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The impact of buprenorphine on treatment of opioid dependence in a Medicaid population: Recent service utilization trends in the use of buprenorphine and methadone
Drug and Alcohol Dependence 123 (2012) 72–78
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The impact of buprenorphine on treatment of opioid dependence in a Medicaid population: Recent service utilization trends in the use of buprenorphine and methadone Bradley D. Stein a,c,∗ , Adam J. Gordon b , Mark Sorbero a , Andrew W. Dick c , James Schuster a , Carrie Farmer c a
Community Care Behavioral Health Organization, One Chatham Center, 112 Washington Place, Suite 700, Pittsburgh, PA 15219, United States Center for Research on Health Care, University of Pittsburgh, 7180 Highland Drive (151-C-H), Pittsburgh, PA 15206, United States c RAND Corporation, 4570 Fifth Avenue, Suite 600, Pittsburgh, PA 15213, United States b
a r t i c l e
i n f o
Article history: Received 3 August 2011 Received in revised form 18 October 2011 Accepted 19 October 2011 Available online 16 November 2011 Keywords: Buprenorphine Methadone Opiate dependence Office-based treatment
a b s t r a c t Background: Buprenorphine provides an important option for individuals with opioid dependence who are unwilling or unable to attend a licensed methadone opioid agonist treatment program to receive opioid agonist therapy (OAT). Little empirical information is available, however, about the extent to which buprenorphine has increased the percentage of opioid dependent individuals receiving OAT, nor to what extent buprenorphine is being used in office based settings. Methods: Using administrative data from the largest Medicaid managed behavioral health organization in a large mid-Atlantic state, we used multivariate regression to examine rates and predictors of opioid agonist use and treatment setting for 14,386 new opioid dependence treatment episodes during 2007–2009. Results: Despite an increase in the use of buprenorphine, the percentage of new treatment episodes involving OAT is unchanged due to a decrease in the percentage of episodes involving methadone. Use of buprenorphine was significantly more common in rural communities, and 64% of buprenorphine use was in office-based settings. Conclusion: Buprenorphine use has increased in recent years, with the greatest use in rural communities and in office based settings. However, the percentage of new opioid dependence treatment episodes involving an opioid agonist is unchanged, suggesting the need for further efforts to increase buprenorphine use among urban populations. © 2011 Published by Elsevier Ireland Ltd.
1. Introduction Opioid use disorders (opioid abuse and opioid dependence) are a significant public health problem, affecting hundreds of thousands of Americans (U.S. Department of Health and Human Services and Substance Abuse and Mental Health Services Administration Office of Applied Studies, 2010) with an estimated societal cost of $20 billion annually (National Consensus Development Panel, 1998). Historically, less than 25% of opioid dependent individuals receive opioid agonist therapy (OAT; American Methadone Treatment Association, 1998), the most effective intervention for opioid dependence with a broad evidence base (Marsch, 1998; Mattick et al., 2003, 2008; National Institute of Drug Abuse, 2006; National Institute of Drug Abuse National Quality Forum, 2005; Volkow, 2004), and one that has been shown to have a range of
∗ Corresponding author. Tel.: +1 412 454 8633. E-mail address: [email protected] (B.D. Stein). 0376-8716/$ – see front matter © 2011 Published by Elsevier Ireland Ltd. doi:10.1016/j.drugalcdep.2011.10.016
individual and societal benefits (Krantz and Mehler, 2004; Marsch, 1998; Mattick et al., 2008; National Consensus Development Panel, 1998). The FDA’s 2002 approval of buprenorphine and buprenorphine/naloxone (collectively buprenorphine) for opioid dependence treatment served as an opportunity to increase the number of patients with opioid dependence receiving OAT (Ducharme and Abraham, 2008). Under the physician waiver program established by the Drug Addiction Treatment Act of 2000, physicians could prescribe buprenorphine in regular officebased settings. This more flexible approach to opioid dependence treatment represented a paradigm shift from prior OAT treatment, which regulations had required to be taken in a licensed methadone program operating under strict state and federal regulations for treatment that commonly included daily attendance for dosing on-site (Ling et al., 2010). Compared to methadone, buprenorphine has been found to be effective and cost-effective (Barnett, 2009; Harris et al., 2005; Jones et al., 2009; Mattick et al., 2009, 2008), and buprenorphine’s approval was therefore expected to increase
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
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access to OAT for individuals unable or unwilling to attend licensed methadone programs (O’Connor et al., 1998; Sullivan et al., 2005). Furthermore, the availability of buprenorphine OAT expanded pharmacologic options in licensed methadone opioid agonist treatment programs as well as in specialty addiction treatment programs that are not licensed to prescribe methadone. While studies have documented buprenorphine use in officebased settings (Arfken et al., 2010) and the diffusion of buprenorphine use among opioid agonist treatment program and specialty addiction treatment program facilities (Ducharme and Abraham, 2008; Knudsen et al., 2006, 2007; Koch et al., 2006), there is a paucity of empirical data examining buprenorphine use and its relationship with methadone use and non-pharmacologic interventions in the treatment of opioid dependence. We are unaware of studies examining to what extent the introduction of buprenorphine has increased the overall number of individuals receiving OAT. Furthermore, if the number of individuals receiving OAT is increasing, it is not known whether this is related primarily to the availability of buprenorphine in office-based settings, or if an increase in OAT use is also occurring among individuals being treated in opioid agonist treatment programs and specialty addiction treatment programs. To better understand the role buprenorphine is playing in expanding access to OAT, we examined the use of buprenorphine and methadone from 2007 to 2009 among publicly insured individuals in a large Mid-Atlantic state. We hypothesized that the use of both buprenorphine and OAT increased over time, with a substantial amount of buprenorphine use observed in office based and rural settings.
Race/ethnicity was categorized as white, African-American, or other. Consistent with other analyses of Medicaid-enrolled populations (Zito et al., 2005), individuals were categorized into Medicaid eligibility categories according to whether their Medicaid eligibility resulted from a disability or was income related. Consistent with other studies, we identified individuals with a comorbid serious mental illness if they had one inpatient or 2 outpatient claims with a diagnosis of schizophrenia, bipolar disorder, and major depression (Lurie et al., 1992). Dually eligible individuals (Medicaid/Medicare) were excluded from the analysis as their pharmacy claims were unavailable in the state provided Medicaid data files. Using provider identifiers in the Medicaid claims, we linked individuals to treatment facilities, and categorized location of opioid dependence treatment as (1) opioid agonist treatment programs (methadone programs providing methadone and buprenorphine), (2) specialty addiction treatment programs (programs not licensed to dispense methadone but able to provide buprenorphine), and (3) office based opioid agonist treatment for individuals who did not receive any services at either of the preceding treatment settings. Office-based treatment includes individuals on buprenorphine who are receiving care in both primary care and outpatient psychiatric settings. Individuals were categorized as living in an urban area if their county of residence had a population density greater than 1000 individuals/ square-mile.
2. Methods
3. Results
2.1. Sample and data source
3.1. Characteristics of population
Using administrative data from the largest Medicaid managed behavioral health organization in a large mid-Atlantic state and state provided pharmacy data, we identified adults age 18–64 years old starting a new treatment episode for opioid dependence between January 1, 2007 and December 31, 2009. The study was conducted in compliance with the University of Pittsburgh Institutional Review Board. The managed behavioral health organization manages behavioral health care for over half of the counties in the state. All Medicaid enrolled individuals in each of these counties have essentially all of their behavioral health care services managed by the managed behavioral health organization, and there are limited block grant funded substance abuse treatment services available in the communities in which these individuals reside. Buprenorphine is available on the Medicaid formulary and commonly requires prior authorization, but in contrast to a number of other states where efforts are being made to limit use of buprenorphine (Clark et al., 2011), there is no “fail first” requirement nor in our conversations with providers do they report finding the prior authorization requirement particularly onerous. 2.2. Outcome and predictor variables We identified adults with a new opioid dependence treatment episode, which we defined as (1) a single inpatient claim or 2 or more outpatient behavioral health claims in a 90-day period with a diagnosis of opioid dependence (ICD code 304.0, 304.00, 304.01, 304.02, 304.03, 304.7, 304.70, 304.71, 304.72, 304.73), (2) a claim for a methadone related treatment service, or (3) a filled buprenorphine prescription (buprenorphine or buprenorphine/naloxone sublingual tablets) following a 90-day period with no claim with a diagnosis of opioid abuse or dependence, no methadone related services, and no prescription for buprenorphine. New treatment episodes were categorized as buprenorphine treatment, methadone treatment, or drug-free treatment. Individuals who received both buprenorphine and methadone within the first 90 days of starting the treatment episode were categorized as having buprenorphine treatment. We examined each year independently, so an individual could have a new treatment episode in each calendar year following a sufficiently long period with no treatment medications or services with a diagnosis of opioid abuse or dependence. Duration of treatment episodes was calculated from the beginning of the episode until the last observed claim, completed prescription, or end of the calendar year. For individuals who had more than one new treatment episode in a year, we included only the first treatment episode. Sociodemographic variables, including age, sex, Medicaid eligibility category, and race/ethnicity were obtained from the state’s membership and eligibility files.
2.3. Analysis We estimated three multivariate logistic regression models. We estimated the first model as a logistic regression of any opioid agonist treatment use among those with a new opioid dependence treatment episode, controlling for sex, race, urban/rural status, age, comorbid serious mental illness, Medicaid eligibility category, and year of episode. We estimated the second model as a logistic regression of buprenorphine use among those receiving any opioid agonist treatment, conditional on the same covariates. We estimated the third model as a logistic regression of office based treatment among those receiving buprenorphine, conditional on the same covariates. In each case, we calculated Huber-White standard errors to account for the intra-person correlation for those who contributed more than one treatment episode to the sample.
We identified 14,386 new opioid dependence treatment episodes by Medicaid-enrolled individuals from 2007 through 2009. The individuals starting treatment episodes were predominantly under the age of 35, white, and Medicaid eligible due to income (Table 1). Approximately half were male, and approximately one third resided in urban communities. The number of individuals starting treatment for opioid dependence increased 35% from 2007 (n = 4115) to 2009 (n = 5569). Twelve percent (n = 1793) of new episodes involved buprenorphine, 25% (n = 3581) involved methadone, and 63% (n = 9012) did not involve an opioid agonist. Of the 9012 individuals receiving drug-free treatment, the majority (71%; n = 6386) were receiving services from specialty addiction treatment programs, 19% were receiving services other than methadone from opioid agonist treatment programs, and 10% (n = 882) were receiving services from mental health providers. 3.2. Trends in the use of medications to treat opioid dependence from 2007 to 2009 We found that the number of new treatment episodes per adult Medicaid enrollees increased slightly from 1.6% in 2007 to 1.7% in 2008 and 2.0% in 2009. The number of new episodes involving buprenorphine more than doubled from 2007 (n = 367) to 2009 (n = 793), while there was a modest 6% increase in the number of new methadone episodes over the same time frame (Table 2). However, as the number of drug-free new treatment episodes increased by 37% over the same period, the overall percentage of new treatment episodes involving opioid agonists was essentially unchanged between 2007 (38%) and 2009 (37%). As highlighted in Table 2, the shifts in type of new treatment episodes were most pronounced in rural communities.
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B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
Table 1 Predictors of starting opioid dependence treatment with an opioid agonist. N
Total 14,386 Age (yrs) 4660 18–25 4857 26–35 2727 36–45 1820 46–55 322 56–64 Gender 7316 Male 7070 Female Race 1371 African American 12,158 White 857 Other Comorbid serious mental illness 2574 Yes No 11,812 Community Rural 9492 Urban 4894 Medicaid eligibility 2717 Disability 11,669 Income Year 4115 2007 2008 4702 2009 5569
Treatment with an opioid agonist (buprenorphine or methadone)
Drug-free treatment
Adjusted odds ratio of receiving an opioid agonist
n
%
n
%
aOR
p-Value
CI
CI
5374
37.4
9012
62.6
1575 1921 1025 703 150
33.8 39.6 37.6 38.6 46.6
3085 2936 1702 1117 172
66.2 60.5 63.4 61.4 53.4
1.31 1.30 1.51 2.60
<0.001 <0.001 <0.001 <0.001
1.20 1.17 1.33 1.99
1.43 1.45 1.72 3.39
2553 2821
34.9 39.9
4249
65.1 60.1
1.30
<0.001
1.21
1.40
393 4578 403
28.7 37.7 47.1
978 7580 454
71.3 62.4 53
0.57
<0.001
0.49
0.66
1.59
<0.001
1.36
1.85
828 4546
32.17 38.49
1746 7266
67.83 61.51
0.75
<0.001
0.68
0.82
3447 1927
36.3 39.3
6045 2967
63.7 60.6
0.83
<0.001
0.77
0.90
911 4463
33.5 38.2
1806 7206
66.5 61.8
1.26
<0.001
1.14
1.39
1555 1768 2051
37.8 37.6 36.8
2560 2934 3518
62.2 62.4 63.2
0.99 0.97
0.81 0.46
0.91 0.89
1.08 1.05
3.3. Characteristics of individuals starting opioid dependence treatment with an opioid agonist Approximately 37% of new treatment episodes (n = 5374) involved an opioid agonist. There were no substantial differences in sociodemographic characteristics of individuals starting treatment for opioid dependence across the different years (data not shown). Females were more likely than males (39.9% vs. 34.9%, aOR 1.29, 95% CI 1.20–1.39) to start their treatment episode with an opioid agonist (buprenorphine or methadone), as were individuals Medicaid-eligible due to income compared to individuals Medicaid-eligible due to disability (38.2% vs. 33.5%, aOR 1.31, 95% CI 1.19–1.44; Table 1). Individuals with a comorbid mental health disorder were significantly more likely than those without a comorbid disorder to start treatment with an opioid agonist (32.2% vs. 38.5%, aOR 0.75, 95% CI 0.68–0.82). Compared to individuals age 18–25, we found that all older age cohorts were significantly more likely to start treatment with an opioid agonist. We also found that
individuals in rural communities were significantly less likely to start treatment with an opioid agonist than individuals in urban communities (36.3% vs. 39.3%, aOR 0.82, 95% CI 0.76–0.89), as were African Americans when compared to whites (28.7% vs. 37.7%, aOR 0.57, 95% CI 0.49–0.66). Individuals in the “other” racial/ethnic category were significantly more likely than whites to start treatment with an opioid agonist (28.7% vs. 37.7%, aOR 1.54, 95% CI 1.33–1.79). There were no substantial differences in sociodemographic characteristics of individuals starting treatment for opioid dependence across the different years (data not shown). 3.4. Characteristics of individuals using buprenorphine vs. methadone Among the 5374 individuals starting treatment with an opioid agonist, one-third (n = 1793) received buprenorphine (Table 3). Across all 3 years, methadone episodes were significantly longer than buprenorphine episodes (74 days vs. 68 days, p < 0.01).
Table 2 Change over time in use of opioid agonists in new opioid dependence treatment episodes. 2007
2008
2009
Total number of adult non-dual eligible medicaid enrollees
256,752
272,617
281,046
Total number of new opioid dependence treatment episodes
N = 4115
N = 4702
N = 5569
Buprenorphine Urban Rural Methadone Urban Rural Drug-free treatment Urban Rural
n
%
n
%
n
%
367 40 327 1188 501 687 2560 866 1694
9 3 12 29 36 25 62 62 63
633 58 575 1135 633 502 2934 1003 1931
13 3 19 24 37 17 62 59 64
793 80 713 1258 615 643 3518 1098 2420
14 4 19 23 34 17 63 61 64
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Table 3 Predictors of starting treatment with buprenorphine among those starting treatment with an opioid agonist. N
Total 5374 Age (yrs) 18–25 (ref) 1575 26–35 1921 36–45 1025 46–55 703 150 56–64 Gender 2553 Male (ref) Female 2821 Race 393 African American White (ref) 4578 403 Other Comorbid serious mental illness 828 Yes 4546 No Community Rural 3447 Urban (ref) 1927 Medicaid eligibility category 911 Disability (ref) 4463 Income Year 1555 2007 (ref) 2008 1768 2009 2051 a
Methadonea
Buprenorphine
Adjusted Odds ratio of receiving buprenorphine
n
%
n
%
1793
33.4
3581
66.6
aOR
p-Value
CI
539 644 379 204 27
34.2 33.52 36.98 29.02 18.00
1036 1277 646 499 123
862 931
33.76 33.00
74 1541 178
CI
65.3 66.48 63.02 70.98 82.00
0.97 1.34 1.17 1.07
0.74 <0.01 0.19 0.80
0.82 1.10 0.93 0.63
1.15 1.64 1.48 1.82
1691 1890
66.24 67.00
0.85
<0.05
0.74
0.97
18.83 33.66 44.17
319 3037 225
81.17 66.34 55.83
0.80
0.14
0.60
1.07
0.86
0.24
0.68
1.10
393 1400
47.46 30.80
435 3146
52.54 69.20
1.67
<0.001
1.41
1.99
1615 178
46.85 9.24
1832 1749
53.15 90.76
9.08
<0.001
7.51
10.98
274 1519
30.08 34.04
637 2944
69.92 65.96
1.42
<0.001
1.18
1.70
367 633 793
23.60 35.80 38.66
1188 1135 1258
76.40 64.20 61.34
2.11 2.21
<0.001 <0.001
1.80 1.89
2.49 2.59
Individuals attended one of 26 methadone programs in 2007, and one of 23 programs in 2008 and 2009.
Controlling for other covariates, residing in a rural community was strongly associated with receiving buprenorphine; rural individuals were over nine times more likely to start treatment with buprenorphine than individuals in urban communities (46.8% vs. 9.2%, aOR 9.37, 95% CI 7.75–11.34). We also found that new treatment episodes in 2008 (35.8%) and 2009 (38.7%) were significantly more likely to involve buprenorphine than new episodes in 2007 (23.6%). 3.5. Treatment setting of individuals starting treatment with buprenorphine Among the 1793 episodes starting treatment with buprenorphine, we found that 64% were receiving office-based treatment. We found that individuals in rural areas receiving buprenorphine were dramatically more likely to be receiving office-based treatment than individuals in urban areas (71% vs. 2%; aOR 160, 168, 95% CI 52–542; Table 4). Age was also strongly predictive, with younger individuals less likely to receive office-based treatment than individuals in older cohorts. Individuals with a comorbid mental health disorder were significantly less likely than those without such a disability to receive office based treatment (54.7% vs. 66.4%; aOR 0.56, 95% CI 0.42–0.73). There were no significant differences by gender or Medicaid eligibility category regarding the treatment setting in which an individual was receiving buprenorphine, nor was there a significant difference in treatment settings for those receiving buprenorphine between 2007, 2008, and 2009. 4. Discussion In our examination of the use of buprenorphine and methadone in the treatment of individuals with opioid dependence from 2007 to 2009, we found that the number of new treatment episodes involving buprenorphine more than doubled during that period. The use of buprenorphine, however, did not appear to have a
substantial impact on the proportion of new treatment episodes involving OAT. While use of buprenorphine increased, consistent with other studies we found a corresponding increase in the overall number of new opioid dependence treatment episodes over the period observed (Baxter et al., 2011). Among individuals receiving OAT, however, we did find a substantial increase from 2007 to 2009 in the percentage of episodes involving buprenorphine. This resulted from a substantial increase in the number of episodes involving buprenorphine over the period with a corresponding slight increase in the number of episodes involving methadone. To the extent that experts hoped that buprenorphine would increase access to opioid agonist treatment (Ducharme and Abraham, 2008; Gordon et al., 2008, 2007; Ling et al., 2010), our finding that buprenorphine appears to be serving as a substitute for methadone rather than a complement suggests that while buprenorphine has increased the treatment options of individuals receiving opioid agonist treatment, the promise of buprenorphine as a way to extend access to opioid agonist treatment has not yet been realized. Among individuals starting treatment with buprenorphine, almost two-thirds (n = 1145) did not receive treatment in opioid agonist treatment programs or specialty addiction treatment programs, but in office-based treatment settings. One of the great advantages in access to buprenorphine compared to methadone was its potential use in office-based settings (Ducharme and Abraham, 2008), and we find substantial numbers of individuals receiving such treatment. The use of office-based treatment was most pronounced in rural areas. Typically, opioid agonist treatment programs and specialty addiction treatment programs are located in more urban areas (Cicero et al., 2007). Those living in rural areas must travel considerable distances to receive methadone treatment, which can be particularly challenging given daily methadone dispensation protocols (U.S. Department of Justice, 2004). Thus, office-based prescribing of buprenorphine is a particularly promising approach to enhancing the access of rural populations to opioid agonist treatment (Ducharme and Abraham, 2008). This is
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Table 4 Predictors of receiving office based treatment among individuals receiving buprenorphine. N
Total 1793 Age (yrs) 539 18–25 644 26–35 379 36–45 46–55 204 56–64 27 Gender 862 Male 931 Female Race 74 African American 1541 White Other 178 Comorbid serious mental illness Yes 393 No 1400 Community 1615 Rural 178 Urban Medicaid 274 Disability Income 1519 Year 367 2007 2008 633 793 2009
Office based opioid treatment settings
Specialty addiction treatment and opioid agonist treatment programs
Adjusted odds ration of receiving office based buprenorphine
n
%
n
%
aOR
1145
63.86
648
36.14
307 433 249 136 20
56.96 67.24 65.70 66.67 74.07
232 211 130 68 7
43.05 32.76 34.30 33.34 25.93
1.50 1.73 1.79 7.38
<0.01 <0.01 <0.01 <0.01
1.15 1.25 1.21 2.08
1.96 2.39 2.65 26.21
513 632
59.51 67.88
349 299
40.49 32.11
1.21
0.10
0.97
1.52
42 1012 91
56.76 65.67 51.12
32 529 87
43.25 34.32 48.88
0.58
0.05
0.33
1.00
0.45
<0.001
0.32
0.64
215 930
54.71 66.43
178 470
45.29 33.57
0.56
<0.001
0.42
0.73
1142 3
70.71 1.69
473 175
29.29 98.32
168.27
<0.001
52.19
542.50
169 976
61.68 64.25
105 543
38.32 35.74
1.21
0.24
0.88
1.65
236 423 486
64.31 66.82 61.29
131 210 307
35.69 33.17 38.71
1.11 0.86
0.50 0.32
0.82 0.65
1.50 1.15
consistent with our findings that individuals receiving opioid agonists in rural communities were over 9 times more likely to receive buprenorphine than individuals in urban communities, and that individuals receiving buprenorphine in rural areas were vastly more likely to receive the medication in office based settings. Yet, controlling for other factors, we found that individuals in rural communities were still less likely than individuals from urban communities to receive an opioid agonist when starting treatment. In addition, African Americans, another population with historically poorer access to and quality of behavioral healthcare than whites (Alegria et al., 2002; Daley, 2005; Moos et al., 2001; Wang et al., 2002; Wells et al., 2001; Young et al., 2001) continued to be significantly less likely than whites to start treatment with an opioid agonist, a finding consistent with other studies documenting a preference for receiving non-pharmacologic interventions (Cooper et al., 2003; Leslie et al., 2003). Opioid disorders remain an important problem in many African-American communities and rural communities (Gfroerer et al., 2007; Wu, 2010). While buprenorphine and office-based treatment are making important contributions to the treatment of opioid dependence, targeted efforts must continue to be made to close the disparity in treatment for these communities. Like all studies, our results must be considered within the context of their limitations. Our study relied on administrative data that lacks rich clinical and social information, such as severity of illness and prior treatment history, which are likely to explain a significant amount of the variation observed. We have no information on the quality or clinical appropriateness of services, such as the nature of non-pharmacologic interventions that individuals are receiving. We are unaware of policy changes similar to those reported in other states (Clark et al., 2011), such as restrictions on the use of buprenorphine, which may have limited Medicaid-enrollees use of buprenorphine. Such policies could influence our findings. We note, however, that the number of methadone programs providing services to Medicaid enrolled
p-Value
CI
CI
individuals remained relatively stable in the time frame examined, suggesting there were neither policies resulting in widespread reductions in the number of programs, nor any substantial increase in the number of available methadone treatment “slots.” We are unable to observe shifts in the treatment of opioid dependence among commercially insured or uninsured populations, and such shifts could affect the availability of slots in OAT programs or with physicians certified to prescribe buprenorphine. We are not aware that any such shifts occurred, however, and an analysis of a subpopulation in a region in which we also have data regarding opioid dependence treatment funded by block grants found that including those individuals increased the total number of new opioid dependence treatment episodes by only 13%, with the pattern of increased buprenorphine use comparable to that seen in the Medicaid population. We also do not know how our findings generalize to different regions with different polices regarding buprenorphine, methadone, or substance abuse treatment more generally, or for which the numbers of substance abuse and mental health providers are either greater or fewer than exist in the area we examined. It is important to note that we do not know the number of individuals with opioid dependence who did not initiate treatment. An important objective of disseminating buprenorphine is to reduce this number. We do not know if our findings generalize to Medicaid enrollees in counties managed by other managed behavioral health organizations, nor do we know if our findings generalize to individuals other than Medicaid-enrollees, although we note that research suggests that Medicaid plays a substantial role in the treatment of individuals with opioid disorders (Baxter et al., 2011; Becker et al., 2008). Services provided under block grants are not observed in Medicaid claims data, and while substance abuse treatment services supported by block grants are limited in the regions in which this sample resides, to the extent those services are provided we may be undercounting opioid dependence treatment provided. Despite these limitations, our findings make an important contribution to our understanding of opioid dependence treatment
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
among Medicaid-enrollees. We found an increase in the overall number of new opioid dependence treatment episodes, a modest increase in the rate of new opioid dependence treatment episodes per capita, and a substantial increase in the percentage of new episodes involving buprenorphine from 2007 through 2009. These findings are reassuring at a time of increasing resource constraints in many communities for treatment of substance abuse disorders. However, the proportion of individuals identified with opioid dependence receiving any opioid agonist therapy did not appreciably change. Given the increased demand, buprenorphine may be serving as a treatment portal for individuals who would not have received OAT, particularly in rural areas, or it may be that buprenorphine is serving as a substitute for methadone treatment among those who would already have initiated treatment. Our findings with respect to differences between rural and urban areas in the use of buprenorphine and office-based treatment episodes suggest that the use of buprenorphine in urban and rural areas may be very different. This may indicate a potential need for increasing the number of office-based providers of buprenorphine in urban areas, or may require additional efforts to increase awareness of office-based buprenorphine use. In addition, public education campaigns targeted to opiate dependent individuals may be warranted, to increase knowledge and awareness about treatment options, including buprenorphine. While buprenorphine continues to hold the promise of increasing access to OAT, our data suggest that merely making buprenorphine available may not be enough; additional interventions aimed at providers and patients may be required to increase the number of opiate dependent individuals receiving OAT. Future research should be directed toward understanding factors influencing the supply of and demand for opioid dependence treatment as well as investigating interventions to optimize the use of buprenorphine, particularly in urban settings and among racial/ethnic minority populations. Role of funding source Support for this study was provided by the Community Care Behavioral Health Organization. Contributors Drs. Stein and Mr. Sorbero designed the study, conducted the analysis, and participated in the writing of the manuscript. Drs. Gordon, Dick, and Farmer also participated in the writing of the manuscript and made critical revisions to manuscript content. Dr. Schuster obtained some of the data for the study, and also made critical revisions to the manuscript. Conflict of interest Drs. Stein and Schuster and Mr. Sorbero are affiliated with Community Care Behavioral Health Organization. No other authors have any conflicts to declare. The authors are indebted to the Community Care Performance Management Committee and Mike Flaherty, Chairman of IRETA, The Institute for Research, Education and Training in Addictions, for their input on prior versions of this work. The authors are indebted to Emily Magee for research assistance and to Laura Greenberg and Amanda Ayers for assistance with the preparation of the manuscript. References Alegria, M., Canino, G., Rios, R., Vera, M., Calderon, J., Rusch, D., Ortega, A.N., 2002. Mental health care for Latinos: Inequalities in use of specialty mental health services among Latinos, African Americans, and non-Latino Whites. Psychiatr. Serv. 53, 1547–1555.
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American Methadone Treatment Association, 1998. Methadone Maintenance Program and Patient Census in the US. American Methadone Treatment Association, New York. Arfken, C.L., Johanson, C.E., di Menza, S., Schuster, C.R., 2010. Expanding treatment capacity for opioid dependence with office-based treatment with buprenorphine: national surveys of physicians. J. Subst. Abuse Treat. 39, 96–104. Barnett, P.G., 2009. Comparison of costs and utilization among buprenorphine and methadone patients. Addiction 104, 982–992. Baxter, J.D., Clark, R.E., Samnaliev, M., Leung, G.Y., Hashemi, L., 2011. Factors associated with Medicaid patients’ access to buprenorphine treatment. J. Subst. Abuse Treat. 41, 88–96. Becker, W.C., Fiellin, D.A., Merrill, J.O., Schulman, B., Finkelstein, R., Olsen, Y., Busch, S.H., 2008. Opioid use disorder in the United States: insurance status and treatment access. Drug Alcohol Depend. 94, 207–213. Cicero, T.J., Surratt, H., Inciardi, J.A., Munoz, A., 2007. Relationship between therapeutic use and abuse of opioid analgesics in rural, suburban, and urban locations in the United States. Pharmacoepidemiol. Drug Saf. 16, 827–840. Clark, R.E., Samnaliev, M., Baxter, J.D., Leung, G.Y., 2011. The evidence doesn‘t justify steps by state Medicaid programs to restrict opioid addiction treatment with buprenorphine. Health Aff. (Millwood) 30, 1425–1433. Cooper, L.A., Gonzales, J.J., Gallo, J.J., Rost, K.M., Meredith, L.S., Rubenstein, L.V., Wang, N.Y., Ford, D.E., 2003. The acceptability of treatment for depression among African-American, Hispanic, and white primary care patients. Med. Care 41, 479–489. Daley, M.C., 2005. Race, managed care, and the quality of substance abuse treatment. Adm. Policy Ment. Health 32, 457–476. Ducharme, L., Abraham, A., 2008. State policy influence on the early diffusion of buprenorphine in community treatment programs. Subst. Abuse Treat. Prev. Policy 3, 17–27. Gfroerer, J.C., Larson, S.L., Colliver, J.D., 2007. Drug use patterns and trends in rural communities. J. Rural Health 23, 10–15. Gordon, A.J., Fiellin, D.A., Friedmann, P.D., Gourevitch, M.N., Kraemer, K.L., Arnsten, J.H., Saitz, R., 2008. Update in addiction medicine for the primary care clinician. J. Gen. Intern. Med. 23, 2112–2116. Gordon, A.J., Trafton, J.A., Saxon, A.J., Gifford, A.L., Goodman, F., Calabrese, V.S., McNicholas, L., Liberto, J., 2007. Implementation of buprenorphine in the Veterans Health Administration: results of the first 3 years. Drug Alcohol Depend. 90, 292–296. Harris, A.H., Gospodarevskaya, E., Ritter, A.J., 2005. A randomised trial of the cost effectiveness of buprenorphine as an alternative to methadone maintenance treatment for heroin dependence in a primary care setting. Pharmacoeconomics 23, 77–91. Jones, E.S., Moore, B.A., Sindelar, J.L., O‘Connor, P.G., Schottenfeld, R.S., Fiellin, D.A., 2009. Cost analysis of clinic and office-based treatment of opioid dependence: results with methadone and buprenorphine in clinically stable patients. Drug Alcohol Depend. 99, 132–140. Knudsen, H.K., Ducharme, L.J., Roman, P.M., 2006. Early buprenorphine adoption in substance abuse treatment centers: data from the public and private sectors. J. Subst. Abuse Treat. 30, 363–373. Knudsen, H.K., Ducharme, L.J., Roman, P.M., 2007. The adoption of medications in substance abuse treatment: associations with organizational characteristics and technology clusters. Drug Alcohol Depend. 87, 164–174. Koch, A.L., Arfken, C.L., Schuster, C.R., 2006. Characteristics of US substance abuse treatment facilities adopting buprenorphine in its initial stage of availability. Drug Alcohol Depend. 83, 274–278. Krantz, M.J., Mehler, P.S., 2004. Treating opioid dependence. Growing implications for primary care. Arch. Intern. Med. 164, 277–288. Leslie, L.K., Weckerly, J., Landsverk, J., Hough, R.L., Hurlburt, M.S., Wood, P.A., 2003. Racial/ethnic differences in the use of psychotropic medication in highrisk children and adolescents. J. Am. Acad. Child Adolesc. Psychiatry 42, 1433–1442. Ling, W., Jacobs, P., Hillhouse, M., Hasson, A., Thomas, C., Freese, T., Sparenborg, S., McCarty, D., Weiss, R., Saxon, A., Cohen, A., Straus, M., Brigham, G., Liu, D., McLaughlin, P., Tai, B., 2010. From research to the real world: buprenorphine in the decade of the Clinical Trials Network. J. Subst. Abuse Treat. 38, S53–S60. Lurie, N., Popkin, M., Dysken, M., Moscovice, I., Finch, M., 1992. Accuracy of diagnoses of schizophrenia in Medicaid claims. Hosp. Community Psych. 43, 69–71. Marsch, L.A., 1998. The efficacy of methadone maintenance interventions in reducing illicit opiate use, HIV risk behavior and criminality: a meta-analysis. Addiction 93, 515–532. Mattick, R.P., Ali, R., White, J.M., O’Brien, S., Wolk, S., Danz, C., 2003. Buprenorphine versus methadone maintenance therapy: a randomized double-blind trial with 405 opioid-dependent patients. Addiction 98, 441–452. Mattick, R.P., Breen, C., Kimber, J., Davoli, M., 2009. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst. Rev., CD002209. Mattick, R.P., Kimber, J., Breen, C., Davoli, M., 2008. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst. Rev., CD002207. Moos, R.H., Moos, B.S., Finney, J.W., 2001. Predictors of deterioration among patients with substance-use disorders. J. Clin. Psychol. 57, 1403–1419. National Consensus Development Panel, 1998. Effective medical treatment of opiate addiction. JAMA 280, 1936–1943. National Institute of Drug Abuse, 2006. Principles of Effective Treatment for Criminal Justice Populations. Rockville, MD.
78
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
National Institute of Drug Abuse National Quality Forum, 2005. Evidence-based Treatment Practices for Substance Use Disorders: Workshop Proceedings , National Quality Forum, Washington, DC. O’Connor, P.G., Oliveto, A.H., Shi, J.M., Triffleman, E.G., Carroll, K.M., Kosten, T.R., Rounsaville, B.J., Pakes, J.A., Schottenfeld, R.S., 1998. A randomized trial of buprenorphine maintenance for heroin dependence in a primary care clinic for substance users versus a methadone clinic. Am. J. Med. 105, 100–105. Sullivan, L.E., Chawarski, M., O’Connor, P.G., Schottenfeld, R.S., Fiellin, D.A., 2005. The practice of office-based buprenorphine treatment of opioid dependence: is it associated with new patients entering into treatment? Drug Alcohol Depend. 79, 113–116. U.S. Department of Health Human Services, 2010. Results from the 2009 National Survey on Drug Use and Health: Vol. 1. Summary of National Findings. Substance Abuse and Mental Health Services Administration, Rockville, MD. U.S. Department of Justice, 2004. Buprenorphine: Potential for Abuse. Intellegence Bulletin. National Drug Intellegence Center, Johnstown, PA, pp. 1–8.
Volkow, N.D., 2004. NIDA at 30: committed to scientific solutions for drug addiction problems. NIDA Notes, 19. http://www.drugabuse.gov/NIDA notes/ NNvol19N1/DirRep. Accessed on January 15 2007. Wang, P.S., Demler, O., Kessler, R.C., 2002. Adequacy of treatment for serious mental illness in the United States. Am. J. Public Health 92, 92–98. Wells, K., Klap, R., Koike, A., Sherbourne, C., 2001. Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care. Am. J. Psychiatry 158, 2027–2032. Wu, L.T., 2010. Gender and racial/ethnic differences in addiction severity, HIV risk, and quality of life among adults in opioid detoxification: results from the National Drug Abuse Treatment Clinical Trials Network. Subst. Abuse Rehabil., 13–22. Young, A.S., Klap, R., Sherbourne, C.D., Wells, K.B., 2001. The quality of care for depressive and anxiety disorders in the United States. Arch. Gen. Psychiatry 58, 55–61. Zito, J.M., Safer, D.J., Zuckerman, I.H., Gardner, J.F., Soeken, K., 2005. Effect of Medicaid eligibility category on racial disparities in the use of psychotropic medications among youths. Psychiatr. Serv. 56, 157–163.
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Drug and Alcohol Dependence journal homepage: www.elsevier.com/locate/drugalcdep
The impact of buprenorphine on treatment of opioid dependence in a Medicaid population: Recent service utilization trends in the use of buprenorphine and methadone Bradley D. Stein a,c,∗ , Adam J. Gordon b , Mark Sorbero a , Andrew W. Dick c , James Schuster a , Carrie Farmer c a
Community Care Behavioral Health Organization, One Chatham Center, 112 Washington Place, Suite 700, Pittsburgh, PA 15219, United States Center for Research on Health Care, University of Pittsburgh, 7180 Highland Drive (151-C-H), Pittsburgh, PA 15206, United States c RAND Corporation, 4570 Fifth Avenue, Suite 600, Pittsburgh, PA 15213, United States b
a r t i c l e
i n f o
Article history: Received 3 August 2011 Received in revised form 18 October 2011 Accepted 19 October 2011 Available online 16 November 2011 Keywords: Buprenorphine Methadone Opiate dependence Office-based treatment
a b s t r a c t Background: Buprenorphine provides an important option for individuals with opioid dependence who are unwilling or unable to attend a licensed methadone opioid agonist treatment program to receive opioid agonist therapy (OAT). Little empirical information is available, however, about the extent to which buprenorphine has increased the percentage of opioid dependent individuals receiving OAT, nor to what extent buprenorphine is being used in office based settings. Methods: Using administrative data from the largest Medicaid managed behavioral health organization in a large mid-Atlantic state, we used multivariate regression to examine rates and predictors of opioid agonist use and treatment setting for 14,386 new opioid dependence treatment episodes during 2007–2009. Results: Despite an increase in the use of buprenorphine, the percentage of new treatment episodes involving OAT is unchanged due to a decrease in the percentage of episodes involving methadone. Use of buprenorphine was significantly more common in rural communities, and 64% of buprenorphine use was in office-based settings. Conclusion: Buprenorphine use has increased in recent years, with the greatest use in rural communities and in office based settings. However, the percentage of new opioid dependence treatment episodes involving an opioid agonist is unchanged, suggesting the need for further efforts to increase buprenorphine use among urban populations. © 2011 Published by Elsevier Ireland Ltd.
1. Introduction Opioid use disorders (opioid abuse and opioid dependence) are a significant public health problem, affecting hundreds of thousands of Americans (U.S. Department of Health and Human Services and Substance Abuse and Mental Health Services Administration Office of Applied Studies, 2010) with an estimated societal cost of $20 billion annually (National Consensus Development Panel, 1998). Historically, less than 25% of opioid dependent individuals receive opioid agonist therapy (OAT; American Methadone Treatment Association, 1998), the most effective intervention for opioid dependence with a broad evidence base (Marsch, 1998; Mattick et al., 2003, 2008; National Institute of Drug Abuse, 2006; National Institute of Drug Abuse National Quality Forum, 2005; Volkow, 2004), and one that has been shown to have a range of
∗ Corresponding author. Tel.: +1 412 454 8633. E-mail address: [email protected] (B.D. Stein). 0376-8716/$ – see front matter © 2011 Published by Elsevier Ireland Ltd. doi:10.1016/j.drugalcdep.2011.10.016
individual and societal benefits (Krantz and Mehler, 2004; Marsch, 1998; Mattick et al., 2008; National Consensus Development Panel, 1998). The FDA’s 2002 approval of buprenorphine and buprenorphine/naloxone (collectively buprenorphine) for opioid dependence treatment served as an opportunity to increase the number of patients with opioid dependence receiving OAT (Ducharme and Abraham, 2008). Under the physician waiver program established by the Drug Addiction Treatment Act of 2000, physicians could prescribe buprenorphine in regular officebased settings. This more flexible approach to opioid dependence treatment represented a paradigm shift from prior OAT treatment, which regulations had required to be taken in a licensed methadone program operating under strict state and federal regulations for treatment that commonly included daily attendance for dosing on-site (Ling et al., 2010). Compared to methadone, buprenorphine has been found to be effective and cost-effective (Barnett, 2009; Harris et al., 2005; Jones et al., 2009; Mattick et al., 2009, 2008), and buprenorphine’s approval was therefore expected to increase
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
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access to OAT for individuals unable or unwilling to attend licensed methadone programs (O’Connor et al., 1998; Sullivan et al., 2005). Furthermore, the availability of buprenorphine OAT expanded pharmacologic options in licensed methadone opioid agonist treatment programs as well as in specialty addiction treatment programs that are not licensed to prescribe methadone. While studies have documented buprenorphine use in officebased settings (Arfken et al., 2010) and the diffusion of buprenorphine use among opioid agonist treatment program and specialty addiction treatment program facilities (Ducharme and Abraham, 2008; Knudsen et al., 2006, 2007; Koch et al., 2006), there is a paucity of empirical data examining buprenorphine use and its relationship with methadone use and non-pharmacologic interventions in the treatment of opioid dependence. We are unaware of studies examining to what extent the introduction of buprenorphine has increased the overall number of individuals receiving OAT. Furthermore, if the number of individuals receiving OAT is increasing, it is not known whether this is related primarily to the availability of buprenorphine in office-based settings, or if an increase in OAT use is also occurring among individuals being treated in opioid agonist treatment programs and specialty addiction treatment programs. To better understand the role buprenorphine is playing in expanding access to OAT, we examined the use of buprenorphine and methadone from 2007 to 2009 among publicly insured individuals in a large Mid-Atlantic state. We hypothesized that the use of both buprenorphine and OAT increased over time, with a substantial amount of buprenorphine use observed in office based and rural settings.
Race/ethnicity was categorized as white, African-American, or other. Consistent with other analyses of Medicaid-enrolled populations (Zito et al., 2005), individuals were categorized into Medicaid eligibility categories according to whether their Medicaid eligibility resulted from a disability or was income related. Consistent with other studies, we identified individuals with a comorbid serious mental illness if they had one inpatient or 2 outpatient claims with a diagnosis of schizophrenia, bipolar disorder, and major depression (Lurie et al., 1992). Dually eligible individuals (Medicaid/Medicare) were excluded from the analysis as their pharmacy claims were unavailable in the state provided Medicaid data files. Using provider identifiers in the Medicaid claims, we linked individuals to treatment facilities, and categorized location of opioid dependence treatment as (1) opioid agonist treatment programs (methadone programs providing methadone and buprenorphine), (2) specialty addiction treatment programs (programs not licensed to dispense methadone but able to provide buprenorphine), and (3) office based opioid agonist treatment for individuals who did not receive any services at either of the preceding treatment settings. Office-based treatment includes individuals on buprenorphine who are receiving care in both primary care and outpatient psychiatric settings. Individuals were categorized as living in an urban area if their county of residence had a population density greater than 1000 individuals/ square-mile.
2. Methods
3. Results
2.1. Sample and data source
3.1. Characteristics of population
Using administrative data from the largest Medicaid managed behavioral health organization in a large mid-Atlantic state and state provided pharmacy data, we identified adults age 18–64 years old starting a new treatment episode for opioid dependence between January 1, 2007 and December 31, 2009. The study was conducted in compliance with the University of Pittsburgh Institutional Review Board. The managed behavioral health organization manages behavioral health care for over half of the counties in the state. All Medicaid enrolled individuals in each of these counties have essentially all of their behavioral health care services managed by the managed behavioral health organization, and there are limited block grant funded substance abuse treatment services available in the communities in which these individuals reside. Buprenorphine is available on the Medicaid formulary and commonly requires prior authorization, but in contrast to a number of other states where efforts are being made to limit use of buprenorphine (Clark et al., 2011), there is no “fail first” requirement nor in our conversations with providers do they report finding the prior authorization requirement particularly onerous. 2.2. Outcome and predictor variables We identified adults with a new opioid dependence treatment episode, which we defined as (1) a single inpatient claim or 2 or more outpatient behavioral health claims in a 90-day period with a diagnosis of opioid dependence (ICD code 304.0, 304.00, 304.01, 304.02, 304.03, 304.7, 304.70, 304.71, 304.72, 304.73), (2) a claim for a methadone related treatment service, or (3) a filled buprenorphine prescription (buprenorphine or buprenorphine/naloxone sublingual tablets) following a 90-day period with no claim with a diagnosis of opioid abuse or dependence, no methadone related services, and no prescription for buprenorphine. New treatment episodes were categorized as buprenorphine treatment, methadone treatment, or drug-free treatment. Individuals who received both buprenorphine and methadone within the first 90 days of starting the treatment episode were categorized as having buprenorphine treatment. We examined each year independently, so an individual could have a new treatment episode in each calendar year following a sufficiently long period with no treatment medications or services with a diagnosis of opioid abuse or dependence. Duration of treatment episodes was calculated from the beginning of the episode until the last observed claim, completed prescription, or end of the calendar year. For individuals who had more than one new treatment episode in a year, we included only the first treatment episode. Sociodemographic variables, including age, sex, Medicaid eligibility category, and race/ethnicity were obtained from the state’s membership and eligibility files.
2.3. Analysis We estimated three multivariate logistic regression models. We estimated the first model as a logistic regression of any opioid agonist treatment use among those with a new opioid dependence treatment episode, controlling for sex, race, urban/rural status, age, comorbid serious mental illness, Medicaid eligibility category, and year of episode. We estimated the second model as a logistic regression of buprenorphine use among those receiving any opioid agonist treatment, conditional on the same covariates. We estimated the third model as a logistic regression of office based treatment among those receiving buprenorphine, conditional on the same covariates. In each case, we calculated Huber-White standard errors to account for the intra-person correlation for those who contributed more than one treatment episode to the sample.
We identified 14,386 new opioid dependence treatment episodes by Medicaid-enrolled individuals from 2007 through 2009. The individuals starting treatment episodes were predominantly under the age of 35, white, and Medicaid eligible due to income (Table 1). Approximately half were male, and approximately one third resided in urban communities. The number of individuals starting treatment for opioid dependence increased 35% from 2007 (n = 4115) to 2009 (n = 5569). Twelve percent (n = 1793) of new episodes involved buprenorphine, 25% (n = 3581) involved methadone, and 63% (n = 9012) did not involve an opioid agonist. Of the 9012 individuals receiving drug-free treatment, the majority (71%; n = 6386) were receiving services from specialty addiction treatment programs, 19% were receiving services other than methadone from opioid agonist treatment programs, and 10% (n = 882) were receiving services from mental health providers. 3.2. Trends in the use of medications to treat opioid dependence from 2007 to 2009 We found that the number of new treatment episodes per adult Medicaid enrollees increased slightly from 1.6% in 2007 to 1.7% in 2008 and 2.0% in 2009. The number of new episodes involving buprenorphine more than doubled from 2007 (n = 367) to 2009 (n = 793), while there was a modest 6% increase in the number of new methadone episodes over the same time frame (Table 2). However, as the number of drug-free new treatment episodes increased by 37% over the same period, the overall percentage of new treatment episodes involving opioid agonists was essentially unchanged between 2007 (38%) and 2009 (37%). As highlighted in Table 2, the shifts in type of new treatment episodes were most pronounced in rural communities.
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B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
Table 1 Predictors of starting opioid dependence treatment with an opioid agonist. N
Total 14,386 Age (yrs) 4660 18–25 4857 26–35 2727 36–45 1820 46–55 322 56–64 Gender 7316 Male 7070 Female Race 1371 African American 12,158 White 857 Other Comorbid serious mental illness 2574 Yes No 11,812 Community Rural 9492 Urban 4894 Medicaid eligibility 2717 Disability 11,669 Income Year 4115 2007 2008 4702 2009 5569
Treatment with an opioid agonist (buprenorphine or methadone)
Drug-free treatment
Adjusted odds ratio of receiving an opioid agonist
n
%
n
%
aOR
p-Value
CI
CI
5374
37.4
9012
62.6
1575 1921 1025 703 150
33.8 39.6 37.6 38.6 46.6
3085 2936 1702 1117 172
66.2 60.5 63.4 61.4 53.4
1.31 1.30 1.51 2.60
<0.001 <0.001 <0.001 <0.001
1.20 1.17 1.33 1.99
1.43 1.45 1.72 3.39
2553 2821
34.9 39.9
4249
65.1 60.1
1.30
<0.001
1.21
1.40
393 4578 403
28.7 37.7 47.1
978 7580 454
71.3 62.4 53
0.57
<0.001
0.49
0.66
1.59
<0.001
1.36
1.85
828 4546
32.17 38.49
1746 7266
67.83 61.51
0.75
<0.001
0.68
0.82
3447 1927
36.3 39.3
6045 2967
63.7 60.6
0.83
<0.001
0.77
0.90
911 4463
33.5 38.2
1806 7206
66.5 61.8
1.26
<0.001
1.14
1.39
1555 1768 2051
37.8 37.6 36.8
2560 2934 3518
62.2 62.4 63.2
0.99 0.97
0.81 0.46
0.91 0.89
1.08 1.05
3.3. Characteristics of individuals starting opioid dependence treatment with an opioid agonist Approximately 37% of new treatment episodes (n = 5374) involved an opioid agonist. There were no substantial differences in sociodemographic characteristics of individuals starting treatment for opioid dependence across the different years (data not shown). Females were more likely than males (39.9% vs. 34.9%, aOR 1.29, 95% CI 1.20–1.39) to start their treatment episode with an opioid agonist (buprenorphine or methadone), as were individuals Medicaid-eligible due to income compared to individuals Medicaid-eligible due to disability (38.2% vs. 33.5%, aOR 1.31, 95% CI 1.19–1.44; Table 1). Individuals with a comorbid mental health disorder were significantly more likely than those without a comorbid disorder to start treatment with an opioid agonist (32.2% vs. 38.5%, aOR 0.75, 95% CI 0.68–0.82). Compared to individuals age 18–25, we found that all older age cohorts were significantly more likely to start treatment with an opioid agonist. We also found that
individuals in rural communities were significantly less likely to start treatment with an opioid agonist than individuals in urban communities (36.3% vs. 39.3%, aOR 0.82, 95% CI 0.76–0.89), as were African Americans when compared to whites (28.7% vs. 37.7%, aOR 0.57, 95% CI 0.49–0.66). Individuals in the “other” racial/ethnic category were significantly more likely than whites to start treatment with an opioid agonist (28.7% vs. 37.7%, aOR 1.54, 95% CI 1.33–1.79). There were no substantial differences in sociodemographic characteristics of individuals starting treatment for opioid dependence across the different years (data not shown). 3.4. Characteristics of individuals using buprenorphine vs. methadone Among the 5374 individuals starting treatment with an opioid agonist, one-third (n = 1793) received buprenorphine (Table 3). Across all 3 years, methadone episodes were significantly longer than buprenorphine episodes (74 days vs. 68 days, p < 0.01).
Table 2 Change over time in use of opioid agonists in new opioid dependence treatment episodes. 2007
2008
2009
Total number of adult non-dual eligible medicaid enrollees
256,752
272,617
281,046
Total number of new opioid dependence treatment episodes
N = 4115
N = 4702
N = 5569
Buprenorphine Urban Rural Methadone Urban Rural Drug-free treatment Urban Rural
n
%
n
%
n
%
367 40 327 1188 501 687 2560 866 1694
9 3 12 29 36 25 62 62 63
633 58 575 1135 633 502 2934 1003 1931
13 3 19 24 37 17 62 59 64
793 80 713 1258 615 643 3518 1098 2420
14 4 19 23 34 17 63 61 64
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Table 3 Predictors of starting treatment with buprenorphine among those starting treatment with an opioid agonist. N
Total 5374 Age (yrs) 18–25 (ref) 1575 26–35 1921 36–45 1025 46–55 703 150 56–64 Gender 2553 Male (ref) Female 2821 Race 393 African American White (ref) 4578 403 Other Comorbid serious mental illness 828 Yes 4546 No Community Rural 3447 Urban (ref) 1927 Medicaid eligibility category 911 Disability (ref) 4463 Income Year 1555 2007 (ref) 2008 1768 2009 2051 a
Methadonea
Buprenorphine
Adjusted Odds ratio of receiving buprenorphine
n
%
n
%
1793
33.4
3581
66.6
aOR
p-Value
CI
539 644 379 204 27
34.2 33.52 36.98 29.02 18.00
1036 1277 646 499 123
862 931
33.76 33.00
74 1541 178
CI
65.3 66.48 63.02 70.98 82.00
0.97 1.34 1.17 1.07
0.74 <0.01 0.19 0.80
0.82 1.10 0.93 0.63
1.15 1.64 1.48 1.82
1691 1890
66.24 67.00
0.85
<0.05
0.74
0.97
18.83 33.66 44.17
319 3037 225
81.17 66.34 55.83
0.80
0.14
0.60
1.07
0.86
0.24
0.68
1.10
393 1400
47.46 30.80
435 3146
52.54 69.20
1.67
<0.001
1.41
1.99
1615 178
46.85 9.24
1832 1749
53.15 90.76
9.08
<0.001
7.51
10.98
274 1519
30.08 34.04
637 2944
69.92 65.96
1.42
<0.001
1.18
1.70
367 633 793
23.60 35.80 38.66
1188 1135 1258
76.40 64.20 61.34
2.11 2.21
<0.001 <0.001
1.80 1.89
2.49 2.59
Individuals attended one of 26 methadone programs in 2007, and one of 23 programs in 2008 and 2009.
Controlling for other covariates, residing in a rural community was strongly associated with receiving buprenorphine; rural individuals were over nine times more likely to start treatment with buprenorphine than individuals in urban communities (46.8% vs. 9.2%, aOR 9.37, 95% CI 7.75–11.34). We also found that new treatment episodes in 2008 (35.8%) and 2009 (38.7%) were significantly more likely to involve buprenorphine than new episodes in 2007 (23.6%). 3.5. Treatment setting of individuals starting treatment with buprenorphine Among the 1793 episodes starting treatment with buprenorphine, we found that 64% were receiving office-based treatment. We found that individuals in rural areas receiving buprenorphine were dramatically more likely to be receiving office-based treatment than individuals in urban areas (71% vs. 2%; aOR 160, 168, 95% CI 52–542; Table 4). Age was also strongly predictive, with younger individuals less likely to receive office-based treatment than individuals in older cohorts. Individuals with a comorbid mental health disorder were significantly less likely than those without such a disability to receive office based treatment (54.7% vs. 66.4%; aOR 0.56, 95% CI 0.42–0.73). There were no significant differences by gender or Medicaid eligibility category regarding the treatment setting in which an individual was receiving buprenorphine, nor was there a significant difference in treatment settings for those receiving buprenorphine between 2007, 2008, and 2009. 4. Discussion In our examination of the use of buprenorphine and methadone in the treatment of individuals with opioid dependence from 2007 to 2009, we found that the number of new treatment episodes involving buprenorphine more than doubled during that period. The use of buprenorphine, however, did not appear to have a
substantial impact on the proportion of new treatment episodes involving OAT. While use of buprenorphine increased, consistent with other studies we found a corresponding increase in the overall number of new opioid dependence treatment episodes over the period observed (Baxter et al., 2011). Among individuals receiving OAT, however, we did find a substantial increase from 2007 to 2009 in the percentage of episodes involving buprenorphine. This resulted from a substantial increase in the number of episodes involving buprenorphine over the period with a corresponding slight increase in the number of episodes involving methadone. To the extent that experts hoped that buprenorphine would increase access to opioid agonist treatment (Ducharme and Abraham, 2008; Gordon et al., 2008, 2007; Ling et al., 2010), our finding that buprenorphine appears to be serving as a substitute for methadone rather than a complement suggests that while buprenorphine has increased the treatment options of individuals receiving opioid agonist treatment, the promise of buprenorphine as a way to extend access to opioid agonist treatment has not yet been realized. Among individuals starting treatment with buprenorphine, almost two-thirds (n = 1145) did not receive treatment in opioid agonist treatment programs or specialty addiction treatment programs, but in office-based treatment settings. One of the great advantages in access to buprenorphine compared to methadone was its potential use in office-based settings (Ducharme and Abraham, 2008), and we find substantial numbers of individuals receiving such treatment. The use of office-based treatment was most pronounced in rural areas. Typically, opioid agonist treatment programs and specialty addiction treatment programs are located in more urban areas (Cicero et al., 2007). Those living in rural areas must travel considerable distances to receive methadone treatment, which can be particularly challenging given daily methadone dispensation protocols (U.S. Department of Justice, 2004). Thus, office-based prescribing of buprenorphine is a particularly promising approach to enhancing the access of rural populations to opioid agonist treatment (Ducharme and Abraham, 2008). This is
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Table 4 Predictors of receiving office based treatment among individuals receiving buprenorphine. N
Total 1793 Age (yrs) 539 18–25 644 26–35 379 36–45 46–55 204 56–64 27 Gender 862 Male 931 Female Race 74 African American 1541 White Other 178 Comorbid serious mental illness Yes 393 No 1400 Community 1615 Rural 178 Urban Medicaid 274 Disability Income 1519 Year 367 2007 2008 633 793 2009
Office based opioid treatment settings
Specialty addiction treatment and opioid agonist treatment programs
Adjusted odds ration of receiving office based buprenorphine
n
%
n
%
aOR
1145
63.86
648
36.14
307 433 249 136 20
56.96 67.24 65.70 66.67 74.07
232 211 130 68 7
43.05 32.76 34.30 33.34 25.93
1.50 1.73 1.79 7.38
<0.01 <0.01 <0.01 <0.01
1.15 1.25 1.21 2.08
1.96 2.39 2.65 26.21
513 632
59.51 67.88
349 299
40.49 32.11
1.21
0.10
0.97
1.52
42 1012 91
56.76 65.67 51.12
32 529 87
43.25 34.32 48.88
0.58
0.05
0.33
1.00
0.45
<0.001
0.32
0.64
215 930
54.71 66.43
178 470
45.29 33.57
0.56
<0.001
0.42
0.73
1142 3
70.71 1.69
473 175
29.29 98.32
168.27
<0.001
52.19
542.50
169 976
61.68 64.25
105 543
38.32 35.74
1.21
0.24
0.88
1.65
236 423 486
64.31 66.82 61.29
131 210 307
35.69 33.17 38.71
1.11 0.86
0.50 0.32
0.82 0.65
1.50 1.15
consistent with our findings that individuals receiving opioid agonists in rural communities were over 9 times more likely to receive buprenorphine than individuals in urban communities, and that individuals receiving buprenorphine in rural areas were vastly more likely to receive the medication in office based settings. Yet, controlling for other factors, we found that individuals in rural communities were still less likely than individuals from urban communities to receive an opioid agonist when starting treatment. In addition, African Americans, another population with historically poorer access to and quality of behavioral healthcare than whites (Alegria et al., 2002; Daley, 2005; Moos et al., 2001; Wang et al., 2002; Wells et al., 2001; Young et al., 2001) continued to be significantly less likely than whites to start treatment with an opioid agonist, a finding consistent with other studies documenting a preference for receiving non-pharmacologic interventions (Cooper et al., 2003; Leslie et al., 2003). Opioid disorders remain an important problem in many African-American communities and rural communities (Gfroerer et al., 2007; Wu, 2010). While buprenorphine and office-based treatment are making important contributions to the treatment of opioid dependence, targeted efforts must continue to be made to close the disparity in treatment for these communities. Like all studies, our results must be considered within the context of their limitations. Our study relied on administrative data that lacks rich clinical and social information, such as severity of illness and prior treatment history, which are likely to explain a significant amount of the variation observed. We have no information on the quality or clinical appropriateness of services, such as the nature of non-pharmacologic interventions that individuals are receiving. We are unaware of policy changes similar to those reported in other states (Clark et al., 2011), such as restrictions on the use of buprenorphine, which may have limited Medicaid-enrollees use of buprenorphine. Such policies could influence our findings. We note, however, that the number of methadone programs providing services to Medicaid enrolled
p-Value
CI
CI
individuals remained relatively stable in the time frame examined, suggesting there were neither policies resulting in widespread reductions in the number of programs, nor any substantial increase in the number of available methadone treatment “slots.” We are unable to observe shifts in the treatment of opioid dependence among commercially insured or uninsured populations, and such shifts could affect the availability of slots in OAT programs or with physicians certified to prescribe buprenorphine. We are not aware that any such shifts occurred, however, and an analysis of a subpopulation in a region in which we also have data regarding opioid dependence treatment funded by block grants found that including those individuals increased the total number of new opioid dependence treatment episodes by only 13%, with the pattern of increased buprenorphine use comparable to that seen in the Medicaid population. We also do not know how our findings generalize to different regions with different polices regarding buprenorphine, methadone, or substance abuse treatment more generally, or for which the numbers of substance abuse and mental health providers are either greater or fewer than exist in the area we examined. It is important to note that we do not know the number of individuals with opioid dependence who did not initiate treatment. An important objective of disseminating buprenorphine is to reduce this number. We do not know if our findings generalize to Medicaid enrollees in counties managed by other managed behavioral health organizations, nor do we know if our findings generalize to individuals other than Medicaid-enrollees, although we note that research suggests that Medicaid plays a substantial role in the treatment of individuals with opioid disorders (Baxter et al., 2011; Becker et al., 2008). Services provided under block grants are not observed in Medicaid claims data, and while substance abuse treatment services supported by block grants are limited in the regions in which this sample resides, to the extent those services are provided we may be undercounting opioid dependence treatment provided. Despite these limitations, our findings make an important contribution to our understanding of opioid dependence treatment
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
among Medicaid-enrollees. We found an increase in the overall number of new opioid dependence treatment episodes, a modest increase in the rate of new opioid dependence treatment episodes per capita, and a substantial increase in the percentage of new episodes involving buprenorphine from 2007 through 2009. These findings are reassuring at a time of increasing resource constraints in many communities for treatment of substance abuse disorders. However, the proportion of individuals identified with opioid dependence receiving any opioid agonist therapy did not appreciably change. Given the increased demand, buprenorphine may be serving as a treatment portal for individuals who would not have received OAT, particularly in rural areas, or it may be that buprenorphine is serving as a substitute for methadone treatment among those who would already have initiated treatment. Our findings with respect to differences between rural and urban areas in the use of buprenorphine and office-based treatment episodes suggest that the use of buprenorphine in urban and rural areas may be very different. This may indicate a potential need for increasing the number of office-based providers of buprenorphine in urban areas, or may require additional efforts to increase awareness of office-based buprenorphine use. In addition, public education campaigns targeted to opiate dependent individuals may be warranted, to increase knowledge and awareness about treatment options, including buprenorphine. While buprenorphine continues to hold the promise of increasing access to OAT, our data suggest that merely making buprenorphine available may not be enough; additional interventions aimed at providers and patients may be required to increase the number of opiate dependent individuals receiving OAT. Future research should be directed toward understanding factors influencing the supply of and demand for opioid dependence treatment as well as investigating interventions to optimize the use of buprenorphine, particularly in urban settings and among racial/ethnic minority populations. Role of funding source Support for this study was provided by the Community Care Behavioral Health Organization. Contributors Drs. Stein and Mr. Sorbero designed the study, conducted the analysis, and participated in the writing of the manuscript. Drs. Gordon, Dick, and Farmer also participated in the writing of the manuscript and made critical revisions to manuscript content. Dr. Schuster obtained some of the data for the study, and also made critical revisions to the manuscript. Conflict of interest Drs. Stein and Schuster and Mr. Sorbero are affiliated with Community Care Behavioral Health Organization. No other authors have any conflicts to declare. The authors are indebted to the Community Care Performance Management Committee and Mike Flaherty, Chairman of IRETA, The Institute for Research, Education and Training in Addictions, for their input on prior versions of this work. The authors are indebted to Emily Magee for research assistance and to Laura Greenberg and Amanda Ayers for assistance with the preparation of the manuscript. References Alegria, M., Canino, G., Rios, R., Vera, M., Calderon, J., Rusch, D., Ortega, A.N., 2002. Mental health care for Latinos: Inequalities in use of specialty mental health services among Latinos, African Americans, and non-Latino Whites. Psychiatr. Serv. 53, 1547–1555.
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American Methadone Treatment Association, 1998. Methadone Maintenance Program and Patient Census in the US. American Methadone Treatment Association, New York. Arfken, C.L., Johanson, C.E., di Menza, S., Schuster, C.R., 2010. Expanding treatment capacity for opioid dependence with office-based treatment with buprenorphine: national surveys of physicians. J. Subst. Abuse Treat. 39, 96–104. Barnett, P.G., 2009. Comparison of costs and utilization among buprenorphine and methadone patients. Addiction 104, 982–992. Baxter, J.D., Clark, R.E., Samnaliev, M., Leung, G.Y., Hashemi, L., 2011. Factors associated with Medicaid patients’ access to buprenorphine treatment. J. Subst. Abuse Treat. 41, 88–96. Becker, W.C., Fiellin, D.A., Merrill, J.O., Schulman, B., Finkelstein, R., Olsen, Y., Busch, S.H., 2008. Opioid use disorder in the United States: insurance status and treatment access. Drug Alcohol Depend. 94, 207–213. Cicero, T.J., Surratt, H., Inciardi, J.A., Munoz, A., 2007. Relationship between therapeutic use and abuse of opioid analgesics in rural, suburban, and urban locations in the United States. Pharmacoepidemiol. Drug Saf. 16, 827–840. Clark, R.E., Samnaliev, M., Baxter, J.D., Leung, G.Y., 2011. The evidence doesn‘t justify steps by state Medicaid programs to restrict opioid addiction treatment with buprenorphine. Health Aff. (Millwood) 30, 1425–1433. Cooper, L.A., Gonzales, J.J., Gallo, J.J., Rost, K.M., Meredith, L.S., Rubenstein, L.V., Wang, N.Y., Ford, D.E., 2003. The acceptability of treatment for depression among African-American, Hispanic, and white primary care patients. Med. Care 41, 479–489. Daley, M.C., 2005. Race, managed care, and the quality of substance abuse treatment. Adm. Policy Ment. Health 32, 457–476. Ducharme, L., Abraham, A., 2008. State policy influence on the early diffusion of buprenorphine in community treatment programs. Subst. Abuse Treat. Prev. Policy 3, 17–27. Gfroerer, J.C., Larson, S.L., Colliver, J.D., 2007. Drug use patterns and trends in rural communities. J. Rural Health 23, 10–15. Gordon, A.J., Fiellin, D.A., Friedmann, P.D., Gourevitch, M.N., Kraemer, K.L., Arnsten, J.H., Saitz, R., 2008. Update in addiction medicine for the primary care clinician. J. Gen. Intern. Med. 23, 2112–2116. Gordon, A.J., Trafton, J.A., Saxon, A.J., Gifford, A.L., Goodman, F., Calabrese, V.S., McNicholas, L., Liberto, J., 2007. Implementation of buprenorphine in the Veterans Health Administration: results of the first 3 years. Drug Alcohol Depend. 90, 292–296. Harris, A.H., Gospodarevskaya, E., Ritter, A.J., 2005. A randomised trial of the cost effectiveness of buprenorphine as an alternative to methadone maintenance treatment for heroin dependence in a primary care setting. Pharmacoeconomics 23, 77–91. Jones, E.S., Moore, B.A., Sindelar, J.L., O‘Connor, P.G., Schottenfeld, R.S., Fiellin, D.A., 2009. Cost analysis of clinic and office-based treatment of opioid dependence: results with methadone and buprenorphine in clinically stable patients. Drug Alcohol Depend. 99, 132–140. Knudsen, H.K., Ducharme, L.J., Roman, P.M., 2006. Early buprenorphine adoption in substance abuse treatment centers: data from the public and private sectors. J. Subst. Abuse Treat. 30, 363–373. Knudsen, H.K., Ducharme, L.J., Roman, P.M., 2007. The adoption of medications in substance abuse treatment: associations with organizational characteristics and technology clusters. Drug Alcohol Depend. 87, 164–174. Koch, A.L., Arfken, C.L., Schuster, C.R., 2006. Characteristics of US substance abuse treatment facilities adopting buprenorphine in its initial stage of availability. Drug Alcohol Depend. 83, 274–278. Krantz, M.J., Mehler, P.S., 2004. Treating opioid dependence. Growing implications for primary care. Arch. Intern. Med. 164, 277–288. Leslie, L.K., Weckerly, J., Landsverk, J., Hough, R.L., Hurlburt, M.S., Wood, P.A., 2003. Racial/ethnic differences in the use of psychotropic medication in highrisk children and adolescents. J. Am. Acad. Child Adolesc. Psychiatry 42, 1433–1442. Ling, W., Jacobs, P., Hillhouse, M., Hasson, A., Thomas, C., Freese, T., Sparenborg, S., McCarty, D., Weiss, R., Saxon, A., Cohen, A., Straus, M., Brigham, G., Liu, D., McLaughlin, P., Tai, B., 2010. From research to the real world: buprenorphine in the decade of the Clinical Trials Network. J. Subst. Abuse Treat. 38, S53–S60. Lurie, N., Popkin, M., Dysken, M., Moscovice, I., Finch, M., 1992. Accuracy of diagnoses of schizophrenia in Medicaid claims. Hosp. Community Psych. 43, 69–71. Marsch, L.A., 1998. The efficacy of methadone maintenance interventions in reducing illicit opiate use, HIV risk behavior and criminality: a meta-analysis. Addiction 93, 515–532. Mattick, R.P., Ali, R., White, J.M., O’Brien, S., Wolk, S., Danz, C., 2003. Buprenorphine versus methadone maintenance therapy: a randomized double-blind trial with 405 opioid-dependent patients. Addiction 98, 441–452. Mattick, R.P., Breen, C., Kimber, J., Davoli, M., 2009. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst. Rev., CD002209. Mattick, R.P., Kimber, J., Breen, C., Davoli, M., 2008. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst. Rev., CD002207. Moos, R.H., Moos, B.S., Finney, J.W., 2001. Predictors of deterioration among patients with substance-use disorders. J. Clin. Psychol. 57, 1403–1419. National Consensus Development Panel, 1998. Effective medical treatment of opiate addiction. JAMA 280, 1936–1943. National Institute of Drug Abuse, 2006. Principles of Effective Treatment for Criminal Justice Populations. Rockville, MD.
78
B.D. Stein et al. / Drug and Alcohol Dependence 123 (2012) 72–78
National Institute of Drug Abuse National Quality Forum, 2005. Evidence-based Treatment Practices for Substance Use Disorders: Workshop Proceedings , National Quality Forum, Washington, DC. O’Connor, P.G., Oliveto, A.H., Shi, J.M., Triffleman, E.G., Carroll, K.M., Kosten, T.R., Rounsaville, B.J., Pakes, J.A., Schottenfeld, R.S., 1998. A randomized trial of buprenorphine maintenance for heroin dependence in a primary care clinic for substance users versus a methadone clinic. Am. J. Med. 105, 100–105. Sullivan, L.E., Chawarski, M., O’Connor, P.G., Schottenfeld, R.S., Fiellin, D.A., 2005. The practice of office-based buprenorphine treatment of opioid dependence: is it associated with new patients entering into treatment? Drug Alcohol Depend. 79, 113–116. U.S. Department of Health Human Services, 2010. Results from the 2009 National Survey on Drug Use and Health: Vol. 1. Summary of National Findings. Substance Abuse and Mental Health Services Administration, Rockville, MD. U.S. Department of Justice, 2004. Buprenorphine: Potential for Abuse. Intellegence Bulletin. National Drug Intellegence Center, Johnstown, PA, pp. 1–8.
Volkow, N.D., 2004. NIDA at 30: committed to scientific solutions for drug addiction problems. NIDA Notes, 19. http://www.drugabuse.gov/NIDA notes/ NNvol19N1/DirRep. Accessed on January 15 2007. Wang, P.S., Demler, O., Kessler, R.C., 2002. Adequacy of treatment for serious mental illness in the United States. Am. J. Public Health 92, 92–98. Wells, K., Klap, R., Koike, A., Sherbourne, C., 2001. Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care. Am. J. Psychiatry 158, 2027–2032. Wu, L.T., 2010. Gender and racial/ethnic differences in addiction severity, HIV risk, and quality of life among adults in opioid detoxification: results from the National Drug Abuse Treatment Clinical Trials Network. Subst. Abuse Rehabil., 13–22. Young, A.S., Klap, R., Sherbourne, C.D., Wells, K.B., 2001. The quality of care for depressive and anxiety disorders in the United States. Arch. Gen. Psychiatry 58, 55–61. Zito, J.M., Safer, D.J., Zuckerman, I.H., Gardner, J.F., Soeken, K., 2005. Effect of Medicaid eligibility category on racial disparities in the use of psychotropic medications among youths. Psychiatr. Serv. 56, 157–163.