Opioid Use Disorder Among Clients of Community Mental Health Clinics: Prevalence, Characteristics, and Treatment Willingness

Untreated substance use disorders are prevalent and can have devastating consequences for people with co-occurring mental illness. In 2019, of 51.5 million Americans with any mental illness, 9.5 million (18.4%) had a co-occurring substance use disorder (1). Co-occurring substance use disorders and psychiatric disorders are associated with increased rates of morbidity, mortality, homelessness, and incarceration and with poor treatment outcomes (2–6). Long-term use of prescription (Rx) opioids is common among individuals with mental illness and is a risk factor for heroin use and the development of opioid use disorder (7–9). People with mood and anxiety disorders are two times as likely to use opioid medications as are people without mental health problems, and people with these disorders are more than three times as likely to use them nonmedically (10, 11). Despite the availability of effective treatment (12–14), substance use disorders among those with mental illness largely go untreated (15, 16). In 2019, among 3.6 million people with any mental illness, 51% did not receive any treatment for their substance use disorder or mental illness (1).

U.S. Food and Drug Administration–approved medications for opioid use disorder have shown effectiveness for individuals with opioid use disorder, including those with mental illness (9, 12–14, 17, 18). Once initiated, both naltrexone long-acting injection (NLAI) and buprenorphine are effective (18).

In mental health settings, both psychosocial treatment and recovery support may be available for people with substance use disorders, but medications for opioid use disorder generally are not (19, 20). Because individuals with co-occurring disorders are more likely to receive mental health treatment than substance use treatment (1), mental health settings are an important medication access point. Increasing access to medications for opioid use disorder in mental health settings requires addressing both the supply of and the demand for treatment (21). On the supply side, clinics and providers must have adequate capacity (22) and organizational readiness (23). On the demand side, prevalence and barriers to access, including client beliefs and perceptions of their need and willingness for treatment, must be understood (24).

To date, little research has been conducted on either supply of or demand for medications for opioid use disorder in public mental health settings. Understanding opioid use disorder prevalence and preferences among people who receive services in these settings is crucial for increasing uptake of opioid use disorder medications. In this article, we report results from a waiting-room survey conducted in eight outpatient clinics directly operated by the Los Angeles County Department of Mental Health (LACDMH) to address the following three questions. What is the estimated prevalence of opioid use disorder among clients of community mental health clinics? Are clients with opioid use disorder willing to take medication for opioid use disorder? Are clients with opioid use disorder willing to receive opioid use disorder medications and other services as part of their mental health treatment?

Methods

Study Setting

This study was conducted in eight of 25 outpatient clinics directly operated by the LACDMH. LACDMH provides treatment to >250,000 individuals annually, serving an ethnically, racially, and geographically diverse population across Los Angeles County. Los Angeles County spans 4,084 square miles and is the most populous county in the United States, with >10 million residents. To maximize diversity, we selected clinics in each of the county’s eight service planning areas. This work was conducted as part of a larger study to develop an implementation tool kit for integrating pharmacotherapy for opioid use disorders into public mental health settings (25).

Clients and Procedures

Adults waiting for a mental health appointment at participating clinics over a 2-week period between April 2019 and February 2020 were asked by a research assistant whether they would like to complete an anonymous, tablet-based, self-administered health survey. They were told that they might qualify for taking a longer survey on the basis of their answers. Clients whose responses indicated heroin use or nonmedical use of Rx opioids in the past year were offered the full survey. Clients who took the screener were offered a $1 incentive; those who completed the full survey were offered a $15 gift card and pamphlets on opioid use disorder. All procedures were approved by the research institution’s and LACDMH’s human subjects research committees.

Measures

Opioid use disorder prevalence.

We assessed probable current opioid use disorder with the National Institute on Drug Abuse–modified Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), which has good concurrent, construct, predictive, and discriminative validities. A score of >3 is concordant with a diagnosis of moderate to severe opioid use disorder (26).

Characteristics of people with co-occurring opioid use disorder.

The screener contained items on demographic characteristics (age, gender, and race-ethnicity) and reason for clinic visit (bipolar disorder, depression, anxiety, schizophrenia, posttraumatic stress disorder, or other mental health problem). It assessed nonmedical use of Rx pain medications, heroin or opium, alcohol, marijuana, methamphetamine, and cocaine in the past year. The full survey asked about housing and homelessness; in addition, it assessed moderate or severe use of the aforementioned substances, pain intensity, and the worst and least pain in the past 24 hours (on a scale ranging from 0 to 100, with 0 being the least pain and 100 being the worst).

Opioid use disorder medication knowledge and attitudes, substance use disorder history, and treatment willingness.

We assessed willingness to take medication for opioid use disorder by asking about familiarity with and opinions about these medications from the Opinions about Medication Assisted Treatment questionnaire (27, 28), substance use treatment history (ever received any treatment or medication for an opioid use disorder or reasons for not receiving treatment), willingness to take buprenorphine or NLAI, willingness to receive medication (buprenorphine or NLAI) as part of opioid use disorder treatment, willingness to receive any opioid use disorder treatment at a specialty substance use disorder clinic, and willingness to receive any treatment as part of mental health treatment (willingness items were rated on a scale from 1 to 100, with 1 being the least willing and 100 being the most willing) (29, 30). Questions about oral naltrexone were not included because of low rates of patient acceptance and adherence (31).

Data Analysis

We conducted univariate analyses to examine opioid use disorder prevalence as well as distribution, central tendencies, and dispersion of variables for clients who screened positive for a probable opioid use disorder (i.e., an ASSIST score >3 for heroin or opium use or nonmedical use of Rx opioids). Next, we conducted chi-square tests on categorical and dichotomous variables and two-sample t tests on continuous variables to examine differences between clients with a probable Rx opioid use disorder and those with a probable heroin use disorder (with or without an Rx opioid use disorder). Bivariate ordinary least squares (OLS) linear regression models were used to explore predictors of four variables: willingness to take buprenorphine, willingness to take NLAI, willingness to receive treatment for opioid use disorder at a specialty substance use disorder clinic, and willingness to receive opioid use disorder care as part of treatment at the mental health clinic.

Predictor variables tested in bivariate models were age, gender, race-ethnicity, reason for clinic visit, pain level, ever received opioid use disorder treatment, ever took substance use disorder medication, belief in the effectiveness of buprenorphine or NLAI, and type of opioid use disorder (Rx or heroin). Because of collinearity between familiarity with each medication and believing that the medication was effective, familiarity was not included in the model. Finally, we fit four multivariate regression models to the data, including all predictor variables from bivariate OLS regression analyses that were significant at p≤0.2. This method was consistent with variable selection procedures aimed at reducing the number of variables included in the multivariable regression model while taking into consideration that some nonsignificant variables (at p<0.05) still could be significant when combined with other variables (32, 33). To assess differences among clinics, we ran intraclass correlations between each outcome and clinic; because not significant relationship between clinic and any variable was detected, we did not include a “clinic” variable in the models. All analyses were done with Stata, version 16.

Results

Characteristics of Clients With Opioid Use Disorder

Of 5,012 clients approached, 3,090 completed the screener. Of the clients who completed the screener, 406 qualified for the full survey, and 340 completed it. Of the clients who took the screener, 309 (10%) had a probable opioid use disorder, 258 (8%) had a probable Rx opioid use disorder only, and 51 (2%) had a probable heroin use disorder either alone or with an Rx opioid use disorder. Those who completed the screener were comparable in age, gender, and race-ethnicity to clients served by the eight clinics and by clinics directly operated by the LACDMH (Table 1).

Table 2 shows the demographic and health characteristics of all clients with a probable opioid use disorder and by type of disorder. In each demographic category, a higher proportion of individuals had a probable Rx opioid use disorder than a heroin use disorder, with women in particular having a larger proportion of those with Rx opioid use disorder rather than heroin use disorder (49% and 25%, respectively); conversely, men had a larger proportion of those with heroin use disorder than Rx opioid use disorder (71% and 48%, respectively). Black clients had a larger proportion of those with probable Rx opioid use disorder than heroin use disorder (43% and 24%, respectively), as did Hispanic clients (33% and 22%, respectively); however, a larger proportion of White clients had heroin use disorder (39%) rather than Rx opioid use disorder (12%).

Of note, compared with the larger LACDMH client community shown in Table 1, Black clients were disproportionately affected by Rx opioid use disorder, representing 23% of the overall LACDMH client population but 43% of those with Rx opioid use disorder (Table 2). Additionally, 15% (N=124 of 816) of all Black clients screened had a probable opioid use disorder (Rx opioid or heroin use disorder), compared with 8% (N=50 of 619) of White and 8% (N=95 of 1,165) of Hispanic clients. In total, 60% of clients with a probable opioid use disorder were also using alcohol in risky amounts, 55% were using marijuana, and 32% and 34% were using cocaine or methamphetamine, respectively (Table 2). Those with probable heroin use disorder had higher rates of injection drug use in the past year and higher rates of use of other substances than those with probable Rx opioid use disorder. No significant differences were found between the two groups related to the reason for their clinic visit. Those with probable Rx opioid use disorder reported significantly higher pain “right now” and higher “least amount of pain in the past 24 hours” than those with heroin use disorder.

Opioid Use Disorder Medication Treatment History, Familiarity, Beliefs, and Willingness

Most (78%) clients with probable Rx opioid use disorder reported never having received treatment for such disorder, whereas this treatment history was true for only 39% of those with heroin use disorder (Table 3). Of those who had never received such treatment but indicated they had ever had wanted treatment, the top two reasons for never receiving treatment among those with Rx opioid use disorder were “believing I could handle it without treatment” (37%) and “didn’t think I needed it” (35%); the top two reasons for those with heroin use disorder were “not being able to afford treatment” (52%) and “believing I could handle it without treatment” (38%).

Most clients with probable Rx opioid use disorder reported that they had never taken a medication for opioid use disorder (82%), whereas among those with probable heroin use disorder, 61% had received medication, including methadone (47%), buprenorphine (35%), or NLAI (8%). Of those with probable heroin use disorder, 33% (N=17) reported that they were currently taking a medication for their disorder, compared with 9% (N=22) of those with Rx opioid use disorder.

Most of those with probable Rx opioid use disorder were not familiar with buprenorphine (76%, N=195) or NLAI (81%, N=209); however, among those with heroin use disorder, 82% (N=42) reported being “somewhat” or “very” familiar with buprenorphine, and 55% (N=28) reported being “somewhat” or “very” familiar with NLAI (Table 4). Fewer clients with Rx opioid use disorder agreed or strongly agreed that either buprenorphine (25%, N=64) or NLAI (20%, N=51) could help people stop using opioids, compared with those with heroin use disorder (67% [N=34] and 49% [N=25], respectively).

Overall, those with probable heroin use disorder indicated significantly higher ratings than those with probable Rx opioid use disorder on willingness to take buprenorphine, take NLAI, receive any opioid use disorder treatment in a specialty program, and receive opioid use disorder treatment as part of mental health treatment (Table 4).

Multivariate Regression Analyses

Willingness to take buprenorphine.

Predictors included in this model (R²=0.10) were age, gender, opioid use disorder type, ever received opioid use disorder treatment, pain level, and belief that buprenorphine can help people stop using opioids. Statistically significant predictors were agreement that buprenorphine can help people stop using opioids (β=13.54, p=0.003), pain level (with increased pain being associated with greater willingness; β=0.19, p=0.003), and younger age (β=−0.33, p=0.026).

Willingness to take NLAI.

Predictors in this model (R²=0.10) were gender, opioid use disorder type, ever received opioid use disorder treatment, pain level, and belief that NLAI can help people stop using opioids. Significant predictors were agreement that NLAI can help people stop using opioids (β=15.83, p<0.001) and pain level (β=0.18, p=0.005).

Willingness to receive opioid use disorder treatment at a specialty clinic.

Predictors in this model (R²=0.06) were gender, opioid use disorder type, pain level, and ever received Rx opioid use disorder treatment. The only significant predictor was pain level (β=0.17, p=0.011).

Willingness to receive opioid use disorder treatment as part of mental health treatment.

Predictors in this model (R²=0.06) were gender, opioid use disorder type, pain level, and ever received Rx opioid use disorder treatment. Significant predictors were having a heroin use disorder (compared with having an Rx opioid use disorder; β=13.61, p=0.026) and ever having received Rx opioid use disorder treatment (β=10.36, p=0.043).

Discussion

To characterize demand for medications for opioid use disorder in public mental health clinics, we conducted a waiting-room survey to assess prevalence of probable opioid use disorder, characteristics of people with opioid use disorder, and willingness to receive opioid use disorder treatment. We found that opioid use disorder was highly prevalent among 3,090 clients in our waiting-room sample, with 10% of the clients having a probable opioid use disorder: 8% with a probable Rx opioid use disorder and 2% with a probable heroin use disorder. By comparison, about 0.8% of people in the general population are thought to have any opioid use disorder (34). Our results also show that of those with probable Rx opioid use disorder, 78% have never received any opioid use disorder treatment compared with 39% of those with a heroin use disorder, suggesting that more efforts are needed in mental health settings to identify and treat individuals who use Rx opioids nonmedically. In addition, more than half of the clients with a probable opioid use disorder were also using alcohol in risky amounts, more than half were using marijuana, and about one-third were using cocaine or methamphetamine; even higher rates were found among those with a heroin use disorder, indicating the need for full assessment.

Among the men in our sample, prevalence of probable heroin use disorder was higher than for Rx opioid use disorder, consistent with findings in the general population (35–37), whereas a slightly higher proportion of women had probable Rx opioid use disorder. This finding is important because providers may not suspect Rx opioid use disorder among women; moreover, women are less likely than men to access opioid use disorder treatment (38).

We found notable differences by race-ethnicity in this study, with heroin use disorder being more common among Whites; conversely, substantially more Blacks, followed by Hispanics, had Rx opioid use disorder compared with Whites. Blacks in our sample were disproportionately affected by Rx opioid use disorder, representing 43% of those with an Rx opioid use disorder but only 23% of clients in the mental health system. In the general population, heroin use disorder is more common among Whites (39), whereas nonmedical Rx opioid use is more evenly distributed, with 3.9% of Whites and Hispanics and 3.5% of Blacks using Rx opioids nonmedically. Understanding these differences may assist in opioid use disorder identification and delivery of appropriate treatment. Historically, Whites have had higher rates of opioid-involved overdose deaths; however, recent data show that the increase in overdose deaths among Blacks in the United States outpaces that of Whites (40), with overdose deaths being similar for Whites and Blacks in central urban areas (41). Whites and those living in high-income areas receive buprenorphine treatment for opioid use disorder at much higher rates than do Black and Hispanic individuals (42–44).

In our analysis, those with either a probable Rx opioid or heroin use disorder were more willing to take buprenorphine or NLAI if they believed that the medication could help people stop using opioids. This finding suggests that education about treatment effectiveness is an important first step. Additionally, given low rates of use of medication for opioid use disorder among people of color and their historical mistrust of medical treatment (45, 46), attention must be paid not only to strategies for educating clients but also to clinic- and system-level strategies to educate providers and reduce stigma.

Those reporting higher pain were more willing to take buprenorphine or NLAI, regardless of disorder type. Pain overall was moderate across both client groups, but it was higher among those with a probable Rx opioid use disorder. Many people with Rx opioid use disorder report substantial pain; moreover, pain is often the reason Rx opioid use is initiated (47, 48). This observation emphasizes the need to assess for opioid use disorder among individuals with chronic pain and to address pain management for those with Rx opioid use disorder (49, 50). Providing treatment for comorbid pain and opioid use disorder is challenging (50), and it is an area in need of specialty training programs (50).

The primary predictor of willingness to receive treatment in a mental health clinic was having a probable heroin use disorder (rather than an Rx opioid use disorder) and having taken medications for opioid use disorder in the past. Although in this sample the number of people with heroin use disorder was relatively low relative to those with Rx opioid use disorder, our findings are consistent with national data indicating higher treatment seeking among those with heroin use disorder than among those with Rx opioid use disorder (39). This difference is likely due to greater identification of heroin use disorder by clients and providers and the challenge of identifying and addressing Rx opioid use disorder among those with comorbid pain. These results highlight the need for a broader view of opioid use disorder that considers Rx opioid and heroin use disorders, chronic pain, and education about available treatment within mental health settings.

We note several limitations of this study. Despite purposive sampling to maximize diversity, neither clinics, clients, nor periods for the study were randomly selected. Additionally, self-selection bias may have occurred because not all clients agreed to participate. Furthermore, the sample did not include people who were on medication for opioid use disorder or those who had not used opioids in the past year. Thus, opinions of those being successfully treated were missed. Finally, the ASSIST, although an instrument congruent with the diagnosis of opioid use disorder, is not a diagnostic measure.

Conclusions

Our findings suggest high prevalence of opioid use disorder, Rx opioid use disorder in particular, among people receiving care in outpatient community mental health clinics in Los Angeles County; moreover, the results highlight the need for systematic identification and treatment. Racial-ethnic differences were found in prevalence, including a higher prevalence of Rx opioid use disorder than heroin use disorder among Blacks and Hispanics than among Whites; a disproportionate prevalence of Rx opioid use disorder among Blacks compared with the proportion of all clients in the LACDMH system; and a higher percentage of Blacks having an opioid use disorder compared with Hispanics or Whites. Given disparities in access to medications for opioid use disorder among people of color and increasing overdose deaths among Blacks, these findings emphasize the importance of increasing access to treatment for these disorders. Offering treatment in community mental health settings could increase uptake of medications for opioid use disorder, reduce racial disparities in treatment, and improve outcomes for people with co-occurring disorders.