | 57.6% | < 0.001 | 49,306 | 66.7% | < 0.001 | 8504 | 60.0% | 0.02 |
| Male | 86,678 | 38.2% | 31,892 | 40.7% | 24,018 | 32.5% | 5564 | 39.3% | |||
| US vs Foreign Born | |||||||||||
| US | 214,694 | 94.7% | 73,384 | 93.7% | < 0.001 | 38,043 | 51.4% | < 0.001 | 5042 | 35.6% | < 0.001 |
| Foreign | 10,570 | 4.7% | 3910 | 5.0% | 35,420 | 47.9% | 9073 | 64.1% | |||
| Insurance | |||||||||||
| Private | 120,537 | 53.2% | 18,482 | 23.6% | < 0.001 | 22,738 | 30.7% | < 0.001 | 9760 | 68.9% | < 0.001 |
| Medicare | 52,212 | 23.0% | 12,118 | 15.5% | 7246 | 9.8% | 1426 | 10.1% | |||
| Medicaid | 26,564 | 11.7% | 29,479 | 37.6% | 25,341 | 34.3% | 1366 | 9.6% | |||
| Other | 17,738 | 7.8% | 4049 | 5.2% | 3147 | 4.3% | 456 | 3.2% | |||
| Marital Status | |||||||||||
| Married or Living with Partner | 134,405 | 59.3% | 19,637 | 25.1% | 35,495 | 48.0% | 7644 | 54.0% | |||
| Divorced or Separated | 35,739 | 15.8% | 17,429 | 22.3% | < 0.001 | 13,712 | 18.5% | < 0.001 | 999 | 7.1% | < 0.001 |
| Never Married | 41,995 | 18.5% | 32,748 | 41.8% | < 0.001 | 19,509 | 26.4% | < 0.001 | 4932 | 34.8% | < 0.001 |
| Widowed | 11,977 | 5.3% | 4477 | 5.7% | < 0.001 | 2740 | 3.7% | < 0.001 | 317 | 2.2% | < 0.001 |
| Income | |||||||||||
| < 10 K | 15,758 | 7.0% | 25,016 | 31.9% | < 0.001 | 11,900 | 16.1% | < 0.001 | 891 | 6.3% | < 0.001 |
| 10–35 K | 36,349 | 16.0% | 18,492 | 23.6% | 16,941 | 22.9% | 1698 | 12.0% | |||
| 35–75 K | 50,413 | 22.2% | 9443 | 12.1% | 11,051 | 14.9% | 2576 | 18.2% | |||
| 75 K–150 K | 59,439 | 26.2% | 4369 | 5.6% | 6186 | 8.4% | 3289 | 23.2% | |||
| > 150 K | 38,096 | 16.8% | 1455 | 1.9% | 2586 | 3.5% | 2797 | 19.8% | |||
| Education | |||||||||||
| < = Grade 11 | 6051 | 2.7% | 11,477 | 14.7% | < 0.001 | 17,593 | 23.8% | < 0.001 | 254 | 1.8% | < 0.001 |
| HS/GED | 28,831 | 12.7% | 26,310 | 33.6% | 18,163 | 24.6% | 957 | 6.8% | |||
| College | 58,350 | 25.7% | 21,906 | 28.0% | 18,512 | 25.0% | 1973 | 13.9% | |||
| Advanced Degree | 131,164 | 57.9% | 15,163 | 19.4% | 17,491 | 23.7% | 10,769 | 76.0% | |||
Cost-Associated Barriers
After adjusting for age, sex, education, and income, Black and Hispanic patients were more likely to seek care from emergency departments (Black aOR 3.83, 95% CI 3.51–4.18; Hispanic aOR 2.49, 95% CI 2.22–2.78), delay care from a generalist (Black aOR 1.67, 95% CI 1.58–1.77; Hispanic aOR 1.72, 95% CI 1.62–1.82), and delay follow-ups (Black aOR 1.49, 95% CI 1.41–1.57; Hispanic aOR 1.55, 95% CI 1.47–1.65). Black patients were also more likely to delay medication refills (aOR 1.09, 95% CI 1.04–1.15) and skip medications (aOR 1.10, 95% CI 1.04–1.16) due to cost concerns. Asians were more likely to delay care from generalist (aOR 1.2, 95% CI 1.1–1.3), but less likely to seek care from emergency departments (aOR 0.67, 95% CI 0.48–0.93) or delay refills (aOR 0.89, 0.80–0.98) (Table 2).
Table 2.
Cost and Non-Cost Associated Barriers to Care Among Racial/Ethnic Minorities, Adjusted for Sex, Foreign Born, and Income
| White | Black | Hispanic | Asian | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Reference | aOR | 95% low | 95% high | P value | aOR | 95% low | 95% high | P value | aOR | 95% low | 95% high | P value | |
| Places to get care—emergency room | - | 3.83 | 3.51 | 4.18 | < 0.001 | 2.49 | 2.22 | 2.78 | < 0.001 | 0.67 | 0.48 | 0.93 | 0.02 |
| Cost-associated barriers | |||||||||||||
| Delayed generalist care due to cost | - | 1.67 | 1.58 | 1.77 | < 0.001 | 1.72 | 1.62 | 1.82 | < 0.001 | 1.19 | 1.06 | 1.33 | 0.004 |
| Delayed specialist care due to cost | - | 0.97 | 0.93 | 1.01 | 0.16 | 1.02 | 0.98 | 1.07 | 0.38 | 1.16 | 1.08 | 1.25 | < 0.001 |
| Delayed follow-up care due to cost | 1.49 | 1.41 | 1.57 | < 0.001 | 1.55 | 1.47 | 1.65 | < 0.001 | 1.02 | 0.92 | 1.15 | 0.67 | |
| Delayed filling prescription due to cost | - | 1.09 | 1.04 | 1.15 | < 0.001 | 0.96 | 0.91 | 1.01 | 0.14 | 0.89 | 0.8 | 0.98 | 0.02 |
| Skipped medication due to cost | - | 1.1 | 1.04 | 1.16 | < 0.001 | 0.98 | 0.92 | 1.05 | 0.6 | 0.94 | 0.83 | 1.06 | 0.28 |
| Non-cost associated barriers | |||||||||||||
| Delay in care—no time off work | - | 1.15 | 1.09 | 1.22 | < 0.001 | 1.7 | 1.62 | 1.78 | < 0.001 | 1.98 | 1.84 | 2.13 | < 0.001 |
| Delay in care—no transportation | - | 1.57 | 1.49 | 1.65 | < 0.001 | 1.45 | 1.37 | 1.54 | < 0.001 | 1.17 | 1.04 | 1.31 | 0.008 |
| Delay in care—no childcare | - | 1.25 | 1.14 | 1.37 | < 0.001 | 2.1 | 1.94 | 2.29 | < 0.001 | 1.11 | 0.95 | 1.31 | 0.19 |
| Delay in care—no elder care | - | 1.14 | 1.02 | 1.26 | 0.02 | 1.46 | 1.32 | 1.63 | < 0.001 | 0.91 | 0.73 | 1.13 | 0.4 |
| Delay in care—living in rural area | - | 0.92 | 0.85 | 0.99 | 0.04 | 1.14 | 1.05 | 1.25 | 0.003 | 0.59 | 0.48 | 0.73 | < 0.001 |
Non-Cost Associated Barriers
Non-White individuals were more likely to delay care due to lack of time off work (Black aOR 1.15, 95% CI 1.09–1.22; Hispanic aOR 1.70, 95% CI 1.62–1.78; Asian aOR 1.98, 95% CI 1.84–2.13) and lack of transportation (Black aOR 1.57, 95% CI 1.49–1.65; Hispanic aOR 1.45, 95% CI 1.37–1.54; Asian aOR 1.17, 95% CI 1.04–1.31). Black and Hispanic individuals were more likely to delay care due to lack of childcare (Black aOR 1.25, 95% CI 1.14–1.37; Hispanic aOR 2.10, 95% CI 1.94–2.29) and elder care (Black aOR 1.14, 95% CI 1.02–1.26; Hispanic aOR 1.46, 95% CI 1.32–1.63). Hispanic individuals are also more likely to delay care due to living in rural areas (aOR 1.14, 95% CI 1.05–1.25).
DISCUSSIONS
This study highlights the pervasive nature cost and non-cost barriers faced by minority populations. Black and Hispanic patients are more likely to utilize emergency departments and delay care due to cost. Previous research also found minority groups have less access to primary care and preventive services, leading to an overreliance on emergency care.5 Interestingly, Asian participants were more likely to delay care but less likely to seek emergency care or delay medications, possibly suggesting distinct barriers or cultural preferences in healthcare utilization.
Similar to prior findings, non-cost barriers such as finding time off work and lack of transportation were ubiquitous within minority groups.1 Addressing financial barriers alone may not sufficiently improve access for these populations. Further strategies must be implemented to enhance access to medical care, such as offering extended hours, telehealth services, and transportation assistance. Additionally, while it is crucial to address these barriers, further studies are needed to evaluate how these barriers impact outcomes for these individuals.
Limitations
Although the AoU Program aims to recruit a socially diverse cohort, there may still be sampling biases that impacts the generalizability of the results. Additionally, this survey lacks information such as the extent or duration of delay in care or medications.
CONCLUSION
Racial/ethnic minority populations continue to face cost, structural, and societal barriers to obtaining care. It is imperative for policy makers, providers, and community leaders to identify these impediments and to address these with targeted strategies to optimally promote health equity.
Declarations:
Conflict of Interest:
ABJ received consulting and speaking for Salix Pharmaceuticals, consulting for Dynavax Therapeutics, and speaking for Madrigal Pharmaceuticals. XY, RZ, SP, NN, RR, and CL have no financial conflicts to report.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
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