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Question to Answer: (W4 PUB650)

The passage of the Patient Protection and Affordable Care Act (most often referred to as the Affordable Care Act or ACA) was a monumental milestone in terms of national health reform.

What were some reasons why previous health reform efforts failed? Why was this effort at national health reform successful? Describe the social, economic, and political contexts that contributed to the passage of the ACA. In your opinion, what elements of the ACA are working, and what are some areas that need improvement? Use evidence to support your viewpoint.


– minimum of 250 words or more

– strong academic writing / APA style 7th Ed (please use in-text citing and References at end )

– Please used any of the attached resources and reference and in-text cite.

– please be original writing and must answer all parts of question for full credit.

Articles attached

Read “Public Health and Public Trust: Survey Evidence From the Ebola Virus Disease Epidemic in Liberia,” by Blair, Morse, and Tsai, from

Social Science and Medicine




Read “Enrollment and Disenrollment Experiences of Families Covered by CHIP,” by Trenholm, Harrington, and Dye, from

Academic Pediatrics




Read “Government’s Role in Protecting Health and Safety,” by Frieden, from

New England Journal of Medicine




Read “Public Health Ethics and Law,” by Gostin and Wiley, located on The Hastings Center website.


Public Health Ethics and Law

Read “Summary of the Affordable Care Act” (2013),

located on the Kaiser Family Foundation website.



Effect of the Affordable Care Act on Racial and
Ethnic Disparities in Health Insurance Coverage
Thomas C. Buchmueller, PhD, Zachary M. Levinson, MPP, Helen G. Levy, PhD, and Barbara L. Wolfe, PhD
Objectives. To document how health insurance coverage changed for White, Black, and
Hispanic adults after the Affordable Care Act (ACA) went into effect.
Methods. We used data from the American Community Survey from 2008 to 2014 to
examine changes in the percentage of nonelderly adults who were uninsured, covered by
Medicaid, or covered by private health insurance. In addition to presenting overall trends
by race/ethnicity, we stratified the analysis by income group and state Medicaid expansion status.
Results. In 2013, 40.5% of Hispanics and 25.8% of Blacks were uninsured, compared with 14.8% of Whites. We found a larger gap in private insurance, which was
partially offset by higher rates of public coverage among Blacks and Hispanics. After
the main ACA provisions went into effect in 2014, coverage disparities declined
slightly as the percentage of adults who were uninsured decreased by 7.1 percentage points for Hispanics, 5.1 percentage points for Blacks, and 3 percentage
points for Whites. Coverage gains were greater in states that expanded Medicaid
Conclusions. The ACA has reduced racial/ethnic disparities in coverage, although
substantial disparities remain. Further increases in coverage will require Medicaid expansion by more states and improved program take-up in states that have already done
so. (Am J Public Health. 2016;106:1416–1421. doi:10.2105/AJPH.2016.303155)
See also Galea and Vaughan, p. 1354.
arge disparities in health insurance
coverage related to race and ethnicity
are a long-standing feature of the US health
care system and a cause for concern among
policymakers and health care professionals.
Several studies have identified these differences in insurance coverage as an important determinant of disparities in access to
care.1–5 In addition, a growing literature shows
that by reducing exposure to large medical
expenses, health insurance leads to better financial outcomes, such as improved credit
scores and a reduced risk of bankruptcy.6–9
Thus, policies that reduce disparities in health
insurance coverage are likely to have a broader
effect on economic inequality.
The Affordable Care Act (ACA) has
made new health insurance options available
to uninsured individuals in low- and
middle-income households, a group in which
Blacks and Hispanics are overrepresented.
A recent study by McMorrow et al.10 that used
Peer Reviewed
Buchmueller et al.
data from the National Health Interview
Survey found that although the uninsured rate
declined overall between 2013 and 2014, it
decreased by a larger amount among Black and
Hispanic adults than among White adults
(8 percentage points vs 4 percentage points).
The uninsured rate for Black and Hispanic adults
decreased significantly in states that embraced
the ACA’s Medicaid expansion and also in those
that did not. For White adults, the percentage
uninsured declined in both sets of states, although the estimated change was not statistically
significant in nonexpansion states.
In this study, we used data from the
American Community Survey (ACS) spanning the years 2008 to 2014 to provide additional evidence on how health insurance
coverage changed for Black and Hispanic
adults compared with White adults in the first
year after the implementation of health care
reform. We extended existing analyses in
several ways. First, in addition to documenting changes in the rate of uninsurance,
we investigated changes in the source of
coverage. This more detailed analysis indicated that the significant disparities in the
percentage of adults with any insurance prior
to 2014 were driven by even larger disparities
in private coverage, which were partially
offset by the fact that minority adults were
more likely than Whites to have public insurance. We found that both types of coverage increased more for Blacks and Hispanics
than for Whites between 2013 and 2014.
As a result, disparities in both overall coverage
and private insurance coverage declined.
Second, we considered important sources
of heterogeneity within the different racial
and ethnic groups. In particular, it is important to account for the fact that approximately
one third of all Hispanic adults living in the
United States are not citizens. Immigrants
who are not citizens have substantially lower
rates of health insurance coverage because
they are less likely to work in jobs that provide
employer-sponsored insurance,11 they face
restrictions on Medicaid eligibility,12 and they
may be less likely to take up coverage when
eligible. Because undocumented immigrants
are excluded from the ACA’s major coverage
Thomas C. Buchmueller is with Ross School of Business, University of Michigan, Ann Arbor. Zachary M. Levinson is with
the Departments of Economics and Health Management and Policy, University of Michigan. Helen G. Levy is with the
Institute for Social Research, University of Michigan. Barbara L. Wolfe is with the Department of Economics and Lafollette
School of Public Policy, University of Wisconsin, Madison.
Correspondence should be sent to Thomas C. Buchmueller, PhD, Ross School of Business, University of Michigan,
701 Tappan St, Ann Arbor, MI 48109 (e-mail: tbuch@umich.edu). Reprints can be ordered at http://www.ajph.org by clicking
the “Reprints” link.
This article was accepted February 19, 2016.
doi: 10.2105/AJPH.2016.303155
August 2016, Vol 106, No. 8
expansions,12 one concern is that this group
will become even more marginalized in the
post-ACA health care system.13
Third, in addition to documenting
changes in coverage rates, we investigated the
extent to which the disparities in coverage
that remained in 2014 were related to income
and to state decisions regarding the ACA’s
Medicaid expansion.
The ACA includes provisions to expand
both Medicaid and private coverage, with the
goal of reaching many of the 50 million individuals who were uninsured in 2010 when
the law was enacted. Prior to the ACA, states
covered low-income children and their
families through Medicaid and the Children’s
Health Insurance Program. However, states
typically did not provide coverage for nonelderly childless adults. In addition, some
low-income parents remained uninsured
because income eligibility levels for parents
were typically significantly lower than those
for children.14
The ACA created substantial new federal
funding for states to extend coverage to all
adults with family income below 138% of the
federal poverty level (FPL) (or about $33 000
for a family of 4 in 2014). Although the ACA
originally required states to extend their
Medicaid programs to this population, a June
2012 Supreme Court ruling essentially made
the expansion optional.15,16 As of January
2016, 31 states plus the District of Columbia
had decided to implement the Medicaid
expansion.17 In most of these states, the new
eligibility rules went into effect in January
The ACA also included some provisions
intended to make private health insurance
more accessible. One of the earliest to take
effect required health plans providing dependent coverage for children to extend that
offer up to age 26 years. This requirement,
which went into effect in September 2010,
led to a significant increase in insurance
coverage among the target population of
those aged 19 to 25 years.18–22 Estimates of
the number of young adults who gained
coverage range from about 1 million18,22 to
3 million.21
August 2016, Vol 106, No. 8
The law also introduced a set of insurance
market reforms, such as prohibiting plans from
denying coverage or charging higher premiums because of an applicant’s preexisting
health condition. It established an essential
benefits package and new health insurance
“marketplaces,” which are intended to facilitate individuals’ plan choices by standardizing
benefit options and providing a Web site
where enrollees can easily compare plans.
Importantly, the law provides premium tax
credits for families with incomes between
100% and 400% of the FPL to purchase
coverage through the marketplaces, provided
that they do not already have access to comprehensive coverage through an employer or
a public program. Families with incomes below 250% of the FPL who are eligible for
premium tax credits are also eligible for additional subsidies to cover cost sharing at the
point of service. Finally, the ACA incentivizes
health insurance enrollment by establishing
penalties for individuals who forgo coverage,
as well as for large employers that do not offer
affordable coverage to their employees.
Important exceptions apply to noncitizens. Undocumented immigrants are excluded from the ACA’s major coverage
expansions.12,23 For example, they are barred
from purchasing coverage on the exchanges
(even unsubsidized coverage).12 By contrast,
lawfully present noncitizens are generally
permitted to purchase coverage on the exchanges, are eligible for premium tax credits
and cost-sharing subsidies based on family
income, and are subject to the individual
mandate.12,23 On the basis of rules that preceded the ACA, some groups of lawfully
present noncitizens are ineligible for full
Medicaid coverage, including most legal
permanent residents who have resided in the
United States for less than 5 years. Perhaps for
this reason, lawfully present noncitizens with
incomes below the poverty level who are
ineligible for Medicaid may instead be eligible
for marketplace premium tax credits and
cost-sharing subsidies (a benefit unavailable to
other groups below the poverty level).12,24
Our analysis was based on repeated
cross-sectional data from the ACS spanning
the years 2008 through 2014. Although the
ACS has been less widely used to study health
insurance coverage than another US Census
Bureau data set, the Annual Social and
Economic Supplement to the Current Population Survey (CPS), a significant redesign of
the CPS in 2014 presents challenges for using
that survey to analyze changes over time.25
Before the CPS redesign, the 2 surveys
produced slightly different estimates of insurance coverage because of differences in
question design. However, because these
differences were constant over time, estimates
of trends in insurance coverage were comparable.26 Another advantage of the ACS is
that it is much larger than other surveys,
making it possible to obtain precise estimates,
even for narrowly defined subpopulations.27
For our analysis, we had samples of nearly
1.7 million observations per year.
The ACS asks about current health insurance coverage and provides a list of possible
sources: through an employer or union, directly from an insurance company, Medicare,
Medicaid, TRICARE, Department of
Veterans Affairs, Indian Health Service, or
other. Respondents may choose all that apply,
and those who state that they do not have
coverage through any of those sources are
coded as being uninsured.
In our analysis, we examined changes in
the percentage of individuals who were uninsured as well as the percentage with private
and public coverage. For nonelderly adults,
Medicaid was the dominant source of public
insurance, but this category also includes
Medicare (covering disabled adults) and the
Department of Veterans Affairs. About 4% of
the adult respondents reported having both
public and private coverage during the year.
When we examined coverage by source,
we categorized these individuals as having
public insurance and limited the private
insurance category to individuals who
reported having only private coverage.
Because the coverage provisions of the
ACA taking effect in 2014 were targeted
mainly at nonelderly adults, we restricted our
sample to individuals between ages 19 and
64 years. We also focused on non-Hispanic
Whites, non-Hispanic Blacks, and Hispanics
Buchmueller et al.
Peer Reviewed
(who may be any race), in line with much of
the literature on health disparities. For simplicity, we refer to these 3 groups as Whites,
Blacks, and Hispanics. In some analyses, we
further divided the Hispanic group into those
who were US citizens and those who were
not. Although, as noted earlier, some ACA
eligibility rules distinguish between undocumented immigrants and those who are
lawfully present in the United States, legal
status is not recorded in the ACS.
It is important to note that the observed
magnitude of differences between groups
depends on the extent to which the analysis
controls for observable characteristics. Many
individual attributes that differ systematically
across racial and ethnic groups—such as income and education levels—likely affect
health outcomes, and there is an active debate
about which attributes should be held constant
when measuring disparities. Three common
approaches for evaluating health disparities
involve comparing (1) unadjusted differences
in means, (2) differences in means after controlling for health needs and preferences (the
definition adopted in the 2003 Institute of
Medicine report Unequal Treatment),28 and (3)
differences in means after controlling for as
many variables as possible (e.g., socioeconomic status).29 Because our primary objective was to document population-level
changes in insurance coverage, much of our
analysis relied on the first approach, but we
also stratified results by income group and state
Medicaid expansion status.
Figure 1 presents trends from 2008
through 2014 in the percentage of White,
Black, and Hispanic adults who were uninsured. For each group, the percentage of
adults who were uninsured increased between 2008 and 2010 before declining
slightly between 2010 and 2013. Over that
period, the average coverage gap between
Blacks and Whites was about 11 percentage
points, and the average gap between Hispanics and Whites was more than twice as
large (27 percentage points).
In 2014, the percentage without coverage
dropped significantly for all 3 groups but
more for minorities than for Whites. The
percentage uninsured fell by 7.1 percentage
points for Hispanics (a 17% decline relative
to 2013), by 5.1 percentage points for Blacks
(a 20% decline), and by 3 percentage points
for Whites (a 21% decline). As a result of these
differential changes, the White–Black coverage gap decreased by 2 percentage points,
from 11 to 9 percentage points, and the
White–Hispanic gap decreased by 4.3 percentage points, from 26.5 to 22.2 percentage
points. This result is in line with the study
by McMorrow et al.,10 which also found
a reduction in the White–Black and
White–Hispanic coverage gaps.
Figure 2 shows that racial and ethnic differences in the percentage of adults with any
insurance represent the combined effect of
very large disparities in private insurance that
are partially offset by the far greater public
FIGURE 1—Percentage of US Nonelderly Adults (Aged 19–64) Uninsured, by Race and
Ethnicity: American Community Survey, United States, 2008–2014
Peer Reviewed
Buchmueller et al.
coverage of minorities, especially Black
adults. For all groups, private coverage declined between 2008 and 2013, before increasing between 2013 and 2014 (Figure 2a).
Both the percentage point increase and the
percent gain (relative to the 2013 level) were
greater for minorities than for Whites. Private
coverage increased by 4.3 percentage points
for Hispanics (an 9.8% increase relative to
the 2013 rate of 43.9%), by 3 percentage
points for Blacks (a 6% increase), and by
1.5 percentage points for Whites (a 2.1%
increase). Thus, the gaps in both any coverage
and private insurance declined. However,
even with these gains, the percentage of
Whites and Blacks with private insurance was
lower in 2014 than in 2008.
In contrast to the case of private insurance,
the percentage of adults enrolled in public
insurance programs increased steadily between 2008 and 2013. Public coverage increased even more between 2013 and 2014:
by 2.8 percentage points for Hispanics,
1.9 percentage points for Blacks, and
1.5 percentage points for Whites.
Table 1 provides more detailed information on how insurance coverage
changed between 2013 and 2014. Here, we
distinguish between Hispanics who are and
are not US citizens. The results show large
differences between these 2 groups. Just prior
to the ACA insurance expansions, more than
60% of Hispanic noncitizens were uninsured,
compared with 28% of Hispanic citizens. The
latter figure is just slightly higher than the
uninsured rate for Blacks. The percentage
point change between 2013 and 2014 was
similar for Hispanic noncitizens and citizens
(7.0 and 6.7 percentage points, respectively),
although the percent increase was much
larger for citizens (23.9% vs 10.9%) because
their baseline rate was much lower. In adults
with family income below 138% of the FPL,
the uninsured rate declined more for Hispanic
citizens than for Hispanic noncitizens (9.3 vs
6.1 percentage points).
Dividing the data by state Medicaid expansion status, we found that the percent
uninsured was lower in expansion states in
2013 and declined more in those states than
in nonexpansion states. The percentage of
Blacks without health insurance decreased by
5.6 percentage points in expansion states and
by 4 percentage points in nonexpansion states.
For Hispanics, the uninsured rate decreased
August 2016, Vol 106, No. 8
FIGURE 2—Percentage of US Nonelderly Adults (Aged 19–64 Years) by Race and Ethnicity
With (a) Private and (b) Public Health Insurance Coverage: American Community Survey,
United States, 2008–2014
by more than 7 percentage points in expansion states and by 5.1 to 5.4 percentage points
in nonexpansion states.
The data suggest that both before and after
the ACA coverage expansions went into effect, differences in income explain much—
but not all—of the coverage gap between
Blacks and Whites. For example, in 2014, the
gap was only 3.2 percentage points among
adults in the lowest income category, compared with a gap of 9 points among all adults.
Income also appears to explain a sizable, although smaller, portion of the coverage gap
between Whites and Hispanic citizens. By
August 2016, Vol 106, No. 8
contrast, even within income categories, the
coverage gap between Whites and Hispanic
noncitizens was extremely large. In the lowest
income category, the gap was more than
40 percentage points in both nonexpansion
and expansion states. Regarding the different
types of coverage, Hispanic noncitizens were
approximately half as likely to have public
insurance as Whites in this income category
(21% nationally vs 40%; data not shown). This
suggests that the eligibility restrictions facing
many Hispanic immigrants, along with language barriers and a reluctance to use benefits
for which they qualify, have a substantial
negative effect on coverage for this group.
Other differences in individual characteristics likely contributed to coverage disparities but in different ways for Blacks and
Hispanics. One factor that is of particular
policy significance was the share of each
group living in an expansion state. In our
sample, the percentage of Blacks living in
expansion states was lower than the percentage of Whites—54% versus 69%—
whereas both groups of Hispanics were more
likely than Whites to live in an expansion state
(73% for citizens and 71% for noncitizens).
However, simple simulation analyses suggested that if coverage changes in nonexpansion states had been comparable to
those observed in expansion states, then the
national uninsured rate for Blacks would have
been only slightly lower than what we actually observed. For example, if we assumed
an equal percentage point change, then
22.3% of the Blacks in nonexpansion states
would have been uninsured in 2014, and the
national rate would have been 20.0% rather
than 20.7%. Alternatively, if we assumed
an equal percent decline, then the national
uninsured rate for Blacks would have been
19.5%, and the coverage gap relative to
Whites would have been 8.4 rather than
9 percentage points.
The fact that racial and ethnic disparities
remain among low-income adults in expansion states implies that further increases in
coverage will require not only the adoption
of Medicaid expansion by more states but
also an improvement in program take-up in
states that have already done so. Evidence
from a previous expansion for children
suggests that linguistically and culturally
targeted outreach strategies can be effective
in increasing program take-up among eligible
At the same time, other approaches will be
necessary to improve access to care for the
large portion of poor noncitizens who remain
ineligible for Medicaid and exchange-based
subsidies. One such approach would be the
expansion of benefits to undocumented individuals using state funds. California recently became the fifth and largest state to
provide health coverage to undocumented
children, and legislators in the state have
considered extending Medicaid coverage to
undocumented adults as well.32,33 Given
estimates that about half of California’s
2.7 million undocumented immigrants have
incomes below 138% of the FPL,34 such
a policy could significantly increase coverage
among this very disadvantaged population.
Buchmueller et al.
Peer Reviewed
TABLE 1—Changes in the US Uninsured Rate by Race/Ethnicity, Income Category, and State Medicaid Expansion Status:
American Community Survey, United States, 2013–2014
All States
All nonelderly adults
Change, Percentage Points
2013, %
2014, %
Change, Percentage Points
2013, %
2014, %
Change, Percentage Points
Hispanic, noncitizen
Expansion States
2014, %
Hispanic, citizen
Nonexpansion States
2013, %
< 139% of FPL White Black 35.6 Hispanic, citizen Hispanic, noncitizen 28.9 a,b –6.7 a,b 40.4 –5.5 40.5 72.7 31.2 66.6 –9.3 –6.1a,b 53.3 81.5 45.8 78.2 –7.5 –3.3a 35.7 68.4 25.6 60.9 –10.1a,b –7.5a,b 18.0 14.5 –3.5a 18.7 16.1 –2.6a 139%–399% of FPL White Black 23.7 Hispanic, citizen 29.5 Hispanic, noncitizen 18.5 21.9 a,b –5.2 a,b –7.6 a,b 24.1 33.4 20.2 27.8 17.7 13.6 –4.1a a,b 23.3 17.0 –6.3a,b a,b 28.0 19.7 –8.3a,b a,b –3.9 –5.6 60.9 53.4 –7.5 68.1 61.5 –6.6 57.7 49.8 –7.9a,b 5.2 4.2 –1.0a 5.6 4.7 –0.9a ‡ 400% of FPL White a,b 5.0 3.9 –1.1a a,b Black Hispanic, citizen 10.2 11.0 7.8 9.0 –2.4 –2.0a,b 10.5 12.8 8.3 11.3 –2.2 –1.5a 10.0 10.3 7.4 8.1 –2.6a,b –2.2a,b Hispanic, noncitizen 38.3 32.3 –6.0a,b 43.2 38.0 –5.2a,b 36.4 30.1 –6.3a,b Note. FPL = federal poverty level. Expansion states are defined as all states that had implemented the Affordable Care Act Medicaid expansion by July 2014. a The change between 2013 and 2014 was significantly different from 0 at the .05 level. b The change between 2013 and 2014 was significantly different from the corresponding change for Whites at the .05 level. We have provided a snapshot of how insurance coverage changed in the first year after the main provisions of the ACA were in place. Consistent with evidence from other data sources, our analysis of the ACS indicates that the reform has not only increased the overall rate of insurance coverage in the United States but also led to a slight reduction in coverage disparities related to race and ethnicity. Hispanics, who have the lowest rate of insurance coverage among all racial/ethnic groups, experienced greater increases in private and public coverage than did Blacks, who experienced greater gains than did Whites. For all 3 groups, coverage increased more in states that implemented the Medicaid expansion than in states that did not. However, even with the gains in coverage brought about by the ACA, more than 30 million Americans remain uninsured.35 Racial and ethnic minorities continue to make up a disproportionate share of both the overall uninsured population and the uninsured with incomes below the Medicaid eligibility threshold. 1420 Research Peer Reviewed Buchmueller et al. CONTRIBUTORS All authors contributed to the analysis and the writing of the article. ACKNOWLEDGMENTS This work has been supported in part by the Russell Sage Foundation (award 83-14-13). H. G. Levy also acknowledges financial support from the National Institute on Aging (grant NIA K01AG034232). Note. Any opinions expressed are those of the authors alone and should not be construed as representing the opinions of the Russell Sage Foundation. 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Available at: http://www.latimes.com/ local/political/la-me-pc-california-immigranthealthcare-20151009-story.html. Accessed January 22, 2016. 34. McConville S, Hill L, Ugo I, Hayes J. Health coverage and care for undocumented immigrants. November 2015. Available at: http://ppic.org/main/publication_quick. asp?i=1167. Accessed January 22, 2016. 35. Smith JC, Medalia C, US Census Bureau. Health Insurance Coverage in the United States: 2014. Washington, DC: US Government Printing Office; 2015. Current Population Reports, P60-253. Available at: http://www. census.gov/content/dam/Census/library/publications/ 2015/demo/p60-253.pdf. Accessed November 16, 2015. 20. O’Hara B, Brault MW. The disparate impact of the ACA-dependent expansion across population subgroups. Health Serv Res. 2013;48(5):1581–1592. 21. Sommers BD. Number of young adults gaining insurance due to the Affordable Care Act now tops 3 million. June 19, 2012. Available at: http://aspe.hhs.gov/ basic-report/number-young-adults-gaining-insurancedue-affordable-care-act-now-tops-3-million. Accessed October 24, 2015. 22. Sommers BD, Buchmueller T, Decker SL, Carey C, Kronick R. The Affordable Care Act has led to significant gains in health insurance and access to care for young adults. Health Aff (Millwood). 2013;32(1):165–174. 23. Fried B, Pintor JK, Graven P, Blewett LA. Implementing federal health reform in the states: who is included and excluded and what are their characteristics? Health Serv Res. 2014;49(suppl 2):2062–2085. 24. HealthCare.gov. Coverage for lawfully present immigrants. 2015. Available at: http://www.healthcare. gov/immigrants/lawfully-present-immigrants. Accessed November 16, 2015. 25. Pascale J, Boudreaux M, King R. Understanding the new Current Population Survey health insurance questions. Health Serv Res. 2016;51(1):240–261. 26. O’Hara B, Medalia C. CPS and ACS health insurance estimates: consistent trends from 2009-2012. September 15, 2014. Available at: http://www.census.gov/hhes/ www/hlthins/data/incpovhlth/2013/CPS_ACS_ Trends.pdf. Accessed October 24, 2015. 27. Davern M, Quinn BC, Kenney GM, Blewett LA. The American Community Survey and health insurance coverage estimates: possibilities and challenges for health August 2016, Vol 106, No. 8 AJPH Buchmueller et al. Peer Reviewed Research 1421 Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. Southern Economic Journal 2018, 84(3), 660–691 DOI: 10.1002/soej.12245 Early Effects of the Affordable Care Act on Health Care Access, Risky Health Behaviors, and Self-Assessed Health Charles Courtemanche,* James Marton,† Benjamin Ukert,‡ Aaron Yelowitz,§ and Daniela Zapata¶ The goal of the Affordable Care Act (ACA) was to achieve nearly universal health insurance coverage through a combination of mandates, subsidies, marketplaces, and Medicaid expansions, most of which took effect in 2014. We use data from the Behavioral Risk Factor Surveillance System to examine the impacts of the ACA on health care access, risky health behaviors, and self-assessed health after two years. We estimate difference-in-difference-indifferences models that exploit variation in treatment intensity from state participation in the Medicaid expansion and pre-ACA uninsured rates. Results suggest that the ACA led to sizeable improvements in access to health care in both Medicaid expansion and nonexpansion states, with the gains being larger in expansion states along some dimensions. However, we do not find clear effects on risky behaviors or self-assessed health. JEL Classification: I12, I13, I18 1. Introduction The goal of the Patient Protection and Affordable Care Act (ACA) was to achieve nearly universal health insurance coverage in the United States through a combination of policies largely implemented in 2014 (Obama 2016). Several recent studies, including Frean, Gruber, and Sommers (2017) and Courtemanche et al. (2017), have shown that the ACA led to gains in insurance coverage. The objective of this article is to evaluate whether or not such coverage increases translated to changes in access to care, risky health behaviors, and, ultimately, short-run health outcomes. A number of 2014 ACA provisions involved overhauling nongroup insurance markets in an effort to ensure that one s health history did not provide a barrier to obtaining coverage. Specific regulations included guaranteed issue laws, which forbid insurers from denying coverage on the basis of an applicant s health status, and modified community rating, which imposes uniform * Department of Economics, Andrew Young School of Policy Studies, P.O. Box 3992, Georgia State University, Atlanta, GA 30302-3992, USA; E-mail: ccourtemanche@gsu.edu; corresponding author. † Department of Economics, Andrew Young School of Policy Studies, P.O. Box 3992, Georgia State University, Atlanta, GA 30302-3992, USA; E-mail: marton@gsu.edu. ‡ The Wharton School and Leonard Davis Institute of Health Economics, Colonial Penn Center, University of Pennsylvania, 3641 Locust Walk, Philadelphia, PA 19104-6218, USA; E-mail: bukert@wharton.upenn.edu. § Department of Economics, Gatton School of Business and Economics, University of Kentucky, Lexington, KY 40506-0034, USA; E-mail: aaron@uky.edu. ¶ Impaq International, 1101 Vermont Avenue, 11th Floor, Washington DC 20005, USA. Received May 2017; accepted September 2017. 660 Ó 2017 by the Southern Economic Association Early Effects of the Affordable Care Act 661 premiums regardless of observable applicant characteristics aside from age and smoking status. In addition, the federal government established a health insurance marketplace to facilitate insurance purchases for individuals and small businesses. Each state was given the option of establishing its own insurance marketplace, and 15 did so in 2014 (KFF 2014). These reforms alone would likely lead to an adverse selection death spiral, with the influx of high-cost beneficiaries causing relatively low-cost beneficiaries to drop their coverage, thus driving up premiums for those remaining in the insurance pool (Courtemanche and Zapata 2014). This concern motivated another component of the ACA: the individual mandate. Beginning in 2014, individuals deemed to be able to afford coverage but electing to remain uncovered were penalized. The largest penalty that could be imposed was the maximum of either the total annual premium for the national average price of a bronze exchange plan, or $285 ($975) in 2014 (2015).1 In addition, an employer mandate, which required employers with 100 or more full-time equivalent employees to offer “affordable” coverage to at least 95% of their full-time employees and their dependents (children up to age 26) or face a penalty, took effect in 2015 (Tolbert 2015). The remaining challenge associated with promoting universal coverage—affordability—was addressed by the ACA in 2014 in two ways. First, sliding scale subsidies in the form of premium tax credits (PTCs) became available to consumers in every state with incomes of 100 to 400% of the federal poverty level (FPL) who did not qualify for other affordable coverage. Second, in states that opted to expand Medicaid via the ACA, low-income adults (with incomes at or below 138% of the FPL) who were not elderly, disabled, or parents of a dependent child became eligible for Medicaid coverage. Previously, Medicaid eligibility was typically restricted to those with low incomes among specific groups (categories of eligibility), such as children, single parents, pregnant women, the disabled, and the elderly.2 According to the Kaiser Family Foundation, 27 states participated in the Medicaid expansion in 2014, with three more implementing it in 2015 and another two in 2016.3 Theoretically, the expansion of insurance coverage brought about by the ACA should increase access to care because of the reduction in out-of-pocket costs, but this is not automatically the case. On the demand side, newly insured individuals may not have sufficient knowledge of the health care system to easily secure a regular primary care doctor. Somers and Mahadevan (2010) report that only 12% of adults have proficient health literacy. On the supply side, concerns have been raised about whether there are sufficient numbers of primary care physicians to treat all of these newly insured patients (Schwartz 2012; Glied and Ma 2015). While the federal government 1 2 3 The maximum increased to $2085 in 2016. For more information, see https://www.healthcare.gov/fees/fee-for-notbeing-covered/. Prior to the ACA, Medicaid income limits varied by category of eligibility, with the federal government setting income limit floors and/or ceilings across categories (Buchmueller, Ham, and Shore-Sheppard 2016). In many categories of eligibility, many states opted for income limits above 138% of the FPL, such as the income limit associated with infants and pregnant women. For example, the Omnibus Budget Reconciliation Act of 1987 allowed states to cover pregnant women and children in families with incomes at or below 185% of the FPL. For those in expansion states that were not categorically eligible for Medicaid or were in categories of eligibility with income limits at or below 138% of the FPL prior to the ACA, the Medicaid expansion increased their eligibility. For those in categories of eligibility with income limits above 138% of the FPL, their income limits generally remained unchanged, other than adjustments associated with the ACA s uniform implementation of modified adjusted gross income. The 2012 Supreme Court ruling on the ACA upheld the individual mandate (the primary mechanism to address selection issues) but made the Medicaid expansion optional for states. For further information on state decisions with respect to the Medicaid expansion, see KFF, Status of State Action on the Medicaid Expansion Decision, http://kff. org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/. 662 Courtemanche et al. increased Medicaid primary care reimbursement rates to Medicare levels in 2013 and 2014, only a few states fully maintained this “fee bump” in 2015.4 Insurance coverage expansions could influence risky health behaviors—such as smoking, drinking, and overeating—in either direction (Cawley and Ruhm 2012). On the one hand, improved access to care among the affected population could translate to improvements in health behaviors via information, accountability, or treatments such as smoking cessation drugs or weight loss programs. Conversely, insurance expansions can theoretically worsen health outcomes through ex ante moral hazard, as the reduction in financial risks associated with unhealthy behaviors incentivizes such behaviors. Moreover, income effects from gaining free or subsidized coverage could influence behaviors by enabling consumers to spend money they had budgeted for the direct purchase of health care on alcohol, cigarettes, and junk food or, conversely, on healthy food and gym memberships (Simon, Soni, and Cawley 2017). The net effect of insurance expansions on population health depends on the changes in both access to care and health behaviors and, therefore, is also theoretically ambiguous. The extent to which increased health care utilization translates to better population health depends on the distribution of affected individuals initial locations along the health production function. Evidence suggests that “flat of the curve” care—perhaps due to uncertainty over treatment effectiveness, the principal-agent nature of the patient-doctor relationship, fee-for-service reimbursement, lack of coordination across health care providers, or malpractice liability—is common in the United States (Garber and Skinner 2008). Moreover, the same issues with health literacy that could hamper efforts by the newly insured to find a primary care doctor could also limit their ability to understand and comply with treatment recommendations.5 The purpose of this article is to estimate the impact of the ACA s 2014 provisions on a variety of outcomes related to health care access, risky health behaviors, and self-assessed health. We separately identify the effects of the private and Medicaid expansion portions of the ACA by using an identification strategy developed in Courtemanche et al. (2017) to estimate the impact of the ACA on insurance coverage by exploiting differences across local areas in pretreatment uninsured rates. To be more specific, we estimate a difference-in-difference-in-differences (DDD) model with the differences coming from time, state Medicaid expansion status, and local area pretreatment uninsured rate. If our objective was merely to isolate the effect of the Medicaid expansion, this could potentially be achieved with a simpler difference-in-differences model comparing changes in states that expanded Medicaid to changes in nonexpansion states. However, identifying the impact of the other components of the ACA (e.g., mandates, subsidies, marketplaces) is more difficult due to their national nature. We therefore exploit an additional layer of plausibly exogenous variation arising from the fact that universal coverage initiatives provide the most intense treatments in areas with high uninsured rates.6 4 5 6 Medicaid reimbursement rates are typically lower that those associated with private insurance plans or Medicare (Buchmueller, Ham, and Shore-Sheppard 2016). The purpose of the fee bump was to encourage more primary care providers to start seeing Medicaid patients, but the temporary nature of the fee bump may have reduced its effectiveness relative to a permanent fee increase. For more on state plans with respect to Medicaid primary care reimbursement, see Snyder, Paradise, and Rudowitz (2014) and Advisory Board (2015). Previous literature has shown a relationship between health literacy and health outcomes including health status, chronic illness, and hospitalization (Cho et al. 2008; Berkman et al. 2011). Finkelstein (2007) uses a similar strategy to identify the impacts of another national program, Medicare, on health care spending. Miller (2012a) also uses this approach to estimate the impact of the Massachusetts reform on emergency room utilization without control states. Early Effects of the Affordable Care Act 663 Our data come from the 2011 to 2015 waves of the Behavioral Risk Factor Surveillance System (BRFSS), with the sample restricted to nonelderly adults. The BRFSS is well suited for our study for three reasons. First, it includes a wide range of questions on health care access and selfassessed health. Second, with over 300,000 observations per year, it is large enough to precisely estimate the effects of state-level interventions. Third, it was among the first large-scale health data sets to release data from 2015, allowing us to examine two calendar years of data after the full implementation of the ACA. Our results suggest that the ACA substantially improved access to health care among nonelderly adults. Gains in insurance coverage were 8.3 percentage points in Medicaid expansion states compared to 5.3 percentage points in nonexpansion states, while reductions in cost being a barrier to care were 5.1 percentage points in expansion states and 2.6 percentage points in nonexpansion states. The ACA also increased the probabilities of having a primary care doctor and a checkup by 3.0 and 2.4 percentage points, respectively, in non-Medicaid-expansion states, with the effects not being statistically different in expansion states. Gains in access were generally largest among individuals with lower incomes. However, the effects of the ACA on risky health behaviors and self-assessed health were less pronounced—at least after two years. For the full sample, we find no statistically significant impacts on any of the risky behavior or health outcomes in either Medicaid expansion or nonexpansion states. This general pattern of null results persists even among the lower-income subsample, though we do observe a marginally significant improvement in mental health in Medicaid expansion states for that group. 2. Literature Review In this section, we review the literature on the impacts of expansions of insurance coverage. We divide the literature into studies focusing on coverage expansions prior to 2014 and those that examine the components of the ACA implemented in 2014. Effects of Pre-2014 Insurance Interventions There is an extensive literature spanning several decades examining the impacts of the receipt of both public and private health insurance on a variety of outcomes related to access to care, utilization, spending, risky health behaviors, and health. Additional outcomes considered in this literature include labor market participation, job lock, and other public program participation. Cutler and Zeckhauser (2000) provide a thorough review of the health insurance literature, while Buchmueller, Ham, and Shore-Sheppard (2016) review the literature on Medicaid and Gruber (2000) reviews the literature on health insurance and the labor market. Here, we provide a brief summary of the evidence on the effects of insurance-related interventions on outcomes related to access, risky behaviors, and health. Causally interpretable evidence on the impacts of health insurance coverage dates back to the RAND Health Insurance Experiment of the 1970s–1980s, which randomly assigned individuals to insurance plans with different coinsurance rates and deductibles. Those assigned to a plan with no cost sharing incurred about 20% higher medical expenses than others (Manning et al. 1987). However, on average, this additional utilization did not translate to statistically significant effects on self-assessed health, smoking, or weight (Brook et al. 1983). 664 Courtemanche et al. A substantial portion of the literature focuses on expansions of the Medicaid program. Evidence suggests that expansions for children and pregnant women in the 1980s and 1990s reduced low birthweight (Currie and Gruber 1996a), infant mortality (Currie and Gruber 1996b), and avoidable hospitalizations among children (Dafny and Gruber 2005). However, other studies suggest that these expansions increased smoking among pregnant women (Dave, Kaestner, and Wehby 2015) and had inconsistent effects on their health care utilization (Epstein and Newhouse 1998). Research has also found that Medicaid expansions for childless adults in the early 2000s increased self-reported access to care and health while reducing mortality, particularly related to HIV (Sommers, Baicker, and Epstein 2012; Sommers 2017). Studies of the randomized 2008 Oregon Medicaid lottery found that Medicaid increased health care access and utilization along a broad range of dimensions and led to large, immediate gains in self-assessed health (Finkelstein et al. 2012; Taubman et al. 2014). However, no evidence was found of changes in smoking, obesity, or clinical indicators of physical health (Finkelstein et al. 2012; Baicker et al. 2013). Tello-Trillo (2016) shows that a large Medicaid disenrollment in Tennessee reduced access to care and selfassessed health. Another branch of the literature studies the impacts of Medicare, the universal coverage program for U.S. seniors. Evidence shows that health care utilization increases sharply at the age of eligibility (Lichtenberg 2002; Card, Dobkin, and Maestas 2008), while mortality among patients admitted to the ER falls sharply (Card, Dobkin, and Maestas 2009). However, other studies suggest that Medicare does not impact mortality more generally (Finkelstein and McKnight 2008) and slightly worsens smoking and drinking habits (Dave and Kaestner 2009). Several studies have focused on the 2006 Massachusetts health care reform, a universal coverage initiative that featured a combination of insurance market reforms, mandates, and subsidies similar to the ACA. Kolstad and Kowalski (2012), Miller (2012a,b), and Van der Wees, Zaslavsky, and Ayanian (2013) all present evidence consistent with the reform improving access to primary care. Van der Wees, Zaslavsky, and Ayanian (2013) and Courtemanche and Zapata (2014) find that the reform also improved adults self-assessed health, though an earlier study by Yelowitz and Cannon (2010) did not observe a statistically significant result. Courtemanche and Zapata (2014) also estimate that the reform reduced body mass index (BMI). Sommers, Kenney, and Epstein (2014) present evidence that the reform reduced mortality rates, though Kaestner (2015) disputes this finding. Another series of articles investigates the effects of the first major insurance expansion to occur under the ACA: A mandate for insurers to cover dependents up to 26 years old that took effect in 2010. Evidence suggests that this dependent coverage expansion increased access to care (Sommers et al. 2013; Barbaresco, Courtemanche, and Qi 2015) and general health care utilization (Chua and Sommers 2014; Akosa Antwi, Moriya, and Simon 2015) but not utilization of preventive services (Barbaresco, Courtemanche, and Qi 2015). Chua and Sommers (2014), Barbaresco, Courtemanche, and Qi (2015), and Burns and Wolfe (2016) present evidence that the dependent coverage provision improved self-assessed health along some dimensions. Finally, Barbaresco, Courtemanche, and Qi (2015) document a reduction in BMI. Kelly and Markowitz (2009) take a different approach to examining the causal effect of health insurance on BMI. Rather than investigating a particular policy change, they use Lewbel s estimator for instrumental variables without exclusion restrictions. They find that insurance increases BMI but not the probability of being obese. To summarize, the available causally interpretable evidence suggests that health insurance can impact access to care, risky behaviors, and health outcomes but that the effects often vary Early Effects of the Affordable Care Act 665 substantially across contexts. For instance, the effects of insurance on self-assessed health appear to have been large and immediate in the cases of the Oregon Medicaid expansion and Massachusetts reform but more modest after the ACA dependent coverage expansion and virtually nonexistent in the RAND experiment. As another example, only the Massachusetts reform and the dependent coverage provision appear to have led to weight loss. These examples underscore the necessity of obtaining credible evidence on the effects of the 2014 components of the ACA rather than simply relying on results from other settings. In particular, even evidence from the prior interventions that have the most in common with the ACA—Medicaid and the Massachusetts reform—may not be reliable indicators. In contrast to the narrower population targeted by Medicaid expansions, the ACA expanded coverage to a much broader range of low- and middle-income families and childless adults, with only part of the expansion occurring via Medicaid. Marketplace plans differ from traditional Medicaid in terms of cost sharing and provider networks. The effects of the Massachusetts reform and ACA could differ because of the relatively low prereform uninsured rate in Massachusetts, differences in the sociodemographic characteristics of those gaining coverage, the relative public enthusiasm surrounding the Massachusetts law compared to the ACA, and the fact that the entire expansion among adults was done though subsidized private coverage in Massachusetts as opposed to the mix of public and private used by the ACA (Gruber 2008). Effects of the 2014 Components of the ACA Much of the early evidence on the effects of the 2014 components of the ACA focuses on changes in coverage. At the national level, simple pre-post comparisons find increases in coverage of 2.8–6.9 percentage points, depending on the time frame, data set and population group (Long et al. 2014; Smith and Medalia 2015; Courtemanche, Marton, and Yelowitz 2016; Obama 2016; Barnett and Vornovitsky 2016; McMorrow et al. 2016).7 Other recent work uses more sophisticated econometric techniques to isolate the impacts of different components of the ACA on coverage. Kaestner et al. (2017) and Wherry and Miller (2016) focus on the Medicaid expansions, while Frean, Gruber, and Sommers (2017) study the Medicaid expansions, subsidized premiums for marketplace coverage, and individual mandate. Using the identification strategy that we employ in this article, Courtemanche et al. (2017) aim to estimate the impact of the ACA more generally, finding that it increased coverage by an average of 5.9 percentage points in Medicaid expansion states compared to 2.8 percentage points in nonexpansion states in 2014. A growing number of studies examine health-related outcomes besides insurance. Polsky et al. (2015), Shartzer, Long, and Anderson (2016), Sommers et al. (2015), Kirby and Vistnes (2016), and Sommers, Blendon, and Orav (2016) show that the timing of the ACA coincided with increased access to care, while Sommers et al. (2015) also document an improvement in selfassessed health. However, it is unclear whether estimates based only on time-series variation are able to disentangle causal effects of the ACA from other national shocks. Three articles use difference-in-differences (DD) approaches to examine the impacts of the 2014 ACA Medicaid 7 Although, we focus our discussion on national studies, single-state investigations generally reach similar conclusions (Sommers, Kenney, and Epstein 2014; Golberstein, Gonzales, and Sommers 2015; Benitez, Creel, and Jennings 2016; Sommers et al. 2016). 666 Courtemanche et al. expansion on access, health behaviors, or self-assessed health after two years.8 Using data from the Gallup-Healthways Well-Being Index, Sommers et al. (2015) find evidence that the Medicaid expansion improved access along some dimensions but did not significantly affect self-assessed health. Abramowitz (2016) finds that the Medicaid expansion was associated with a reduction in self-reported overall health using data from the Current Population Survey Annual Social and Economic Supplement. Simon, Soni, and Cawley (2017) use data from the BRFSS and find that the Medicaid expansion increased some aspects of access and preventive care use among lowincome childless adults. However, they find no evidence of effects on risky health behaviors or most of their self-assessed health measures. Relative to these previous studies, our main contribution is to present causally interpretable evidence on the effects of the full ACA—as opposed to just its Medicaid portion—on access to health care, risky health behaviors, and self-assessed health. This is critical information in light of ongoing policy debates about the future of the ACA. While we adopt the DDD strategy of Courtemanche el al. (2017), our work is distinct because we examine outcomes beyond just insurance coverage, use a second year of posttreatment data, and use a different dataset (BRFSS instead of the American Community Survey [ACS]). A secondary contribution of our work is to offer an alternative identification strategy for the impact of the Medicaid expansion that relies on weaker assumptions than the DD approach used previously. Specifically, we do not need to assume that any differential changes in the outcomes between the expansion and nonexpansion states in 2014 are attributable to Medicaid. Instead, our approach allows for other factors (e.g., underlying trends or enthusiasm for the other parts of the ACA) to contribute to this differential as long as they are not correlated with pretreatment uninsured rates. 3. Data Our primary data source is the BRFSS, an annual telephone survey conducted by state health departments and the US Centers for Disease Control and Prevention that collects data on preventive services, risky behaviors, and self-assessed health for all 50 states and the District of Columbia. A random digit dialing method is used to select a representative sample of respondents from the noninstitutionalized adult population. The BRFSS is appealing for our study because its large number of observations, more than 300,000 per year, allows us to precisely estimate the effects of the ACA. This is important since only a fraction of the population is affected by the change in legislation, limiting plausible effect sizes. Our main sample consists of 19- to 64-year-olds from the 2011–2015 waves. We exclude individuals older than 64 since the ACA was not intended to affect the health care coverage of seniors. We begin the sample in 2011 because that was the first year in which the BRFSS included cell phones in its sampling. As individuals who exclusively use cell phones are disproportionately young, this inclusion results in a discrete change in the sample means of many of our key variables (including insurance coverage) between 2010 and 2011. An additional benefit of excluding years prior to 2011 is that this limits the sample to years after the implementation of the ACA s 8 Additionally, Sommers, Baicker, and Epstein (2012) find that early Medicaid expansions under the ACA in New York, Maine, and Arizona were associated with increases in access to care and self-assessed health. Early Effects of the Affordable Care Act 667 dependent coverage expansion, preventing confounding from differences in state dependent coverage mandates prior to the ACA. We utilize 11 different health-related dependent variables.9 The first set relates to health care access since such access, specifically to primary care, has repeatedly been shown to be an important predictor of health outcomes (Starfield, Shi, and Macinko 2005). Our four access measures consist of dummy variables reflecting whether the respondent has any health insurance, had any medical care needed but not obtained because of cost in the previous year, has a primary care physician, and had a well-patient checkup (e.g., a physical) in the previous year. The next three outcomes relate to risky health behaviors: a binary indicator for whether one smokes, a count of alcoholic drinks consumed per month, and a continuous variable measuring the respondents body weight in the form of BMI.10 These are three of the leading causes of preventable death in the United States, costing 467,000, 64,000, and 216,000 lives, respectively, per year as of 2005 (Danaei et al. 2009; Cawley and Ruhm 2012). Another set of outcomes relates to self-assessed health status: a dummy for whether overall health is very good or excellent, days of the last 30 not in good mental health, days of the last 30 not in good physical health, and days of the last 30 with health-related functional limitations.11 Self-assessed health variables, although subjective, have been shown to be correlated with objective measures of health, such as mortality (e.g., Idler and Benyamini 1997; DeSalvo et al. 2006; Phillips, Der, and Carroll 2010). While one might initially be skeptical that insurance expansions could meaningfully affect health in their first two years, prior evidence from the randomized Oregon Medicaid experiment (Finkelstein et al. 2012) and the Massachusetts universal coverage initiative (Van der Wees, Zaslavsky, and Ayanian 2013; Courtemanche and Zapata 2014) has shown that immediate gains in self-assessed health can indeed occur. We include a wide range of control variables. The controls from the BRFSS are dummy variables for age groups (five-year increments from 25–29 to 60–64, with 19–24 as the reference group), gender, race/ethnicity (non-Hispanic black, Hispanic, and non-Hispanic white, with “other” as the reference group), marital status, education (high school degree, some college, and college graduate, with less than a high school degree as the reference group), household income ($10,000– $15,000, $15,000–$20,000, $20,000–$25,000, $25,000–$35,000, $35,000–$50,000, $50,000–$75,000, and >$75,000, with
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