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Ohio’s Medicaid Expansion and Unmet Health Needs Among Low-Income Women of Reproductive Age

  • Thalia P. Farietta
  • Bo Lu
  • Rachel Tumin
Article
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Abstract

Objective To examine changes in the prevalence and odds of unmet healthcare needs and healthcare utilization among low-income women of reproductive age (WRA) after Ohio’s 2014, ACA-associated Medicaid expansion, which extended coverage to non-senior adults with a family income ≤ 138% of the federal poverty level. Methods We analyzed publically available data from the 2012 and 2015 Ohio Medicaid Assessment Survey (OMAS), a cross-sectional telephone survey of Ohio’s non-institutionalized adult population. The study included 489 low-income women in 2012 and 1273 in 2015 aged 19–44 years who were newly eligible for Medicaid after expansion in January 2014. Four unmet healthcare need and three healthcare utilization measures were examined. We fit survey-weighted logistic regression models adjusted for race/ethnicity, working status, and educational attainment to determine whether the odds of each measure differed between 2012 and 2015. Results In 2015, low-income WRA had a significantly lower odds of reporting an unmet dental care need (ORadj = 0.72, 95% CI 0.54, 0.95), unmet vision care need (ORadj = 0.68, 95% CI 0.50, 0.93), unmet mental health need (ORadj = 0.57, 95% CI 0.39, 0.83), and unmet prescription need (ORadj = 0.39, 95% CI 0.45, 0.80) compared to 2012. There were no significant differences in the odds of seeing a doctor or dentist in the past year or of having a usual source of care for low-income WRA in 2012 and 2015. Conclusions for Practice After Ohio’s 2014 Medicaid expansion the odds of low-income WRA having unmet healthcare needs was reduced. Future research should examine outcomes after a longer period of follow-up and include additional measures, such as self-rated health status.

Keywords

Medicaid expansion Unmet health needs Women of reproductive age Affordable Care Act (ACA) Ohio Medicaid Assessment Survey (OMAS) 

Significance

Analyses of prior Medicaid expansions have documented improvements in adults’ access to healthcare and general health status, but few studies of ACA-associated Medicaid expansion have specifically examined outcomes among women of reproductive age (WRA). After Ohio’s 2014 Medicaid expansion, adjusting for race/ethnicity, working status, and educational attainment, fewer low-income WRA had unmet healthcare needs compared to before the expansion. These reductions in unmet needs may translate to improved health for low-income women, and potentially correspond to improved access to preconception and interconception care and preventive services across the lifespan.

Introduction

As of December 2017, the Affordable Care Act (ACA) has extended healthcare coverage to more than 17.4 million Americans (Kaiser Family Foundation 2018), in part through the optional expansion of Medicaid coverage to all non-senior adults whose household income did not exceed 138% of the federal poverty level (FPL) (133% FPL plus a 5% disregard). Analyses of prior Medicaid expansions have documented improvements in adults’ access to healthcare and general health (Baicker et al. 2013; Sommers et al. 2012). The voluntary nature of the ACA-associated Medicaid expansion led states to expand their eligibility criteria at different times, and results from some early-expansion, pre-ACA states show improved access to care and improved health and well-being (Finkelstein et al. 2012; Ndumele et al. 2014; Sommers et al. 2012).

Few studies of ACA-associated Medicaid expansion have assessed changes in access to healthcare and health status among women of reproductive age (WRA). Most studies examining women have focused on changes in insurance coverage post-expansion (Jones and Sonfield 2016; Ranji and Salganicoff 2015). The population of low-income women ages 19–44 years is of interest because WRA have historically churned on and off Medicaid depending on pregnancy status. Prior to ACA-associated Medicaid expansion, Medicaid eligibility for adults was limited to those with certain qualifying characteristics such as parenthood or disability, and the income limitation for most Medicaid eligibility groups was lower than 90% FPL. In Ohio, pregnant women in families with income up to 200% of the federal poverty level are eligible for Medicaid. Services available to them include education, care coordination, high risk monitoring, nurse midwife services, prenatal care, ultrasounds, delivery, and transportation (Ohio Department of Medicaid 2017).

Prior to ACA-associated expansion, women in Ohio who were not pregnant were only eligible for Medicaid if their income was ≤ 90% FPL and they were a parent (Medicaid.gov 2017; Ohio Department of Job and Family Services 2009). Many women who enrolled in Ohio Medicaid during pregnancy therefore lost their coverage approximately 60 days post birth, resulting in a loss of access to primary care, family planning services, and preventive services (Adams et al. 2003). For example, in 2013, 14% of mothers in Ohio who were Medicaid-eligible at birth were no longer eligible within 120 days of their delivery (Ohio Department of Medicaid Claims Data 2018). This inability to gain or retain coverage hindered women’s ability to realize better health prior to becoming pregnant and between subsequent pregnancies, contributing to worse health outcomes for themselves and their children (Johnson 2012). In Ohio, over 50% of births were financed by Medicaid in 2014, suggesting that losing Medicaid coverage may negatively affect the continuity of healthcare and health status for a majority of WRA (Ohio Department of Medicaid 2016).

In response to calls for a more comprehensive examination of the effect of ACA-associated Medicaid expansion on women’s access to healthcare and general health status (Keating et al. 2013), we analyzed two iterations of Ohio-specific survey data to examine the association between Ohio’s 2014 Medicaid expansion and prevalence of healthcare needs and the use of health services among low-income women aged 19–44 years who became eligible for coverage under this expansion. We hypothesized that Ohio’s Medicaid expansion would be associated with a lower prevalence of unmet healthcare needs and increased utilization of care for WRA.

Methods

Data

We used data from the 2012 and 2015 Ohio Medicaid Assessment Surveys (OMAS), the two iterations that preceded and followed Ohio’s 2014 Medicaid expansion. The OMAS is a cross-sectional telephone survey that examines access to the health system, health status, and health determinant characteristics of Ohio’s non-institutionalized adult population (Ohio Medicaid Assessment Survey 2015). The 2012 and 2015 iterations used complex, stratified designs to probabilistically sample landline and cell phones. Their designs included an oversample of African-Americans, Asians and Hispanics, and in 2012, households with children were also oversampled. Trained interviewers administered the survey to adult respondents age 19 years and older. Proxy respondents were allowed for those unable to complete the interview themselves. All participants verbally consented to taking part in the surveys.

The 2012 OMAS was fielded from May through September of 2012 and the 2015 OMAS was fielded from January to June of 2015. The 2015 OMAS therefore covered respondents’ health care utilization from early 2014 to mid-2015, which was an appropriate time period for evaluating the initial changes in unmet healthcare needs and utilization of care following Ohio’s Medicaid expansion. This is also consistent with approaches other researchers have taken when examining the early effects of Medicaid expansion (Sommers et al. 2016; Wherry and Miller 2016). The response rate in 2012 was 29.4% and in 2015, it was 24.1%. Both years the weighting process included post-adjustments for non-response and raking to key population totals representative to American Community Survey estimate standards and Ohio Medicaid administrative data. We used the publically available datasets (Ohio Medicaid Assessment Survey 2016b) and The Ohio State University IRB did not consider this study human subjects research.

Study Population

The 2012 and 2015 OMAS iterations collected data from 22,929, and 42,876 adults 19 years of age and older, respectively. To capture WRA who should have become eligible for Medicaid coverage under the 2014 expansion, we limited our analyses to women ages 19 through 44 years whose self-reported annual family incomes were at or below 138% FPL (n = 1357 in 2012, n = 2815 in 2015), referred to in our analysis as “low-income.” The FPL analysis used self-reported family income and family size (values were imputed via regression-based imputation methods when missing), both of which were provided in the public dataset. Some women with incomes ≤ 138% FPL were eligible for Medicaid coverage prior to this ACA-associated expansion and they were therefore excluded from both our 2012 and 2015 study populations in order to better identify the population of low-income WRA who should have been affected by the 2014 expansion in coverage. These previously eligible groups included WRA who were currently pregnant, ≤ 90% FPL and currently a parent, receiving coverage under an Ohio Medicaid Waiver, or on the Ohio Medicaid/Medicare aged, blind, or disabled (ABD) program at the time of survey administration. These filters eliminated 760 WRA from the 2012 sample and 1427 from the 2015 sample. The use of self-reported prior year’s income and disability status data to identify these previously eligible groups comes with some imprecision; therefore, we expected some women in our 2012 study population to still report having Medicaid coverage. After eliminating observations with a missing value for the measures of interest (108 and 115 for 2012 and 2015, respectively) the final study sample was 489 women in 2012 and 1273 women in 2015.

Measures

Outcomes

Unmet healthcare needs. Four separate indicators of having an unmet need in the past 12 months were used. These were dichotomous measures of self-reported inability to get (1) dental care, (2) vision care or eyeglasses, (3) mental healthcare or counseling, and (4) being unable to fill a prescription due to the cost. All respondents were asked about each of these potential unmet needs. For example, unmet dental health care needs were assessed through the question, “During the past 12 months, was there a time when you needed dental care but could not get it at that time?”

Healthcare utilization. Three dichotomous measures to describe utilization of care were used: (1) having a dental visit in the past year, (2) having a doctor’s visit in the past year, and (3) having a usual source of care. Women reporting any type of dental visit, including visiting an orthodontist, oral surgeon, any other dental specialist, or a dental hygienist were considered to have visited a dentist in the past year. Women were classified as having visited a doctor if they reported visiting a doctor or other healthcare professional about their own health in the past year. Women were classified as having a usual source of care if they reported having at least one place that they usually went to when they were sick or needed advice regarding their health (including an emergency department).

Independent Variable

The cross-sectional nature of the OMAS data prohibits tracking the same WRA cohort over time to directly assess the effect of Medicaid expansion on their unmet health needs and utilization of care. We therefore created a binary time variable to indicate whether the measurement was taken in 2015 (after Ohio’s Medicaid expansion) or in 2012 (before Ohio’s Medicaid expansion) to test if unmet healthcare needs and utilization patterns differed in the post-Medicaid expansion period compared to the pre-expansion period.

Covariates

The study included seven covariates: race/ethnicity (non-Hispanic White, non-Hispanic Black, and other); age in years; educational attainment (less than a high school education, high school education, some college or an associate’s degree, bachelor’s degree or higher); insurance status (Medicaid, employer-sponsored insurance [ESI], other insured,1 and uninsured), parental status (parent of a child in the household vs. not), working status (working a full- or part-time job in the last week vs. not working); and county type (metropolitan, suburban, rural Appalachian, and rural non-Appalachian). Imputed variables included in the public dataset were used for insurance status, race/ethnicity, education, county type, and age to account for missing values (Ohio Medicaid Assessment Survey 2016a). The percentage of missing data for these covariates ranged from 1.4 to 2.4%. Hot deck imputation was used for all of these variables.

Analytic Strategy

We first examined the distribution of each covariate in 2012 and 2015 and performed a Pearson’s Chi-Square test to determine if the distribution of these covariates differed across survey years. Unless otherwise noted, all analyses were performed on weighted data. In order to examine changes in unmet needs and utilization, prevalence was estimated for each measure overall and stratified by type of insurance coverage for 2012 and 2015. Due to the potential for small cell counts in some of these prevalence estimates, we computed the relative standard error (RSE) and marked those estimates with an RSE greater than 30% as potentially unreliable. We then fit logistic regression models that examined the odds of each unmet healthcare need and healthcare utilization measure as a function of the Ohio Medicaid expansion. The models were fixed models that adjusted for race/ethnicity, educational attainment, and working status because these factors are associated with the outcomes of interest and may have varied between the two time points. We did not account for insurance status (or type of insurance) because we expected changes in the percentage of WRA with Medicaid were contributing to any observed changes in the odds of the outcomes. We also did not adjust for age, race, or county type because of lack of variation within these measures across years. We considered a p-value < .05 to be statistically significant. All analyses were performed using Stata 14.0 MP (Stata 2016) and accounted for the complex survey design (Ohio Medicaid Assessment Survey 2016a).

Results

Table 1 presents the demographic characteristics of the weighted sample of WRA in 2012 (population estimate of 340,691) and 2015 (population estimate of 356,302) who met the study criteria.

Table 1

Demographic characteristics of low-income WRA (women of reproductive age), 2012 and 2015 OMAS (Ohio Medicaid Assessment Survey)

 

2012

2015

% (95% CI)b

Weighted Nb

Unweighted n

% (95% CI)b

Weighted Nb

Unweighted n

Age (mean and SE)

29.19 (0.42)

340,691

489

29.67 (0.27)

356,302

1273

Race/ethnicity (%)

 Non-Hispanic White

77 (72, 81)

260,878

316

75 (72, 78)

267,572

848

 Non-Hispanic Black

17 (13, 20)

57,078

103

18 (16, 21)

64,199

273

 Other

7 (4, 9)

22,734

70

7 (5, 8)

24,531

152

County type (%)

 Rural Appalachian

19 (15, 23)

64,966

110

18 (15, 20)

63,830

244

 Metro

58 (53, 63)

198,409

285

57 (53, 60)

202,027

687

 Rural non-Appalachian

10 (7, 14)

35,137

44

11 (9, 13)

40,057

166

 Suburban

12 (9, 16)

42,178

50

14 (12, 16)

50,389

176

Insurance** (%)

 Medicaid

28 (23, 32)

94,332

166

52 (48, 55)

183,840

699

 ESI

20 (16, 25)

68,883

96

24 (21, 27)

84,183

271

 Uninsured

36 (31, 41)

121,532

171

14 (12, 16)

49,796

190

 Othera

16 (12, 21)

55,944

56

11 (9, 13)

38,483

113

Education** (%)

 Less than high school

12 (8, 16)

41,669

51

13 (10, 15)

45,799

138

 High school

44 (39, 49)

149,765

209

32 (29, 35)

115,783

516

 Some college or associate’s degree

33 (28, 38)

113,087

158

43 (40, 47)

154,484

443

 Bachelor’s degree or higher

11 (8, 14)

36,169

71

11 (9, 13)

40,235

176

Parent of child in household (%)

38 (33, 43)

129,752

209

39 (46, 43)

139,987

508

Working*(%)

54 (49, 59)

184,518

250

62 (58, 65)

220,179

780

*p < 0.05, **p < 0.01 for testing difference between 2012 and 2015 distribution, Pearson Chi square test

aOther insurance is comprised of directly purchased, unknown insurance type, and self-reported other insurance status

bColumn percentages may not sum to 100% due to rounding; similar issues may occur when adding weighted values

The average age and distribution by race/ethnicity, county type, and parental status were similar in both years. There were, however, some significant differences in the distribution of educational attainment and working status between years. WRA tended to be more educated in 2015, compared to 2012: 54% of women in 2015 had completed at least some college or an associate’s degree, compared to 44% in 2012. A greater percentage of women were working in 2015, compared to 2012 (62% compared to 54%). As expected, the most substantial change from 2012 to 2015 was the distribution of insurance coverage. A much larger percentage of low-income women were on Medicaid in 2015 (52%), compared to 2012 (28%), and a smaller percentage of women were uninsured in 2015 (14%), compared to 2012 (36%).

Tables 2 and 3 present the prevalence of unmet needs and utilization of care among low-income WRA in 2012 and 2015, overall and by insurance status.

Table 2

Prevalence of unmet healthcare needs (weighted percentages) among low-income WRA (women of reproductive age) overall and stratified by type of insurance coverage, 2012 and 2015 OMAS (Ohio Medicaid Assessment Survey)

 

Dental

Vision care

Mental health

Prescription drugs

2012

2015

2012

2015

2012

2015

2012

2015

Overall %, 95% CI

33 (28, 38)

27 (24, 30)

23 (19, 28)

17 (14, 19)

17 (13, 21)

10 (8, 12)

33 (28, 38)

23 (20, 26)

Insurance %, 95% CI

 Medicaid

19 (12, 27)

22 (18, 25)

20 (12, 27)

14 (11, 17)

13 (6, 19)

9 (7, 12)

21 (14, 29)

16 (13, 19)

 ESIa

21 (11, 30)

24 (18, 31)

21 (12, 31)

15 (10, 20)

20 (10, 30)

7 (3, 10)

39 (27, 51)

25 (19, 31)

 Uninsured

52 (43, 61)

50 (41, 59)

33 (25, 42)

33 (24, 41)

24 (16, 31)

21 (13, 29)

49 (40, 58)

45 (36, 54)

 Other

28 (15, 41)

24 (15, 34)

8 (0, 16)b

12 (5, 19)

7 (0, 15)b

11 (4, 17)b

15 (4, 25)b

24 (15, 34)

Total n, unweighted

167

325

120

218

75

137

161

290

Insurance n, unweighted

 Medicaid

39

150

35

107

19

65

38

107

 ESIa

22

58

20

40

17

20

39

70

 Uninsured

89

93

61

57

34

38

74

85

 Other

17

24

4

14

5

14

10

28

aESI

bUnreliable estimate

Table 3

Prevalence of healthcare utilization (weighted percentages) among low-income WRA (women of reproductive age) overall and stratified by type of insurance coverage, 2012 and 2015 OMAS (Ohio Medicaid Assessment Survey)

 

Physician in past year

Dentist in past year

Usual source of care

2012

2015

2012

2015

2012

2015

Overall %, 95% CI

65 (60, 70)

70 (67, 74)

65 (60, 70)

66 (63, 69)

86 (83, 90)

90 (88, 92)

Insurance

 Medicaid

85 (78, 92)

78 (74, 82)

78 (70, 85)

68 (63, 72)

95 (91, 99)

92 (90, 94)

 ESIa

73 (63, 84)

75 (69, 81)

74 (64, 84)

79 (74, 85)

88 (79, 96)

91 (87, 95)

 Uninsured

45 (36, 54)

42 (33, 51)

42 (33, 51)

45 (37, 54)

77 (69, 84)

81 (75, 88)

 Other

65 (51, 79)

64 (53, 75)

82 (71, 93)

57 (46, 69)

93 (85, 100)

87 (79, 94)

Total n, unweighted

334

917

314

839

427

1143

Insurance n, unweighted

 Medicaid

147

559

128

476

155

644

 ESIa

71

197

68

206

88

246

 Uninsured

81

84

74

89

133

155

 Other

35

77

44

68

51

98

aESI

Across all four measures, fewer WRA had an unmet healthcare need in 2015 compared to 2012 (Table 2). The largest reduction in unmet needs was for prescription drugs, where there was a 10 percentage point decrease; this decrease was statistically significant, as was the decrease in unmet vision healthcare needs. The percentages of low-income WRA who saw a physician or dentist, or who had a usual source of care were higher in 2015 than in 2012 (Table 3). Uninsured WRA had the highest prevalence of unmet needs and lowest utilization of care in both 2012 and 2015. Although the point estimates were typically lower, most of the changes between 2012 and 2015 were not significant.

Table 4 presents the results of the logistic regression analysis predicting odds of each unmet healthcare need and healthcare utilization measure in the post-Medicaid expansion period (2015), compared to the pre-Medicaid expansion period (2012) for low-income WRA.

Table 4

Odds of having an unmet healthcare need or utilizing care in 2015 compared to 2012 among low-income WRA (women of reproductive age), adjusted for demographic characteristics, 2012 and 2015 OMAS (Ohio Medicaid Assessment Survey, 2012 sample size: 489, 2015 sample size: 1273) (n = 1762)

 

Unmet healthcare need

Utilization of care

 

Dental

Vision care

Mental health

Prescription drugs

Physician in past year

Dentist in past year

Usual source of care

 

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

OR

95% CI

Year

 2012 (Pre-Medicaid expansion)

1.00

1.00

1.00

1.00

1.00

1.00

1.00

 2015 (Post-Medicaid expansion)

0.72*

(0.54, 0.95)

0.68*

(0.50, 0.93)

0.57**

(0.39, 0.83)

0.60***

(0.45, 0.80)

1.28

(0.97, 1.69)

1.05

(0.80, 1.37)

1.36

(0.92, 2.02)

Race

 Non-Hispanic White

1.00

1.00

1.00

1.00

1.00

1.00

––

1.00

 Non-Hispanic Black

1.23

(0.87, 1.74)

1.39

(0.93, 2.06)

0.64

(0.36, 1.13)

1.19

(0.83, 1.71)

1.54*

(1.06, 2.25)

0.76

(0.54, 1.06)

0.91

(0.54, 1.54)

 Other

0.64

(0.38, 1.09)

1.00

(0.56, 1.79)

0.83

(0.45, 1.54)

0.89

(0.53, 1.51)

0.79

(0.47, 1.33)

0.53*

(0.33, 0.86)

0.71

(0.37, 1.35)

Education

 Less than high school

1.00

1.00

1.00

1.00

1.00

1.00

1.00

 High School

0.71

(0.43, 1.15)

0.71

(0.42, 1.20)

0.51*

(0.29, 0.93)

0.82

(0.50, 1.35)

1.27

(0.79, 2.04)

1.20

(0.76, 1.87)

0.65

(0.31, 1.34)

 Some college or associate’s degree

1.11

(0.68, 1.79)

0.73

(0.43, 1.22)

0.58

(0.33, 1.04)

0.90

(0.55, 1.48)

1.52

(0.94, 2.46)

1.43

(0.91, 2.24)

0.72

(0.34, 1.51)

 Bachelor’s degree or higher

0.89

(0.51, 1.57)

0.56

(0.30, 1.06)

0.35**

(0.17, 0.72)

1.08

(0.61, 1.91)

1.47

(0.84, 2.59)

1.61

(0.95, 2.74)

0.68

(0.30, 1.56)

Working status

 Not working

1.00

1.00

1.00

1.00

1.00

1.00

1.00

 Working

0.79

(0.59, 1.06)

0.73

(0.53, 1.02)

0.65*

(0.44, 0.97)

0.73*

(0.54, 0.98)

0.76

(0.57, 1.02)

1.04

(0.79, 1.37)

0.89

(0.58, 1.37)

*p < 0.05, **p < 0.01, ***p < 0.0001

An improvement in the odds of having an unmet healthcare need would correspond to an odds ratio lower than one, while an odds ratio greater than one would imply an increase in the utilization of healthcare. Adjusting for race/ethnicity, education, and working status, low-income WRA in 2015 had significantly lower odds of reporting an unmet dental care, vision care, mental healthcare and prescription need compared to 2012. For example, WRA in 2015 had 28% lower odds of reporting an unmet dental care need, (ORadj = 0.72, 95% CI 0.54, 0.95) and 43% lower odds of reporting an unmet mental healthcare need (ORadj = 0.57, 95% CI 0.39, 0.83) compared to 2012. None of the healthcare utilization measures were significant.

Discussion

Underlying the efforts to extend Medicaid coverage to more low-income adults as part of the ACA was the assumption that expanded coverage would improve adults’ access to care, and subsequently, their health, as has been documented with earlier Medicaid expansions (Sommers et al. 2012). Few studies of ACA-associated Medicaid expansion have specifically examined WRA; of those studies, most have focused on access to women-specific healthcare rather than healthcare needs and utilization more broadly (Jones and Sonfield 2016; Ranji and Salganicoff 2015; Johnston et al. 2018). While our study did not find the hypothesized increase in healthcare utilization, the observed reductions in odds of having unmet healthcare needs post- versus pre-ACA are promising as they may translate to health improvements over time. These findings are especially encouraging when considering the potential impacts of improved access to care on both pre-and inter-conception health, something that has not been studied extensively in this population.

The lower odds of unmet healthcare needs among WRA following Ohio’s Medicaid expansion are similar to earlier findings examining unmet needs among those with Medicaid compared to those who are uninsured (Clemans-Cope et al. 2013) and among states with Medicaid expansion compared to those without (Benitez et al. 2016). Overall, the trends in unmet needs are consistent with previous findings on utilization and receipt of care among all adults showing a positive relationship between Medicaid expansion and behavioral healthcare utilization (Ali et al. 2016) as well as between expansion and use of preventative services and prescription drug access (Baicker et al. 2013; Han et al. 2016). Evaluations of the effect of previous Medicaid expansions on women’s healthcare needs have found that the increase in coverage was associated with increases in utilization of healthcare services, including routine check-up and gynecological services (Adams et al. 2013; Lantz and Soliman 2009). Our observed decrease in odds of four measures of unmet healthcare need among low-income WRA suggests that Medicaid expansion may have positive ramifications for WRA’s health more broadly, beyond their reproductive healthcare needs.

Contrary to our hypothesis, we found no evidence that Ohio’s Medicaid expansion was associated with an increase in having a usual source of care among low-income WRA. Researchers analyzing data from the National Health Interview Survey also found no significant difference between the percentage of adults younger than 65 years with incomes ≤ 138% FPL who had a usual source of healthcare when comparing states that expanded Medicaid versus those that did not before and after the expansion (Wherry and Miller 2016). More specific to our population, researchers using the California Health Information Survey examined the effect of insurance coverage on reporting a usual source of care among similar women aged 18–44 years found that the percentage reporting a usual source of care stayed consistent within a year of Medicaid expansion (Early et al. 2016). While the researchers did find an association between insurance status and a usual source of care in multivariable models, this conclusion was drawn using different comparison groups (insured vs. uninsured women). Additional research is needed to better understand the extent to which expanding Medicaid coverage may increase the percentage of low-income WRA with a usual source of care.

We also found no evidence of increased odds of low-income WRA having a physician or dental visit after Ohio’s Medicaid expansion. This is consistent with previous research showing that increases in dental coverage do not translate to improvements in utilization of dental care (Fingar et al. 2015) and that the Medicaid expansion does not necessarily decrease most barriers to care (Flynn et al. 2014). The lack of change in odds of having a dental visit in 2015 compared to 2012 may seem incongruous with our finding that self-reported unmet dental need did decline. However, it may be that the percentage of low-income WRA with a dental provider did not change, but among those who already had a dental provider, more were able to receive care when needed because they had Medicaid coverage (and could presumably afford the care). Shortages in dental providers across Ohio, coupled with limited participation of dentists and physicians in Medicaid, may explain the lack of improvements in the odds of having dental and medical visits in the past year (Ohio Department of Health 2016; Decker 2012; Sommers et al. 2013). These difficulties in assuring access to care have been specifically reported among new enrollees within a year of enrollment (Cheong et al. 2016).

The strengths of our study include a large sample size and generalizability to low-income WRA across Ohio. Ohio is similar to the United States with respect to sex and age composition, and working and insurance status (U.S. Census Bureau 2016), suggesting that our results may be generalizable beyond Ohio. However, differences in Medicaid eligibility, coverage patterns, and health systems among the 32 Medicaid expansion states may limit the generalizability of our findings. Another limitation of our study is that the data were cross-sectional and hence, could not be tracked as a cohort over time. The use of only two time points also meant we could not make any statement about the general trajectory of unmet healthcare needs or healthcare utilization in Ohio over time.

Summary

Our study estimated the association between Ohio’s 2014 Medicaid expansion and odds of unmet healthcare needs and utilization of healthcare among WRA in the income range and categories made newly eligible for Medicaid coverage in Ohio. Increased Medicaid coverage was a key pathway for increased access and decreased unmet needs. The study showed that Ohio low-income WRA experienced a decrease in unmet dental care, vision care, mental healthcare and prescription needs, which may stem in part, from increased eligibility and enrollment in Medicaid. Despite reductions in unmet needs, we did not find a significant change in healthcare utilization measures. Additional research examining outcomes after a longer follow-up period and including other healthcare and health status measures is needed to further understand the extent to which expanding Medicaid eligibility improves low-income women’s access to health care, including reproductive health services, and how this affects their overall health status.

Footnotes

  1. 1.

    Other insurance is comprised of directly purchased, unknown insurance type, and self-reported other insurance status.

Notes

Acknowledgements

This study was funded by the Ohio Department of Medicaid and administered by the Ohio Colleges of Medicine Government Resource Center. The views expressed in this manuscript are solely those of the authors and do not represent the views of the state of Ohio or federal Medicaid programs.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Outcomes Research and EvaluationYale UniversityNew HavenUSA
  2. 2.The Ohio State University College of Public HealthColumbusUSA
  3. 3.Ohio Colleges of Medicine Government Resource CenterColumbusUSA

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