Skip to main content

Main menu

  • Home
  • Articles
    • Current
    • Published Ahead of Print
    • Archive
    • Supplemental Issues
    • Collections - French
    • Collections - English
  • Info for
    • Authors & Reviewers
    • Submit a Manuscript
    • Advertisers
    • Careers & Locums
    • Subscribers
    • Permissions
  • About CFP
    • About CFP
    • About the CFPC
    • Editorial Advisory Board
    • Terms of Use
    • Contact Us
  • Feedback
    • Feedback
    • Rapid Responses
    • Most Read
    • Most Cited
    • Email Alerts
  • Blogs
    • Latest Blogs
    • Blog Guidelines
    • Directives pour les blogues
  • Mainpro+ Credits
    • About Mainpro+
    • Member Login
    • Instructions
  • Other Publications
    • http://www.cfpc.ca/Canadianfamilyphysician/
    • https://www.cfpc.ca/Login/
    • Careers and Locums

User menu

  • My alerts

Search

  • Advanced search
The College of Family Physicians of Canada
  • Other Publications
    • http://www.cfpc.ca/Canadianfamilyphysician/
    • https://www.cfpc.ca/Login/
    • Careers and Locums
  • My alerts
The College of Family Physicians of Canada

Advanced Search

  • Home
  • Articles
    • Current
    • Published Ahead of Print
    • Archive
    • Supplemental Issues
    • Collections - French
    • Collections - English
  • Info for
    • Authors & Reviewers
    • Submit a Manuscript
    • Advertisers
    • Careers & Locums
    • Subscribers
    • Permissions
  • About CFP
    • About CFP
    • About the CFPC
    • Editorial Advisory Board
    • Terms of Use
    • Contact Us
  • Feedback
    • Feedback
    • Rapid Responses
    • Most Read
    • Most Cited
    • Email Alerts
  • Blogs
    • Latest Blogs
    • Blog Guidelines
    • Directives pour les blogues
  • Mainpro+ Credits
    • About Mainpro+
    • Member Login
    • Instructions
  • RSS feeds
  • Follow cfp Template on Twitter
Research ArticleResearch

Opioid agonist therapy during residential treatment of opioid use disorder

Cohort study on access and outcomes

Sheryl Spithoff, Christopher Meaney, Karen Urbanoski, Katy Harrington, Bill Que, Meldon Kahan, Pamela Leece, Vivian Shehadeh and Frank Sullivan
Canadian Family Physician October 2019, 65 (10) e443-e452;
Sheryl Spithoff
Lecturer in the Department of Family and Community Medicine at the University of Toronto in Ontario, and a family physician and addiction physician in the Department of Family and Community Medicine at Women’s College Hospital.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: sheryl.spithoff@wchospital.ca
Christopher Meaney
At the time of manuscript submission, was a biostatistician in the Department of Family and Community Medicine at the University of Toronto.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karen Urbanoski
Canada Research Chair in Substance Use, Addictions and Health Services Research, a scientist at the Canadian Institute for Substance Use Research, and Assistant Professor in Public Health and Social Policy at the University of Victoria in British Columbia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katy Harrington
At the time of writing, was a Family medicine resident with the South East Toronto Family Health Team and in the Department of Family and Community Medicine at the University of Toronto.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bill Que
IT Specialist, DATIS, Evaluation and Data Management, Provincial System Support Program at the Centre for Addiction and Mental Health in Toronto.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Meldon Kahan
Associate Professor in the Department of Family and Community Medicine at the University of Toronto and Director of the Substance Use Service at Women’s College Hospital.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pamela Leece
Public health physician at Public Health Ontario in Toronto, and Assistant Professor in the Department of Family and Community Medicine and in the Dalla Lana School of Public Health at the University of Toronto.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vivian Shehadeh
Project Leader at the Centre for Addiction and Mental Health at the time of submission.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Frank Sullivan
Professor in the Department of Family and Community Medicine at the University of Toronto and Gordon F. Cheesbrough Research Chair in Family and Community Medicine at North York General Hospital.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF
Loading

Abstract

Objective To determine access to opioid agonist therapy (OAT) for those entering residential treatment for opioid use disorder; to report on treatment outcomes for those taking OAT and those not taking OAT; and to determine the association between OAT use and residential treatment completion.

Design Retrospective cohort study.

Setting Ontario.

Participants Patients with opioid use disorder admitted to publicly funded residential treatment programs in the province of Ontario between January 1, 2013, and December 31, 2016.

Main outcome measures Access to OAT during residential treatment using descriptive statistics. Treatment outcomes (ie, completed the program, voluntarily left early, involuntary discharged, and other) for the entire cohort and for the OAT and non-OAT groups using descriptive statistics. Association between OAT use at admission and treatment completion (a binary outcome) using bivariate and multivariate models.

Results Among an identified cohort of 1910 patients with opioid use disorder, 52.8% entered programs that permitted access to OAT. Overall, 56.8% of patients completed treatment, 23.3% voluntarily left early (eg, were no-shows, dropped out), 17.0% were involuntarily discharged, and 2.9% were discharged early for other reasons. Those taking OAT were as likely to complete treatment as those not taking OAT (53.9% vs 57.5%, respectively; adjusted odds ratio of 1.07, 95% CI 0.77 to 1.38).

Conclusion This study demonstrates 2 large gaps in care for patients with opioid use disorder. First, these patients have poor access to OAT—the first-line treatment of opioid use disorder—while in publicly funded residential treatment programs; and second, many are involuntarily discharged from treatment. Additionally, this study indicates that patients taking OAT have similar likelihood of completing residential treatment as those not taking OAT do. Limitations of this study are that it is based on observational data for patients who self-selected before admission to use OAT or not, and it is likely not all confounders were accounted for.

Access to effective treatment of opioid use disorder has never been more important. In Canada, there was a 45% increase in the number of opioid-related deaths from January to September 2017 compared with the same time period in 2016.1 In the province of Ontario, opioids are responsible for 1 in 8 deaths for those aged between 25 and 34.2 In 2015, more than 2.5 million Americans had opioid use disorder,3 and in 2016 more than 42 000 people died from an opioid overdose.4

Opioid agonist therapy (OAT), with methadone or buprenorphine, is the first-line treatment of opioid use disorder. It has higher rates of retention in outpatient treatment than treatments that do not incorporate OAT.5–8 Opioid agonist therapy is also associated with improved psychosocial functioning and health status; fewer risky and criminal behaviours; and reduced all-cause mortality.9–13 The effect of psychosocial treatment alone on addiction, health, and social outcomes is much less clear.14 Outcomes appear to improve with longer duration (at least 8 to 12 weeks) in treatment.15–20

To improve access to OAT, Canada’s National Guideline for the Clinical Management of Opioid Use Disorder,14 a 2017 coroner’s inquest in the province of British Columbia,21 a report by the Ontario Ministry of Health and Long-Term Care’s Methadone Treatment and Services Advisory Committee,22 and the US President’s Commission on Combating Drug Addiction and the Opioid Crisis23 all recently recommended removing barriers to OAT within the addiction treatment system.

This might require changes in residential addiction treatment programs. Historically many programs have not permitted the use of OAT,24–26 and recent surveys indicate that might still be the case.27,28 In 2018, Health Quality Ontario reported that approximately 1 in 4 residential facilities in Ontario do not allow patients to take OAT during admission.29 Health service data on access to OAT during residential treatment have not been reported in the United States or Canada.

Additionally, the effect of OAT on residential treatment outcomes has not been adequately studied.24 Based on the evidence from outpatient studies, initiating OAT before discharge from a residential facility would improve outcomes after discharge, including retention in ongoing outpatient treatment, health, and social functioning, and would reduce mortality.5–7,10 However, it is unknown if initiating or continuing OAT from the start of the residential stay affects retention in residential treatment. Therefore, we sought to 1) determine access to OAT for the population entering residential treatment for opioid use disorder, 2) report on treatment outcomes for those taking OAT and those not taking OAT, and 3) determine the association between OAT use and residential treatment completion.

METHODS

We conducted a retrospective population-based cohort study of patients who entered publicly funded residential treatment programs for opioid use disorder in Ontario between January 1, 2013, and December 31, 2016. The study was approved by the Research Ethics Board of Women’s College Hospital in Toronto, Ont.

Setting

Ontario is an ethnically diverse province in Canada with a population of 14 million in 2016.30 The provincial government provides all residents with publicly funded coverage for all necessary laboratory and radiologic testing, clinic and hospital visits, and psychosocial addiction treatment. Ontarians can also access private addiction treatment programs, either by paying out of pocket or by being funded by a third-party payer such as an employer.

Data sources

We used data from the Drug and Alcohol Treatment Information System (DATIS), which captures all publicly funded admissions to inpatient and residential treatment programs in Ontario. Approximately 170 agencies, which administer more than 200 programs, submit data, with less than 5% of data missing.31 Agencies report demographic data and service type, as well as information on patients’ health, social, psychological, and legal status. They also submit data on treatment including treatment completion and reasons for failure to complete treatment. The database has been used in a number of studies.31–35

We used the ConnexOntario Health Services Information database to determine which programs permitted patients to use OAT—methadone or buprenorphine or both—during residential treatment, and which programs dispensed or prescribed OAT on-site. ConnexOntario is an organization funded by the Government of Ontario that maintains a database of detailed health service information including information on which programs permit OAT, dispense OAT on-site, and prescribe OAT on-site. ConnexOntario conducts program validations for each organization on an annual basis to ensure that program details are accurate.

We linked the ConnexOntario data to the DATIS database using a unique program identifier: the Drug and Alcohol Registry of Treatment number, which allows for merging information between the DATIS and ConnexOntario databases. We stored, linked, and analyzed data on a secure, central server located at the Centre for Addiction and Mental Health in Toronto, Ont. We anonymized and aggregated patient data before extraction and reporting.

Identification of the cohort

Using the DATIS database, we identified all patients aged 18 and older, who were admitted to residential treatment programs on or after January 1, 2013, and were discharged by December 31, 2016 (accrual period), who reported opioids as a presenting problem substance, and who had used opioids daily in the past 30 days. We excluded those who reported use of opioids but did not report that opioids were a problem substance. We also excluded those admitted to a detoxification or outpatient program. We selected a single randomly chosen admission for each patient during the accrual period (as some patients had multiple admissions in the accrual time period). We defined the OAT group as patients taking OAT at admission to the program and defined the non-OAT group as patients not taking OAT at admission. The DATIS database does not record OAT use after the time of admission to the program.

We used the ConnexOntario database to determine access to OAT. We defined a program that “permitted OAT” as a program that allowed patients to use methadone or buprenorphine or both during the admission. We defined a program that “prescribed OAT” as a program that prescribed methadone or buprenorphine or both. We defined a program that “dispensed OAT” as a program that dispensed methadone or buprenorphine or both on-site.

We used the DATIS database to assess treatment outcomes. Reasons for program termination included the following: completed the program, internal program transfer, agreed to terminate, client withdrew, client dropped out or was a no-show, incarceration, death, hospitalization, other, unknown, or staff termination. For our second objective, reporting on treatment outcomes for those taking OAT and those not taking OAT, we grouped the reasons for failure to complete treatment into voluntarily left early (client withdrew, dropped out or was a no-show, or agreed to terminate), involuntary discharge (terminated by staff), and other (internal program transfer, incarcerated, deceased, hospitalized, other, or unknown). For our third objective, determining the association between OAT use and treatment completion, we dichotomized the treatment outcomes variable as completed the program or failed to complete treatment (ie, binary outcome).

Statistical analysis

For our first objective we used descriptive statistics to report on the demographic and clinical characteristics of the entire cohort and the OAT group and the non-OAT group. We also described access to OAT during residential treatment in 2 ways: first, as the percentage of programs that permitted OAT, prescribed OAT, or dispensed OAT; and second, as the percentage of patients who were admitted to a program that permits OAT, prescribes OAT, or dispenses OAT.

For our second objective, we reported on treatment outcomes (ie, completed the program, voluntarily left early, involuntarily discharged, and other) for the entire cohort and for the OAT and non-OAT groups using descriptive statistics. To determine if differences in treatment outcomes existed between the OAT and the non-OAT groups, we fit a random intercept multinomial regression model. Probability estimates are obtained from a random intercept multinomial regression model (4-level outcome: complete, voluntary discharge, involuntary discharge, and other). The linear predictor includes only a fixed intercept effect, a fixed binary treatment effect, and a random intercept term for each site. We estimated the conditional probability of treatment completion in each treatment arm and their associated pairwise differences. Delta method–style arguments were used to obtain standard errors for the pairwise probability difference estimates. Traditionally this type of subanalysis could be performed using a simple Embedded Image2 test (and subsequent follow-up pairwise binomial tests on each level of the outcome); however, given the clustered nature of the data from this design, a random intercept multinomial logit model was used to properly estimate standard error for the associated hypothesis tests.

For our third objective, we estimated bivariate and multivariate models to determine if there was an association between OAT use at admission and treatment completion, a binary outcome. We determined the intraclass correlation and fit a random intercept logistic regression model. We used this approach because our outcome (treatment completion) is a patient-level response nested within treatment programs (and hence responses are expected to be positively correlated within treatment centres). We presented the results as adjusted odds ratios and 95% CIs. In the models, we excluded patients who were taking OAT at admission but entered a program where OAT was not permitted (Figure 1). We excluded these patients because, although we assume they were tapered off OAT during the admission, we did not have access to this information.

Statistical analyses were performed using SAS, version 9.4,36 and R, version 3.4.3.37

Figure 1.
  • Download figure
  • Open in new tab
Figure 1.

Flow diagram of exclusion criteria for study cohort

DART—Drug and Alcohol Registry of Treatment, OAT—opioid agonist therapy.

RESULTS

After exclusions (Figure 1), we identified 1910 individuals who were eligible for inclusion in our cohort. These individuals were admitted to 36 different residential treatment programs across Ontario. The average length of programs was 61.8 days with a median program length of 35 days (interquartile range of 21 to 90 days). Eight of the programs admitted women only and 9 admitted men only. Overall, 20 out of 36 (55.6%) programs permitted patients to use OAT. Of the 20 programs that permitted OAT, 2 prescribed OAT on-site and 2 dispensed OAT on-site.

The cohort was young (median age 31.9 years), predominantly men (66.4%), and resided mostly in urban areas (83.7%). Overall 38.5% had recent injection drug use, 22.4% were fully employed, and 20.3% were taking OAT (Table 1). We determined that 52.8% (1008 of 1910) of patients in the cohort entered programs that permitted OAT (Table 2). Most of those in the OAT group entered programs where OAT was permitted. However, 5.2% (20 of 388) entered programs that banned OAT. Tables 1 and 2 present further information on the cohort and the stratifications (OAT group and the non-OAT group).

View this table:
  • View inline
  • View popup
Table 1.

Description of the opioid use disorder cohort and of the stratifications, OAT and non-OAT groups

View this table:
  • View inline
  • View popup
Table 2.

Description of patient-level access to OAT during admission for the opioid use disorder cohort and the stratifications, OAT and non-OAT groups

For our second objective, we determined that overall 56.8% of the cohort completed the program, 17.0% were involuntarily discharged early from the program, 23.3% voluntarily left early from the program, and 2.9% did not complete the program for other reasons. Treatment outcomes for the entire cohort and the stratifications are presented in Table 3. We found no statistically significant differences in treatment completion outcomes between the OAT group and the non-OAT group (53.9% and 57.5%, respectively). For the group taking OAT that entered a program where OAT was banned, 11 out of 20 individuals completed treatment (55.0%). Results for the other treatment outcomes for this group were too small to report. Aggregate outcomes ranged from 5% to 25%.

View this table:
  • View inline
  • View popup
Table 3.

Crude rates of treatment completion and failure to complete treatment (voluntary discharge, involuntary discharge, and other) for the opioid use disorder cohort and for the stratifications, OAT and non-OAT groups

For our third objective, we determined that the intraclass correlation was 0.083. This indicates that 8.3% of the total response variation can be attributed to site-level effects. In the bivariate analysis (Table 4), those in the OAT group were as likely to complete treatment as those in the non-OAT group (odds ratio of 0.96, 95% CI 0.73 to 1.26). As OAT was our primary target of inference, we forced this variable into our final multivariable random intercept logistic regression model. Additionally, we included covariates that were associated with treatment completion on bivariate analysis at a 5% α level (Table 4). On multivariate modeling, we observed that the OAT group was as likely to complete treatment as the non-OAT group was (adjusted odds ratio of 1.07, 95% CI 0.77 to 1.38) (Table 5).

View this table:
  • View inline
  • View popup
Table 4.

Odds of residential treatment completion (binary outcome: complete vs not complete) for patients with opioid use disorder in bivariate random intercept logistic regression analyses

View this table:
  • View inline
  • View popup
Table 5.

Odds of residential treatment completion (binary outcome: complete vs not complete) for patients with opioid use disorder in adjusted multivariate random intercept logistic regression model

DISCUSSION

In this large study of people with opioid use disorder entering residential treatment in Ontario, we found that almost half entered programs where they were not permitted to have access to OAT, the first-line treatment of opioid use disorder,5,14 during their admission. Few entered programs with on-site access to OAT. About 20% were taking OAT at the time of admission (the OAT group). More than 40% of people did not complete treatment and 17.0% were involuntarily discharged from a treatment program. The OAT group was as likely as those not taking OAT to complete treatment.

To our knowledge, this is the first study to clearly quantify patients’ access to OAT in publicly funded residential treatment by linking administrative data on patient admissions to program policies. Other studies have estimated access by surveying programs.28,38 The poor access to OAT is concerning. Many patients leaving residential treatment will relapse soon after discharge.14 Given the data on the benefits of OAT for outpatients,5–7,10 initiation of OAT before discharge is likely to prevent many of these outpatient relapses and lead to health and social benefits.

As reported in other studies,39 many patients in our study were involuntarily discharged from treatment. Despite the important role involuntary discharge plays in failure to complete treatment, it has received little attention in the medical literature.40 In 1 small study reasons for premature discharge ranged from conflict with counselors to tampering with urine drug test samples to missing treatment.41 Some argue that involuntary discharges are essential to avoid program disruption and to ensure individuals actively engage with treatment.42 Others argue that involuntary discharge leads to harm and has no evidence to support its use.39,43 Either way, a high rate of involuntary discharge means that a large number of people—who have not made the decision to withdraw—are denied the opportunity to continue treatment.

Our finding that those taking OAT have the same likelihood of completing residential treatment as those not taking OAT might be due to confounding. Our results are contrary to numerous randomized controlled trials among outpatients where the use of OAT leads to much better retention in treatment.6–8 It is possible that patient factors we could not measure—such as addiction severity—led to confounding. Given that patients self-select to use OAT, this is very likely. It is also possible that program factors caused confounding. For example there is evidence that patients who take OAT face stigma and discrimination in treatment programs.24,25,44,45 This might also lead them to leave treatment prematurely. Finally, it is also possible that the duration of the residential programs was too short to see an effect from OAT use. Most of the residential programs in our study had a very short planned duration of stay (median duration of 35 days). It is possible that with longer duration of stay, OAT would have an effect. In outpatient studies retention is typically measured at 6 months.6–8 In any case, our results should not be interpreted as reason to withhold offering OAT. It is also possible that OAT might not have an effect on retention during residential treatment. Another small cohort study of 125 patients found that those taking OAT had similar outcomes to those not taking OAT.46 The lack of association between OAT use and treatment completion might be owing to the nature of residential programs. These programs provide a short-term, highly structured, and controlled treatment environment47 where OAT’s role in reducing cravings and blocking the euphoric effect of illicit opioids might be less important. Even if OAT does not affect residential treatment completion, it clearly provides addiction, health, and social benefits for patients after discharge.11 This is particularly important as most residential programs in our study were less than 8 to 12 weeks in duration and therefore unlikely to have an effect on longer-term outcomes. A residential admission therefore is an opportunity for programs to encourage patients to initiate OAT before discharge.

Limitations

Our study has several limitations. First, we were unable to access data for those admitted to privately funded treatment programs, as such programs are not required to report to DATIS. Second, the diagnosis of opioid use disorder was not available in DATIS. Instead we used patient reports of opioids as a problem substance, combined with recent daily use. Additionally, as data on OAT use were only recorded at the time of admission, some people might have stopped or started OAT during their admission. To address this we excluded from the adjusted analysis those who were taking OAT but were admitted to a program that banned OAT, as these patients likely discontinued OAT before or during admission. Finally, we did not have data on addiction severity before admission nor data on outcomes after discharge from a treatment program. Linking the DATIS database to hospital data would allow researchers to look at important long-term outcomes after residential stay such as emergency department visits for opioid use disorder.

Conclusion and next steps

Our study demonstrates 2 large gaps in care for people with opioid use disorder that have received little attention to date. First, they have poor access to OAT—the first-line treatment of opioid use disorder—while in publicly funded residential treatment programs. Second, many are involuntarily discharged from treatment. Additionally, our study indicates that patients taking OAT have a similar likelihood of completing residential treatment as those not taking OAT do.

To address current guidelines and recommendations, and the evidence indicating poor access to OAT in our study, programs should receive support to create the appropriate infrastructure to allow patients to access OAT. As the guidelines for the clinical management of opioid use disorder state:

Given the known benefits of opioid agonist treatment, priority should be given to programs and initiatives aimed at strengthening both the opioid agonist and residential treatment systems of care through an integration of evidence-based treatment approaches to opioid use disorder.14

Researchers should further examine the effect of OAT on residential stay and longer-term outcomes after discharge. They should also identify ways to reduce involuntary discharge from residential programs.

Acknowledgments

Dr Spithoff was supported by a graduate research award from the Department of Family and Community Medicine at the University of Toronto.

Notes

Editor’s key points

  • ▸ Opioid agonist therapy (OAT), with methadone or buprenorphine, is the first-line treatment of opioid use disorder. As various North American guidelines are recommending the removal of barriers to OAT within addiction treatment programs, changes within these programs might be required. This study sought to determine access to OAT and treatment outcomes in residential treatment programs.

  • ▸ In this large study of 1910 people with opioid use disorder entering residential treatment in Ontario, the authors found that slightly more than half entered programs that permitted access to OAT during their admission; few entered programs with on-site access to OAT. About 20% of the cohort was taking OAT at the time of admission (ie, the OAT group). More than 40% of people did not complete treatment. Seventeen percent of the cohort was involuntarily discharged from the treatment program. The OAT group was as likely as those not taking OAT to complete treatment.

  • ▸ Although the OAT group was not more likely to complete treatment, this might be due to confounding. Data from outpatient studies suggest that OAT leads to much better retention in treatment. Residential treatment programs should receive support to create the appropriate infrastructure to allow patients to access OAT. Researchers should further examine the effect of OAT on residential stay and longer-term outcomes after discharge. They should also identify ways to reduce involuntary discharge from residential programs.

Points de repère du rédacteur

  • ▸ La thérapie aux agonistes opioïdes (TAO), avec de la méthadone ou de la buprénorphine, représente le traitement de première intention pour un trouble de consommation d’opioïdes. Diverses lignes directrices nord-américaines recommandent d’éliminer les obstacles à la TAO au sein des programmes de désintoxication. C’est pourquoi il y aurait peut-être lieu d’apporter des changements à de tels programmes. Cette étude cherchait à déterminer l’accès à une TAO et ses issues thérapeutiques dans des programmes de traitement en établissement.

  • ▸ Dans cette étude d’envergure portant sur 1910 personnes souffrant d’un trouble de consommation d’opioïdes et ayant été admises dans un programme de désintoxication en établissement en Ontario, les auteurs ont constaté qu’un peu plus de la moitié d’entre elles amorçaient des programmes où l’accès à la TAO était permis durant leur séjour; peu d’entre elles suivaient des programmes qui offraient sur place l’accès à la TAO. Environ 20 % des patients de la cohorte suivaient une TAO au moment de leur admission (le groupe de la TAO). Plus de 40 % des personnes n’ont pas terminé le traitement. Quelque 17 % des sujets de la cohorte ont involontairement été retirés du programme de désintoxication. La probabilité de terminer le traitement était à peu près égale dans le groupe de la TAO et dans celui qui n’en suivait pas.

  • ▸ Même s’il n’était pas plus probable que le groupe de la TAO suive le traitement jusqu’à la fin, cela pourrait être attribuable à des facteurs confusionnels. Des données provenant d’études sur des patients en consultation externe font valoir que la TAO favorise une meilleure rétention en désintoxication. Les programmes de traitement en établissement devraient recevoir du soutien pour établir l’infrastructure appropriée permettant aux patients d’avoir accès à la TAO. Les recherches devraient examiner plus en profondeur les effets de la TAO sur le séjour en établissement et sur les résultats à long terme après le congé. Ils devraient aussi cerner des façons de réduire les retraits involontaires des programmes en établissement.

Footnotes

  • Contributors

    All authors contributed to the concept and design of the study; data gathering, analysis, and interpretation; and preparing the manuscript for submission.

  • Competing interests

    None declared

  • This article has been peer reviewed.

  • Cet article a fait l’objet d’une révision par des pairs.

  • Copyright© the College of Family Physicians of Canada

References

  1. 1.↵
    1. Government of Canada [website].
    National report: apparent opioid-related deaths in Canada. Ottawa, ON: Public Health Agency of Canada; 2018. Available from: www.canada.ca/en/public-health/services/publications/healthy-living/national-report-apparent-opioid-related-deaths-released-march-2018.html. Accessed 2018 Apr 23.
  2. 2.↵
    1. Gomes T,
    2. Mamdani MM,
    3. Dhalla IA,
    4. Cornish S,
    5. Paterson JM,
    6. Juurlink DN
    . The burden of premature opioid-related mortality. Addiction 2014;109(9):1482-8. Epub 2014 Jul 7.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. American Society of Addiction Medicine.
    Opioid addiction 2016 facts and figures. Chevy Chase, MD: American Society of Addiction Medicine; 2016. Available from: www.asam.org/docs/default-source/advocacy/opioid-addiction-disease-facts-figures.pdf. Accessed 2018 Apr 23.
  4. 4.↵
    1. Seth P,
    2. Scholl L,
    3. Rudd RA,
    4. Bacon S
    . Overdose deaths involving opioids, cocaine, and psychostimulants—United States, 2015–2016. MMWR Morb Mortal Wkly Rep 2018;67(12):349-58.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Dunlap B,
    2. Cifu AS
    . Clinical management of opioid use disorder. JAMA 2016;316(3):338-9.
    OpenUrl
  6. 6.↵
    1. Mattick RP,
    2. Breen C,
    3. Kimber J,
    4. Davoli M
    . Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev 2009;(3):CD002209.
  7. 7.↵
    1. Mattick RP,
    2. Breen C,
    3. Kimber J,
    4. Davoli M
    . Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev 2014;(2):CD002207.
  8. 8.↵
    1. Nielsen S,
    2. Larance B,
    3. Degenhardt L,
    4. Gowing L,
    5. Kehler C,
    6. Lintzeris N
    . Opioid agonist treatment for pharmaceutical opioid dependent people. Cochrane Database Syst Rev 2016;(5):CD011117.
  9. 9.↵
    1. Marsch LA
    . The efficacy of methadone maintenance interventions in reducing illicit opiate use, HIV risk behavior and criminality: a meta-analysis. Addiction 1998;93(4):515-32.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Gibson A,
    2. Degenhardt L,
    3. Mattick RP,
    4. Ali R,
    5. White J,
    6. O’Brien S
    . Exposure to opioid maintenance treatment reduces long-term mortality. Addiction 2008;103(3):462-8. Epub 2008 Jan 8.
    OpenUrlCrossRefPubMed
  11. 11.↵
    1. Garcia-Portilla MP,
    2. Bobes-Bascaran MT,
    3. Bascaran MT,
    4. Saiz PA,
    5. Bobes J
    . Long term outcomes of pharmacological treatments for opioid dependence: does methadone still lead the pack? Br J Clin Pharmacol 2014;77(2):272-84.
    OpenUrl
  12. 12.
    1. Sordo L,
    2. Barrio G,
    3. Bravo MJ,
    4. Indave BI,
    5. Degenhardt L,
    6. Wiessing L,
    7. et al
    . Mortality risk during and after opioid substitution treatment: systematic review and meta-analysis of cohort studies. BMJ 2017;357:j1550.
    OpenUrlAbstract/FREE Full Text
  13. 13.↵
    1. Pierce M,
    2. Bird SM,
    3. Hickman M,
    4. Marsden J,
    5. Dunn G,
    6. Jones A,
    7. et al
    . Impact of treatment for opioid dependence on fatal drug-related poisoning: a national cohort study in England. Addiction 2016;111(2):298-308. Epub 2015 Nov 25.
    OpenUrlCrossRefPubMed
  14. 14.↵
    1. Bruneau J,
    2. Ahamad K,
    3. Goyer MÈ,
    4. Poulin G,
    5. Selby P,
    6. Fischer B,
    7. et al
    . Management of opioid use disorders: a national clinical practice guideline. CMAJ 2018;190(9):E247-57.
    OpenUrlFREE Full Text
  15. 15.↵
    1. Ghodse AH,
    2. Reynolds M,
    3. Baldacchino AM,
    4. Dunmore E,
    5. Byrne S,
    6. Oyefeso A,
    7. et al
    . Treating an opiate-dependent inpatient population: a one-year follow-up study of treatment completers and noncompleters. Addict Behav 2002;27(5):765-78.
    OpenUrlCrossRefPubMed
  16. 16.
    1. Zhang Z,
    2. Friedmann PD,
    3. Gerstein DR
    . Does retention matter? Treatment duration and improvement in drug use. Addiction 2003;98(5):673-84.
    OpenUrlCrossRefPubMed
  17. 17.
    1. Arria AM,
    2. TOPPS-II Interstate Cooperative Study Group.
    Drug treatment completion and post-discharge employment in the TOPPS-II Interstate Cooperative Study. J Subst Abuse Treat 2003;25(1):9-18.
    OpenUrlCrossRefPubMed
  18. 18.
    1. Messina N,
    2. Wish E,
    3. Nemes S
    . Predictors of treatment outcomes in men and women admitted to a therapeutic community. Am J Drug Alcohol Abuse 2000;26(2):207-27.
    OpenUrlCrossRefPubMed
  19. 19.
    1. Fernández-Hermida JR,
    2. Secades-Villa R,
    3. Fernández-Ludeña JJ,
    4. Marina-González PA
    . Effectiveness of a therapeutic community treatment in Spain: a long-term follow-up study. Eur Addict Res 2002;8(1):22-9.
    OpenUrlPubMed
  20. 20.↵
    1. Smyth BP,
    2. Barry J,
    3. Keenan E,
    4. Ducray K
    . Lapse and relapse following inpatient treatment of opiate dependence. Ir Med J 2010;103(6):176-9.
    OpenUrlPubMed
  21. 21.↵
    1. Ministry of Public Safety and Solicitor General Coroners Service Province of British Columbia.
    Verdict at Coroners Inquest into death of Brandon Juhani Jansen. Vancouver, BC: Government of British Columbia; 2017. File no. 2016:10270004. Available from: www2.gov.bc.ca/assets/gov/birth-adoption-death-marriage-and-divorce/deaths/coroners-service/inquest/2017/jansen-brandon-juhani-2016-1027-0004-final-verdict.pdf. Accessed 2019 Sep 11.
  22. 22.↵
    1. Ministry of Health and Long-Term Care Ontario; Methadone Treatment and Services Advisory Committee.
    Final report. Toronto, ON: Ministry of Health and Long-Term Care Ontario; 2016. Available from: http://health.gov.on.ca/en/public/programs/drugs/ons/docs/methadone_advisory_committee_report.pdf. Accessed 2019 Sep 11.
  23. 23.↵
    President’s Commission on Combating Drug Addiction and the Opioid Crisis. Washington, DC: President’s Commission on Combating Drug Addiction and the Opioid Crisis; 2017. Available from: www.whitehouse.gov/sites/whitehouse.gov/files/images/Final_Report_Draft_11-1-2017.pdf. Accessed 2019 Sep 11.
  24. 24.↵
    1. Hettema JE,
    2. Sorensen JL
    . Access to care for methadone maintenance patients in the United States. Int J Ment Health Addict 2009;7(3):468-74.
    OpenUrl
  25. 25.↵
    1. Zweben JE,
    2. Aly T,
    3. Martin J,
    4. Wengrofsky S,
    5. Bacci J,
    6. Meddaugh R
    . Making residential treatment available to methadone clients. J Subst Abuse Treat 1999;17(3):249-56.
    OpenUrlPubMed
  26. 26.↵
    1. Brend Y,
    2. Dufresne M
    . What we learned phoning every drug rehab facility in British Columbia. CBC News 2016 Sep 11. Available from: www.cbc.ca/news/canada/british-columbia/what-we-learned-phoning-every-drug-rehab-facility-in-british-columbia-1.3756425. Accessed 2017 Dec 22.
  27. 27.↵
    1. Heinrich CJ,
    2. Cummings GR
    . Adoption and diffusion of evidence-based addiction medications in substance abuse treatment. Health Serv Res 2014;49(1):127-52. Epub 2013 Jul 16.
    OpenUrl
  28. 28.↵
    1. Alderks CE
    . Trends in the use of methadone, buprenorphine, and extended-release naltrexone at substance abuse treatment facilities: 2003–2015 (update). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration; 2017. Available from: www.samhsa.gov/data/sites/default/files/report_3192/ShortReport-3192.html. Accessed 2018 Apr 23.
  29. 29.↵
    1. Health Quality Ontario.
    Quality standards: opioid use disorder. Toronto, ON: Queen’s Printer for Ontario; 2018. Available from: www.hqontario.ca/portals/0/documents/evidence/quality-standards/qs-opioid-use-disorder-clinician-guide-en.pdf. Accessed 2018 Apr 3.
  30. 30.↵
    1. Statistics Canada [website].
    Population estimates on July 1st, by age and sex. Ottawa, ON: Government of Canada; 2019. Available from: www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/demo02a-eng.htm. Accessed 2019 Sep 11.
  31. 31.↵
    1. Rotondi NK,
    2. Rush B
    . Monitoring utilization of a large scale addiction treatment system: the Drug and Alcohol Treatment Information System (DATIS). Subst Abuse 2012;6:73-84. Epub 2012 Jun 25.
    OpenUrlPubMed
  32. 32.
    1. Popova S,
    2. Lange S,
    3. Burd L,
    4. Urbanoski K,
    5. Rehm J
    . Cost of specialized addiction treatment of clients with fetal alcohol spectrum disorder in Canada. BMC Public Health 2013;13:570.
    OpenUrlCrossRefPubMed
  33. 33.
    1. Fischer B,
    2. Nakamura N,
    3. Urbanoski K,
    4. Rush B,
    5. Rehm J
    . Correlations between population levels of prescription opioid use and prescription-opioid-related substance use treatment admissions in the USA and Canada since 2001. Public Health 2012;126(9):749-51. Epub 2012 Jul 5.
    OpenUrlCrossRefPubMed
  34. 34.
    1. Fischer B,
    2. Jones W,
    3. Urbanoski K,
    4. Skinner R,
    5. Rehm J
    . Correlations between prescription opioid analgesic dispensing levels and related mortality and morbidity in Ontario, Canada, 2005–2011. Drug Alcohol Rev 2014;33(1):19-26. Epub 2013 Nov 21.
    OpenUrl
  35. 35.↵
    1. Urbanoski K,
    2. Kenaszchuk C,
    3. Inglis D,
    4. Rotondi NK,
    5. Rush B
    . A system-level study of initiation, engagement, and equity in outpatient substance use treatment. J Subst Abuse Treat 2018;90:19-28. Epub 2018 Apr 17.
    OpenUrl
  36. 36.↵
    1. Statistical Analysis System [software].
    Cary, NC: SAS Institute; 2018. Version 9.4.
  37. 37.↵
    1. R Core Team
    . R: a language and environment for statistical computing. Vienna, Aus: R Foundation for Statistical Computing; 2018.
  38. 38.↵
    1. Knudsen HK,
    2. Abraham AJ,
    3. Roman PM
    . Adoption and implementation of medications in addiction treatment programs. J Addict Med 2011;5(1):21-7.
    OpenUrlCrossRefPubMed
  39. 39.↵
    1. White WL,
    2. Scott CK,
    3. Dennis ML,
    4. Boyle MG
    . It’s time to stop kicking people out of addiction treatment. Counselor (Deerfield Beach) 2005;6(2):12-25.
    OpenUrl
  40. 40.↵
    1. Williams IL
    . Moving clinical deliberations on administrative discharge in drug addiction treatment beyond moral rhetoric to empirical ethics. J Clin Ethics 2016;27(1):71-5.
    OpenUrl
  41. 41.↵
    1. Reisinger HS,
    2. Schwartz RP,
    3. Mitchell SG,
    4. Peterson JA,
    5. Kelly SM,
    6. O’Grady KE,
    7. et al
    . Premature discharge from methadone treatment: patient perspectives. J Psychoactive Drugs 2009;41(3):285-96.
    OpenUrlCrossRefPubMed
  42. 42.↵
    1. Tozman S,
    2. Dejesus E
    . The positive side of administrative discharge (in a drug program). Int J Addict 1981;16(1):135-9.
    OpenUrl
  43. 43.↵
    1. Jackson TR
    . Treatment practice and research issues in improving opioid treatment outcomes. Sci Pract Perspect 2002;1(1):22-8.
    OpenUrlPubMed
  44. 44.↵
    1. Monico L,
    2. Schwartz RP,
    3. Gryczynski J,
    4. O’Grady KE,
    5. Mitchell SG
    . Two models of integrating buprenorphine treatment and medical staff within formerly “drug-free” outpatient programs. J Psychoactive Drugs 2016;48(2):101-8. Epub 2016 Mar 3.
    OpenUrl
  45. 45.↵
    1. Greenberg B,
    2. Hall DH,
    3. Sorensen JL
    . Methadone maintenance therapy in residential therapeutic community settings: challenges and promise. J Psychoactive Drugs 2007;39(3):203-10.
    OpenUrlPubMed
  46. 46.↵
    1. Sorensen JL,
    2. Andrews S,
    3. Delucchi KL,
    4. Greenberg B,
    5. Guydish J,
    6. Masson CL,
    7. et al
    . Methadone patients in the therapeutic community: a test of equivalency. Drug Alcohol Depend 2009;100(1–2):100-6. Epub 2008 Nov 14.
    OpenUrlPubMed
  47. 47.↵
    1. Stahler GJ,
    2. Mennis J,
    3. DuCette JP
    . Residential and outpatient treatment completion for substance use disorders in the U.S.: moderation analysis by demographics and drug of choice. Addict Behav 2016;58:129-35. Epub 2016 Feb 17.
    OpenUrl
PreviousNext
Back to top

In this issue

Canadian Family Physician: 65 (10)
Canadian Family Physician
Vol. 65, Issue 10
1 Oct 2019
  • Table of Contents
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on The College of Family Physicians of Canada.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Opioid agonist therapy during residential treatment of opioid use disorder
(Your Name) has sent you a message from The College of Family Physicians of Canada
(Your Name) thought you would like to see the The College of Family Physicians of Canada web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Opioid agonist therapy during residential treatment of opioid use disorder
Sheryl Spithoff, Christopher Meaney, Karen Urbanoski, Katy Harrington, Bill Que, Meldon Kahan, Pamela Leece, Vivian Shehadeh, Frank Sullivan
Canadian Family Physician Oct 2019, 65 (10) e443-e452;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Share
Opioid agonist therapy during residential treatment of opioid use disorder
Sheryl Spithoff, Christopher Meaney, Karen Urbanoski, Katy Harrington, Bill Que, Meldon Kahan, Pamela Leece, Vivian Shehadeh, Frank Sullivan
Canadian Family Physician Oct 2019, 65 (10) e443-e452;
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • METHODS
    • RESULTS
    • DISCUSSION
    • Acknowledgments
    • Notes
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • Systematic assessment of opioid advertisements in general medical journals
  • Timely access to primary care in New Brunswick
  • Older persons living with dementia and their use of acute care services over 2 years in Alberta
Show more Research

Similar Articles

Subjects

  • Collection française
    • Résumés de recherche

Navigate

  • Home
  • Current Issue
  • Archive
  • Collections - English
  • Collections - Française

For Authors

  • Authors and Reviewers
  • Submit a Manuscript
  • Permissions
  • Terms of Use

General Information

  • About CFP
  • About the CFPC
  • Advertisers
  • Careers & Locums
  • Editorial Advisory Board
  • Subscribers

Journal Services

  • Email Alerts
  • Twitter
  • RSS Feeds

Copyright © 2023 by The College of Family Physicians of Canada

Powered by HighWire