Use of Drug Treatment Services Among Adults With Opioid Use Disorder: Rates, Patterns, and Correlates
Abstract
Objectives:
The study examined rates, patterns, and correlates of drug treatment services use among adults with opioid use disorder compared with adults with other drug use disorders.
Methods:
Data were from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III, which surveyed a nationally representative sample of noninstitutionalized U.S. civilian adults. The proportions reporting drug treatment services use were compared between those with opioid use disorder and those with other drug use disorders. Multivariable-adjusted regression analyses identified factors associated with service use.
Results:
Adults with opioid use disorder (N=330, unweighted) reported a very low rate of any drug-related health services use (17.3%), although the rate was higher than among adults with other drug use disorders (7.4%) (p<0.001). Crisis-related services were the most common type of service used among adults with opioid use disorder (6.2%)—significantly higher than the rate among those with other drug use disorders (0.6%) (p<0.001). Few (3.3%) adults with opioid use disorder used outpatient drug treatment services. Among all adults with drug use disorders, opioid use disorder was associated with greater odds of using drug treatment services (adjusted odds ratio=2.43; 95% confidence interval=1.38–4.28). Living in the West and reporting moderate to extreme pain were associated with a lower likelihood of service use among all adults with drug use disorders (p<0.05 for each).
Conclusions:
Most adults with opioid use disorder remain untreated, much less received outpatient treatment to address their addiction. Interventions are needed to improve access to and motivation for care among these vulnerable adults.
HIGHLIGHTS
•
About 17.3% of adults with opioid use disorder used any health services for drug addiction treatment in the past year.
•
Among adults with opioid use disorder, crisis-related services were most commonly used (6.2%), and only 3.3% used outpatient drug treatment services.
•
The vast majority of adults with opioid use disorder remains untreated, with few receiving outpatient treatment capable of addressing their addiction.
•
Interventions are needed to improve access to care and motivation for care among these vulnerable adults.
Since the late 1990s, nonmedical use of both opioid analgesics and heroin has grown markedly in the United States, contributing to a catastrophic increase in opioid-related overdose deaths (1, 2). In 2017, about 68% of all drug overdose deaths involved opioids (3, 4), and on average, 130 Americans died every day after an overdose involving opioids (5). It has recently been estimated that about 2.1 million Americans suffered from the adverse effects of opioid use disorder in 2016 (6), profoundly reducing their quality of life and ability to work (7).
As part of the response to the epidemic, providing treatment for opioid use disorder has become a public health priority. In particular, it is important for individuals with opioid use disorder to have access to comprehensive and sustained addiction treatment services. Previous studies have suggested that medication-assisted treatment (e.g., buprenorphine, methadone, and naltrexone) is effective in the treatment of opioid use disorder, but it is effective only as a sustained outpatient treatment over many months or years of outpatient care (8–12). In addition, a systematic review suggested that psychosocial interventions, such as cognitive-behavioral therapy and contingency management, in conjunction with medications are also effective, although effects varied depending on study designs and settings (13).
Providing appropriate treatment services for opioid use disorder is a major national goal. Few studies have examined rates and correlates of service use among individuals with opioid use disorder in the United States (1, 14–19). All have been based on data from the National Survey on Drug Use and Health (NSDUH), administered annually by the Substance Abuse and Mental Health Services Administration (20). The most recent analysis examined changes in service use among individuals with a likely opioid use disorder between 2004 and 2008 and between 2009 and 2013 and concluded that the rate of services use was low, increasing from only 18.8% in 2004–2008 to 19.7% in 2009–2013 (1). These studies have investigated patterns of treatment use in relation to insurance status (17) and, more specifically, in relation to implementation of the Affordable Care Act (16); studies have also looked at patterns across age groups—for example, adolescents (18) and nonelderly adults (16). Additional limitations of previous studies are that they did not differentiate use of potentially long-term outpatient treatment from use of acute hospital, residential, or emergency services; they did not explicitly compare services use among adults with opioid use disorder with use among those with other illicit drug use disorders; and they used the definition of opioid use disorder from the DSM-IV. These distinctions may be important because although short-term emergency and residential services may be essential for resolving acute crises, they are poorly suited to addressing the core problems of drug dependence and addiction, which require long-term treatment, and because patients with opioid use disorder may have to compete for limited resources with other drug users.
Using national survey data from the National Epidemiologic Survey on Alcohol and Related Conditions Wave III (NESARC-III), the study reported here addressed several issues not considered in previous NSDUH-based studies and sought to answer the following questions: What are the rates and patterns of drug-related health services use among adults with opioid use disorder (e.g., acute-emergency and outpatient care)? Do these rates differ from those among adults with drug use disorder diagnoses other than opioid use disorder? When the analysis adjusts for other potential confounders, are these differences altered by factors that affect service use among adults with opioid use disorder and among adults with other illicit drug use disorders? Among adults with opioid use disorder, what sociodemographic and clinical factors are associated with a higher likelihood of using drug-related health services? Understanding these questions may help guide both health care providers and policy makers in expanding access to comprehensive addiction-related services among adults with opioid use disorder across diverse settings (e.g., inpatient, outpatient, and community based).
Methods
Data Source and Study Sample
We examined the restricted version of data from NESARC-III, which is sponsored by the National Institute on Alcohol Abuse and Alcoholism (21). NESARC-III was a nationally representative cross-sectional survey, conducted from April 2012 to June 2013, of diagnoses of physical and mental disorders and use of drug-related services use among noninstitutionalized civilian adults ages 18 and older, with a focus on alcohol and other substance use disorders (22). We limited our sample to adults ages 18 and older who were diagnosed as having past-year illicit drug use disorders (i.e., cannabis, cocaine, heroin, hallucinogen, inhalant-solvent, sedative, stimulant, and club drug) as defined by DSM-5 criteria (N=1,478 unweighted). We classified those with illicit drug use disorders into two groups: those with past-year opioid use disorder (N=330 unweighted) and those with past-year illicit drug use disorders other than opioid use disorder (N=1,148 unweighted). The overall survey response rate for NESARC-III was 60.1% (22). Our study was declared exempt by the Yale School of Medicine Institutional Review Board (IRB) (#2000022543) because we used deidentified secondary data. All research procedures performed in this study are in accordance with the ethical standards of the IRB. Further details of the survey, including descriptions, questionnaires, sampling methodology and data sets, are available on the NESARC-III Web site (21).
Measures
Drug-related health services use.
Survey participants were asked whether they used any of ten drug-related health services for treatment of drug use problems (yes or no). We grouped these services into four clinically meaningful categories: self-help (Narcotics or Cocaine Anonymous, Alcoholics Anonymous, or any 12-step meeting); potentially extended outpatient treatment (family services or another social service agencies; and outpatient mental health or medical clinics, including outreach programs, day or partial hospital programs, or methadone maintenance programs); short-term or residential treatment (drug or alcohol detoxification ward or clinic; inpatient ward of a psychiatric or general hospital or community mental health programs; drug or alcohol rehabilitation programs; or halfway houses, including therapeutic communities); and crisis-related services (emergency room encounters for any reason related to participant’s drug use or crisis center visits for any reason related to participant’s drug use).
Sociodemographic characteristics.
Sociodemographic variables potentially related to service use included age (18–44, 45–64, or ≥65), gender, race-ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other), marital status (married, never married, or other), family income (<$20,000, $20,000–$39,999, or ≥$40,000), employment (percentage employed), education (less than high school, high school or equivalent, some college, or bachelor’s degree or higher), insurance coverage (private insurance, Medicare, Medicaid, or other sources), disability income support (percentage receiving), and geographic region (23, 24).
Behavioral comorbidities.
Using DSM-5 criteria, NESARC-III asked respondents about the following past-year psychiatric disorders (yes or no), including (24, 25) major depressive disorder (hierarchical), dysthymia (hierarchical), bipolar I disorder, generalized anxiety disorder, posttraumatic stress disorder, and panic disorder. Using these variables, we further constructed a dichotomous variable representing any past-year psychiatric disorder. We also included past-year alcohol use disorder and past-year tobacco use disorder as assessed by DSM-5 criteria.
Finally, self-reported pain symptoms in the past 4 weeks (never or a little versus moderately, quite a bit, or extremely) and the mental component summary (MCS) score of the health-related quality-of-life (HRQOL) measure (26–28) were also included. HRQOL MCS was constructed by using the 12-Item Short-Form Health Survey. When constructing HRQOL MCS scores, standardized scoring algorithms were used, in which each 10 points represents a 1 SD difference, with 50 representing the U.S. national average HRQOL MCS score (26, 27).
The physical component summary (PCS) score was not included as a separate measure because it includes the pain measure, which we preferred to examine as a separate measure of special relevance to opioid use disorder.
Data Analysis
First, we estimated the rates and patterns of drug-related health services use among adults with past-year opioid use disorder and adults with illicit drug use disorders other than opioid use disorder . We compared the differences between these two groups by using a weight-corrected Pearson’s chi-square statistic. Second, to identify potentially confounding factors that might also have influenced service use, we identified differences in sociodemographic characteristics and behavioral comorbidities between respondents who used any drug-related health services and those who did not. Using bivariate logistic regression analyses, we report bivariate odds ratios and their statistical significances at the level of p<0.05.
Third, we performed a multivariable logistic regression analysis to understand whether the diagnosis of opioid use disorder was associated with a higher or lower likelihood of using drug-related health services compared with other illicit drug use disorders. We also identified sociodemographic and clinical factors independently associated with drug-related services use. Finally, we used multivariable logistic regression analysis within the group of adults with opioid use disorder to identify sociodemographic and clinical factors associated with a higher likelihood of using drug-related health services in this group.
Results
Rates and Patterns of Drug-Related Health Services Use
Of adults with illicit drug use disorders, those with opioid use disorder reported a low rate of any drug-related health services use (17.3%)—a rate higher than among those with drug use disorders other than opioid use disorder (7.4%) (p<0.001) (Figure 1). Adults with opioid use disorder reported especially low rates of utilizing self-help (3.0%), outpatient clinical services (3.3%), and short-term or residential services (4.9%), and these rates were not significantly different from rates among those with other illicit drug use disorders. Adults with opioid use disorder reported a slightly higher rate (6.2%) of use of crisis-related health services, significantly higher than the rate reported by adults with other illicit drug use disorders (0.6%) (p<0.001). Furthermore, 10.1% of adults with opioid use disorder reported using two or more drug-related health services, and this rate was significantly higher than the rate reported by those with drug use disorders other than opioid use disorder (4.2%) (p<0.001).
FIGURE 1. Prevalence of use of drug-related health services among adults with any past-year illicit drug use disordera
aData are from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III. Percentages are weighted, and vertical bars represent 95% confidence intervals. Use of crisis-related health services and overall health services differed by opioid use disorder status (p<.001).
Sociodemographic Characteristics and Service Use
When data from our analyses were extrapolated from the survey sample to the U.S. population, it was estimated that about 9.1 million U.S. adults were affected by past-year illicit drug use disorders. Of the 9.1 million adults, only 9.7% (0.9 million) used any form of drug-related health services. In addition, of the 9.1 million adults, about 23.1% (2.1 million) were diagnosed as having past-year opioid use disorder. Overall, use of drug-related health services was associated with indicators of lower socioeconomic status (Table 1). For example, compared with those who did not use services, service users were less likely to be employed (p<0.05) or to have an educational level of bachelor’s degree or higher (p<0.05) and were more likely to be covered by Medicaid (p<0.01) or to receive disability income support (p<0.001). In addition, adults with any illicit drug use disorders were more likely to use drug-related health services if they were previously, but not currently, married (i.e., divorced, separated, widowed, and so forth) (p<0.01), and they were less likely to use services if they lived in the West region of the United States, compared with the Northeast (p<0.05).
| Used drug-related health services | ||||
|---|---|---|---|---|
| Yes | No | Total | Bivariate | |
| Characteristic | (N=148) | (N=1,330) | (N=1,478) | OR |
| Age | ||||
| 18–44 (reference) | 70.8 | 75.1 | 74.7 | |
| 45–64 | 28.3 | 21.2 | 21.9 | 1.41 |
| ≥65 | 1.0 | 3.7 | 3.4 | .29 |
| Gender | ||||
| Male (reference) | 56.9 | 61.0 | 60.6 | |
| Female | 43.1 | 39.0 | 39.4 | 1.19 |
| Race-ethnicity | ||||
| Non-Hispanic white (reference) | 67.6 | 61.9 | 62.5 | |
| Non-Hispanic black | 17.4 | 18.0 | 18.0 | .88 |
| Hispanic | 12.0 | 15.0 | 14.7 | .73 |
| Other racial-ethnic group | 3.1 | 5.1 | 4.9 | .55 |
| Marital status | ||||
| Married (reference) | 12.4 | 21.7 | 20.8 | |
| Never married | 44.0 | 48.7 | 48.2 | 1.59 |
| Otherb | 43.7 | 29.6 | 31.0 | 2.59** |
| Family income | ||||
| <$20,000 (reference) | 54.3 | 41.5 | 42.7 | |
| $20,000–$39,999 | 22.4 | 25.7 | 25.4 | .66 |
| ≥$40,000 | 23.3 | 32.8 | 31.9 | .54 |
| Employed (reference: no) | 62.9 | 73.9 | 72.8 | .60* |
| Education | ||||
| Less than high school (reference) | 21.0 | 16.4 | 16.9 | |
| High school or equivalent | 38.5 | 30.1 | 30.9 | 1.00 |
| Some college | 34.9 | 39.3 | 38.9 | .69 |
| Bachelor's degree or higher | 5.6 | 14.2 | 13.4 | .31* |
| Insurance coveragec | ||||
| Private | 32.2 | 42.9 | 41.9 | .63 |
| Medicare | 22.4 | 14.9 | 15.6 | 1.65 |
| Medicaid | 32.9 | 18.6 | 20.0 | 2.14** |
| Otherd | 28.0 | 34.9 | 34.2 | .73 |
| Uninsured | 29.7 | 25.6 | 26.0 | 1.23 |
| Disability income support (reference: no) | 24.2 | 13.0 | 14.1 | 2.13*** |
| Region | ||||
| Northeast (reference) | 25.1 | 17.7 | 18.4 | |
| Midwest | 22.3 | 19.7 | 20.0 | .80 |
| South | 32.5 | 34.4 | 34.2 | .67 |
| West | 20.1 | 28.2 | 27.5 | .50* |
| Residence | ||||
| Rural (reference) | 22.0 | 16.0 | 16.6 | |
| Urban | 78.0 | 84.0 | 84.4 | .68 |
a
Data are from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III. Percentages are weighted on the basis of a weighted sample of 9,075,642 adults with any past-year illicit drug use disorder, including 878,009 users (9.7%) and 8,197,632 nonusers (90.3%) of drug-related health services.
b
Divorced, separated, widowed, partnered, or other type.
c
Items about each insurance type had a response of yes or no.
d
Other state or federal insurance types, such as the U.S. Department of Veterans Affairs health care program.
*
p<.05, **p<.01, ***p<.001.
Behavioral Comorbidities and Service Use
Among adults with opioid use disorder, the proportion of service users (41.3%) was significantly larger than the proportion not using such services (21.1%) (odds ratio [OR]=2.64, 95% confidence interval [CI]=1.63–4.25) (Table 2). Among adults with any past-year illicit drug use disorders, service users had a mean±SD HRQOL MCS score of 40.7±12.4, which was significantly lower (i.e., indicating poorer mental health functioning) than the score of those who did not use services (44.0±12.0). Furthermore, service users were more likely to have a psychiatric disorder (63.3%), compared with those who did not use services (47.6%) (OR=1.90, 95% CI=1.23–2.93). In particular, service users were more likely than those who did not use services to be diagnosed as having bipolar 1 disorder (p<0.001), posttraumatic stress disorder (p<0.05), and panic disorder (p<0.05). Similarly, the proportions of adults who had other behavioral comorbidities were higher among service users than among those who did not use services. These included several illicit drug use disorders, such as sedative use disorder (p<0.01), cocaine use disorder (p<0.001), stimulant use disorder (p<0.001), heroin use disorder (p<0.001), and hallucinogen use disorder (p<0.01). However, among those with a cannabis use disorder, the proportion not using services was higher than the proportion using services (OR=0.37, 95% CI=0.23–0.59).
| Used drug-related health services | ||||
|---|---|---|---|---|
| Yes | No | Total | Bivariate | |
| Variable | (N=148) | (N=1,330) | (N=1,478) | OR |
| Past-year opioid use disorder | 41.3 | 21.1 | 23.1 | 2.64*** |
| Pain | ||||
| Never or a little (reference) | 68.1 | 68.1 | 68.1 | |
| Moderately, quite a bit, or extremely | 31.9 | 31.9 | 31.9 | 1.00 |
| Health-related quality of life mental component summary (M±SD score) | 40.7±12.4 | 44.0±12.0 | 43.7±12.1 | .98* |
| Past-year psychiatric disorder | ||||
| Any | 63.3 | 47.6 | 49.1 | 1.90** |
| Major depressive disorder | 30.1 | 26.8 | 27.1 | 1.17 |
| Dysthymia | 10.0 | 10.3 | 10.2 | .97 |
| Bipolar 1 disorder | 21.4 | 7.4 | 8.7 | 3.40*** |
| Generalized anxiety disorder | 19.2 | 14.4 | 14.9 | 1.41 |
| Posttraumatic stress disorder | 26.5 | 16.9 | 17.8 | 1.77* |
| Panic disorder | 16.3 | 9.6 | 10.2 | 1.85* |
| Past-year substance use disorder | ||||
| Alcohol | 55.2 | 53.8 | 53.9 | 1.06 |
| Any illicit drug | 86.1 | 85.8 | 85.8 | 1.02 |
| Cannabis | 44.2 | 68.2 | 65.9 | .37*** |
| Sedative | 20.8 | 8.5 | 9.7 | 2.83** |
| Cocaine | 22.0 | 7.7 | 9.0 | 3.40*** |
| Stimulant | 22.5 | 6.8 | 8.3 | 3.98*** |
| Heroin | 23.7 | 1.2 | 3.4 | 25.11*** |
| Hallucinogen | 4.5 | .9 | 1.3 | 5.08** |
| Inhalant-solvent | .7 | 1.1 | 1.1 | .62 |
| Club drug | 6.3 | 2.7 | 3.1 | 2.39 |
| Tobacco | 77.7 | 60.0 | 61.7 | 2.33** |
a
Data are from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III. Percentages are weighted on the basis of a weighted sample of 9,075,642 adults with any past-year illicit drug use disorder, including 878,009 users (9.7%) and 8,197,632 nonusers (90.3%) of drug-related health services.
*
p<.05, **p<.01, ***p<.001.
Factors Associated With Drug-Related Health Services Use
Table 3 presents a multivariable-adjusted analysis of factors associated with use of drug-related health services among all adults with illicit drug use disorders. Among those with opioid use disorder, the odds of using such services were 2.43 times greater than among those without opioid use disorder, when the analysis controlled for all other factors shown in Table 3. In addition, moderate to extreme self-reported pain was associated with a lower likelihood of using drug-related health services (adjusted odds ratio [AOR]=0.47). No other independent correlates of service use among all adults with illicit drug use disorders were identified.
| Factor | AOR | 95% CI |
|---|---|---|
| Opioid use disorder diagnosis (reference: other illicit drug use disorder diagnosis) | 2.43** | 1.38–4.28 |
| Age | 1.01 | .99–1.03 |
| Female (reference: male) | 1.01 | .65–1.57 |
| Race-ethnicity (reference: non-Hispanic white) | ||
| Non-Hispanic black | .81 | .46–1.43 |
| Hispanic | .96 | .50–1.84 |
| Other racial-ethnic group | .64 | .24–1.74 |
| Marital status (reference: married) | ||
| Never married | 1.78 | .75–4.19 |
| Otherb | 2.12 | 1.05–4.31 |
| Family income (reference: <$20,000) | ||
| $20,000–$39,999 | .81 | .47–1.40 |
| ≥$40,000 | .76 | .41–1.42 |
| Employed (reference: no) | .85 | .48–1.52 |
| Education (reference: less than high school) | ||
| High school or equivalent | 1.17 | .62–2.21 |
| Some college | .88 | .47–1.65 |
| Bachelor's degree or higher | .51 | .14–1.83 |
| Insurance coverage (reference: no) | .83 | .51–1.36 |
| Disability income support (reference: no) | 1.64 | .95–2.81 |
| Region (reference: Northeast) | ||
| Midwest | .75 | .39–1.46 |
| South | .62 | .34–1.12 |
| West | .54* | .32–.91 |
| Urban residence (reference: rural) | .74 | .42–1.30 |
| Pain felt moderately, quite a bit, or extremely (reference: never or a little bit) | .47* | .27–.84 |
| Health-related quality of life mental component summary | .99 | .97–1.01 |
| Any psychiatric disorder (reference: no) | 1.46 | .87–2.44 |
| Alcohol use disorder (reference: no) | 1.00 | .59–1.70 |
| Tobacco use disorder (reference: no) | 1.65 | .94–2.90 |
a
Data are from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III. Results are from a multivariable adjusted analysis (adjusted for all variables listed). AOR, adjusted odds ratio.
b
Divorced, separated, widowed, partnered, or other type.
*
p<.05, **p<.01.
Table 4 presents sociodemographic and clinical factors associated with drug-related health services use among the subgroup of adults with opioid use disorder. In the final multivariable-adjusted model, never being married and having another illicit drug use disorder in addition to opioid use disorder were the only two factors associated with a higher likelihood of using drug-related health services (p<0.05 for both). Two factors associated with a lower likelihood of using such services were being non-Hispanic black compared with non-Hispanic white (AOR=0.22) and, paradoxically, having any insurance coverage versus none (AOR=0.35).
| Factor | OR | 95% CI | AOR | 95% CI |
|---|---|---|---|---|
| Age | .96** | .94–.99 | 1.00 | .96–1.04 |
| Female (reference: male) | .71 | .36–1.39 | .69 | .30–1.57 |
| Race-ethnicity (reference: non-Hispanic white) | ||||
| Non-Hispanic black | .20*** | .10–.42 | .22** | .08–.63 |
| Hispanic | .73 | .29–1.81 | 1.22 | .35–4.23 |
| Other racial-ethnic group | .10* | .01–.80 | .19 | .01–2.43 |
| Marital status (reference: married) | ||||
| Never married | 4.48** | 1.61–12.45 | 5.02* | 1.31–19.24 |
| Otherb | 1.76 | .58–5.31 | 1.24 | .37–4.12 |
| Family income (reference: <$20,000) | ||||
| $20,000–$39,999 | .49 | .21–1.15 | .88 | .32–2.40 |
| ≥$40,000 | .78 | .31–1.95 | 1.40 | .53–3.71 |
| Employed (reference: no) | 1.63 | .71–3.76 | 1.10 | .42–2.89 |
| Education (reference: less than high school) | ||||
| High school or equivalent | 1.08 | .49–2.40 | .87 | .31–2.44 |
| Some college | 1.14 | .49–2.69 | 1.11 | .33–3.80 |
| Bachelor's degree or higher | .07* | .01–.62 | .11 | .01–1.70 |
| Insurance coverage (reference: no) | .29*** | .14–.57 | .35* | .14–.86 |
| Disability income support (reference: no) | .61 | .29–1.30 | 1.29 | .37–4.49 |
| Region (reference: Northeast) | ||||
| Midwest | .95 | .26–3.44 | 1.76 | .49–6.30 |
| South | 1.19 | .37–3.87 | 1.60 | .47–5.50 |
| West | .58 | .17–1.97 | .87 | .26–2.91 |
| Urban residence (reference: rural) | .86 | .41–1.83 | .65 | .24–1.72 |
| Pain felt moderately, quite a bit, or extremely (reference: never or a little bit) | .48* | .24–.96 | 1.04 | .37–2.98 |
| Health-related quality of life mental component summary | 1.00 | .96–1.03 | 1.01 | .97–1.05 |
| Any psychiatric disorder (reference: no) | 1.97 | .87–4.43 | 1.79 | .72–4.40 |
| Alcohol use disorder (reference: no) | 1.26 | .62–2.56 | .55 | .23–1.30 |
| Any additional illicit drug use disorder (reference: no) | 4.07*** | 1.99–8.30 | 2.66* | 1.07–6.63 |
| Tobacco use disorder (reference: no) | 3.93** | 1.65–9.38 | 1.87 | .62–5.61 |
a
Data are from the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III. Results are from a multivariable adjusted analysis (adjusted for all variables listed). AOR, adjusted odds ratio.
b
Divorced, separated, widowed, partnered, or other type.
*
p<.05, **p<.01, ***p<.001.
Discussion and Conclusions
Our analysis of the NESARC-III data showed that the proportion of adults with opioid use disorder in the United States who reported use of any drug-related health services was low—less than 20%—and was considerably lower for use of potentially longer-term outpatient services that could address the problem of addiction itself. We found modestly greater likelihood of service use among adults with opioid use disorder, compared with adults with other illicit drug use disorders—but all levels of service use were low. The slightly higher overall rate of use of drug-related health services among those with opioid use disorder largely reflected a significantly higher rate of use of crisis-related services. Use of potentially long-term services from outpatient or community providers was alarmingly low, ranging from only 3.3% to 4.9% across service types.
In the final multivariable-adjusted logistic regression model, only two factors were associated with increased use of drug-related health services among adults with an illicit drug use disorder: having an opioid use disorder diagnosis and having less than moderate to extreme self-reported pain. Finally, in the subgroup analysis of adults with opioid use disorder, four main factors were independently associated with utilization of drug-related health services use (i.e., being non-Hispanic black, being never married, having any insurance coverage, and having another comorbid illicit drug use disorder), providing limited guidance for targeting the most underserved populations. The findings are consistent with those of previous studies (30–32), which showed that persons from racial-ethnic minority groups and those with lower socioeconomic status are less likely to have access to care for addiction treatments, compared with non-Hispanic whites and with those at higher socioeconomic levels. Thus one implication for improving access to drug abuse treatments among adults with opioid use disorder is to focus on underserved or disadvantaged populations (e.g., racial-ethnic minority groups or those with lower socioeconomic status).
The rate of using drug-related health services among adults with past-year opioid use disorder was slightly lower than rates in previous studies, which ranged from 18.8% in 2004–2008 to 19.7% in 2009–2013 (1). These differences may reflect less availability of services as the number of Americans needing such services has increased, but the differences may also be attributable to different definitions of opioid use disorder (e.g., DSM-5 versus DSM-IV) or different sampling methodologies across nationally representative survey samples. Despite these differences, all recent studies have shown that few U.S. adults with opioid use disorder reported using drug-related health services. In addition, despite evidence supporting the effectiveness of several treatment approaches for opioid use disorder, such as buprenorphine and methadone use as well as psychotherapy (8, 13), the rate of outpatient drug treatment remains very low, suggesting that developing an infrastructure that facilitates access to relevant treatment services is critically important to address the opioid epidemic in the United States.
Second, our findings indicated that adults with opioid use disorder were more likely than adults with other illicit drug use disorders to use drug-related health services, particularly crisis-related health services (e.g., emergency department visits) for their drug-related problems. A possible explanation for this phenomenon is that opioid use disorder is more likely to lead to life-threatening overdoses (33). Furthermore, this finding suggests that crisis-related health services may be a promising point of intervention to improve treatment use and related outcomes among adults with opioid use disorder. For example, a randomized clinical trial reported that initiating buprenorphine treatment for opioid-dependent adults in the emergency department setting had multiple benefits, including increased engagement in addiction treatment, reduced self-reported illicit opioid use, and decreased use of inpatient addiction treatment services (34–36). Overall, across diverse treatment settings, continued efforts toward expanding use of medication-assisted treatment (37) are needed to facilitate access to care for these vulnerable adults.
Third, sociodemographic and clinical factors associated with a higher likelihood of using drug-related health services were similar to those identified in earlier studies (16, 19, 33). This study adds to the literature in showing that moderate to extreme pain was associated with a lower likelihood of using drug-related health services among adults with illicit drug use disorders, perhaps because they are more likely to seek care for their pain rather than for their addiction. Thus, ironically, pain, which is very common among adults with opioid use disorder (9, 38), can be an impediment to seeking drug-related services. Health care providers and policy makers should take pain into consideration as a potential barrier to receipt of drug treatment services, especially because opiate drug use can increase pain sensitivity. Expanding access to care for treating opioid use disorder should encompass pain management, which may be linked to better quality of care and treatment outcomes among adults with opioid use disorder.
Several methodological limitations of this study deserve comment. First, the survey on which we reported was conducted from 2012 to 2013, and there is evidence that the epidemic of opioid use disorder, and particularly overdose-related deaths, has grown since then. Although some temporal differences may exist, we believe that our findings are likely to have persisted or worsened as the need for services has increased. Second, consistent with other nationally representative epidemiologic surveys, NESARC-III was not based on clinician-administered diagnoses. However, NESARC-III adopted a structured interview that used the Alcohol Use Disorder and Associated Disabilities Interview Schedule–5 (AUDADIS-5) (39), and the reliability and validity of the AUDADIS-5 have been well documented (23, 39–41). Third, data on service use was based on unvalidated self-report survey data. Thus we do not know how frequently medication-assisted treatment (e.g., buprenorphine prescribing) was provided to adults with opioid use disorder in primary care settings. Although these data may not be as precise as administrative data, they concern services provided by any and all health systems, which is an important advantage in the fragmented U.S. system of care.
Several strengths of this study also deserve comment, including the use of nationally representative survey data to characterize the utilization of diverse drug-related services, especially noncrisis outpatient services; the comparison of services use among adults with opioid use disorder and adults with other drug use disorders; and the use of DSM-5 definitions of opioid use disorder and other clinical diagnoses. Overall, our study clearly demonstrates high levels of untreated opioid use disorder in the United States, and findings suggest an urgent need for multilevel interventions (e.g., individual, institutional, and community based) to improve access to care and motivation for care among adults with opioid use disorder.
References
1.
Saloner B, Karthikeyan S: Changes in substance abuse treatment use among individuals with opioid use disorders in the United States, 2004–2013. JAMA 2015; 314:1515–1517
2.
Dart RC, Severtson SG, Bucher-Bartelson B: Trends in opioid analgesic abuse and mortality in the United States. N Engl J Med 2015; 372:1573–1574
3.
Opioid Overdose: Understanding the Epidemic. Atlanta, Centers for Disease Control and Prevention, 2018
4.
Opioid Overdose: Drug Overdose Death Data. Atlanta, Centers for Disease Control and Prevention, 2017
5.
Opioid Overdose Crisis. Bethesda, MD, National Institute on Drug Abuse, 2019
6.
Key Substance Use and Mental Health Indicators in the United States: Results From the 2016 National Survey on Drug Use and Health. Rockville, MD, Substance Abuse and Mental Health Services Administration, 2017
7.
Rhee TG, Rosenheck RA: Association of current and past opioid use disorders with health-related quality of life and employment among US adults. Drug Alcohol Depend 2019; 199:122–128
8.
Volkow ND, Frieden TR, Hyde PS, et al: Medication-assisted therapies—tackling the opioid-overdose epidemic. N Engl J Med 2014; 370:2063–2066
9.
Schuckit MA: Treatment of opioid-use disorders. N Engl J Med 2016; 375:357–368
10.
Maglione MA, Raaen L, Chen C, et al: Effects of medication assisted treatment (MAT) for opioid use disorder on functional outcomes: a systematic review. J Subst Abuse Treat 2018; 89:28–51
11.
Thornton JD, Goyat R, Dwibedi N, et al: Health-related quality of life in patients receiving long-term opioid therapy: a systematic review with meta-analysis. Qual Life Res 2017; 26:1955–1967
12.
Gowing L, Ali R, White JM, et al: Buprenorphine for managing opioid withdrawal. Cochrane Database Syst Rev 2017; 2:CD002025
13.
Dugosh K, Abraham A, Seymour B, et al: A systematic review on the use of psychosocial interventions in conjunction with medications for the treatment of opioid addiction. J Addict Med 2016; 10:93–103
14.
Ali MM, Dowd WN, Classen T, et al: Prescription drug monitoring programs, nonmedical use of prescription drugs, and heroin use: evidence from the National Survey of Drug Use and Health. Addict Behav 2017; 69:65–77
15.
Novak P, Feder KA, Ali MM, et al: Behavioral health treatment utilization among individuals with co-occurring opioid use disorder and mental illness: evidence from a national survey. J Subst Abuse Treat 2019; 98:47–52
16.
McKenna RM: Treatment use, sources of payment, and financial barriers to treatment among individuals with opioid use disorder following the national implementation of the ACA. Drug Alcohol Depend 2017; 179:87–92
17.
Becker WC, Fiellin DA, Merrill JO, et al: Opioid use disorder in the United States: insurance status and treatment access. Drug Alcohol Depend 2008; 94:207–213
18.
Wu LT, Blazer DG, Li TK, et al: Treatment use and barriers among adolescents with prescription opioid use disorders. Addict Behav 2011; 36:1233–1239
19.
Wu LT, Zhu H, Swartz MS: Treatment utilization among persons with opioid use disorder in the United States. Drug Alcohol Depend 2016; 169:117–127
20.
National Survey on Drug Use and Health. Rockville, MD, Substance Abuse and Mental Health Services Administration, 2019
21.
National Epidemiologic Survey on Alcohol and Related Conditions–III (NESARC-III). Bethesda, MD, National Institute on Alcohol Abuse and Alcoholism, 2017
22.
National Epidemiologic Survey on Alcohol and Related Conditions–III (NESARC-III): Source and Accuracy Statement. Bethesda, MD, National Institute on Alcohol Abuse and Alcoholism, 2018
23.
Grant BF, Saha TD, Ruan WJ, et al: Epidemiology of DSM-5 drug use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions–III. JAMA Psychiatry 2016; 73:39–47
24.
Rhee TG, Rosenheck RA: Comparison of opioid use disorder among male veterans and non-veterans: disorder rates, socio-demographics, co-morbidities, and quality of life. Am J Addict 2019; 28:92–100
25.
Kerridge BT, Pickering RP, Saha TD, et al: Prevalence, sociodemographic correlates and DSM-5 substance use disorders and other psychiatric disorders among sexual minorities in the United States. Drug Alcohol Depend 2017; 170:82–92
26.
Brazier JE, Roberts J: The estimation of a preference-based measure of health from the SF-12. Med Care 2004; 42:851–859
27.
Ware J Jr, Kosinski M, Keller SD: A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care 1996; 34:220–233
28.
Gandek B, Ware JE, Aaronson NK, et al: Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998; 51:1171–1178
29.
Stata Statistical Software: Release 15. College Station, TX, StataCorp LP, 2017
30.
Creedon TB, Cook BL: Access to mental health care increased but not for substance use, while disparities remain. Health Aff 2016; 35:1017–1021
31.
Saloner B, Lê Cook B: Blacks and Hispanics are less likely than whites to complete addiction treatment, largely due to socioeconomic factors. Health Aff 2013; 32:135–145
32.
Cook BL, Alegría M: Racial-ethnic disparities in substance abuse treatment: the role of criminal history and socioeconomic status. Psychiatr Serv 2011; 62:1273–1281
33.
Braden JB, Russo J, Fan MY, et al: Emergency department visits among recipients of chronic opioid therapy. Arch Intern Med 2010; 170:1425–1432
34.
Liebschutz JM, Crooks D, Herman D, et al: Buprenorphine treatment for hospitalized, opioid-dependent patients: a randomized clinical trial. JAMA Intern Med 2014; 174:1369–1376
35.
D’Onofrio G, Chawarski MC, O’Connor PG, et al: Emergency department–initiated buprenorphine for opioid dependence with continuation in primary care: outcomes during and after intervention. J Gen Intern Med 2017; 32:660–666
36.
D’Onofrio G, O’Connor PG, Pantalon MV, et al: Emergency department–initiated buprenorphine/naloxone treatment for opioid dependence: a randomized clinical trial. JAMA 2015; 313:1636–1644
37.
Saloner B, Stoller KB, Barry CL: Medicaid coverage for methadone maintenance and use of opioid agonist therapy in specialty addiction treatment. Psychiatr Serv 2016; 67:676–679
38.
Speed TJ, Parekh V, Coe W, et al: Comorbid chronic pain and opioid use disorder: literature review and potential treatment innovations. Int Rev Psychiatry 2018; 30:136–146
39.
Hasin DS, Greenstein E, Aivadyan C, et al: The Alcohol Use Disorder and Associated Disabilities Interview Schedule–5 (AUDADIS-5): procedural validity of substance use disorders modules through clinical re-appraisal in a general population sample. Drug Alcohol Depend 2015; 148:40–46
40.
Grant BF, Goldstein RB, Saha TD, et al: Epidemiology of DSM-5 alcohol use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry 2015; 72:757–766
41.
Hasin DS, Sarvet AL, Meyers JL, et al: Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry 2018; 75:336–346
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Received: 27 March 2019
Revision received: 29 April 2019
Accepted: 6 June 2019
Published online: 30 July 2019
Published in print: November 01, 2019
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The authors report no financial relationships with commercial interests.
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