Treatment Of Opioid Use Disorder Among Commercially Insured US Adults, 2008-17

How Does Telehealth Expansion Change Access to Healthcare for Patients With Different Types of Substance Use Disorders?

BACKGROUND

Patients with substance use disorders (SUDs) exhibit low healthcare utilization despite high medical need. Telehealth could boost utilization, but variation in uptake across SUDs is unknown.

METHODS

Using Wisconsin Medicaid enrollment and claims data from December 1, 2018, to December 31, 2020, we conducted a cohort study of telemedicine uptake in the all-ambulatory and the primary care setting during telehealth expansion following the COVID-19 public health emergency (PHE) onset (March 14, 2020). The sample included continuously enrolled (19 months), nonpregnant, nondisabled adults aged 19 to 64 years with opioid (OUD), alcohol (AUD), stimulant (StimUD), or cannabis (CannUD) use disorder or polysubstance use (PSU). Outcomes: total and telehealth visits in the week, and fraction of visits in the week completed by telehealth. Linear and fractional regression estimated changes in in-person and telemedicine utilization. We used regression coefficients to calculate the change in telemedicine utilization, the proportion of in-person decline offset by telemedicine uptake ("offset"), and the share of visits completed by telemedicine ("share").

RESULTS

The cohort (n = 16 756) included individuals with OUD (34.8%), AUD (30.1%), StimUD (9.5%), CannUD (9.5%), and PSU (19.7%). Total and telemedicine utilization varied by group post-PHE. All-ambulatory: total visits dropped for all, then rose above baseline for OUD, PSU, and AUD. Telehealth expansion was associated with visit increases: OUD: 0.489, P < .001; PSU: 0.341, P < .001; StimUD: 0.160, P < .001; AUD: 0.132, P < .001; CannUD: 0.115, P < .001. StimUD exhibited the greatest telemedicine share. Primary care: total visits dropped for all, then recovered for OUD and CannUD. Telemedicine visits rose most for PSU: 0.021, P < .001; OUD: 0.019, P < .001; CannUD: 0.011, P < .001; AUD: 0.010, P < .001; StimUD: 0.009, P < .001. PSU and OUD exhibited the greatest telemedicine share, while StimUD exhibited the lowest. Telemedicine fully offset declines for OUD only.

CONCLUSIONS

Telehealth expansion helped maintain utilization for OUD and PSU; StimUD and CannUD showed less responsiveness. Telehealth expansion could widen gaps in utilization by SUD type.

Growing importance of high-volume buprenorphine prescribers in OUD treatment: 2009-2018

BACKGROUND

We examined the number and characteristics of high-volume buprenorphine prescribers and the nature of their buprenorphine prescribing from 2009 to 2018.

METHODS

In this observational cohort study, IQVIA Real World retail pharmacy claims data were used to characterize trends in high-volume buprenorphine prescribers (clinicians with a mean of 30 or more active patients in every month that they were an active prescriber) during 2009-2018. Very high-volume prescribing (mean of 100+ patients per month) was also examined.

RESULTS

Overall, 94,491 clinicians prescribed buprenorphine dispensed during 2009-2018. The proportion of active prescribers meeting high-volume criteria increased from 7.4 % in 2009 to 16.7 % in 2018. High-volume prescribers accounted for 80 % of dispensed buprenorphine prescriptions during 2009-2018; very high-volume prescribers accounted for 26 %. Adult primary care physicians consistently comprised the majority of high-volume prescribers. Addiction specialists were much more likely to be high-volume prescribers compared to other specialties, including psychiatrists and pain specialists. By 2018, the proportion of prescriptions from high-volume prescribers paid by Medicaid had doubled to 40 %, accompanied by a decline in both self-pay and commercial insurance. High-volume prescribers were overwhelmingly concentrated in urban counties with the highest fatal overdose rates. In 2018, the highest density of high-volume prescribers was in New England and the mid-Atlantic region.

CONCLUSIONS

Growth in high-volume prescribers outpaced the overall growth in buprenorphine prescribers across 2009-2018. High-volume prescribers play an increasingly central role in providing medication for OUD in the U.S., yet results indicate key regional variation in the availability of high-volume buprenorphine prescribers.

Identifying patients with opioid use disorder using International Classification of Diseases (ICD) codes: Challenges and opportunities

BACKGROUND AND AIMS

International Classification of Diseases (ICD) diagnosis codes are often used in research to identify patients with opioid use disorder (OUD), but their accuracy for this purpose is not fully evaluated. This study describes application of ICD-10 diagnosis codes for opioid use, dependence and abuse from an electronic health record (EHR) data extraction using data from the clinics' OUD patient registries and clinician/staff EHR entries.

DESIGN

Cross-sectional observational study.

SETTING

Four rural primary care clinics in Washington and Idaho, USA.

PARTICIPANTS

307 patients.

MEASUREMENTS

This study used three data sources from each clinic: (1) a limited dataset extracted from the EHR, (2) a clinic-based registry of patients with OUD and (3) the clinician/staff interface of the EHR (e.g. progress notes, problem list). Data source one included records with six commonly applied ICD-10 codes for opioid use, dependence and abuse: F11.10 (opioid abuse, uncomplicated), F11.20 (opioid dependence, uncomplicated), F11.21 (opioid dependence, in remission), F11.23 (opioid dependence with withdrawal), F11.90 (opioid use, unspecified, uncomplicated) and F11.99 (opioid use, unspecified with unspecified opioid-induced disorder). Care coordinators used data sources two and three to categorize each patient identified in data source one: (1) confirmed OUD diagnosis, (2) may have OUD but no confirmed OUD diagnosis, (3) chronic pain with no evidence of OUD and (4) no evidence for OUD or chronic pain.

FINDINGS

F11.10, F11.21 and F11.99 were applied most frequently to patients who had clinical diagnoses of OUD (64%, 89% and 79%, respectively). F11.20, F11.23 and F11.90 were applied to patients who had a diagnostic mix of OUD and chronic pain without OUD. The four clinics applied codes inconsistently.

CONCLUSIONS

Lack of uniform application of ICD diagnosis codes make it challenging to use diagnosis code data from EHR to identify a research population of persons with opioid use disorder.

High-deductible Health Plans and Nonfatal Opioid Overdose

OBJECTIVES

Opioid-related overdose is a public health emergency in the United States. Meanwhile, high-deductible health plans (HDHPs) have become more prevalent in the United States over the last 2 decades, raising concern about their potential for discouraging high-need populations, like those with opioid use disorder (OUD), from engaging in care that may mitigate the probability of overdose. This study assesses the impact of an employer offering an HDHP on nonfatal opioid overdose among commercially insured individuals with OUD in the United States.

RESEARCH DESIGN

We used deidentified insurance claims data from 2007 to 2017 with 97,788 person-years. We used an intent-to-treat, difference-in-differences regression framework to estimate the change in the probability of a nonfatal opioid overdose among enrollees with OUD whose employers began offering an HDHP insurance option during the study period compared with the change among those whose employer never offered an HDHP. We also used an event-study model to account for dynamic time-varying treatment effects.

RESULTS

Across both comparison and treatment groups, 2% of the sample experienced a nonfatal opioid overdose during the study period. Our primary model and robustness checks revealed no impact of HDHP offer on the probability of a nonfatal overdose.

CONCLUSIONS

Our study suggests that HDHP offer was not associated with an observed increase in the probability of nonfatal opioid overdose among commercially insured person-years with OUD. However, given the strong evidence that medications for OUD (MOUD) can reduce the risk of overdose, research should explore which facets of insurance design may impact MOUD use.

National Trends in Buprenorphine Treatment for Opioid Use Disorder From 2007 to 2018

BACKGROUND

Buprenorphine is a key medication to treat opioid use disorder (OUD). Since its approval in 2002, buprenorphine access has grown markedly, spurred by major federal and state policy changes. This study characterizes buprenorphine treatment episodes during 2007 to 2018 with respect to payer, provider specialty, and patient demographics.

METHODS

In this observational cohort study, IQVIA Real World pharmacy claims data were used to characterize trends in buprenorphine treatment episodes across four time periods: 2007-2009, 2010-2012, 2013-2015, and 2016-2018.

RESULTS

In total, we identified more than 4.1 million buprenorphine treatment episodes among 2 540 710 unique individuals. The number of episodes doubled from 652 994 in 2007-2009 to 1 331 980 in 2016-2018. Our findings indicate that the payer landscape changed dramatically, with the most pronounced growth observed for Medicaid (increased from 17% of episodes in 2007-2009 to 37% of episodes in 2016-2018), accompanied by relative declines for both commercial insurance (declined from 35 to 21%) and self-pay (declined from 27 to 11%). Adult primary care providers (PCPs) were the dominant prescribers throughout the study period. The number of episodes among adults older than 55 increased more than 3-fold from 2007-2009 to 2016-2018. In contrast, youth under age 18 experienced an absolute decline in buprenorphine treatment episodes. Buprenorphine episodes increased in length from 2007-2018, particularly among adults over age 45.

CONCLUSIONS

Our findings demonstrate that the U.S. experienced clear growth in buprenorphine treatment-particularly for older adults and Medicaid beneficiaries-reflecting some key health policy and implementation success stories. Yet, since the prevalence of OUD and fatal overdose rate have also approximately doubled during this period, the observed growth in buprenorphine treatment did not demonstrably impact the pronounced treatment gap. To date, only a minority of individuals with OUD currently receive treatment, indicating continued need for systemic efforts to equitably improve treatment uptake.

Association of polysubstance use disorder with treatment quality among Medicaid beneficiaries with opioid use disorder

INTRODUCTION

The opioid crisis is transitioning to a polydrug crisis, and individuals with co-occurring substance use disorder (SUDs) often have unique clinical characteristics and contextual barriers that influence treatment needs, engagement in treatment, complexity of treatment planning, and treatment retention.

METHODS

Using Medicaid data for 2017-2018 from four states participating in a distributed research network, this retrospective cohort study documents the prevalence of specific types of co-occurring SUD among Medicaid enrollees with an opioid use disorder (OUD) diagnosis, and assesses the extent to which different SUD presentations are associated with differential patterns of MOUD and psychosocial treatments.

RESULTS

We find that more than half of enrollees with OUD had a co-occurring SUD, and the most prevalent co-occurring SUD was for "other psychoactive substances", indicated among about one-quarter of enrollees with OUD in each state. We also find some substantial gaps in MOUD treatment receipt and engagement for individuals with OUD and a co-occurring SUD, a group representing more than half of individuals with OUD. In most states, enrollees with OUD and alcohol, cannabis, or amphetamine use disorder are significantly less likely to receive MOUD compared to enrollees with OUD only. In contrast, enrollees with OUD and other psychoactive SUD were significantly more likely to receive MOUD treatment. Conditional on MOUD receipt, enrollees with co-occurring SUDs had 10 % to 50 % lower odds of having a 180-day period of continuous MOUD treatment, an important predictor of better patient outcomes. Associations with concurrent receipt of MOUD and behavioral counseling were mixed across states and varied depending on co-occurring SUD type.

CONCLUSIONS

Overall, ongoing progress toward increasing access to and quality of evidence-based treatment for OUD requires further efforts to ensure that individuals with co-occurring SUDs are engaged and retained in effective treatment. As the opioid crisis evolves, continued changes in drug use patterns and populations experiencing harms may necessitate new policy approaches that more fully address the complex needs of a growing population of individuals with OUD and other types of SUD.

The association of state-level drug and opioid overdose deaths with the capacity of behavioural health professionals in the United States

As behavioural health occupations have diversified, more specialists such as social workers and counsellors are involved in providing substance use disorder treatment services. This study examined the association between changes in the number of different types of behavioural health professionals and changes in drug and opioid overdose deaths in the United States. Using publicly available state-level data from 2008 to 2017, we constructed multivariate linear regression models with state- and year fixed-effects to examine the effect of changes in the number of different types of behavioural health professionals (i.e. psychiatrists, psychologists, social workers and counsellors) on changes in drug and opioid overdose deaths at the state level, controlling for state population characteristics and other state-level factors. After controlling for confounding factors, a 1% increase in the number of social workers and counsellors at the state level was significantly associated with a 0.215% reduction in drug overdose deaths per 100,000 state population and with a 0.358% reduction in opioid overdose deaths per 100,000 state population. We did not find statistically significant associations between changes in drug overdose death rates and increases in the number of psychiatrists or psychologists alone. Our findings suggest efforts to facilitate a prepared and skilled workforce, such as expanding the capacity of social workers and counsellors, to maximise access to substance use disorder treatment services.

Demographic and Clinical Correlates of Treatment Completion among Older Adults with Heroin and Prescription Opioid Use Disorders

In this study using 2015-2018 Treatment Episode Data Set-Discharge (TEDS-D) cases age 55+ for heroin (N = 101,524) or prescription opioids (PO; N = 25,510) as the primary substance, we examined treatment completion rates and correlates. We fit separate logistic regression models for heroin and PO cases with treatment completion status (completed vs. discontinued due to dropout/termination/other reasons) for each treatment setting (detoxification, residential rehabilitation, and outpatient) as the dependent variable. Results show that detoxification cases had the highest completion rates and outpatient cases had the lowest (14.8% for heroin and 24.0% for PO cases). A consistently significant correlate of treatment completion was legal system referral for heroin cases and having a bachelor's degree for PO cases. Medication-assisted therapy was associated with higher odds of completing residential treatment for both types of opioids but lower odds of completing detoxification and outpatient treatment. Treatment duration >30 days tended to have higher odds of completion. PO cases age 65+ had higher odds of completing residential treatment than cases age 55-64. Racial/ethnic minorities tended to have lower odds of outpatient treatment completion. Study findings underscore the importance of helping older adults complete treatment, especially those who are racial/ethnic minorities and receiving outpatient treatment.

Quality of Life and Opioid Use Motives: Direct and Indirect Associations with Risky Opioid Use in a Community Sample of Adults

Purpose: The opioid epidemic in the United States has resulted in mass mortality and economic costs exceeding $1 trillion. Poor health-related quality of life is evident among individuals entering treatment for opioid use disorder (OUD). Yet, little research has examined the influence of quality of life on risky opioid use among non-treatment-seeking adults. To help inform OUD prevention efforts, this study examined the association among quality of life domains, opioid use motives, and risky opioid behaviors in a community sample of opioid users. Methods: Participants (N = 278) were adults who endorsed past month opioid use and were not currently in treatment for OUD. Participants responded to questions regarding their opioid use and misuse, opioid use motives, opioid use consequences, and quality of life. Results: The physical health domain of quality of life was associated with risky opioid use. Specifically, poorer physical health predicted risky opioid use and this relationship was partially explained by more social and pain motives to use opioids. Surprisingly, no other quality of life domains predicted risky opioid use. Conclusion: This study represents a meaningful first step in identifying optimal targets for OUD prevention efforts with community samples. Our findings suggest that physical health is an important quality of life indicator to prevent opioid-related harm and development of OUD.

Factors Associated With Initial Treatment Choice, Engagement, and Discontinuation for Patients With Opioid Use Disorder

OBJECTIVE

Pharmacotherapy for opioid use disorder is effective but underused from a clinical perspective, and average treatment duration is shorter than current recommendations. In this analysis, the authors examined factors associated with initiation of, engagement in, and duration of treatment among patients with opioid use disorder.

METHODS

Using the OptumLabs Data Warehouse (a large, national, deidentified database of commercial or Medicare Advantage plan enrollees), the authors identified a sample of 204,225 patients with opioid use disorder between July 1, 2010, and April 1, 2019. Factors associated with initial treatment type were identified with multinomial logistic regression. The odds of treatment engagement, defined as two claims for treatment and a treatment episode of ≥30 days, were estimated with logistic regression. The hazard ratios for treatment discontinuation were estimated with a Cox proportional hazards model.

RESULTS

Treatment initiation with pharmacotherapy (alone or in combination with psychosocial therapy) was associated with higher odds of treatment engagement and a lower hazard of treatment discontinuation. Patients with certain behavioral health conditions (e.g., anxiety or mood disorders) had higher odds of initiating treatment with pharmacotherapy and engaging in treatment and a lower hazard of discontinuing treatment. Patients with certain painful general health conditions (e.g., fibromyalgia or musculoskeletal disorders) had lower odds of initiating and engaging in treatment.

CONCLUSIONS

Treatment initiation with pharmacotherapy was associated with treatment engagement and duration. Previous contact with behavioral health treatment may support initiating, engaging in, and remaining in treatment. Patients with painful conditions may benefit from provider support in initiating treatment for opioid use disorder.

Trends in Engagement With Opioid Use Disorder Treatment Among Medicaid Beneficiaries During the COVID-19 Pandemic

Question

During the COVID-19 public health emergency, did patients with opioid use disorder experience decreased access to opioid use disorder treatment?

Findings

In this cohort study of 6453 Medicaid beneficiaries with opioid use disorder in Wisconsin, buprenorphine possession remained stable at the onset and for the first 6 months of the public health emergency. In contrast, completion of urine drug tests and receipt of opioid treatment program services declined with the onset of the public health emergency and recovered partially 6 months into the public health emergency.

Meaning

The findings of this study suggest that the COVID-19 public health emergency did not disrupt access to buprenorphine but did disrupt urine drug testing and access to opioid treatment program services.

Importance

Disruptions in care during the COVID-19 pandemic may have decreased access to care for patients with opioid use disorder.

Objective

To examine trends in opioid use disorder treatment including buprenorphine possession, urine drug testing, and opioid treatment program services during the COVID-19 public health emergency.

Design, Setting, and Participants

This cohort study included 6453 parent and childless adult Medicaid beneficiaries, aged 18 to 64 years, with opioid use disorder and continuous enrollment from December 1, 2018, to September 30, 2020, in Wisconsin. Logistic regression compared differences in study outcomes before, early, and later in the COVID-19 public health emergency. Analyses were conducted from January 2021 to October 2021.

Exposures

Early (March 16, 2020, to May 15, 2020) and later (May 16, 2020, to September 30, 2020) in the public health emergency.

Main Outcomes and Measures

Person-week outcomes included possession of buprenorphine, completion of outpatient urine drug testing, and receipt of opioid treatment program services.

Results

The final cohort of 6453 participants included 3986 (61.8%) childless adults; 5741 (89%) were younger than 50 years, 3435 (53.2%) were women, 5036 (78.0%) White, and 22.0% were racial and ethnic minority groups (American Indian, 269 [4.2%]; Asian, 26 [0.4%]; Black, 458 [7.1%]; Hispanic, 292 [4.5%]; Pacific Islander, 1 [.02%]; Multiracial, 238 [3.7%]). Overall, 2858 (44.3%), 5074 (78.6%), and 2928 (45.4%) received buprenorphine, urine drug testing, or opioid treatment program services during the study period, respectively. Probability of buprenorphine possession did not change in the early or later part of the public health emergency. Probability of urine drug testing initially decreased (marginal effect [ME], –0.04; 95% CI, –0.04 to –0.03; P < .001) and then partially recovered in the later public health emergency (ME, –0.02; 95% CI, –0.03 to –0.02; P < .001). Probability of opioid treatment program services followed a similar pattern, with an early decrease (ME, –0.05; 95% CI, –0.05 to –0.04; P < .001) followed by partial recovery (ME, –0.02; 95% CI, –0.03 to –0.02; P < .001).

Conclusions and Relevance

In a sample of continuously enrolled adult Medicaid beneficiaries, the COVID-19 public health emergency was not associated with decreased probability of buprenorphine possession, but was associated with decreased probability of urine drug testing and opioid treatment program services. These findings suggest patients in office-based settings retained access to buprenorphine despite decreased on-site services like urine drug tests, whereas patients at opioid treatment programs experienced greater disruption in care. Given the importance of medications for opioid use disorder in preventing overdose, policy makers should consider permanent policy changes based on lessons learned from the public health emergency to enable ongoing enhanced access to these medications.

Emergency department-based efforts to offer medication treatment for opioid use disorder: What can we learn from current approaches?

BACKGROUND

The opioid epidemic remains a public health crisis and most people with opioid use disorder (OUD) do not receive effective treatment. The emergency department (ED) can be a critical entry point for treatment. EDs are developing and implementing ED-based efforts to address OUD to improve access to OUD treatment. This study's objective is to identify features of ED-based OUD treatment programs that relate to program implementation, effectiveness, and sustainability.

METHODS

We obtained data through literature review and semistructured interviews with ED physicians and leaders. The study analyzed these data to develop a framework of key components of ED-based efforts and highlight barriers and facilitators to implementation and program effectiveness.

RESULTS

We identify five key features of ED-based opioid treatment programs that vary across programs and may influence effectiveness and impact: patient identification methods; treatment approaches; program structure; relationship with community partners; and financing and sustainability. Successful implementation of ED-based OUD treatment includes having a champion, a reliable referral network, and systematic tracking and reporting of data for monitoring and feedback.

CONCLUSION

Going forward, attention to these features may help to improve effectiveness. As researchers conduct studies of ED-based care models, they should assess the impact of variation in key features to improve program effectiveness.

Use of Medications for Treatment of Opioid Use Disorder Among US Medicaid Enrollees in 11 States, 2014-2018

Importance

There is limited information about trends in the treatment of opioid use disorder (OUD) among Medicaid enrollees.

Objective

To examine the use of medications for OUD and potential indicators of quality of care in multiple states.

Design, Setting, and Participants

Exploratory serial cross-sectional study of 1 024 301 Medicaid enrollees in 11 states aged 12 through 64 years (not eligible for Medicare) with International Classification of Diseases, Ninth Revision (ICD-9 or ICD-10) codes for OUD from 2014 through 2018. Each state used generalized estimating equations to estimate associations between enrollee characteristics and outcome measure prevalence, subsequently pooled to generate global estimates using random effects meta-analyses.

Exposures

Calendar year, demographic characteristics, eligibility groups, and comorbidities.

Main Outcomes and Measures

Use of medications for OUD (buprenorphine, methadone, or naltrexone); potential indicators of good quality (OUD medication continuity for 180 days, behavioral health counseling, urine drug tests); potential indicators of poor quality (prescribing of opioid analgesics and benzodiazepines).

Results

In 2018, 41.7% of Medicaid enrollees with OUD were aged 21 through 34 years, 51.2% were female, 76.1% were non-Hispanic White, 50.7% were eligible through Medicaid expansion, and 50.6% had other substance use disorders. Prevalence of OUD increased in these 11 states from 3.3% (290 628 of 8 737 082) in 2014 to 5.0% (527 983 of 10 585 790) in 2018. The pooled prevalence of enrollees with OUD receiving medication treatment increased from 47.8% in 2014 (range across states, 35.3% to 74.5%) to 57.1% in 2018 (range, 45.7% to 71.7%). The overall prevalence of enrollees receiving 180 days of continuous medications for OUD did not significantly change from the 2014-2015 to 2017-2018 periods (-0.01 prevalence difference, 95% CI, -0.03 to 0.02) with state variability in trend (90% prediction interval, -0.08 to 0.06). Non-Hispanic Black enrollees had lower OUD medication use than White enrollees (prevalence ratio [PR], 0.72; 95% CI, 0.64 to 0.81; P < .001; 90% prediction interval, 0.52 to 1.00). Pregnant women had higher use of OUD medications (PR, 1.18; 95% CI, 1.11-1.25; P < .001; 90% prediction interval, 1.01-1.38) and medication continuity (PR, 1.14; 95% CI, 1.10-1.17, P < .001; 90% prediction interval, 1.06-1.22) than did other eligibility groups.

Conclusions and Relevance

Among US Medicaid enrollees in 11 states, the prevalence of medication use for treatment of opioid use disorder increased from 2014 through 2018. The pattern in other states requires further research.

Stigmatization of medications for opioid use disorder in 12-step support groups and participant responses

Background: 12-step groups are the most common approach to managing opioid use disorder (OUD) in the U.S. Medications for OUD (MOUD) are the most effective tool for preventing opioid misuse and relapse. Previous research has identified stigma of MOUD in 12-step groups. Objectives: We sought to identify how MOUD stigma is operationalized in 12-step groups and to identify responses to stigma. Methods: We recruited individuals with both MOUD experience and 12-step group experience from three syringe exchange programs in the U.S. using snowball sampling. We conducted individual telephone semi-structured interviews during 2018 and 2019. We coded data in Dedoose software and conducted thematic analysis using iterative categorization. Results: We recruited 30 individuals meeting our inclusion criteria. The following stigma operationalization methods were identified: prohibiting people using MOUD from speaking at meetings; encouraging shortened duration of MOUD treatment; refusing to sponsor people using MOUD; and refusing to let people using MOUD claim recovery time. Responses to stigma included the following: feeling shame; feeling anger; shopping around for different groups, leaving the group, or forming a new group; not revealing MOUD utilization or only telling a sponsor; speaking out on behalf of MOUD; and using cognitive approaches to avoid stigma internalization. Cognitive approaches included believing that anti-MOUD stigma is contrary to 12-step principles; disregarding statements as inaccurate based on one's experience of MOUD benefits; and accepting that all groups of humans have some ignorant people. Conclusion: Healthcare systems should help address MOUD stigma experienced by patients in 12-step groups, such as by offering non-12-step alternative groups and encouraging MOUD healthcare providers to prepare patients for potential stigma they may face. Some stigma response options, like shopping around for different groups, may not be feasible in rural areas or for participants newer to recovery.

Diagnosis of Opioid Use Disorder by Youths Assessed in Acute Care Settings in British Columbia, Canada

OBJECTIVES

To describe trends in the number of youths diagnosed with opioid use disorder (OUD) and to identify factors associated with OUD diagnosis in acute care settings.

STUDY DESIGN

Data from a population-based retrospective cohort study with linkage of 6 health administrative databases for 13 009 youth age 12-24 years identified with OUD between 2001 and 2018 in British Columbia, Canada were used to describe annual diagnoses. Using a multiple logistic regression model, we estimated the association between past-year health care utilization and OUD diagnosis in acute settings, controlling for sociodemographic and OUD-related comorbid conditions.

RESULTS

Annual OUD diagnoses quadrupled between 2003 and 2017 (from 326 to 1473). Among the 6579 youth diagnosed with OUD between April 1, 2013 and September 30, 2018, 88.1% had past-year health system contacts. Youth age 12-18 had higher odds of OUD diagnosis in acute care (aOR 2.04; 95% CI 1.78, 2.34). Compared with no health care contact, youth receiving outpatient care only were less likely to be diagnosed with OUD in acute care (aOR 0.69; 95% CI 0.56, 0.84) and those with >1 urgent hospitalization were more likely to be diagnosed with OUD in acute care (aOR 1.87; 95% CI 1.40,2.49).

CONCLUSIONS

More than 88% of youth had past-year health system contacts prior to diagnosis. Those age 12-18 years and with urgent hospitalizations in the year prior to diagnosis were more likely to have OUD diagnosed in acute care settings. Establishing an effective evidence-based system for early detection and intervention among youth with OUD must be a priority.

The cascade of care for opioid use disorder among youth in British Columbia, 2018

BACKGROUND

Medication for opioid use disorder (MOUD) is associated with substantial reductions in the risk of mortality, and American and Canadian guidelines recommend it as part of the full range of available treatments for youth with opioid use disorder (OUD). We estimated the OUD cascade of care for all adolescents (ages 12-18) and young adults (19-24) with OUD in British Columbia, Canada (BC) in 2018.

METHODS

Using a provincial-level linkage of six health administrative databases, we classified youth with OUD as adolescents (ages 12-18) or young adults (19-24) to compare with older adults (≥25) and described key factors known to influence engagement in health care. The eight-stage cascade of care included diagnosed with OUD, ever engaged in MOUD, recently in MOUD, currently in MOUD, and retained in MOUD for ≥1 month, ≥3 months, ≥12 months, ≥24 months.

RESULTS

We identified 4048 youth diagnosed with OUD as of September 30, 2018 (6.3% of all people with OUD). Most were young adults, aged 19-24 (n = 3602; 89.0% of all youth), a majority of whom were males (n = 1984; 55.1%). In contrast, adolescents diagnosed with OUD (n = 446; 11.0% of all youth) were mostly females (n = 287; 64.4%). Compared to adolescents, there were more young adults diagnosed with OUD ever engaged in MOUD (71.4% v. 36.5%), currently on MOUD (29.3% v. 16.8%), and retained in care for ≥1 year (8.6% v. 2.0%).

CONCLUSIONS

A high proportion of youth aged 12-24 diagnosed with OUD in a health care setting in British Columbia received MOUD yet continued engagement is infrequent, particularly for adolescents. Long-term treatment plans for youth need to consider including MOUD when appropriate as part of tailored, youth-friendly services.

Report of the 2020 Special Committee on Substance Use and Pharmacy Education

EXECUTIVE SUMMARYThe 2020 Special Committee on Substance Use and Pharmacy Education was charged to update the work of the 2010 Special Committee on Substance Abuse and Pharmacy Education Report (SAPER) specifically with recommendations on core curricular content and delivery processes on substance misuse and substance use disorder (SUD). This report provides information on the committee's process to address the charges, background information and resources pertaining to the charges, and rationale for SUD being a critical topic for curriculum at colleges and schools of pharmacy. This committee offers several recommendations to the Association of Colleges of Pharmacy (AACP) pertaining to the committee charges.