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. Author manuscript; available in PMC: 2023 Jun 1.
Published in final edited form as: J Subst Abuse Treat. 2021 Dec 29;137:108710. doi: 10.1016/j.jsat.2021.108710

Healthcare coverage and service access for low-income adults with substance use disorders

Mark Olfson 1,2, Christine Mauro 2, Melanie M Wall 1,2,3, C Jean Choi 3, Colleen L Barry 4,5, Ramin Mojtabai 4,5
PMCID: PMC9086121  NIHMSID: NIHMS1772399  PMID: 34998642

Abstract

Introduction:

Although health coverage facilitates service access to adults in the general population, uncertainty exists over the extent to which this relationship extends to low-income adults with substance use disorders.

Methods:

The health status and service use patterns of low-income adults with substance use disorders who had continuous, discontinuous, and no past year health coverage were compared using data from the 2015–2019 National Survey on Drug Use and Health (NSDUH). The NSDUH is a nationally representative survey of the civilian non-institutionalized population.

Results:

In the weighted sample (unweighted n=9,243), approximately 65.66% of low-income adults with substance use disorders had continuous coverage, 17.03% had discontinuous coverage, and 17.31% had no insurance coverage during the past year. Although few group differences were observed in self-reported health status, the uninsured group compared to the discontinously and continuously covered groups, respectively, was less likely to report a past year substance use treatment visit (11.03% vs. 14.83% vs. 15.61%), an outpatient care visit (53.39% vs. 71.27% vs. 79.04%), an emergency department visit (33.33% vs. 45.76% vs. 45.57%), or an inpatient admission (9.24% vs. 15.11% vs. 15.58%).

Conclusions:

Although the cross sectional design limits causal inferences, the correlations between lacking health insurance and low rates of substance use treatment and healthcare use raise the possibility that increasing healthcare coverage might increase access to substance use treatment and other needed healthcare services for low-income adults with substance use disorders.

Keywords: Substance use, Health insurance, Service access

1. Introduction

Health insurance coverage has several health benefits (Sommers et al., 2017). These include increasing the likelihood of having a usual source of care (Shartzer et al., 2016), accessing preventive services (Sommers et al., 2014), receiving routine primary care (Sommers et al., 2105), and reducing the risks of premature mortality (Sommers et al., 2014). As compared to uninsured adults placed on a wait list, adults who were randomly assigned to Medicaid also attained greater financial security, better health-related quality of life, and lower rates of depression (Baicker et al., 2013). Yet despite strong evidence supporting the health advantages of health coverage for the general population, these benefits appear less straightforward for people with substance use disorders.

Uninsured adults compared to insured adults tend to have poorer health including more frequent undiagnosed and uncontrolled chronic medical illnesses (Wilper et al., 2009a) and shorter life expectancy (Wilper et al., 2009b; McWilliams et al., 2004). Yet little is known about whether and to what extent the health profile of adults with substance use disorders varies by their health insurance coverage.

Individuals with substance use disorders tend to underuse outpatient healthcare. Only a small fraction of adults with substance use disorders receive treatment for their conditions during the course of a year (Olfson et al., 2019; Edlund et al., 2012). There is also a general tendency for adults with substance use disorders to underuse outpatient and preventive general health services (Lasser et al., 2011, Artenie et al., 2015, Ross et al., 2015), even though their use of emergency and inpatient services exceeds use by the general population (Lewer et al., 2020).

It is not known whether health insurance increases the likelihood that adults with substance use disorders receive treatment or other health services. In the first years following the Affordable Care Act Medicaid expansion, time series analyses did not find a significant increase in the proportion of adults with substance use disorders that received treatment (Creedon & Le Cook, 2016; Saloner et al., 2017; Olfson et al., 2018). However, because these population-level policy evaluations did not compare treatment rates of insured and uninsured adults with substance use disorders, they do not directly inform the basic question of whether health insurance is associated with increased substance use disorder treatment.

Because adults with substance use disorders have an elevated risk of being uninsured (Wang & Xie, 2017), it is particularly important to help clarify associations between their coverage and service use. If, among people with substance use disorders, coverage were associated with greater use of substance use treatment and other health services, it would bolster the rationale for targeted outreach efforts to increase their enrollment in healthcare plans. To our knowledge, the following analysis represents the first direct comparison of service access among individual adults with substance use disorders with and without health insurance.

Much also remains to be learned about the healthcare consequences of disruptions in insurance, which may be especially common among people with substance use disorders (McFarland et al., 2006). Although disruptions in coverage have been related to delays in treatment for serious medical conditions (Tarazi et al., 2017), difficulties in accessing primary medical care (Seo et al., 2019), and lower outpatient treatment of mental health conditions other than substance use disorders (Xu et al., 2019), the implications of discontinuous coverage on health service use for adults with substance use disorders are not known. We focus on low-income adults, the income group with the highest risk of being uninsured (Kastner & Lubotsky, 2016) and experiencing financial strain from health care expenditures (McKenna et al., 2018).

We used 2015–2019 National Survey on Drug Use and Health (NSDUH) data to probe connections between continuous, discontinuous, and no insurance coverage and use of hospital, emergency, and outpatient care by people with substance use disorders. Because low-income adults have a low rate of coverage (Keisler-Starkey & Bunch, 2020), we focused on the low-income population. To provide context for these analyses, we first compared the socio-demographic characteristics and health status of low-income adults with and without substance use disorders. Given the association of substance use disorders with medical comorbidities (Young et al., 2015, Bahorik et al., 2017), we anticipated that among low-income adults, people with substance use disorders compared to those without substance use disorders would have poorer self-perceived health status. In addition, we expected that among people with substance use disorders, those without health coverage as compared to those with coverage would report less favorable health status, lower outpatient care and substance use treatment, and as a result of this lower use, a greater reliance on inpatient and emergency services.

2. Methods

2.1. Study population

The NSDUH, which is described in detail elsewhere (Center for Behavioral Health Statistics and Quality, 2019), is a national survey of the civilian non-institutionalized population conducted annually by the Substance Abuse and Mental Health Services Administration (SAMHSA) through face-to-face interviews with sampled adults and adolescents. A stratified, multistage, area probability sampling design was used with states as the primary strata and state sampling regions as the secondary strata. Persons without a household address, such as homeless persons not in shelters, active-duty military, and institutional residents were not eligible for the survey. Although NSDUH oversampled young adults, the weighted NSDUH sample is representative of the US general population. During the 2015–2019 period, the mean weighted response rate was 67.25% (range: 69.25% to 64.92%) and the total achieved sample size ranged from 68,073 (2015) to 67,625 (2019). In NSDUH, missing data are addressed via Predictive Mean Neighborhoods (Singh et al., 2002).

Because most US adults become eligible for Medicare at age 65 years, the present cross sectional analysis was limited to individuals aged 18–64 years. Because low income is associated with a lack of health insurance (US Census Bureau, 2017), we restricted the study sample to adults with self-reported family incomes up to twice the Federal Poverty Level (US Census Bureau, 2021), a common definition of low-income (Berkowitz et al., 2017). Most of the analyses are further restricted to adults who met past year Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) (American Psychiatric Association, 1994) for alcohol, heroin, pain relievers, hallucinogens, inhalants, tranquilizers, cocaine, stimulants, sedatives or marijuana, hereafter, “substance use disorders”. These criteria were ascertained using structured interviews based on the DSM-IV. Reliability and validity of these assessments have been previously established (Substance Abuse and Mental Health Services Administration, 2010; Jordan et al., 2008).

2.2. Health insurance groups

Respondents with substance use disorders were partitioned into 3 groups on the basis of their self-reported healthcare coverage during the past year: 1) continuous coverage, 2) discontinuous coverage, and 2) no coverage. After a brief description of each type of health coverage, respondents were asked if they were currently covered by Medicare, Medicaid, private health insurance, military healthcare (TRICARE, CHAMPUS, CHAMPVA, or VA), or any other type of coverage. Respondents were then asked how many of the last 12 months they were without coverage and the time since they last had coverage if they were currently without coverage. Respondents without current coverage and who were last covered ≥12 months before the survey were defined as having no past year coverage. Respondents who had coverage either currently or within the last 12 months and had a 1 to 11 month coverage gap in the last year were defined as having discontinuous coverage. Finally, respondents with uninterrupted past 12-month coverage were defined as having continuous coverage.

2.3. Socio-demographic and health variables

Information was collected on respondent age, sex, race/ethnicity, and educational attainment. Respondents were also assessed for their self-perceived general health status (fair/poor, good, very good, excellent), and whether they had ever been diagnosed with several health conditions with high population-level disease burden (GBD 2019 Diseases and Injuries Collaborators) including heart disease, diabetes, chronic obstructive pulmonary disease, cirrhosis or hepatitis, hypertension, or cancer (excluding skin cancers other than melanoma). Serious psychological distress was defined by a Kessler-6 score of ≥13 (Kessler et al., 2003).

2.4. Healthcare access variables

Access to healthcare was evaluated with several items. Respondents were asked how many times during the past 12 months they had been “treated in an emergency room for any reason”, “stayed overnight or longer as in inpatient in a hospital”, “visited a doctor, nurse, physician assistant or nurse practitioner about your own health at a doctor’s office, a clinic, or some other place”. Those who reported one or more such visit were considered, respectively, to have had an emergency visit, hospital admission, and outpatient care visit in the past year. Respondents were also asked if they had received any treatment or counseling for their substance use (substance use treatment) or for their “emotions, nerves, or mental health” (mental health treatment) during the past 12 months. They were further asked about whether any doctor or other healthcare professional asked them about tobacco use in the past 12 months (tobacco screening). A separate item asked those with hypertension whether they were currently taking prescription medications for their high blood pressure.

2.5. Statistical analysis

Logistic regression models were used to estimate the proportions and risk differences with 95% confidence intervals of the socio-demographic (age, sex, race/ethnicity, and education) and clinical characteristics (self-assessed health, self-reported health condition, serious psychological distress) between low-income adults with and without substance use disorders. Analyses of clinical characteristics were adjusted for age, sex, race/ethnicity, and education. Similar analyses were also performed among low-income adults with substance use disorders stratified by continuous, discontinuous, or no insurance. Risk differences with 95% confidence intervals were obtained from the logistic regression models and were used to test differences between groups, with confidence intervals not crossing zero considered statistically significant.

Among the low-income adults with substance use disorders stratified by level of health insurance, comparisons were performed for past year substance use disorders, levels of self-assessed health, self-reported medical conditions, and presence of serious psychological distress. Similar comparisons were also performed for access to different types of healthcare as well as by one or more healthcare visit stratified by self-reported medical conditions and level of self-assessed health.

Finally, these analyses were repeated comparing low-income adults with substance use disorders hierarchically organized into three groups with continuous insurance: 1) private insurance, 2) Medicaid, and 3) other insurance coverage.

All analyses were performed with SAS software (Version 9.4, Carey, NC). Analyses using callable SUDAAN accounted for the complex survey design and sampling weights of NSDUH. All reported percentages were weighted by survey weights to provide US population estimates. The weighted population estimates were divided by number of included survey years to provide an average annual estimate for the 2015–2019 period. The Institutional Review Board at RTI International approved the NSDUH data collection protocol.

3. Results

3.1. Socio-demographic and health characteristics of adults with and without substance use disorders

As compared to low-income adults without substance use disorders, those with substance use disorders were younger and more likely to be men, of non-Hispanic white race/ethnicity, and to have received some college education, while they were less likely to have graduated from college and to be of non-Hispanic Black or Hispanic race/ethnicity. In adjusted analyses, low-income adults without substance use disorders compared to those with substance use disorders were significantly more likely to perceive their health as either fair/poor or as good and were less likely to perceive it as either very good or as excellent after controlling for the potentially confounding effects of age, sex, race/ethnicity, and education (Table 1). Also in adjusted analyses, the substance use disorder group was significantly more likely to report a lifetime history of either chronic obstructive pulmonary disease or chronic liver disease (cirrhosis or hepatitis), but less likely to report a history of diabetes mellitus. The group with substance use disorders also reported a higher proportion of serious psychological distress than those without substance use disorders.

Table 1.

Socio-demographic and health characteristics of low-income adults with and without substance use disorders, 2015–2019A

Characteristics Adults with Substance Use Disorders (n=9,357) Adults without Substance Use Disorders (n=69,506) Percentage Difference
Unadjusted % (SE) Unadjusted % (SE) Unadjusted % (95% CI)
Age, years
 18–25 33.40 (0.65) 23.53 (0.21) 9.86 (8.59, 11.14)
 26–34 24.55 (0.69) 21.46 (0.23) 3.09 (1.66, 4.53)
 35–49 23.88 (0.66) 28.92 (0.24) −5.04 (−6.54, −3.55)
 50–64 18.17 (0.87) 26.09 (0.27) −7.92 (−9.74, −6.09)
Sex
 Male 59.34 (0.95) 43.39 (0.32) 15.94 (13.80, 18.08)
 Female 40.66 (0.95) 56.61 (0.32) −15.94 (−18.08, −13.80)
Race/Ethnicity
 White, non-Hispanic 53.19 (0.85) 44.07 (0.40) 9.12 (7.38, 10.86)
 Black, non-Hispanic 18.08 (0.70) 19.37 (0.28) −1.29 (−2.53, −0.04)
 Hispanic 20.70 (0.71) 28.17 (0.43) −7.47 (−8.73, −6.21)
 Other 8.04 (0.47) 8.40 (0.21) −0.36 (−1.27, 0.54)
Education
 < High school 22.94 (0.70) 24.22 (0.30) −1.27 (−2.74, 0.20)
 High school graduate 33.54 (0.63) 33.51 (0.29) 0.03 (−1.28, 1.34)
 Some college 33.81 (0.69) 31.28 (0.26) 2.53 (1.12, 3.93)
 College graduate 9.71 (0.49) 10.99 (0.21) −1.28 (−2.35, −0.21)
Adjusted % (SE) Adjusted % (95% CI) Adjusted % (SE)
Self-assessed health
 Fair/poor health 27.46 (0.66) 20.30 (0.22) 7.17 (5.78, 8.55)
 Good health 35.97 (0.65) 32.31 (0.30) 3.66 (2.32, 5.01)
 Very good health 26.21 (0.56) 29.43 (0.28) −3.22 (−4.44, −2.00)
 Excellent health 11.51 (0.43) 17.99 (0.21) −6.47 (−7.42, −5.53)
Self-reported health condition, lifetime
 Heart disease 19.80 (1.00) 19.19 (0.45) 0.61 (−1.48, 2.69)
 Diabetes 21.30 (1.16) 28.34 (0.41) −7.04 (−9.56, −4.51)
 Chronic obstructive pulmonary disease 17.15 (1.08) 12.85 (0.32) 4.30 (2.29, 6.31)
 Cirrhosis or hepatitis 5.05 (0.44) 1.50 (0.07) 3.54 (2.65, 4.44)
 Hypertension 36.94 (1.28) 39.24 (0.66) −2.29 (−4.95, 0.36)
 Cancer (excluding skin, not melanoma) 2.50 (0.29) 2.33 (0.09) 0.18 (−0.37, 0.73)
Serious psychological distress
 Present 26.89 (0.76) 8.67 (0.16) 18.22 (16.81, 19.64)
Open in a new tab

Data from the 2015–2019 National Survey on Drug Use and Health. Adjusted for age, sex race/ethnicity and education.

A

Low income defined as ≤200% of the Federal Poverty Level (FPL).

3.2. Background characteristics of adults with substance use disorders

Most low-income adults in this nationally representative sample had continuous health insurance during the year before the survey. In the weighted sample, approximately 65.66% were continuously insured, 17.03% were discontinuously insured, and 17.31% were uninsured during this period. Of those with continuous coverage, 42.11% had any private insurance, 46.91% had Medicaid, but not private insurance, and 10.98% had another type of insurance. Of those with discontinuous coverage, 43.66% had any private insurance, 48.48% had Medicaid, but not private insurance, and 7.86% had another type of insurance (Data Not Shown in Tables).

As compared to the groups with continuous or discontinuous coverage, those without coverage included a higher percentage of males (75.63% vs. 55.39% and 57.60%, respectively) and a higher percentage of Hispanic adults (33.30% vs. 17.55% and 19.70%, respectively) (Table 2). Among those with discontinuous coverage, the mean number of months in the past year without coverage was 4.5 (SD=3.1). In relation to continuously and discontinuously insured groups, adults without past year coverage were also less likely to be aged 18–25 years (22.88% vs. 35.55% and 34.20%) and more likely not to have graduated from high school (36.12% vs. 20.41% and 19.69%, respectively).

Table 2.

Background socio-demographic characteristics of low-income adults with substance use disorders by level of health insurance coverage, 2015–2019A

Adults with Continuous Insurance (n=6,253) Adults with Discontinuous Insurance (n=1,636) Adults without Insurance (n=1,354)
% (SE) % (SE) % (SE)
Characteristics
Age, years
 18–25 35.55 (0.77) 34.20 (1.21) 22.88 (1.46)
 26–34 20.58 (0.75) 33.16 (1.81) 31.78 (2.01)
 35–49 23.55 (0.77) 20.03 (1.29) 29.55 (1.80)
 50–64 20.32 (0.96) 12.62 (1.82) 15.79 (2.29)
Sex
 Male 55.39 (1.13) 57.60 (1.87) 75.63 (1.50)
 Female 44.61 (1.13) 42.40 (1.87) 24.37 (1.50)
Race/Ethnicity
 White, non-Hispanic 55.23 (1.13) 54.41 (1.56) 44.77 (2.00)
 Black, non-Hispanic 18.09 (0.78) 18.28 (1.50) 17.91 (1.76)
 Hispanic 17.55 (0.90) 19.70 (0.97) 33.30 (2.26)
 Other 9.12 (0.65) 7.60 (0.91) 4.02 (0.57)
Education
 < High school 20.41 (0.77) 19.69 (1.21) 36.12 (2.07)
 High school graduate 32.70 (0.88) 34.75 (1.78) 35.56 (1.71)
 Some college 36.07 (0.90) 34.65 (1.94) 23.46 (1.52)
 College graduate 10.82 (0.54) 10.91 (1.24) 4.86 (0.69)
Open in a new tab

Data from the 2015–2019 National Survey on Drug Use and Health.

A

Low income defined as ≤200% of the Federal Poverty Level (FPL).

3.3. Health of adults with substance use disorders

There were few significant differences in the health characteristics of the three insurance coverage groups with substance use disorders after controlling for background socio-demographic characteristics (Table 3). Compared to adults without past year insurance, adults with continuous insurance were more likely to have cannabis use disorder and to report a lifetime history of hypertension or a cancer. Adults with continuous insurance were significantly more likely than those with discontinuous insurance to perceive their health as excellent, although they were also more likely to report a lifetime history of cirrhosis or hepatitis. Finally, people with discontinuous insurance were more likely than those without past year insurance to report a lifetime history of cancer.

Table 3.

Prevalence of health characteristics of low income-adults with substance use disorders by level of health insurance in past year, 2015–2019A

Characteristics 1. Adults with Continuous Insurance (n=6,253) 2. Adults with Discontinuous Insurance (n=1,636) 3. Adults without Insurance (n=1,354) Percentage Difference (1–2) Percentage Difference (1–3) Percentage Difference (2–3)
AdjustedB % (SE) AdjustedB % (SE) AdjustedB % (SE) AdjustedB % (95% CI) AdjustedB % (95% CI) AdjustedB % (95% CI)
Substance use disorder, past year
 Alcohol 66.88 (0.90) 67.90 (1.49) 70.26 (1.68) −1.02 (−4.20, 2.16) −3.38 (−7.16, 0.40) −2.36 (−6.88, 2.16)
 Cannabis 24.01 (0.74) 23.52 (1.45) 20.50 (1.23) 0.49 (−2.81, 3.80) 3.51 (0.97, 6.06) 3.02 (−0.49, 6.52)
 Cocaine 6.47 (0.46) 6.14 (0.79) 8.28 (1.28) 0.33 (−1.36, 2.02) −1.81 (−4.33, 0.71) −2.14 (−5.24, 0.96)
 Pain relievers 10.97 (0.49) 12.91 (0.94) 10.38 (1.08) −1.94 (−4.13, 0.25) 0.59 (−1.91, 3.09) 2.52 (−0.06, 5.11)
 Heroin 4.83 (0.38) 4.99 (0.71) 4.50 (0.77) −0.16 (−1.63, 1.30) 0.33 (−1.43, 2.09) 0.49 (−1.68, 2.66)
 OtherC 14.79 (0.57) 15.68 (1.10) 15.38 (1.39) −0.89 (−3.29, 1.50) −0.59 (−3.32, 2.15) 0.30 (−3.15, 3.75)
Alcohol and drug use disorder, past yearD 14.08 (0.62) 16.31 (1.39) 15.26 (1.49) −2.24 (−5.40, 0.93) −1.18 (−4.55, 2.20) 1.06 (−2.75, 4.87)
Self-assessed health
 Fair/poor health 24.75 (0.80) 23.25 (1.58) 23.90 (1.59) 1.49 (−1.88, 4.86) 0.85 (−2.81, 4.51) −0.64 (−5.15, 3.87)
 Good health 34.26 (0.77) 36.70 (1.58) 34.37 (1.89) −2.44 (−6.41, 1.52) −0.11 (−3.96, 3.73) 2.33 (−2.16, 6.83)
 Very good health 27.80 (0.78) 30.11 (1.29) 28.40 (1.44) −2.31 (−5.38, 0.76) −0.60 (−3.99, 2.78) 1.71 (−1.73, 5.14)
 Excellent health 13.10 (0.55) 10.22 (0.87) 13.50 (1.39) 2.88 (1.08, 4.68) −0.40 (−3.42, 2.62) −3.28 (−6.70, 0.14)
Self-reported health condition, lifetime
 Heart disease 19.34 (1.31) 18.75 (2.55) 21.25 (2.99) 0.59 (−4.66, 5.84) −1.91 (−8.99, 5.16) −2.50 (−10.99, 5.99)
 Diabetes 18.54 (1.34) 19.57 (2.73) 17.58 (2.76) −1.03 (−7.00, 4.94) 0.96 (−5.33, 7.24) 1.99 (−5.01, 8.99)
 Chronic obstructive pulmonary disease 15.20 (1.23) 17.38 (3.15) 17.11 (2.78) −2.17 (−9.33, 4.99) −1.91 (−7.34, 3.52) 0.26 (−8.05, 8.58)
 Cirrhosis or hepatitis 5.13 (0.46) 3.37 (0.71) 3.77 (0.85) 1.76 (0.13, 3.39) 1.35 (−0.46, 3.16) −0.41 (−2.53, 1.71)
 Hypertension 34.45 (1.26) 32.36 (2.93) 25.17 (4.18) 2.09 (−3.93, 8.12) 9.28 (0.75, 17.80) 7.19 (−2.77, 17.14)
 Cancer (excluding skin, not melanoma) 2.12 (0.27) 2.16 (0.53) 0.73 (0.34) −0.04 (−1.25, 1.18) 1.40 (0.61, 2.18) 1.43 (0.17, 2.70)
Serious psychological distress
 Present 26.99 (0.96) 30.27 (1.63) 26.50 (2.00) −3.28 (−7.03, 0.48) 0.49 (−3.79, 4.77) 3.77 (−1.36, 8.89)
Open in a new tab

Data from the 2015–2019 National Survey on Drug Use and Health.

A

Low income defined as ≤200% of the Federal Poverty Level (FPL).

B

Percentages and percentage differences adjusted for age, sex, race/ethnicity, and education.

C

“Other” includes hallucinogens, inhalants, methamphetamine, tranquilizers, stimulants, and sedatives.

D

Drug use disorder includes one or more of cannabis, cocaine, pain reliever, heroin, hallucinogens, inhalants, methamphetamine, tranquilizers, stimulants, and sedative use disorder in past year.

3.4. Healthcare use of adults with substance use disorders

After adjusting for socio-demographic characteristics, a significantly larger percentage of continuously or discontinuously insured than uninsured low-income adults with substance use disorders reported past year hospitalizations and emergency visits (Table 4). Various types of outpatient care visits also tended to be highest for the group with continuous insurance coverage, closely followed by those with discontinuous coverage, and lowest for those without past year coverage. People with continuous coverage were significantly more likely than those without coverage to have received at least one outpatient care visit, substance use treatment visit, and screening for tobacco use in the past year. In addition, among those with psychological distress, the continuously insured adults were more likely than the uninsured adults to have received mental health treatment. Similarly, among those with hypertension, the continuously insured adults were more likely than the uninsured adults to have received antihypertensive medications. Similar differences in treatment were also observed in comparisons between adults with discontinuous coverage and no coverage.

Table 4.

Differences in health care access of low-income adults with substance use disorders by level of health insurance in past year, 2015–2019A

Health Care Access Group 1. Adults with Continuous Insurance (n=6,253) 2. Adults with Discontinuous Insurance (n=1,636) 3. Adults without Insurance (n=1,354) Percentage Difference (1–2) Percentage Difference (1–3) Percentage Difference (2–3)
AdjustedB % (SE) AdjustedB % (SE) AdjustedB % (SE) AdjustedB % (95% CI) AdjustedB % (95% CI) AdjutedB % (95% CI)
Health care access group
One or more hospitalizations, past year 15.58 (0.76) 15.11 (1.37) 9.24 (1.04) 0.47 (−2.45, 3.39) 6.33 (3.68, 8.99) 5.86 (2.66, 9.07)
One or more emergency visits, past year 45.57 (0.98) 45.76 (1.54) 33.33 (1.56) −0.18 (−4.34, 3.98) 12.24 (8.48, 16.00) 12.42 (7.81, 17.04)
One or more outpatient care visit, past year 79.04 (0.71) 71.27 (1.74) 53.39 (2.02) 7.76 (3.94, 11.58) 25.65 (21.19, 30.10) 17.89 (12.60, 23.17)
Substance use treatment, past year 15.61 (0.67) 14.83 (1.30) 11.03 (1.14) 0.78 (−2.32, 3.88) 4.59 (1.72, 7.45) 3.81 (0.50, 7.12)
Screened for tobacco use, past year 65.99 (0.78) 63.14 (1.64) 46.06 (1.74) 2.86 (−0.62, 6.33) 19.93 (16.39, 23.48) 17.07 (12.66, 21.49)
Mental health care, past yearC 40.85 (1.65) 35.54 (2.89) 19.13 (3.09) 5.31 (−0.39, 11.01) 21.71 (15.11, 28.32) 16.40 (7.28, 25.53)
Medications for hypertension, past yearD 62.55 (2.70) 52.61 (6.58) 32.85 (9.11) 9.94 (−2.54, 22.42) 29.71 (11.76, 47.65) 19.76 (−4.58, 44.11)
One or more healthcare visit, past year E
 Heart disease 88.73 (2.31) 79.99 (5.18) 69.33 (5.37) 8.74 (−2.38, 19.86) 19.40 (9.26, 29.54) 10.66 (−3.54, 24.86)
 Diabetes 92.29 (2.13) 91.70 (6.06) 83.41 (7.32) 0.59 (−11.72, 12.91) 8.88 (−6.30, 24.07) 8.29 (−9.62, 26.20)
 Chronic obstructive pulmonary disease 92.66 (1.70) 89.73 (5.32) 75.26 (10.30) 2.93 (−7.90, 13.76) 17.39 (−3.44, 38.23) 14.46 (−9.01, 37.94)
 Cirrhosis or hepatitis 91.90 (2.07) 90.90 (3.93) 43.10 (10.90) 1.00 (−7.26, 9.25) 48.79 (26.96, 70.63) 47.80 (26.67, 68.93)
 Hypertension 90.27 (1.57) 88.90 (4.01) 66.47 (6.45) 1.37 (−6.89, 9.63) 23.79 (10.76, 36.83) 22.42 (7.31, 37.54)
 Cancer (excluding skin, not melanoma) 70.43 (6.72) 64.35 (13.10) 27.90 (23.87) 6.08 (−24.83, 36.99) 42.53 (−8.03, 93.08) 36.45 (−24.29, 97.19)
One or more healthcare visit, past year F
 Fair/poor health 85.26 (1.59) 78.00 (3.87) 56.76 (4.06) 7.26 (−0.49, 15.02) 28.50 (19.35, 37.64) 21.23 (10.09, 32.38)
 Good health 77.99 (1.16) 66.60 (2.91) 54.62 (4.09) 11.39 (5.46, 17.32) 23.38 (14.52, 32.24) 11.99 (2.54, 21.43)
 Very good health 77.11 (1.44) 71.15 (2.62) 49.94 (3.17) 5.96 (0.93, 10.99) 27.17 (19.80, 34.54) 21.21 (13.89, 28.53)
 Excellent health 74.21 (2.50) 73.71 (3.88) 52.30 (4.46) 0.49 (−8.17, 9.16) 21.91 (11.19, 32.62) 21.41 (8.42, 34.41)
Open in a new tab

Data from the 2015–2019 National Survey on Drug Use and Health.

A

Low income defined as ≤200% of the Federal Poverty Level (FPL)

B

Percentages and percentage differences adjusted for age, sex, race/ethnicity, and education

C

Analysis limited to respondents with serious psychological distress.

D

Analysis limited to respondents with self-reported lifetime diagnosis of hypertension.

E

Analysis limited, respectively, to respondents who endorsed a lifetime history of heart disease, diabetes, chronic obstructive pulmonary disease, cirrhosis or hepatitis, hypertension, of cancer (excluding skin or melanoma).

F

Analysis limited, respectively, to respondents with fair/poor, good, very good, and excellent, self-perceived health.

Differences were also observed in the percentage of the three coverage groups with specific medical conditions that had received past year outpatient care visits (Table 4). These differences were particularly pronounced among individuals with cirrhosis or hepatitis in which 91.90% of respondents with continuous coverage, 90.90% with discontinuous coverage, but only 43.10% without coverage reported receiving at least one healthcare visit in the past year. Across each level of perceived health, adults with continuous and discontinuous coverage were significantly more likely than those without coverage to report a past year outpatient care visit. Among people in good or very good health, those with continuous coverage were also more likely than those with discontinuous coverage to report a past year outpatient care visit. The group differences in healthcare use were little changed in a sensitivity analysis that also controlled for self-perceived health status (Table S1).

In a sub-analysis of continuously insured low-income adults with substance use disorders, adults with Medicaid were less likely than those with either private or other insurance to have been hospitalized, received an emergency visit, or received substance use treatment in the past year (Table 5). A similar proportion of each coverage group received at least one healthcare visit during this period. Among those reporting fair or poor health, however, a lower percentage of those with Medicaid than with other insurance received a past year healthcare visit. By contrast, among those with serious psychological distress, the Medicaid group was more likely than the group with other insurance to have received mental healthcare. Among those with heart disease, however, the other insurance group was more likely than those with Medicaid or private insurance to have received a healthcare visit.

Table 5.

Differences in health care access of continuously insured low-income adults with substance use disorders by insurance type in past year, 2015–2019A

Health Care Access Group 1. Adults with Continuous Medicaid Insurance (n=2,886) 2. Adults with Continuous Private Insurance (n=2,707) 3. Adults with Continuous Other InsuranceB (n=660) Percentage Difference (1–2) Percentage Difference (1–3) Percentage Difference (2–3)
AdjustedC % (SE) AdjustedC % (SE) AdjustedC % (SE) AdjustedC % (95% CI) AdjustedC % (95% CI) AdjustedC % (95% CI)
Health care access group
One or more hospitalizations, past year 9.39 (0.98) 20.10 (1.20) 17.85 (2.09) −10.70 (−13.62, −7.78) −8.46 (−13.21, −3.70) 2.24 (−2.65, 7.14)
One or more emergency visits, past year 36.39 (1.45) 53.31 (1.50) 46.62 (2.84) −16.92 (−20.95, −12.89) −10.23 (−16.73, −3.73) 6.69 (0.47, 12.91)
One or more outpatient care visit, past year 78.59 (1.36) 81.80 (0.84) 77.93 (2.43) −3.21 (−6.50, 0.08) 0.65 (−4.78, 6.09) 3.87 (−1.41, 9.15)
Substance use treatment, past year 9.53 (0.97) 20.19 (0.98) 14.43 (1.97) −10.66 (−13.45, −7.86) −4.89 (−9.23, −0.55) 5.76 (1.42, 10.11)
Screened for tobacco use, past year 66.73 (1.63) 68.67 (1.15) 64.22 (2.58) −1.94 (−6.11, 2.24) 2.51 (−3.81, 8.84) 4.45 (−1.44, 10.33)
Mental health care, past yearD 46.39 (2.21) 41.47 (2.66) 34.10 (5.24) 4.92 (−2.36, 12.20) 12.29 (1.57, 23.01) 7.37 (−3.53, 18.26)
Medications for hypertension, past yearE 66.70 (5.22) 65.12 (3.91) 57.98 (8.75) 1.58 (−11.41, 14.57) 8.72 (−11.07, 28.50) 7.14 (−14.42, 28.70)
One or more healthcare visit, past year F
 Heart disease 80.11 (5.70) 91.41 (2.55) 99.12 (0.66) −11.30 (−23.74, 1.14) −19.00 (−30.10, −7.90) −7.70 (−13.02, −2.39)
 Diabetes 95.64 (2.50) 92.12 (2.57) 88.43 (6.27) 3.52 (−3.33, 10.38) 7.21 (−6.15, 20.57) 3.68 (−8.88, 16.25)
 Chronic obstructive pulmonary disease 92.30 (4.70) 93.52 (1.80) 95.77 (3.13) −1.23 (−11.57, 9.12) −3.47 (−14.65, 7.71) −2.24 (−9.18, 4.69)
 Cirrhosis or hepatitis 67.94 (9.50) 70.38 (6.10) 76.72 (13.90) −2.45 (−27.78, 22.89) −8.78 (−46.38, 28.82) −6.33 (−41.00, 28.34)
 Hypertension 88.60 (3.67) 91.36 (1.85) 92.29 (4.09) −2.76 (−10.98, 5.46) −3.69 (−15.07, 7.70) −0.93 (−9.58, 7.73)
 Cancer (excluding skin, not melanoma) 69.65 (25.05) 64.31 (14.21) 40.86 (22.73) 5.35 (−47.80, 58.49) 28.79 (−49.92, 107.51) 23.44 (−40.79, 87.68)
One or more healthcare visit, past year G
 Fair/poor health 80.43 (3.24) 88.24 (1.77) 85.51 (4.61) −7.81 (−15.59, −0.03) −5.08 (−16.20, 6.04) 2.73 (−5.91, 11.37)
 Good health 78.97 (2.05) 79.09 (1.76) 80.99 (2.56) −0.12 (−5.68, 5.44) −2.02 (−8.03, 3.99) −1.90 (−8.62, 4.82)
 Very good health 76.93 (2.00) 80.30 (2.38) 73.58 (5.20) −3.37 (−10.20, 3.45) 3.35 (−6.65, 13.34) 6.72 (−5.36, 18.81)
 Excellent health 78.31 (3.03) 76.34 (3.60) 63.00 (6.97) 1.97 (−7.76, 11.69) 15.31 (1.01, 29.61) 13.34 (−0.56, 27.25)
Open in a new tab

Data from the 2015–2019 National Survey on Drug Use and Health.

A

Low income defined as less than or equal to 200% of the Federal Poverty Level (FPL)

B

Other insurance includes Medicare, CHAMPUS, CHAMPVA, Tricare, VA, Military, and any other insurance. Analysis excludes.

C

Percentages and percentage differences adjusted for age, sex, race/ethnicity, and education

D

Analysis limited to respondents with serious psychological distress (n1=2,843, n2=2,654, n3=652).

E

Analysis limited to respondents with self-reported lifetime diagnosis of hypertension (n1=188, n2=281, n3=72). .

F

Analysis limited, respectively, to respondents who endorsed a lifetime history of heart disease (n1=104, n2=160, n3=49), diabetes (n1=79, n2=194, n3=32), chronic obstructive pulmonary disease (n1=67, n2=143, n3=25), cirrhosis or hepatitis (n1=49, n2=162, n3=17), hypertension (n1=186, n2=272, n3=71), of cancer (excluding skin or melanoma) (n1=30, n2=50, n3=10).

G

Analysis limited, respectively, to respondents with fair/poor (n1=327, n2=686, n3=134), good (n1=834, n2=951, n3=239), very good (n1=1,118, n2=673, n3=172), and excellent, self-perceived health (n1=558, n2=306, n3=92).

4. Discussion

Approximately one third of low-income US adults with substance use disorders had either discontinuous or no health insurance coverage. Despite roughly similar health profiles, those with no insurance coverage were less likely than those with discontinuous or continuous coverage to receive inpatient care, emergency visits, and a range of outpatient services including substance use treatment, mental health treatment, and medical care. While the cross sectional design of this analysis restricts causal conclusions, these corelations raise the possibility that insurance coverage, which enables healthcare use in the general population (Sommers et al., 2017), may operate similarly among low-income adults with substance use disorders. If this were true, policies and interventions that expand healthcare coverage for uninsured low-income adults with substance use disorders would increase their access to needed healthcare services.

Adults with substance use disorders face complex health and mental health challenges. As compared to low-income adults without substance use disorders, those with substance use disorders were more likely to report fair or poor self-reported health, chronic obstructive pulmonary diseases, (presumably related to a high prevalence of smoking) (Weinberger et al., 2016), and chronic liver diseases (presumably due to alcoholic cirrhosis from persistant heavy alcohol use (Otete et al., 2016) or from hepatitis C related to intravenous drug use (Abara et al., 2019)). Low-income adults with substance use disorders were also roughly three times more likely than their counterparts without substance use disorders to have serious psychological distress. Substance use disorders have previously been strongly related to serious psychological distress among veterans (Golub et al., 2013). The high prevalence of serious psychological distress among adults with substance use disorders might be a consequence of direct effects of substance use on regulation of mood or anxiety (Koob & Volkow, 2016) or an indirect effect of substance use on stressful life circumstances, such as unemployment or marital instability, that are connected to serious psychological distress (Dhringa et al., 2011). In the context of these various health and behavioral health threats, health insurance may provide a key policy lever for helping low-income adults with substance use disorders into care.

Among low-income people with substance use disorders, lack of coverage was broadly related to a significantly lower likelihood of receiving healthcare services. Contrary to our expectations, there was no evidence that the lower use of outpatient services by the uninsured group was related to a compensatory increase in their use of inpatient or emergency services. The uninsured group was less likely than the continuously and discontinuously insured groups to receive inpatient and emergency services. This difference was observed despite the federal Emergency Medical Treatment and Labor Act, which requires anyone presenting to an emergency department to receive treatment regardless of insurance status. A prior general population analysis and facility-based analysis also reported that uninsured adults used emergency services less than Medicaid insured adults (Zhou et al., 2017).

The consequences of lower healthcare access for the uninsured group were evident in the treatment of hypertension, a chronic condition that was reported by roughly one-third to one-quarter of the low-income adults with substance use disorders and was somewhat less common than objectively measured hypertension in the general adult population (22.4%, aged 18–39 years, 54.5%, ages 40–59 years) (Ostchega et al., 2020). Among low-income adults with substance use disorders who reported having hypertension, those without insurance were approximately half as likely to have received medication treatment (32.8% vs. 62.6%) in the last year. Because untreated hypertension is the leading contributor to all-cause death and disability (Forouzanfar et al., 2015) through its role in risk of cardiovascular disease, chronic kidney disese, and cognitive impairment, the large gap in hypertension treatment likely has serious adverse health effects for uninsured low-income adults with substance use disorders.

Also contrary to our expectations, there were few significant differences in the self-reported health status of uninsured, discontinously insured, and continuously insured low-income adults with substance use disorders. These findings contrast with the observation in the general population that uninsured compared to insured adults have an increased risk of poor health, even after controlling for background demographic characteristics (Powell-Griner et al., 1999). One practical implication of the present findings for policymakers is that given that the uninsured group has a generally similar health profile as the insured group, the healthcare costs of covering the uninsured group may not be substantially higher than that of covering the insured group.

Among low-income adults with substance use disorders, men, individuals with less formal education, and Hispanics were disproportionately uninsured. Similar coverage patterns have been reported in the general population (Cha et al., 2020). These findings emphasize the importance of extending outreach efforts to increase coverage to these low-income groups. Assisting these groups with Medicaid enrollment or with gaining private coverage through health exchanges may be facilitated by navigators and social workers who have experience in advocating for people with substance use disorders and who are knowledgeable concerning the local health insurance enrollment processes (McCabe et al., 2016). For Hispanic adults who are uninsured, outreach efforts may be more effective if they are culturally sensitive and available in Spanish and English (Doty et al., 2014), while for adults with lower educational attainment, outreach efforts might be more effective if they accommodate lower health insurance literacy.

There were also few differences in the healthcare profile of low-income adults with substance use disorders who had continuous and discontinuous coverage, yet the group with discontinuous coverage was less likely to report a past year outpateint care visit. Similar findings have been reported from a sample of primary care patients with continuous and discontinuous Medicaid coverage (Seo et al., 2019). These findings suggest that policies that reduce discontinuities in coverage could alleviate barriers for obtaining medical care. For example, although Federal regulations require Medicaid eligibility recertification on at least an annual basis (Bindman et al., 2008), several states require more frequent recertification45 that could contribute to increased discontinuities in coverage.

4.1. Limitations

Several limitations of this study should be considered. First, healthcare coverage and service use were assessed by self-report and therefore were vulnerable to recall and social desirability biases. Second, NSDUH did not evaluate the continuity, quality, or effectiveness of the healthcare services that may be influenced by healthcare coverage. Furthermore, healthcare coverage was considered in the aggregate and important differences likely exist in service access across type of coverage (Bouchery et al., 2012). Third, homeless populations are outside of the NSDUH sampling frame. A capture-recapture analysis, which overcame this limitation, found that the total population with opioid use disorder was substantially larger than that reported by NSDUH findings (Barcoas et al., 2018). Fourth, incarcerated people are also outside of the NSDUH sampling frame. Available evidence suggests that only a small minority of incarcerated adults has health insurance (Wang et al., 2008). Although correctional facilities are required to provide health services, many adults with substance use or other mental health problems do not receive treatment for their conditions during their incarcerations (Belenko et al., 2013; Gonzalez & Connor, 2014). Fifth, because the public use NSDUH files do not include place of residence, we were unable to control for state level factors that may be associated with insurance coverage and the outcomes of interest. More generally, residual confounding might account for some or all of the observed group differences. Finally, because of the study’s cross sectional design, causal relationships can not be inferred from assocations between coverage and service use. Moreover, health status and group differences in health and healthcare use may be confounded by unmeasured health behaviors, environmental influences, and other factors thereby further limiting causal inferences. For example, if people with a strong proclivity for seeking care preferentially obtained insurance, such selection could account for the observed assocations independent of the effects of coverage itself. However, the analyses were controlled for several potentially confounding socio-demographic variables and financial barriers that have been reported as common reasons for not receiving treatment among uninsured adults with substance use disorders (Saloner et al., 2017).

4.2. Conclusion

In the present cross sectional analysis, consistent healthcare coverage was associated with greater access to substance use, mental health, and medical care services for low-income adults with substance use disorders. Although these patterns raise the possibility that expanding healthcare benefits for this population might have health benefits, prior quasi-experimental research has found that implementation of Medicaid expansion was not associated with a significant increase in substance use treatment (Creedon & Le Cook, 2016; Saloner et al., 2017; Olfson et al., 2018). Future prospective research, which randomly assigns patients to different levels of insurance (Baicker et al., 2011), is needed to determine whether expansion of healthcare coverage for uninsured low-income adults with substance use disorders increases their access to needed services.

To increase healthcare coverage to this population, consideration should be given to Medicaid expansion under the Affordable Care Act for the 12 remaining states (Kaiser Family Foundation, 2021), re-investing in promotion of outreach for Marketplace exchanges (Anderson & Shafer, 2019), and simplifying Medicaid enrollment and recertification processes. While expanding coverage might increase service access for uninsured people with substance use disorders, low rates of treatment for substance use, mental health, and general medical problems, even among adults with substance use disorders with coverage, including especially low substance use treatment rates among individuals with Medicaid coverage, underscore the scope of the challenge. These findings emphasize the need to complement insurance coverage reform with programs and policies that address other structural and logistical barriers to appropriate service use in this population. At the same time, the healthcare consequences of unisurance for low-income adults with substance use disorders appear real and strengthen the argument for universal healthcare coverage.

Supplementary Material

1

Highlights.

1 in 3 low-income US adults with substance use disorders have gaps or no insurance

Compared to insured adults, the uninsured were less likely to receive SUD treatment

They were also less likely to receive medical care including hypertension treatment

Acknowledgements

This work was supported by NIDA R01 DA039137.

Funding sources

Drs. Olfson, Mauro, Wall, Barry, Mojtabai and Ms. Choi were supported by NIDA R01 DA019606.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Declaration of competing interest

None.

References

  1. Abara WE, Trujillo L, Broz D, Finlayson T, Teshale E, Paz-Bailey G,…Braunstein S (2019). Age-related differences in past or present hepatitis C virus infection among people who inject drugs: National Human Immunodeficiency Virus Behavioral Surveillance, 8 US cities, 2015. Journal of Infectious Diseases, 220(3), 377–385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. American Psychiatric Association. Diagnostic and statistical manual of mental disorders : DSM-IV. 4th ed. Washington, DC: American Psychiatric Association, 1994. [Google Scholar]
  3. Anderson D & Shafer P (2019). The Trump effect: post-inauguration changes in Marketplace enrollment. Journal of Health Politics Policy and Law, 2019,44(5),715–736. [DOI] [PubMed] [Google Scholar]
  4. Artenie A, Justras-Aswad D, Roy E, Zang G, Bamvita JM, Levesque A & Bruneau J (2015). Visits to primary care physicians among persons who inject drugs at high risk of hepatitis C virus infection: room for improvement. Journal of Viral Hepatitis, 22(10),792–799. [DOI] [PubMed] [Google Scholar]
  5. Bahorik A, Satre D, Kline-Simon A, Weisner C & Campbell C (2017). Alcohol, cannabis, and opioid use disorders, and disease burden in an integrated system. Journal of Addiction Medicine, 11(1),3–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Baicker K, Taubman SL, Allen HL, Bernstein M Gruber JH, Newhouse JP, …Oregon Health Study Group. (2013). The Oregon experiment - effects of Medicaid on clinical outcomes. New England Journal of Medicine 368,1713–1722. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Barocas JA, White LF, Wang J, Walley AY, LaRochelle MR, Benson D… Linas BP (2018). Estimated prevalence of opioid use disorder in Massachusetts, 2011–2015: A capture–recapture Analysis. American Journal of Public Health 108,1675–1681. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Belenko S, Hiller M & Hamilton L (2013). Treating substance use disorders in the criminal justice system. Current Psychiatry Reports, 15(11):414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Berkowitz SA, Seligman HK, Rigdon J, Meigs JB, & Basu S (2017). Supplemental Nutrition Assistance Program (SNAP) participation and health care expenditures among low-income adults. JAMA Internal Medicine 177,(11),1642–1649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bindman AB, Chattopadhyay A & Auerback GM (2008). Medicaid re-enrollment policies and children’s risk of hospitalizations for ambulatory care sensitive conditions. Medical Care, 46,1049–1054. [DOI] [PubMed] [Google Scholar]
  11. Bouchery EE, Harwood JH, Dilonardo J & Vandivort-Warren R (2012). Health insurance and the substance abuse treatment gap. Journal of Substance Abuse Treatment, 42,289–300. [DOI] [PubMed] [Google Scholar]
  12. Center for Behavioral Health Statistics and Quality. 2019. National Survey on Drug Use and Health: Methodological summary and definitions. Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/ [Google Scholar]
  13. Cha AE & Cohen RA (2020). Reasons for being uninsured among adults aged 18–64 in the United States, 2019. NCHS Data Brief, no 382. Hyattsville, MD: National Center for Health Statistics. [PubMed] [Google Scholar]
  14. Creedon TB & Le Cook B (2016). Access to mental health care increased but not for substance use, while disparities remain. Health Affairs, 35(6),1017–1021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Cummings JR, Wen H, Ko M, & Druss BG (2014). Race/ethnicity and geographic access to Medicaid substance use disorder treatment facilities in the United States. JAMA Psychiatry, 71(2),190–196. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Dhringa SS, Zack MM, Strine TW, Druss BG, Berry JT & Balluz LS (2011). Psychological distress severity of adults reporting receipt of treatment for mental health problems in the BRFSS. Psychiatric Services, 62(4),396–403. [DOI] [PubMed] [Google Scholar]
  17. Doty MM, Rasmussen PW, & Collins SR (2014). Catching up: Latino health coverage gains and challenges under the Affordable Care Act: results from the Commonwealth Fund Affordable Care Act Tracking Survey. Issue Briefs (Commonwealth Fund), 26,1–15. [PubMed] [Google Scholar]
  18. Edlund MJ, Booth BM, & Han X (2012). Who seeks care where? Utilization of mental health and substance use disorder treatment in two national samples of individuals with alcohol use disorders. Journal of Studies on Alcohol and Drugs, 73,635–646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Forouzanfar MH, Afshin A, Alexander LT, Anderson HR, Bhutta ZA, Biryukov S…Murray CJL(2015). Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet, 388,1659–1724. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. GBD 2019 Diseases and Injuries Collaborators (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study, 2019. Lancet 396,12041222. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Golub A, Vazan P, Bennett AS, & Liberty HJ (2013). Unmet need for treatment of substance use disorders and psychological distress among veterans: a nationwide analysis using the NSDUH. Military Medicine, 178(1),107–114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Gonzalez JMR & Connell NM (2014). Mental health of prisoners: identifying barriers to mental health treatment and medication continuity. American Journal of Public Health, 104(12), 23282–333. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Jordan BK, Karg RS, Batts KR, Epstein JF & Wiesen C (2008). A clinical validation of the National Survey on Drug Use and Health assessment of substance use disorders. Addictive Behaviors, 33(6),782–798. [DOI] [PubMed] [Google Scholar]
  24. Kaiser Family Foundation, Status of state action on the Medicaid expansion decision. https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-careact/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D Accessed February 28, 2021.
  25. Kaestner R & Lubotsky D (2016). Health insurance and income inequality. Journal of Economic Perspectives, 30(2),53–78. [DOI] [PubMed] [Google Scholar]
  26. Keisler-Starkey K & Bunch LN Census Bureau Current Population Reports, P60–271 (2020). Health insurance coverage in the United States: 2019, U.S. Government Publishing Office, Washington, DC. https://www.census.gov/content/dam/Census/library/publications/2020/demo/p60-271.pdf [Google Scholar]
  27. Kessler RC, Barker PR, Colpe LJ, Epstein JF, Gfroerer JC Hiripi E…, Zaslavsky AM (2003). Screening for serious mental illness in the general population. Archives of General Psychiatry, 60(2),184–189. [DOI] [PubMed] [Google Scholar]
  28. Koob GF & Volkow ND (2016), Neurobiology of addiction: a neurocircuitry analysis. Lancet Psychiatry, 3(8),760–773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lasser KE, Kim TW, Alford DP, Cabral H, Saitz R & Samet JH (2011). Is unhealthy substance use associated with failure to receive cancer screening and flu vaccination? A retrospective cross-sectional study. BMJ Open, 7,1 (1): e0000046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Lewer D, Freer J,, King E, Larney S, Degenhardt L, Tweed EJ…Morley KI (2020). Frequency of health-care utilization by adults who use illicit drugs: a systematic review and meta-analysis. Addiction, 115(6),1011–1023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. McCabe HA & Wahler EA (2016). The Affordable Care Act, substance use disorders, and low-income clients: implications for social work. Social Work, 61(3),227–233. [DOI] [PubMed] [Google Scholar]
  32. McFarland BH, Lynch FL, Freeborn DK, Green CA, Polen MR, Deck DD & Dickinsen DM (2006). Substance abuse treatment duration of Medicaid versus commercial clients in a health maintenance organization. Medical Care, 44, 601–606. [DOI] [PubMed] [Google Scholar]
  33. McKenna RM, Langellier BA, Alcala HE, Roby DH, Grande DT & Ortega AN (2018). The Affordable Care Act attenuates financial strain according to poverty level. Inquiry 55,1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. McWilliams JM, Zaslavsky AM, Meara E, & Ayanian JZ (2004). Health insurance coverage and mortality among the near-elderly. Health Affairs, 23(4),223–233. [DOI] [PubMed] [Google Scholar]
  35. Olfson M, Blanco C, Wall M, Liu SM & Grant B (2019). Treatment of common mental disorders in the United States, results from the National Epidemiological Survey on Alcohol and Related Conditions-III. Journal of Clinical Psychiatry, 28(3),18m12532. [DOI] [PubMed] [Google Scholar]
  36. Olfson M, Wall M, Barry CL, Mauro C & Mojtabai R (2018). Impact of Medicaid expansion on coverage and treatment of low-income adults with substance use disorders. Health Affairs, 37(8),1208–1215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Ostchega Y, Fryar CD, Nwankwo T & Nguyen DT (2020). Hypertension prevalence among adults aged 18 and over: United States, 2017–2018. NCHS Data Brief, no 364. Hyattsville, MD: National Center for Health Statistics. [PubMed] [Google Scholar]
  38. Otete HE, Orton E, Fleming KM & West J (2016). Alcohol-attributable healthcare attendances up to 10 years prior to diagnosis of alcoholic cirrhosis: a population based case-control study. Liver International, 36(4),538–546. [DOI] [PubMed] [Google Scholar]
  39. Powell-Griner E, Bolen J & Bland S (1999). Health care coverage and use of preventive services among the near elderly in the United States. American Journal of Public Health, 86(6),882–886. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Ross DC & Cox L (2005). In a time of growing need: state choices influence health coverage access for children and families: a 50 state update on eligibility rules, enrollment and renewal procedures, and cost-sharing practices in Medicaid and SCHIP for children and families. Menlo Park, CA: The Henry J. Kaiser Family Foundation. Available at: http://www.cbpp.org/archiveSite/10-18-05health.pdf. [Google Scholar]
  41. Ross LE, Vigod S, Wishart J, Waese M, Spence JD, Oliver J…Shields R. (2105). Barriers and facilitators for people with mental health and/or substance use issues: a qualitative study. BMC Family Practice, 16,135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Saloner B, Bandara S, Bachhuber M & Barry CL (2017). Insurance coverage and treatment use under the Affordable Care Act among adults with mental and substance use disorders. Psychiatric Services, 68(6),542–548. [DOI] [PubMed] [Google Scholar]
  43. Seo V, Baggett TP, Thorndike AN, Hull P, Newhouse JP & Fung V (2019). Access to care among Medicaid and uninsured patients in community health centers after the Affordable Care Act. BMC Health Services Research, 19,291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Singh AC, Grau EA, & Folsom RE, (2002). Predictive Mean Neighborhood Imputation with application to the person-pair data of the National Household Survey on Drug Abuse. Proceedings of the American Statistical Association, Survey Research Methods Section. [Google Scholar]
  45. Shartzer A, Long SK & Anderson N (2016). Access to care and affordability have improved following Affordable Care Act implementation; problems remain. Health Affairs, 35,161–168. [DOI] [PubMed] [Google Scholar]
  46. Sommers BD, Gawande AA, & Baicker K (2017). Health insurance coverage and health- what the recent evidence tells us. New England Journal of Medicine, 377(6),586–593. [DOI] [PubMed] [Google Scholar]
  47. Sommers BD, Gunja MZ, Finegold K & Musco T (2015). Changes in self-reported insurance coverage, access to care, and health under the Affordable Care Act. JAMA, 314(4),366–374. [DOI] [PubMed] [Google Scholar]
  48. Sommers BD, Long SK & Baicker K (2014). Changes in mortality after Massachusetts’ health care reform: a quasi-experimental study. Annals of Internal Medicine, 160,585–593. [DOI] [PubMed] [Google Scholar]
  49. Substance Abuse and Mental Health Services Administration (2010). Reliability of key measures in the National Survey on Drug Use and Health Rockville, MD: Substance Abuse and Mental Health Services Administration. Available from: https://www.samhsa.gov/data/sites/default/files/2k6ReliabilityP/2k6ReliabilityP.pdf. [PubMed] [Google Scholar]
  50. Tarazi WW, Bradley CJ, Bear HD, Harless DW & Sabik LM (2017). Impact of Medicaid disenrollment in Tennessee on breast cancer stage at diagnosis and treatment. Cancer, 123,3312–3319. [DOI] [PubMed] [Google Scholar]
  51. Tsuchiya K, Leung CW, Jones AD & Caldwell CH (2020). Multiple financial stressors and serious psychological distress among adults in the USA. International Journal of Public Health, 65(3),335–344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. US Census Bureau, HI-01 Health insurance coverage status and type of coverage by selected characteristics. https://www.census.gov/data/tables/time-series/demo/income-poverty/cps-hi/hi-01.2017.html Accessed July 28, 2021.
  53. US Census Bureau, Poverty thresholds. https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html Accessed February 28, 2021.
  54. Wang EA, White MC, Jamison R, Goldenson J, Estes M & Tulsky JP (2008). Discharge planning and continuity of health care: findings from the San Francisco County Jail. American Journal of Public Health, 98(12), 2182–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Wang N & Xie X (2017). The impact of race, income, drug abuse and dependence on health insurance coverage among US adults. European Journal of Health Economics, 18,537–546. [DOI] [PubMed] [Google Scholar]
  56. Wienberger AH, Funk AP & Goodwin RD (2016). A review of epidemiological research on smoking behavior among persons with alcohol and illicit substance use disorders. American Journal of Preventive Medicine, 92,148–159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wilper AP, Woolhander S, Lasser KE, McCormick D, Bohr DH, & Himmelstein DU (2009a). Hypertension, diabetes, and elevated cholesterol among insured and uninsured US adults. Health Affairs, 28(6),1151–1159. [DOI] [PubMed] [Google Scholar]
  58. Wilper AP, Woolhandler S, Lasser KE, McCormick D, Bohr DH, & Himmelstein DU (2009b). Health insurance and mortality in US adults. American Journal of Public Health, 2009,99(12),2289–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Xu J, Wilk AS, Druss BG & Cummings JR (2019). Effect of Medicaid disenrollment on health care utilization among adults with mental health disorders. Medical Care, 57,574–583. [DOI] [PubMed] [Google Scholar]
  60. Young JQ, Kline-Simon AH, Mordecai DJ & Weisner C (2015). Prevalence of behavioral health disorders and associated chronic disease burden in a commercially insured health system: findings of a case-control study. General Hospital Psychiatry, 37(2),101–108. [DOI] [PubMed] [Google Scholar]
  61. Zhou RA, Baicker K, Taubman S, & Finkelstein AN (2017). The uninsured do not use the emergency department more - they use other care less. Health Affairs, 36(12),2115–2122. [DOI] [PMC free article] [PubMed] [Google Scholar]

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