Insurance-Based Discrimination Reports and Access to Care Among Nonelderly US Adults, 2011–2019

Kathleen Thiede Call is with the School of Public Health, Division of Health Policy and Management, and the State Health Access Data Assistance Center (SHADAC), University of Minnesota, Minneapolis. At the time of this writing, Giovann Alarcon-Espinoza was with the School of Public Health, SHADAC, University of Minnesota, Minneapolis. Natalie Schwer Mac Arthur is with the School of Public Health, State Health Access Data Assistance Center, SHADAC, University of Minnesota, Minneapolis. Rhonda Jones-Webb is with the School of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis.

Correspondence should be sent to Kathleen Thiede Call, 420 Delaware Street SE, MMC 729, University of Minnesota, Minneapolis, MN 55455 (e-mail: ude.nmu@100xllac). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link.

K. T. Call contributed to the conceptualization and design, data collection, data interpretation, drafting, and critical revision of the article, and approval of the final version. G. Alarcon-Espinoza contributed to the conceptualization and design, data collection, data analysis and interpretation, drafting, and critical revision of the article, and approval of the final version. N. S. Mac Arthur contributed to the data analysis and interpretation, critical revision of the article, and approval of the final version. R. Jones-Webb contributed to the conceptualization and design, drafting and critical revision of the article, and approval of the final version.

Abstract

Objectives. To report insurance-based discrimination rates for nonelderly adults with private, public, or no insurance between 2011 and 2019, a period marked by passage and implementation of the Affordable Care Act (ACA) and threats to it.

Methods. We used 2011–2019 data from the biennial Minnesota Health Access Survey. Each year, about 4000 adults aged 18 to 64 years report experiences with insurance-based discrimination. Using logistic regressions, we examined associations between insurance-based discrimination and (1) sociodemographic factors and (2) indicators of access.

Results. Insurance-based discrimination was stable over time and consistently related to insurance type: approximately 4% for adults with private insurance compared with adults with public insurance (21%) and no insurance (27%). Insurance-based discrimination persistently interfered with confidence in getting needed care and forgoing care.

Conclusions. Policy changes from 2011 to 2019 affected access to health insurance, but high rates of insurance-based discrimination among adults with public insurance or no insurance were impervious to such changes.

Public Health Implications. Stable rates of insurance-based discrimination during a time of increased access to health insurance via the ACA suggest deeper structural roots of health care inequities. We recommend several policy and system solutions. (Am J Public Health. 2023;113(2):213–223. https://doi.org/10.2105/AJPH.2022.307126)

Health insurance is not a universal right in the United States. Consequently, people lacking health insurance face greater barriers to accessing primary care and timely sick care. 1 , 2 Furthermore, access to health insurance in the United States is based on an individual’s or group’s resources. Private insurance is available to some through employment or their financial ability to pay; public insurance is available to some with low incomes or who meet categorical eligibility (e.g., elderly, disabled, children), whereas others remain uninsured, citing inability to afford coverage and ineligibility for existing coverage as top barriers. 1 Health insurance systems that are based on individual resources can lead to inequities—such as insurance-based discrimination—and perpetuate the notion that some people are more deserving of receiving care than others.

Insurance-based discrimination refers to unfair treatment that patients receive from health care providers because of the type of insurance they have (or because they do not have insurance). As is true of all forms of discrimination, insurance-based discrimination manifests at multiple levels: individual (e.g., internalized shame for needing assistance), interpersonal (e.g., treated with disrespect, told they are wasting taxpayer money), 3 and institutional (e.g., policies and practices in organizations that provide differential access to services). 4 Insurance-based discrimination at the interpersonal level is rooted and reinforced in policies like lower physician compensation for Medicaid services than for Medicare and private insurance, which results in differential treatment, such as instructions to schedulers to prioritize private over public pay patients, long wait times, separation of public and private pay patients in academic medical center clinics, and narrow networks where providers do not accept new Medicaid patients. 5 – 10

Past research consistently shows dramatically higher rates of insurance-based discrimination among people with public rather than private insurance. 3 , 11 – 15 Past research also consistently demonstrates that reports of insurance-based discrimination are tied to delayed and forgone care, 3 , 12 , 13 lack of confidence in getting needed care, 12 reports of poor-quality care, 7 and receipt of suboptimal care. 14 Experiences of discrimination are also associated with using more costly emergency department services instead of primary care. 3

The 2010 passage of the Affordable Care Act (ACA) represents one of several federal efforts to address inequities in access to health insurance, health care, and, possibly, insurance-based discrimination. Beginning in 2014, states that expanded Medicaid received a 100% federal match to encourage covering a broader group of people with low incomes. To ensure an adequate supply of providers, the ACA also mandated a 2-year increase in physician payment rates for Medicaid to the level of Medicare, 5 yet this was not enough to stem the financial preference for private over public patients. 6 The individual mandate (i.e., the requirement to have insurance or face a penalty) held promise for reducing stigma attached to insurance available through government interventions because public insurance was the only affordable option for some people to meet this requirement. 16 However, in 2017, the new presidential administration set this penalty at zero, marking the first challenge to the ACA. Other efforts to dismantle the ACA followed, along with renewed efforts to tie notions of deservedness to public insurance, such as state attempts to link work requirements to Medicaid. 17

By all measures, the ACA was successful in expanding insurance coverage and lowering uninsured rates, mostly through large gains in Medicaid enrollment. 1 Evidence of gains in access and quality of care for adults with public versus private insurance is mixed. Some studies reported similar access to outpatient care, affordability, and quality ratings for adults with both forms of insurance. 2 Other studies found that adults with private insurance fared better in terms of stability of coverage, affordability, having a personal physician, and obtaining specialist and dental care. 2 , 18 , 19 However, adults with private insurance reported less financial protection and were more likely to report medical debt than Medicaid beneficiaries. 2 , 18

The controversial nature of the ACA’s passage, its incremental implementation, and repeated efforts to repeal it begs the question of whether ongoing public and policy debates surrounding this legislation have influenced insurance-based discrimination and, in turn, access to health care among those most vulnerable. Extending coverage to a broader group of people may not eliminate experiences of insurance-based discrimination given long-standing negative views of public insurance in health care and society. This assumption is supported by dueling terms surrounding the ACA—the “woodwork” and “welcome mat” effects—which indicate polarized opinions in public and policy circles. The former term insinuates that people previously eligible now “crawl out of the woodwork” to enroll in Medicaid, as opposed to “welcoming” enrollment with the latter. 20 This important question has not been addressed in the research on insurance-based discrimination. Past research has provided single-year snapshots of the presence and impact of insurance-based discrimination on access to health care, yet almost all studies precede either ACA passage 3 , 11 , 14 , 15 , 21 – 23 or full implementation. 12 , 24 The exception is the study by Skopec and Long, who use data from 2016, which is after full implementation but before the change of administration and formal efforts to repeal. 13 This article addresses important gaps in current research on insurance-based discrimination, health care access, and the ACA.

The specific objectives of this article are to (1) examine experiences of insurance-based discrimination in Minnesota from 2011 to 2019, (2) describe the correlates of insurance-based discrimination, and (3) investigate the association between insurance-based discrimination and health care access. Our study covers the early years of ACA implementation (which were marked by challenges to Medicaid expansion 17 ), through full implementation (marked by state variation in Medicaid expansion and launch of Marketplace plans), through a change of administration (marked by efforts to dismantle the ACA and create obstacles to Medicaid enrollment), through a subsequent change of administration backing ACA initiatives; the study stops, however, before the onset of the COVID-19 pandemic. Understanding these events and their impact on public policy and opinion is an important step in grasping how broader forces operate in shaping insurance-based discrimination in our health care system, how insurance-based discrimination relates to health care access over time, and what can be done to reduce insurance-based discrimination. Results may be informative to health care institutions and policymakers seeking effective multilevel and multicomponent strategies to reduce inequities in health care delivery.

METHODS

Data were from the Minnesota Health Access Survey (MNHA), a biennial survey representative of the noninstitutionalized population in Minnesota. The MNHA undersamples older adults and oversamples rural populations and areas with concentrations of individuals who identify as racial or ethnic minority, and those with lower incomes. The MNHA collects information about sociodemographic characteristics, health insurance coverage, and access to care for a randomly selected household member. We used data from 2011, 2013, 2015, 2017, and 2019. However, 2 changes in the survey design in 2019 limit comparability with previous years. First, the 2019 MNHA added an address-based sample frame to the standard dual random digit dialing frame used in previous years. Second, the address-based sample frame collected data primarily through a computer-assisted Web interview program. This change in survey administration, from interacting directly with an interviewer to answering the questions via self-guided Web site, could affect respondents’ reports of discrimination in 2019.

Sample

We restricted the population to nonelderly adults aged 18–64 years because of the high uptake of Medicare among adults aged older than 64 years and enduring differences in narratives of deservedness between Medicare and Medicaid. 7 We also excluded proxy reports, such as responding for a child or a spouse. Limiting the analysis to adults responding for themselves about insurance and experiences of discrimination provides a more conscientious examination of the association between insurance-based discrimination and insurance type ( Table 1 ).

TABLE 1—

Sociodemographic Characteristics, Health Status, and Health Care Access by Year Among Adults Aged 18–64 Years: Minnesota, 2011–2019

Source. Minnesota Health Access Survey. Data were weighted to represent the state’s population.

b Any reports of forgone care due to cost including prescribed medications, dental care, routine care, and specialist care in the last 12 months; beginning in 2013, mental or behavioral care was added.

Consistent with national trends, response rates decreased over time from 44% (2011) to 22% (2019). 25 Because of the 2019 change in sampling strategy, we retroactively implemented the updated weighting approach to all previous years of data. We weighted data to adjust for nonresponse bias and to reflect the general population in Minnesota. 26

Measures

The MNHA asks, “How often do health care providers treat you unfairly because of the type of health insurance you have?” or “because you don’t have health insurance?” We coded someone as experiencing insurance-based discrimination if they reported that health care providers always, usually, or sometimes (vs never) treated them unfairly because of their health insurance (or lack thereof). The survey also includes a measure of race-based discrimination (“How often do health care providers treat you unfairly because of your race, ethnicity, or nationality?”).

We measured insurance type by providing a list of responses that we recoded as private insurance (i.e., employer-sponsored, self-purchased, and, starting in 2015, MNsure [Minnesota’s Marketplace plan]) or public insurance (i.e., Medicare, Medicaid, MinnesotaCare). We coded respondents reporting both private and public insurance as having public because of our research focus on public insurance. Consistent with federal surveys, we classified adults responding no to all sources (or who reported only Indian Health Services) as uninsured.

We examined 3 indicators of access: (1) usual source of care (excluding emergency departments), (2) confidence in getting care when needed (very or somewhat confident vs a little or not at all confident), and (3) reports of forgone care due to cost in the last 12 months (prescribed medications, dental care, routine care, specialist care, and mental or behavioral care).

The survey included measures tied to societal opportunities, power, and resources such as gender, age, race/ethnicity, nativity, family income, education, marital status, employment status, self-reported health status, and place of residency (rural or urban).

Analyses

RESULTS

Table 1 describes the nonelderly adult sample each year. Full implementation of the ACA resulted in a significant decrease in the uninsured rate between 2013 and 2015 (10.7% to 3.6%, respectively) and a corresponding increase in public insurance enrollment (17.7% to 23.1%). Most adults were covered by private insurance; however, the decrease in private insurance for adults between 2015 and 2017 (73.3% to 69.6%) corresponded with an increase in uninsurance (3.6% to 7.7%).

On average, approximately 10% of nonelderly adults reported insurance-based discrimination ( Figure 1 ), although this increased from 7.7% in 2015 to 11.0% in 2017, the same year that the uninsured rate doubled and private insurance dropped significantly ( Table 1 ). Reports of insurance-based discrimination by type of insurance were stable between 2011 and 2019, ranging from 24.7% to 28.1% for uninsured adults and 18.4% to 24.0% for publicly insured adults, compared with 3.0% to 5.4% for adults with private insurance. In terms of our access measures, fewer than 20% of adults reported lacking a usual source of care, fewer than 13% reported lacking confidence in receiving needed care, and fewer than 37% reported forgone care over the study period.

Reports of Insurance-Based Discrimination Among Nonelderly Adults and by Type of Health Insurance Among Adults (Aged 18–64 Years): Minnesota, 2011–2019

Note. ACA = Affordable Care Act.

Source. Minnesota Health Access Survey. Data were weighted to represent the state’s population.

*Indicates a statistically significant change with respect to the previous year (P < .05).

Correlates of Insurance-Based Discrimination

Three sociodemographic characteristics were consistently associated with insurance-based discrimination over the period of analysis: type of health insurance, income, and health status ( Table 2 ). Being uninsured showed a consistent association with insurance-based discrimination in all years (AORs ranged from 3.63 to 9.40). Having public coverage was associated with insurance-based discrimination in all years except 2017.

TABLE 2—

Association Between Insurance-Based Discrimination and Insurance Type, Participant Characteristics, and Health Status Among Adults Aged 18–64 Years: Minnesota, 2011–2019

Note. AOR = adjusted odds ratio; CI = confidence interval; FPG = federal poverty guidelines (https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines).

Source. Minnesota Health Access Survey. Data were weighted to represent the state’s population.

a In 2013, results for other race were suppressed because of small sample size, which produced a lack of convergence in the model.

Minnesotan adults with greater family income relative to the federal poverty guidelines (https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines) had consistently lower odds of experiencing insurance-based discrimination compared with families with income below 139% of the federal poverty guidelines. Adults reporting “fair” or “poor” health status had about double the odds of reporting insurance-based discrimination as those with better self-reported health.

We tested the robustness of our results by adding race-based discrimination to our model. Reports of race-based and insurance-based discrimination were highly associated. However, even when we adjusted for race-based discrimination, insurance-based discrimination remained highly associated with health insurance, income, and health status (Appendix A, available as a supplement to the online version of this article at http://www.ajph.org).

Discrimination and Access to Health Care

We found that people who experienced insurance-based discrimination were more likely to report forgoing care because of costs in all 5 years observed (AORs ranged from 2.39 to 4.64; Table 3 and online Appendix B). Insurance-based discrimination was associated with increased odds of lacking confidence in getting needed care in 4 of 5 years (AORs ranged from 3.03 to 9.16). Having a usual source of care was not consistently associated with insurance-based discrimination. The results were robust in models including race-based discrimination (online Appendix C).

TABLE 3—

Association Between 3 Access Measures and Insurance-Based Discrimination Among Adults Aged 18–64 Years: Minnesota, 2011–2019

Note. AOR = adjusted odds ratio; CI = confidence interval. All models were adjusted for health insurance, gender, race/ethnicity, nativity, age, poverty, education, marital status, employment status, place of residence, and health status.

Source. Minnesota Health Access Survey. Data were weighted to represent the state’s population.

a Any reports of forgone care due to cost, including prescribed medications, dental care, routine care, and specialist care in the last 12 months; beginning in 2013, mental or behavioral care was added.

DISCUSSION

Although more Minnesota adults gained public coverage and fewer adults were uninsured following ACA implementation, reports of insurance-based discrimination by type of insurance remained remarkably stable between 2011 and 2019. Compared with adults with private insurance (4% on average), insurance-based discrimination was 5 or 6 times higher for adults with public insurance (21% on average) and about 7 times higher for adults with no insurance (27% on average). Consistent with past research, there was little association between insurance-based discrimination and having a usual source of care. 3 However, insurance-based discrimination persistently interfered with confidence in getting needed care and reports of forgoing care. These access barriers for adults reporting insurance-based discrimination hold even when we account for reports of race-based discrimination, which is important given historical and ongoing race-based discrimination in the United States. 17 , 22 This suggests that insurance-based and race-based discrimination are both important to address in creating equitable access to health care. Future analysis will examine these intersecting forces of discrimination more deeply.

To our knowledge, this study is the first to examine rates of insurance-based discrimination over time following passage and full implementation of the ACA. The association between insurance-based discrimination and income was strong even when we controlled for type of health insurance ( Table 2 ). This direct association between income and insurance-based discrimination suggests that adults with lower incomes are more likely to experience discrimination regardless of the type of insurance they have.

Limitations

Our study provides important information about persistent reports of insurance-based discrimination and its negative association with access to care, but there are limitations. First, the data are repeat cross-sections measuring insurance type and access experiences at the time of the survey and forgone care in the past 12 months, which unfortunately impeded our ability to establish causal associations. Second, we use data from 1 state—Minnesota, a state with historically high rates of private insurance, low uninsured rates, generous public program eligibility prior to the ACA, and early participation in Medicaid expansion. Nevertheless, our results are consistent with past single-year studies in other states 3 , 14 , 15 , 23 and at the national level. 13 , 22 , 24 Third, our single-item measure of insurance-based discrimination is straightforward and easy to administer, yet it admittedly lacks a specific time reference. Thus, people who recently changed coverage (e.g., public to private) may be reporting their experiences with providers based on their prior insurance. However, the associations we report between insurance-based discrimination and type of insurance are consistent with other studies using measures with no time referent, 3 , 14 , 21 , 22 studies that reference a specific hospitalization, 24 and studies that reference the past 6 months 23 or the past 12 months. 13 , 15

Fourth, we cannot confidently identify nonelderly people who have Medicaid and Medicare (because of health challenges and disability); their experience with insurance-based discrimination is likely to be more nuanced than that of someone with only Medicaid and in relatively better health. Finally, our measure refers to “health care providers” generally rather than specific roles or provider types (staff, nurse, physician, etc.). This is both consistent with all insurance-based discrimination measures we reviewed and pragmatic, because each clinical encounter involves interactions with a variety of people who shape the experience. For instance, negative stereotypes about uninsured, low-income, and publicly insured patients held by physicians can set the tone for clinic staff. 8

Public Health Implications

High rates of insurance-based discrimination among nonelderly adults with public insurance and those who lack health insurance were impervious to political and policy shifts between 2011 and 2019, suggesting that this inequity has deeper structural roots. Although insurance-based discrimination is experienced at individual and interpersonal levels, these instances are intertwined with structural and institutional policies such that structural solutions are needed.

Policy solutions

Implementing a single-payer system of coverage that prioritizes our multiracial working class may be a possible solution to addressing insurance-based discrimination. As of 2020, 63% of US adults agreed that “it is the federal government’s responsibility to make sure all Americans have health care coverage,” with 36% favoring a single national government program. 28 Additionally, beginning in 2016, just over 50% of persons in the United States supported “a national health plan, sometimes called Medicare-for-all, in which all Americans would get their insurance from a single government plan.” 29 Although not a panacea, assigning everyone the same insurance removes 1 layer of structural discrimination inherent in a system where people with more resources have private insurance and people with fewer resources have public insurance or no insurance.

Even with a single-payer system, societal perspectives of worth based on income may persist and take the place of insurance-based discrimination. Given the pervasiveness of insurance-based and other forms of discrimination, we also encourage greater structural competency at all levels of government, health care systems, and society. Qualitative research indicates that lower-income patients feel disrespected, ignored, and devalued by health care professionals compared with middle-income patients. 30 Some reported that providers downplayed their health concerns and involved them less in decisions when on public insurance compared with their experience when covered by private insurance. 30 Metzl and Hansen argue for structural competency training for health professionals to overcome the stereotype that people in poverty are more difficult to treat and to instead recognize the complexity of circumstances—social, economic, and political—that make achieving good health extremely challenging for people with low incomes. 31 Shifting blame from people to the structural barriers to power and resources among poor and marginalized people holds promise for reducing insurance-based discrimination.

A second policy solution focuses on altering reimbursement rates for public insurance programs. In the current health care system, it is rational for providers to treat patients with private insurance better than patients with public insurance, whether intentional or not; they are literally paid to do so. States are already exploring ways to structure Medicaid payments and incentives for providers and managed care organizations to define and meet health equity priorities, and some are engaging the community in setting these goals. 32 However, it is critical to monitor whether financing changes translates into improved patient experiences or into greater burden for providers, which, in turn, may increase reports of unfair treatment by Medicaid enrollees. Furthermore, changing incentives is not the same as altogether removing the profit motive from health care.

Institutional and systems solutions

Improved monitoring of insurance-based discrimination in health care is both necessary and possible, as evidenced by inclusion in the supplemental Cultural Competence Item Set of the Consumer Assessment of Healthcare Providers & Systems, a national survey of patients’ experiences with health care administered by the Agency for Healthcare Research and Quality. 33 We endorse the call for direct measures of discrimination (e.g., insurance-based discrimination, race-based discrimination) rather than only proxy measures (e.g., insurance type, race, ethnicity) in these monitoring efforts. 34 The Centers for Medicare and Medicaid Services could mandate their use and reward systems with low and improved rates of discrimination. The ACA set out to strengthen nondiscrimination policies. Reporting acts of discrimination was initially required; however, notification expectations were relaxed in 2019. 17 Regardless of this revision, few people file complaints. 13 This may be through lack of awareness about reporting requirements, lack of knowledge about how to file a report, or lack of confidence that anything will come of a complaint, among other things. Including discrimination measures in ongoing quality assessments removes the burden of reporting from people experiencing discrimination.

Embedding community health workers (CHWs) in health care teams is a promising systems solution to promoting both trust in health care and comfort in reporting suboptimal care. CHWs are trusted and trained members of the historically marginalized communities they represent and serve; they contribute to reducing health inequities through education and advocacy, thus creating a bridge between providers and their patients, who otherwise have little power and voice. 35 CHWs increase the comfort level of patients with whom they share life experiences, which increases their trust and ability to navigate and use health care services. 35 CHWs potentially increase patients’ knowledge of their rights, which may foster the reporting of discriminatory encounters.

Monitoring insurance-based discrimination and enforcing antidiscrimination policies are important because even though we found reports of insurance-based discrimination to be stable over time, exposure to insurance-based discrimination is growing at the rate of public program enrollment growth. As shown in the current study and past research, insurance-based discrimination consistently results in delayed and forgone care. 3 , 12 , 23

SUMMARY

We examined insurance-based discrimination and access to health care during the creation and implementation of—as well as challenge to—the ACA. We found that during this period, insurance-based discrimination persisted despite increased access to health insurance, especially public health insurance. We suggest several strategies at the policy and institutional levels to ensure a more equitable health care system that all persons in the United States deserve.

ACKNOWLEDGMENTS

This research was supported by the Minnesota Department of Health, Minnesota Department of Human Services, and SHADAC through a grant from the Robert Wood Johnson Foundation.

We appreciate the contributions of Neha Potlapalli and Sydney Bernard, who conducted literature searches to support this research. We are grateful for the magic of SHADAC staff members Andrea Stewart for copyediting and Lindsey Theis for graphics. We thank Kelly McAnnany for her review of an earlier version of the article and many helpful insights. Finally, we are thankful to the talented staff at SSRS for administering the survey and the thousands of Minnesotans over the years who took the time to complete the survey and share their experiences with insurance coverage and access.

Note. The views expressed here do not necessarily reflect the views of our funders or our employers.

CONFLICTS OF INTEREST

The authors declare no conflicts of interests for this article.

HUMAN PARTICIPANT PROTECTION

This study was approved by the University of Minnesota’s institutional review board.