State-Targeted Funding and Technical Assistance to Increase Access to Medication Treatment for Opioid Use Disorder
Abstract
Objective:
As the United States grapples with an opioid epidemic, expanding access to effective treatment for opioid use disorder is a major public health priority. Identifying effective policy tools that can be used to expand access to care is critically important. This article examines the relationship between state-targeted funding and technical assistance and adoption of three medications for treating opioid use disorder: oral naltrexone, injectable naltrexone, and buprenorphine.
Methods:
This study draws from the 2013–2014 wave of the National Drug Abuse Treatment System Survey, a nationally representative, longitudinal study of substance use disorder treatment programs. The sample includes data from 695 treatment programs (85.5% response rate) and representatives from single-state agencies in 49 states and Washington, D.C. (98% response rate). Logistic regression was used to examine the relationships of single-state agency targeted funding and technical assistance to availability of opioid use disorder medications among treatment programs.
Results:
State-targeted funding was associated with increased program-level adoption of oral naltrexone (adjusted odds ratio [AOR]=3.14, 95% confidence interval [CI]=1.49–6.60, p=.004) and buprenorphine (AOR=2.47, 95% CI=1.31–4.67, p=.006). Buprenorphine adoption was also correlated with state technical assistance to support medication provision (AOR=1.18, 95% CI=1.00–1.39, p=.049).
Conclusions:
State-targeted funding for medications may be a viable policy lever for increasing access to opioid use disorder medications. Given the historically low rates of opioid use disorder medication adoption in treatment programs, single-state agency targeted funding is a potentially important tool to reduce mortality and morbidity associated with opioid disorders and misuse.
In 2014, an estimated 4.7 million Americans were dependent on opioids, including both prescription opioids and heroin (1). Prescription opioid overdose, abuse, and misuse cost an estimated $78.5 billion in 2013 (2). Opioid use disorder is associated with a range of health issues, including cardiovascular disease, diabetes, HIV/AIDS, and hepatitis C (3–10). Of particular concern is the dramatic rise in opioid overdose deaths related to prescription opioids and heroin (11,12). The rate of opioid-related overdose deaths has increased more than 200% since 2000. In 2015, opioids were involved in 33,091 overdose deaths (13).
Increasing access to medications for treating opioid use disorder is widely acknowledged to be a key strategy for addressing the opioid epidemic (11,14,15). The effectiveness of methadone maintenance therapy has been demonstrated in many trials (16). Buprenorphine, a partial opioid agonist, and naltrexone, an opioid antagonist, the main focus of this article, can be readily prescribed in outpatient treatment settings and have also demonstrated efficacy (17–21). Poor compliance associated with oral naltrexone suggests that it may be more effective for patients who are highly motivated or patients who are closely monitored. Patients must also be free from opioids for seven to 10 days prior to initiating treatment with naltrexone.
Buprenorphine is a schedule II narcotic and can be prescribed only by a physician holding a Drug Addiction Treatment Act of 2000 waiver. Physicians are limited to prescribing buprenorphine to a maximum of 30 patients at one time in the first year of holding a wavier, a maximum of 100 patients in the second year, and a maximum of 275 patients in the third year. There are no such prescribing regulations on naltrexone.
Use of medications for treating opioid use disorder is associated with reductions in opioid use, withdrawal and craving, infectious disease transmission, and treatment dropout (18,19,22–25). Research also has shown that buprenorphine and both formulations of naltrexone are cost-effective and that their use is associated with reductions in other types of health care utilization (26–28). For many Americans with opioid use disorder, these medications, used in conjunction with psychosocial therapy, are the most effective treatment option (17–20).
Despite the efficacy of buprenorphine and naltrexone, few treatment programs in the United States prescribe them (29). Data indicate that less than half of nonopioid treatment programs (non-OTPs; specifically, specialty treatment programs that are not licensed to dispense methadone) prescribe a single medication and that less than 40% have a physician on staff. Buprenorphine is the most commonly prescribed medication in non-OTPs, followed by oral naltrexone and injectable naltrexone (29).
The reasons for low rates of adoption of these medications in treatment programs are complex. Financial barriers have been a long-standing challenge for patients and treatment programs. Because many patients are unable to afford these medications, treatment programs that serve clients who are predominantly low-income and uninsured are less likely to offer them. Prior research has demonstrated that treatment programs that are large, for-profit, and accredited and that also serve a higher percentage of patients with private health insurance are significantly more likely to offer treatment medications for opioid use disorder such as buprenorphine and naltrexone (30–37).
Additionally, access to prescribers of medications has been a challenge for many treatment programs because of a lack of resources and federal restrictions limiting the number of physicians who can prescribe buprenorphine and the number of patients they can serve. As a result, it has been difficult for specialty treatment programs to attract and retain physicians who have the capacity to prescribe medications for treating opioid use disorder. Hospital-based programs and programs with a physician on staff have historically been more likely to adopt medications (29,31,36,38).
The Role of States in Medication Adoption
Substance use disorder treatment in the United States is delivered by the more than 14,000 programs that compose the specialty substance use disorder treatment system. Approximately two-thirds of specialty treatment programs rely on Substance Abuse Prevention and Treatment block grant funding provided by the Substance Abuse and Mental Health Services Administration (SAMHSA) and administered through each state’s single-state agency (SSA) (39–42). SSAs are state governmental organizations responsible for overseeing and licensing substance use disorder treatment programs. Each state’s SSA organizes and administers the distribution of the block grant, including determining treatment provider qualifications, payment methods and rates, and reporting requirements (39,43,44).
State policies influence adoption of medications by treatment programs (43,45). Rieckmann and colleagues (45) reported that a majority of SSAs used contract language (that is, contracts with treatment programs that either required or encouraged evidence-based practices) as a tool to promote implementation of evidence-based practices, including use of medications. Other studies examining the influence of state policy on medication adoption have focused exclusively on the adoption of buprenorphine. Using data from 2006, Ducharme and Abraham (31) found a positive association between state Medicaid coverage of buprenorphine and programs’ adoption of buprenorphine. A more recent study by Andrews and colleagues (30) examined the adoption of buprenorphine in a national sample of OTPs and found that the odds of offering buprenorphine were greater in OTPs located in states that provided subsidies to support buprenorphine adoption.
Taken together, these studies suggest that state-targeted funding, that is, funding specifically allocated to support medications, and incentives may have a significant influence on programs’ decisions to offer medications. However, these studies report on data collected nearly a decade ago—a particularly problematic lag in light of significant changes in structure and financing of the specialty treatment system spurred by the Affordable Care Act (30,31). Moreover, these studies do not include oral and injectable naltrexone, important medications for treatment of opioid use disorder (30,31). To address this gap in the literature, this study examined the influence of state-targeted funding and technical assistance on the adoption of three medications used to treat opioid use disorder: oral naltrexone, injectable naltrexone, and buprenorphine. The study focused on non-OTPs, which represent 90% of the substance use disorder treatment system and historically have low rates of medication adoption.
Methods
This study draws data from the sixth wave of the National Drug Abuse Treatment System Survey, a nationally representative, longitudinal study of treatment programs in the United States. The National Drug Abuse Treatment System Survey uses a split-panel design with replacement sampling to replace programs that exit the sample over time and refresh the sample to ensure a nationally representative sample at each wave of data collection. Survey weights account for possible nonresponse bias and ensure that the sample was representative of the study population. Data from program directors and clinical services supervisors of treatment programs were collected from November 2013 to June 2014. Interviews were 90 minutes long and were conducted via Internet-based survey. Interviews were completed with 695 treatment programs (response rate=85.5%); see D’Aunno and colleagues (46) for a complete description of the study methods. Of these programs, this study reports data from 456 non-OTP programs. To measure state-targeted funding and incentives for treatment medications, we conducted a 15-minute, Internet-based survey with representatives from SSAs, which included a population of all states and the District of Columbia (response rate=98%). These data were collected from October 2013 to July 2014. The institutional review boards at Miriam Hospital (Providence, RI), the University of Chicago, the University of South Carolina, and the University of Georgia approved this study.
Measures
Dependent variables.
The study included three dependent variables measuring whether treatment programs provided each of the following medications for the treatment of opioid use disorder: oral naltrexone, injectable naltrexone, and buprenorphine.
Independent variables.
Our primary independent variables of interest were designed to gauge the extent to which SSAs provided targeted funding and technical assistance to encourage the availability of medications. We assessed whether states specifically allocated block grant funding for each of the three medications and whether any state funds, other than those available through Medicaid, were used to subsidize the availability of buprenorphine. The study also measured the extent of technical assistance provided by states to treatment programs to address potential barriers to adoption of medications by using seven items: creating information technology and electronic health records infrastructure, obtaining Medicaid certification, becoming in-network providers within private insurance plans, collaborating with federally qualified health centers, collaborating with other medical providers, collaborating with mental health providers, and providing education and training to increase the number of counselors for substance abuse and dependence. [A brief description of items measuring technical assistance provided by SSAs to substance use disorder treatment providers is available as an online supplement to this article.] The response to each item was coded 1 if the state responded affirmatively and 0 otherwise. Items were then summed to create a scale ranging from 0 to 7, with higher scores indicating receipt of more comprehensive technical assistance. In addition, we conducted a factor analysis and retained the first factor. The results did not change; thus, we used the summed score for ease of interpretation.
Control variables.
We included measures of treatment programs that have been significantly related to medication adoption in prior research (29–37,47–58). These included program ownership (private for-profit, private nonprofit, and public), program type (outpatient, inpatient-residential), accreditation by the Joint Commission or Commission on Accreditation of Rehabilitation Facilities, the number of clients served by each program in the past year (log transformed to adjust for skewness), the percentage of staff with a master’s degree, and the percentage of program revenues in the past year from private insurance. We also measured each program’s percentage of black, Hispanic, and female clients in the past year.
To control for patient demand for treatment services and perceptions of market competition that might also influence adoption of medications, we measured the percentage of treatment program clients experiencing heroin and prescription opioid disorder in the past year. These measures also indicate the extent to which treatment programs specialize in these patient populations. To capture perceptions of competition, we included a survey measure that assessed whether the program director perceived an increase in competition in the local labor market in the past year.
Analytic Technique
Descriptive statistics were calculated for all study variables. Using logistic regression, we examined the relationship of state-targeted funding and technical assistance to adoption of opioid use disorder medications among treatment programs. Models accounted for the nesting of treatment programs in states. To account for sampling strata, models included sample weights using the svy command suite in Stata (59). Imputation was conducted with the mi impute command suite in Stata (59), to account for missing data on treatment program–level independent variables. The total number of treatment programs included in multivariate analyses varied on the basis of the amount of missing data on each dependent variable. All analyses were conducted in Stata, version 14.1 (59).
Results
Descriptive Statistics
Among the 50 SSAs, six allocated block grant funding to treatment programs for provision of oral naltrexone, seven allocated block grant funding for injectable naltrexone, and eight allocated block grant funding for buprenorphine in 2014 (Table 1). Fifteen SSAs reported subsidizing the use of buprenorphine with state funds other than Medicaid. Most SSAs reported providing at least some technical assistance to assist treatment programs with adoption of opioid use disorder treatment medications; on average, SSAs offered about five assistance services to treatment providers. Among treatment programs, approximately 11% offered oral naltrexone and injectable naltrexone, and 26% offered buprenorphine in 2014.
| Characteristic | N | % |
|---|---|---|
| State policy (N=50) | ||
| Single-state agency (SSA) block grant funding for oral naltrexone | 6 | 13 |
| SSA block grant funding for injectable naltrexone | 7 | 15 |
| SSA block grant funding for buprenorphine | 8 | 17 |
| SSA subsidizes buprenorphine with state funds | 15 | 31 |
| SSA level of technical assistance (M±SD) | 4.62±1.68 | |
| Treatment programs (N=456) | ||
| Dependent variable | ||
| Oral naltrexone | 45 | 11 |
| Injectable naltrexone | 45 | 11 |
| Buprenorphine | 112 | 26 |
| Control variable | ||
| Organizational characteristic | ||
| Program ownership | ||
| Private for-profit | 99 | 23 |
| Private nonprofit | 280 | 66 |
| Public | 45 | 11 |
| Program type | ||
| Outpatient | 323 | 71 |
| Inpatient-residential | 133 | 29 |
| Accredited by Joint Commission or Commission on Accreditation of Rehabilitation Facilities | 193 | 49 |
| Program size (number of clients served, log) (M±SD) | 5.29±1.18 | |
| Staff professionalism (M±SD) | 40.01±30.16 | |
| % private insurance revenues (M±SD) | 14.39±22.93 | |
| Client sociodemographic characteristic | ||
| % black (M±SD) | 19.02±23.74 | |
| % Hispanic (M±SD) | 13.57±19.43 | |
| % women (M±SD) | 37.23±26.91 | |
| Market factors | ||
| Perceived increase in competition | 140 | 32 |
| % heroin clients (M±SD) | 23.61±27.06 | |
| % prescription opioid clients (M±SD) | 26.74±23.65 |
a
Descriptive statistics are presented for all programs in the study. The number of programs and states included in multivariate analyses varies by medication on the basis of the amount of missing data.
Logistic Regression Models
The adjusted odds of adopting oral naltrexone were greater in treatment programs located in states that provided block grant funding specifically for opioid use disorder medications (adjusted odds ratio [AOR]=3.14; Table 2). The adjusted odds of adopting buprenorphine (AOR=2.47) were positively associated with provision of state funding for buprenorphine as well as the extent of state-based technical assistance provided to treatment programs (AOR=1.18). Although the odds ratios of receiving technical assistance in the naltrexone models were similar to the odds in the buprenorphine model, they were not statistically significant.
| Oral naltrexone (N=383) | Injectable naltrexone (N=383) | Buprenorphine (N=397) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Variable | AOR | 95% CI | p | AOR | 95% CI | p | AOR | 95% CI | p |
| State policy | |||||||||
| Single-state agency (SSA) block grant funding for medication | 3.14 | 1.49–6.60 | .004 | 1.44 | .66–3.16 | .350 | .54 | .27–1.11 | .093 |
| SSA subsidizes buprenorphine with state funds | 2.47 | 1.31–4.67 | .006 | ||||||
| SSA level of technical support | 1.13 | .88–1.46 | .332 | 1.25 | .94–1.65 | .115 | 1.18 | 1.00–1.39 | .049 |
| Control variable | |||||||||
| Organizational characteristic | |||||||||
| Program ownership | |||||||||
| Private nonprofit (reference: private for-profit) | 3.59 | 1.40–9.20 | .009 | 1.17 | .34–4.06 | .789 | 2.56 | 1.09–6.02 | .032 |
| Public ownership (reference: private for-profit) | 3.07 | .74–12.69 | .117 | .60 | .10–.71 | .573 | 2.87 | .88–9.36 | .078 |
| Program type inpatient-residential (reference: outpatient) | 3.14 | 1.07–9.22 | .038 | 2.22 | 1.01–4.91 | .049 | 1.51 | .87–2.63 | .138 |
| Accredited by Joint Commission or Commission on Accreditation of Rehabilitation Facilities | 1.41 | .60–3.32 | .424 | 1.58 | .51–4.93 | .420 | 1.16 | .49–2.76 | .732 |
| Program size (number of clients served, log) | 1.24 | .91–1.69 | .176 | 1.06 | .74–1.50 | .759 | 1.53 | 1.21–1.94 | .001 |
| Staff professionalism | .53 | .11–2.65 | .428 | 3.74 | .65–21.52 | .135 | 1.18 | .27–5.09 | .817 |
| % private insurance revenues | 1.02 | .99–1.04 | .167 | 1.01 | .99–1.04 | .274 | 1.01 | .99–1.03 | .171 |
| Client sociodemographic characteristic | |||||||||
| % black | .98 | .96–1.01 | .135 | .99 | .97–1.01 | .343 | .99 | .98–.00 | .183 |
| % Hispanic | .99 | .96–1.01 | .394 | 1.00 | .97–1.03 | .854 | 1.00 | .97–1.03 | .893 |
| % women | 1.01 | .99–1.02 | .259 | 1.00 | .98–1.03 | .692 | 1.00 | .99–1.01 | .903 |
| Market factors | |||||||||
| Perceived increase in competition | 2.33 | 1.34–4.03 | .004 | .54 | .28–1.04 | .064 | 1.08 | .51–2.31 | .829 |
| % heroin clients | 1.00 | .98–1.02 | .661 | 1.02 | 1.01–1.04 | .013 | 1.01 | .99–1.02 | .057 |
| % prescription opioid clients | 1.00 | .98–1.03 | .689 | 1.00 | .97–1.02 | .784 | 1.01 | 1.00–1.02 | .146 |
a
The number of programs and states included in multivariate analyses varies by medication on the basis of the amount of missing data.
Organizational factors were also positively associated with adoption of opioid use disorder medications. The adjusted odds of adopting oral naltrexone and buprenorphine were greater in private nonprofit programs (AOR=3.59) compared with private for-profit programs (AOR=2.56). The adjusted odds of adopting buprenorphine were greater in larger programs (AOR=1.53). The adjusted odds of adopting oral naltrexone (AOR=3.14) and injectable naltrexone (AOR=2.22) were higher in inpatient and residential programs than in outpatient programs.
Market factors were also associated with the adoption of oral and injectable naltrexone. The adjusted odds of adopting injectable naltrexone were greater in programs that reported an increase in competition in the past year (AOR=2.33), and the adjusted odds of adopting injectable naltrexone were greater in programs with a higher percentage of patients with heroin use disorder (AOR=1.02).
Discussion
This national survey found that state-targeted funding was linked to adoption of two medications for opioid use disorder: oral naltrexone and buprenorphine. However, adoption of medications among substance use disorder treatment programs remains low, with less than 27% of treatment programs offering buprenorphine and less than 12% of programs offering either oral or injectable naltrexone.
Given the increase in demand for opioid use disorder treatment and the rise in opioid overdose deaths over the past 15 years, it is critically important to increase access to these medications (11). Our findings suggest that state-targeted funding for medications may be one viable policy lever to increase their availability in treatment programs. Through the 21st Century Cures Act, states are receiving additional funding administered through SAMHSA to directly address the opioid crisis. One goal of this funding is to expand access to opioid use disorder medications. Thus, it will be particularly important to monitor how states are using these funds and whether these additional funds result in increased access to opioid use disorder medications.
Although states act relatively autonomously to make decisions about the allocation of Substance Abuse Prevention and Treatment block grant dollars to prevention, treatment, outreach, and administrative costs, SAMHSA might consider offering additional incentives to states to increase availability of opioid use disorder medications. The federal government could also encourage the Centers for Medicare and Medicaid Services to offer incentives to providers to encourage comprehensive coverage of opioid use disorder medications. This approach may be particularly important for states hardest hit by the opioid crisis. At present, only three states with the highest rates of opioid overdose deaths or opioid use disorder rates allocate any block grant funding for opioid use disorder medications (60).
In addition to allocating a portion of treatment dollars from the federal block grant to medications, our findings suggest that subsidizing the use of medications using other streams of state funding may also be a viable strategy. Both this study and prior research demonstrate the utility of this strategy to facilitate adoption of buprenorphine (30). However, the states using this strategy are not always the states with the greatest need. Among the 15 states subsidizing buprenorphine with state funding (other than Medicaid and the block grant), only seven states are among those with the highest rates of opioid overdose deaths, and only four states are among those with the highest rates of opioid use disorder (60,61).
We also found that programs located in states with SSAs that provide a greater level of technical assistance were more likely to adopt buprenorphine. This finding suggests that the availability of technical assistance indicates a more supportive state policy environment that places an emphasis on the use of evidence-based practices, collaboration with primary care and mental health providers, adoption of electronic health records, and obtaining Medicaid certification, all of which might contribute to increased accessibility and quality of treatment. Indeed, treatment providers who begin collaborating with primary care and mental health providers may gain access to prescribing staff for the first time. Taken together, these findings suggest that when states help programs overcome financial and technological barriers to offering these medications, treatment programs respond as hoped—by adopting medications.
Although SSA policy influenced adoption of oral naltrexone and buprenorphine, it did not affect adoption of injectable naltrexone. This outcome may be related to the cost of injectable naltrexone, which can be as much as $1,000 per injection. Even when the medication is covered by insurance, it still may not be an affordable option for patients. The administration of the injection also requires a higher degree of technical expertise than the other, orally administered medications (62). Staff may need additional training, or new staff may need to be hired. Our findings suggest that the adoption and implementation of injectable naltrexone may require a greater commitment of resources on the part of SSAs and treatment programs.
In contrast to some prior research, we found that private nonprofit treatment programs were more likely to offer oral naltrexone and buprenorphine compared with private for-profit programs. There may be several explanations for this finding. First, data from the National Survey of Substance Abuse Treatment Services and prior studies that used data from this survey indicate that private for-profit programs were more likely to be early adopters of buprenorphine compared with private nonprofit programs (31,33). However, by 2015, the percentage of private nonprofit, private for-profit, and publicly owned programs offering buprenorphine was very similar (63). Second, studies that found that private for-profit programs were more likely to adopt oral naltrexone compared with private nonprofit programs (34) restricted their sample to privately funded programs. Our study did not use eligibility criteria based on sources of funding; thus, direct comparisons with these studies cannot be drawn. Third, other studies that included both samples of privately and publicly funded programs (36) used separate variables to measure funding and profit status. Therefore, our results are not directly comparable with these prior studies. Fourth, most of these studies did not control for state policy or market characteristics, which may account for these differences.
This study had several limitations. First, the data are cross-sectional; hence, we are unable to draw any causal inferences. Second, the study did not examine the relationship between Medicaid coverage and adoption of medications because of a lack of variation in coverage. In 2014, all state Medicaid plans covered buprenorphine, and 48 states covered injectable naltrexone. Third, the survey did not ask whether states used non-Medicaid state funds to support oral or injectable naltrexone. Fourth, our study relied on self-report data, which are subject to response bias. Fifth, there may be other factors not included in these analyses that account for variation in availability of medications.
Conclusions
Given historically low rates of medication adoption in treatment programs and the rise in opioid overdose deaths and treatment admissions for opioid use disorder, increasing access to these potentially life-saving medications is imperative. SSA-targeted funding and technical assistance may be viable policy levers to increase access to effective medications in the great majority of treatment programs that do not offer medications. SSAs in many states with the highest rates of opioid use disorder and opioid-related overdose deaths are not currently using these funding and assistance strategies; thus, additional federal incentives may be necessary.
Footnote
These views represent the opinions of the authors and not necessarily those of the National Institutes of Health.
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References
1.
Behavioral Health Trends in the United States: Results From the 2014 National Survey on Drug Use and Health. Rockville, MD, Substance Abuse and Mental Health Services Administration, 2015
2.
Florence CS, Zhou C, Luo F, et al: The economic burden of prescription opioid overdose, abuse, and dependence in the United States, 2013. Medical Care 54:901–906, 2016
3.
Howard AA, Hoover DR, Anastos K, et al: The effects of opiate use and hepatitis C virus infection on risk of diabetes mellitus in the Women’s Interagency HIV Study. Journal of Acquired Immune Deficiency Syndromes 54:152–159, 2010
4.
Costenbader EC, Zule WA, Coomes CM: The impact of illicit drug use and harmful drinking on quality of life among injection drug users at high risk for hepatitis C infection. Drug and Alcohol Dependence 89:251–258, 2007
5.
Rowe TA, Jacapraro JS, Rastegar DA: Entry into primary care–based buprenorphine treatment is associated with identification and treatment of other chronic medical problems. Addiction Science and Clinical Practice 7:22, 2012
6.
Batki SL, Canfield KM, Ploutz-Snyder R: Psychiatric and substance use disorders among methadone maintenance patients with chronic hepatitis C infection: effects on eligibility for hepatitis C treatment. American Journal on Addictions 20:312–318, 2011
7.
Grella CE, Karno MP, Warda US, et al: Gender and comorbidity among individuals with opioid use disorders in the NESARC study. Addictive Behaviors 34:498–504, 2009
8.
Haddad MS, Zelenev A, Altice FL: Integrating buprenorphine maintenance therapy into federally qualified health centers: real-world substance abuse treatment outcomes. Drug and Alcohol Dependence 131:127–135, 2013
9.
Modesto-Lowe V, Brooks D, Petry N: Methadone deaths: risk factors in pain and addicted populations. Journal of General Internal Medicine 25:305–309, 2010
10.
Baldini A, Von Korff M, Lin EH: A review of potential adverse effects of long-term opioid therapy: a practitioner’s guide. Primary Care Companion for CNS Disorders 14:PCC.11m01326, 2012
11.
Rudd RA, Aleshire N, Zibbell JE, et al: Increases in drug and opioid overdose deaths—United States, 2000–2014. Morbidity and Mortality Weekly Report 64:1378–1382, 2016
12.
Volkow ND, Frieden TR, Hyde PS, et al: Medication-assisted therapies—tackling the opioid-overdose epidemic. New England Journal of Medicine 370:2063–2066, 2014
13.
Rudd RA, Seth P, David F, et al: Increases in drug and opioid-involved overdose deaths—United States, 2010–2015. Morbidity and Mortality Weekly Report 65:1445–1452, 2016
14.
ASPE Issue Brief: Opioid Abuse in the US and HHS Actions to Address Opioid-Drug Related Overdoses and Deaths. Washington, DC, US Department of Health and Human Services, 2015
15.
Strang J, Babor T, Caulkins J, et al: Drug policy and the public good: evidence for effective interventions. Lancet 379:71–83, 2012
16.
Mattick RP, Breen C, Kimber J, et al: Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database of Systematic Reviews 2:CD002207, 2014
17.
Amass L, Ling W, Freese TE, et al: Bringing buprenorphine-naloxone detoxification to community treatment providers: the NIDA Clinical Trials Network field experience. American Journal on Addictions 13(Suppl 1):S42–S66, 2004
18.
Amato L, Minozzi S, Davoli M, et al: Psychosocial combined with agonist maintenance treatments versus agonist maintenance treatments alone for treatment of opioid dependence. Cochrane Database of Systematic Reviews 10:CD004147, 2011
19.
Amato L, Minozzi S, Davoli M, et al: Psychosocial and pharmacological treatments versus pharmacological treatments for opioid detoxification. Cochrane Database of Systematic Reviews 9:CD005031, 2011
20.
Krupitsky E, Nunes EV, Ling W, et al: Injectable extended-release naltrexone for opioid dependence. Lancet 378:665, author reply 666, 2011
21.
Johansson BA, Berglund M, Lindgren A: Efficacy of maintenance treatment with naltrexone for opioid dependence: a meta-analytical review. Addiction 101:491–503, 2006
22.
Comer SD, Sullivan MA, Yu E, et al: Injectable, sustained-release naltrexone for the treatment of opioid dependence: a randomized, placebo-controlled trial. Archives of General Psychiatry 63:210–218, 2006
23.
Krupitsky E, Nunes EV, Ling W, et al: Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled, multicentre randomised trial. Lancet 377:1506–1513, 2011
24.
Fiellin DA, Pantalon MV, Chawarski MC, et al: Counseling plus buprenorphine-naloxone maintenance therapy for opioid dependence. New England Journal of Medicine 355:365–374, 2006
25.
Ziedonis DM, Amass L, Steinberg M, et al: Predictors of outcome for short-term medically supervised opioid withdrawal during a randomized, multicenter trial of buprenorphine-naloxone and clonidine in the NIDA Clinical Trials Network drug and alcohol dependence. Drug and Alcohol Dependence 99:28–36, 2009
26.
Hartung DM, McCarty D, Fu R, et al: Extended-release naltrexone for alcohol and opioid dependence: a meta-analysis of healthcare utilization studies. Journal of Substance Abuse Treatment 47:113–121, 2014
27.
Baser O, Chalk M, Fiellin DA, et al: Cost and utilization outcomes of opioid-dependence treatments. American Journal of Managed Care 17(Suppl 8):S235–S248, 2011
28.
Lynch FL, McCarty D, Mertens J, et al: Costs of care for persons with opioid dependence in commercial integrated health systems. Addiction Science and Clinical Practice 9:16, 2014
29.
Abraham AJ, Knudsen HK, Rieckmann T, et al: Disparities in access to physicians and medications for the treatment of substance use disorders between publicly and privately funded treatment programs in the United States. Journal of Studies on Alcohol and Drugs 74:258–265, 2013
30.
Andrews CM, D’Aunno TA, Pollack HA, et al: Adoption of evidence-based clinical innovations: the case of buprenorphine use by opioid treatment programs. Medical Care Research and Review 71:43–60, 2014
31.
Ducharme LJ, Abraham AJ: State policy influence on the early diffusion of buprenorphine in community treatment programs. Substance Abuse Treatment, Prevention, and Policy 3:17, 2008
32.
Knudsen HK, Ducharme LJ, Roman PM: Early adoption of buprenorphine in substance abuse treatment centers: data from the private and public sectors. Journal of Substance Abuse Treatment 30:363–373, 2006
33.
Heinrich CJ, Cummings GR: Adoption and diffusion of evidence-based addiction medications in substance abuse treatment. Health Services Research 49:127–152, 2014
34.
Oser CB, Roman PM: Organizational-level predictors of adoption across time: naltrexone in private substance-use disorders treatment centers. Journal of Studies on Alcohol and Drugs 68:852–861, 2007
35.
Knudsen HK, Abraham AJ, Johnson JA, et al: Buprenorphine adoption in the National Drug Abuse Treatment Clinical Trials Network. Journal of Substance Abuse Treatment 37:307–312, 2009
36.
Knudsen HK, Ducharme LJ, Roman PM: The adoption of medications in substance abuse treatment: associations with organizational characteristics and technology clusters. Drug and Alcohol Dependence 87:164–174, 2007
37.
Ducharme LJ, Roman PM: Opioid treatment programs in the Clinical Trials Network: representativeness and buprenorphine adoption. Journal of Substance Abuse Treatment 37:90–94, 2009
38.
Ducharme LJ, Knudsen HK, Roman PM, et al: Innovation adoption in substance abuse treatment: exposure, trialability, and the Clinical Trials Network. Journal of Substance Abuse Treatment 32:321–329, 2007
39.
Buck JA: The looming expansion and transformation of public substance abuse treatment under the Affordable Care Act. Health Affairs 30:1402–1410, 2011
40.
Mark TL, Levit KR, Vandivort-Warren R, et al: Trends in spending for substance abuse treatment, 1986–2003. Health Affairs 26:1118–1128, 2007
41.
McCarty D, Gustafson D, Capoccia VA, et al: Improving care for the treatment of alcohol and drug disorders. Journal of Behavioral Health Services and Research 36:52–60, 2009
42.
Stewart MT, Horgan CH: Health services and financing of treatment. Alcohol Research and Health 33:389–394, 2011
43.
Rieckmann TR, Kovas AE, Cassidy EF, et al: Employing policy and purchasing levers to increase the use of evidence-based practices in community-based substance abuse treatment settings: reports from single state authorities. Evaluation and Program Planning 34:366–374, 2011
44.
Rieckmann TR, Kovas AE, Fussell HE, et al: Implementation of evidence-based practices for treatment of alcohol and drug disorders: the role of the state authority. Journal of Behavioral Health Services and Research 36:407–419, 2009
45.
Rieckmann T, Abraham A, Zwick J, et al: A longitudinal study of state strategies and policies to accelerate evidence-based practices in the context of systems transformation. Health Services Research 50:1125–1145, 2015
46.
D’Aunno T, Friedmann PD, Chen Q, et al: Integration of substance abuse treatment organizations into accountable care organizations: results from a national survey. Journal of Health Politics, Policy and Law 40:797–819, 2015
47.
Abraham AJ, Roman PM: Early adoption of injectable naltrexone for alcohol-use disorders: findings in the private-treatment sector. Journal of Studies on Alcohol and Drugs 71:460–466, 2010
48.
Abraham AJ, Knudsen HK, Roman PM: A longitudinal examination of alcohol pharmacotherapy adoption in substance use disorder treatment programs: patterns of sustainability and discontinuation. Journal of Studies on Alcohol and Drugs 72:669–677, 2011
49.
Knudsen HK, Roman PM, Oser CB: Facilitating factors and barriers to the use of medications in publicly funded addiction treatment organizations. Journal of Addiction Medicine 4:99–107, 2010
50.
Andrews C, D’Aunno TA, Pollack HA, et al: Adoption of evidence-based clinical innovations: the case of buprenorphine use by opioid treatment programs. Medical Care Research and Review 71:43–60, 2014
51.
Roman PM, Johnson JA: Adoption and implementation of new technologies in substance abuse treatment. Journal of Substance Abuse Treatment 22:211–218, 2002
52.
Oser CB, Roman PM: A categorical typology of naltrexone-adopting private substance abuse treatment centers. Journal of Substance Abuse Treatment 34:433–442, 2008
53.
Wallack SS, Thomas CP, Martin TC, et al: Substance abuse treatment organizations as mediators of social policy: slowing the adoption of a congressionally approved medication. Journal of Behavioral Health Services and Research 37:64–78, 2010
54.
Koch AL, Arfken CL, Schuster CR: Characteristics of US substance abuse treatment facilities adopting buprenorphine in its initial stage of availability. Drug and Alcohol Dependence 83:274–278, 2006
55.
Abraham AJ, Rieckmann T, McNulty T, et al: Counselor attitudes toward the use of naltrexone in substance abuse treatment: a multi-level modeling approach. Addictive Behaviors 36:576–583, 2011
56.
Garner BR: Research on the diffusion of evidence-based treatments within substance abuse treatment: a systematic review. Journal of Substance Abuse Treatment 36:376–399, 2009
57.
Ducharme LJ, Knudsen HK, Roman PM: Trends in the adoption of medications for alcohol dependence. Journal of Clinical Psychopharmacology 26(Suppl 1):S13–S19, 2006
58.
Heinrich CJ, Hill CJ: Role of state policies in the adoption of naltrexone for substance abuse treatment. Health Services Research 43:951–970, 2008
59.
Stata: Release 14: Statistical Software. College Station, TX, Stata Corp, 2014
60.
Opioid Overdoes Death Rates and All Drug Overdose Death Rates per 100,000 Population (Age-Adjusted), 2014. Menlo Park, CA, Kaiser Family Foundation, 2016
61.
Jones CM, Campopiano M, Baldwin G, et al: National and state treatment need and capacity for opioid agonist medication-assisted treatment. American Journal of Public Health 105:e55–e63, 2015
62.
Vivitrol [package insert]. Waltham, MA, Alkermes, Inc; Revised July 2013
63.
National Survey of Substance Abuse Treatment Services (N-SSATS). Bethesda, MD, Substance Abuse and Mental Health Services Administration, 2015
Information & Authors
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Published In
Cover: Decorative Landscape, Hot Morning Sunlight, by Charles Burchfield, 1916. Transparent watercolor on white wove paper with color notations in graphite. Edward W. Root bequest, Munson-Williams-Proctor Arts Institute, Utica, NY. Photo credit: Munson-Williams-Proctor Arts Institute/Art Resource, New York City.
History
Received: 26 April 2017
Revision received: 11 August 2017
Revision received: 12 September 2017
Accepted: 22 September 2017
Published online: 15 December 2017
Published in print: April 01, 2018
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Authors
Competing Interests
Dr. Friedmann received in-kind medication for research from Alkermes, received training and reimbursement for local travel from Braeburn, and was paid for legal consultation to Endo Pharmaceuticals. The other authors report no financial relationships with commercial interests.
Funding Information
National Institute on Drug Abuse10.13039/100000026: R01DA034634
The research reported in this study was supported by National Institute on Drug Abuse Grant R01-DA-034634.Metrics & Citations
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