Pre-Reform Health Care Access and Affordability within the ACA's Medicaid Target Population
Stephen Zuckerman, John Holahan, Sharon Long, Dana Goin, Michael Karpman, and Ariel Fogel
January 28, 2014
As originally signed into law, the Affordable Care Act (ACA) expanded Medicaid to all individuals with family incomes at or below 138 percent of the federal poverty level (FPL).1 The establishment of uniform requirements sought to address the extensive variation across states in Medicaid eligibility. That variation meant that income eligibility rules varied extensively and few states offered coverage to childless adults. The US Supreme Court’s June 2012 decision to make Medicaid expansion optional leaves the extensive variation in eligibility rules in place. So far, only 25 states have decided to expand Medicaid.
In this brief, we examine patterns of pre-reform health care access and affordability within the ACA’s adult Medicaid target population, more than 40 percent of whom were uninsured at the time of the survey (see Blavin et al. 2012). Specifically, we focus on comparing the adults in this income group who had Medicaid or other public coverage at the time of the survey (based on pre-ACA rules) and were continuously insured for the entire prior year (with either public or private coverage) with those who were uninsured all or part of the prior year. Although these comparisons are not intended to show the impact of public coverage on previously uninsured adults, they do show the gaps in access and affordability before the ACA and suggest the potential gains to this population from enrolling in Medicaid. For comparison, we examine access and affordability differences between adults with pre-reform public versus private health insurance.
What We Did
The analysis draws on data collected in June–July 2013 from the Health Reform Monitoring Survey (HRMS) using a sample of nonelderly adults age 18–64. In addition to providing data on insurance coverage at a point in time, the HRMS has information on whether individuals had coverage over the prior year. Thus, the Medicaid target population can be placed into three categories based on the type of pre-reform insurance coverage:
Adults with pre-reform public coverage are more likely to be in fair or poor health and less likely to be young (18–30 years old) or male than uninsured adults (table 1). There are no statistically significant differences by education. Since these and other characteristics can influence access to and affordability of health care, we use multivariate models to control for such characteristics and present both unadjusted and regression-adjusted differences by insurance type.2
The access questions ask respondents whether they have a usual source of care, had a routine checkup in the past year, or had trouble finding a doctor or other health care provider; and the type of difficulty obtaining care (including trouble finding a doctor who would accept them as a new patient, finding a doctor who would accept their insurance, or getting an appointment with a doctor). The affordability questions ask respondents whether they had unmet needs for medical care (including medical care, general doctor care, specialist care, medical tests, treatments or follow-up care), dental care, mental health care or counseling, or prescription drugs due to costs during the prior year, and whether they had problems paying or were unable to pay medical bills over the prior year.
What We Found
The uninsured are much less likely than the publicly insured to have a usual source of care and less likely to have had a regular checkup in the prior year; they are more likely to have had trouble finding a doctor (table 2). Only 43.8 percent of the uninsured report having a usual source of care, compared with 82.4 percent of the publicly insured. The uninsured are much less likely to have had a regular checkup in the prior year (38.1 percent versus 76.2 percent) and more likely to have had trouble finding a doctor or other health care provider (13.4 percent versus 9.2 percent). The magnitude of these differences varies slightly when regression-adjusted, but all remain statistically significant (figure 1). However, the uninsured and the publicly insured have similar degrees of difficulty finding a doctor who would take them as a new patient or who would accept their insurance, but only the regression-adjusted difference for the new-patient variable was significant.
Uninsured adults in the Medicaid target population are also more likely than the publicly insured to have unmet health care needs because of costs and more problems paying their medical bills. All the affordability measures show that adults with public coverage (possibly interspersed with some periods of private coverage) for a full year are significantly less likely to report affordability problems than uninsured adults. For example, 44.0 percent of uninsured adults report forgoing medical care because of costs compared with only 25.4 percent of the public coverage group (see table 2). Similarly, the uninsured are more likely to report unmet prescription drug needs relative to those with public coverage (31.0 percent versus 21.3 percent). Reported problems paying bills are also much more prevalent among the uninsured than among the publicly insured (39.3 percent versus 24.0 percent). In all instances, the regression-adjustment strengthens these findings (figure 2).
Differences between adults in the Medicaid target population with public versus private health insurance suggest that access problems have been less pronounced for adults if they have private insurance, but that affordability problems have been worse for the privately insured. Although privately insured adults in this income range are less likely to have a usual source of care than the publicly insured, they are still less likely to have had difficulties getting a doctor’s appointment. The simple differences suggest that the publicly insured are more likely to have had a routine checkup in the prior year than the privately insured, and the regression-adjusted difference remains significant. However, those with public insurance are less likely to have problems in paying medical bills and less likely to experience unmet medical care and prescription drug needs due to costs than the privately insured.
What It Means
Among the ACA’s Medicaid target population, having public coverage relative to being uninsured is associated with better access to care along several dimensions. The differences related to affordability are even more consistent and dramatic. Affordability problems are much more likely to be reported by individuals who are uninsured for all or part of the year than by individuals with public coverage. This finding is consistent with the recent randomized study of the Oregon Medicaid program showing that Medicaid provided strong financial protections for its beneficiaries (Baicker et al. 2013; Finkelstein et al. 2012). These results suggest that adults newly eligible for Medicaid in states that choose the ACA expansion option will experience financial protection and may experience better access to care. These potential benefits will not accrue to uninsured adults living in states that do not participate in the ACA Medicaid expansion.
One other noteworthy finding: Although the uninsured are much less likely to have a usual source of care or to have had a routine checkup than those with public coverage, the two groups have experienced similar degrees of difficulty finding a doctor as a new patient and a doctor who would accept their insurance type. This suggests that low-income adults who obtain coverage under the ACA’s Medicaid expansion option may continue to have some problems actually obtaining care even with their new insurance.
Baicker, Katherine, Sarah Taubman, Heidi Allen, Mira Bernstein, Jonathan Gruber, Joseph P. Newhouse, Eric Schneider, Bill Wright, Alan Zaslavsky, Amy Finkelstein, and the Oregon Health Study Group. 2013. “The Oregon Experiment—Effects of Medicaid on Clinical Outcomes.” New England Journal of Medicine 368(18): 1713–22.
Blavin, Fredric, John Holahan, Genevieve M. Kenney, and Vicki Chen. 2012. “A Decade of Coverage Losses: Implications for the Affordable Care Act.” Washington, DC: The Urban Institute.
Finkelstein, Amy, Sarah Taubman, Bill Wright, Mira Bernstein, Jonathan Gruber, Joseph P. Newhouse, Heidi Allen, Katherine Baicker, and the Oregon Health Study Group. 2012. “The Oregon Health Insurance Experiment: Evidence from the First Year.” Quarterly Journal of Economics 127(3): 1057–1106.
About the Series
This brief is part of a series drawing on the Health Reform Monitoring Survey (HRMS), a quarterly survey of the nonelderly population that is exploring the value of cutting-edge Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. The briefs provide information on health insurance coverage, access to and use of health care, health care affordability, and self-reported health status, as well as timely data on important implementation issues under the ACA. Funding for the core HRMS is provided by the Robert Wood Johnson Foundation, the Ford Foundation, and the Urban Institute.
For more information on the HRMS and for other briefs in this series, visit www.urban.org/hrms.
About the Authors
Stephen Zuckerman is codirector and senior fellow, John Holahan is an Institute fellow, and Sharon K. Long is a senior fellow in the Urban Institute’s Health Policy Center. Dana Goin, Michael Karpman, and Ariel Fogel are research associates in the Urban Institute’s Health Policy Center.
1 The ACA also provides income-related subsidies through tax credits for individuals with incomes between 138 percent and 400 percent of FPL. If a state does not adopt the Medicaid expansion, subsidies begin at an income of 100 percent of FPL. The law also establishes health insurance Marketplaces that ease the purchase of health insurance coverage for individuals and small businesses.
2 The regressions control for age, gender, race and ethnicity, health status, education, marital status, home ownership, and an indicator of residence in a metropolitan area. The regression-adjusted differences should not be interpreted as the impact of having one type of insurance as opposed to another (or of having no insurance). There may be unmeasured differences between insurance groups that affect who has a particular type of insurance and relate to access and affordability.