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In this session, Drs. Rossom and Hooker discussed the design and implementation of Opioid Wizard, a clinical decision support tool embedded in the EHR for primary care clinicians and developed as part of NIDA Clinical Trials Network protocol CTN-0095. The goal of the tool is to help clinicians identify, screen, diagnose and treat opioid use disorder (OUD).

They also discussed one of the supplements to CTN-0095, which tested a training to reduce stigma towards people with OUD among primary care clinicians.

Related protocols: CTN-0095

Objectives: To identify and value resources required to implement and sustain the Massachusetts model of office-based addiction treatment (MA Model) in the Primary Care Opioid Use Disorders Treatment trial (NCT03407638) using a nurse care manager (NCM) to support medication for opioid use disorder in primary care settings.

Study design: A site-specific microcosting analysis was conducted via activity-based costing. Guided by a structured costing instrument, we conducted semistructured interviews with relevant personnel and assigned nationally representative costs.

Methods: Data came from 6 health care systems. Costs were categorized as fixed start-up, time dependent, or variable and estimated as annual per-clinic and per-patient costs for implementation and sustainment phases.

Results: Mean implementation cost (ie, year 1 fixed start-up, time-dependent, and variable) was $238,888 per clinic ($3185 per patient); each subsequent year cost $229,676 ($3062 per patient), assuming 75 patients per month and 29% new patient case mix. Mean onetime fixed start-up costs were $9212 per clinic and included supplies and training. Time-dependent costs were $70,446 per clinic and included rent and meetings. Variable costs were $159,229 per clinic and included NCMs’ and prescribers’ clinical duties. On average, NCMs spent 1967.6 hours on MA Model-related work per year (26.2 hours per patient). In sensitivity analyses, costs varied drastically with patient caseload, provider mix, and new patient case mix.

Conclusions: Fixed start-up and time-dependent costs were minimal. Variable costs were 66.7% of implementation costs and 69.3% of costs annually afterward. The primary cost driver was NCM time conducting MA Model-related work. The additional value of the model will depend on associated downstream outcomes. These results may be helpful to health care systems considering implementing the MA Model.

Related protocols: CTN-0074

Background: Rural communities face disproportionate rates of opioid use disorder (OUD) and overdose mortality but continue to be underrepresented in clinical research and underserved in access to medications for opioid use disorder (MOUD). Structural barriers including shortages of qualified providers, transportation challenges, and stigma limit uptake of evidence-based treatment. To address these gaps, the National Drug Abuse Treatment Clinical Trials Network (CTN) launched two pragmatic trials focused exclusively on rural populations: CTN-0102, a telemedicine (TM) feasibility study connecting rural primary care patients to external MOUD providers, and CTN-0102XR (RXR), a pilot randomized trial evaluating extended-release buprenorphine (Brixadi®) compared to sublingual buprenorphine-naloxone.

Objective: The article aims to describe the implementation of these two rural pragmatic trials, identify challenges encountered in study implementation, and present lessons learned. We applied frameworks from implementation science, including the Consolidated Framework for Implementation Research (CFIR) and the Expert Recommendations for Implementing Change (ERIC), to demonstrate how pragmatic trial implementation mirrors implementation of evidence-based programs and practices, and can benefit from established implementation frameworks and strategies.

Results: Across 13 rural clinics in 10 states, both trials demonstrated the feasibility of integrating MOUD into primary care settings through pragmatic study designs closely aligned with routine clinical workflows. Principal challenges included limited clinic research capacity, staff stigma toward OUD treatment, communication barriers between local clinics and external TM vendors, and variable digital access. Solutions included engaging local champions, co-developing workflows tailored to each clinic’s operations, simplifying technology requirements, and emphasizing bi-directional communication among clinic, research, and vendor teams. Continuous technical assistance and protocol flexibility and adaptation were crucial for sustaining engagement and aligning study procedures with clinical realities. Findings demonstrated that rural clinics can feasibly implement TM-based MOUD coordination and extended-release buprenorphine with adequate support and contextual adaptation.

Conclusions: Lessons from CTN-0102 and CTN-0102XR underscore that pragmatic trials in rural settings benefit from early contextual assessment, engagement of community stakeholders, adaptable protocols, and strong implementation support. Applying implementation science frameworks facilitates solutions to real-world barriers and enhances study sustainability. Future CTN efforts should continue to prioritize rural site inclusion, capacity building, and equitable access to evidence-based OUD treatment.

Related protocols: CTN-0102, CTN-0102-XR

Primary care is a critical setting to provide care for the 75-79% of patients who have opioid use disorder (OUD) but do not receive medications for OUD. However, patient perceptions of primary care of OUD are not well understood. Patients completed surveys about their experience with opioid-related clinical decision support system (CDSS) printouts and OUD treatment in the first 7-9 months of implementation of an OUD-CDSS. Survey responses were presented overall and by reason for study eligibility. Of 277 patients completing surveys, 22% recalled seeing the printouts; of these, 85% said the printouts made them more comfortable discussion opioid risk. Of all respondents, half discussed opioids during their visit; of these, 84% felt conversations were conducted sensitively. Overall, 88% felt primary care was the right setting to discuss opioid risks. The opioid-related printouts and discussions were generally well-received, and patients felt primary care was a suitable setting for opioid-related care.

Background: Opioid use disorder (OUD) remains a significant public health issue. Yet, few primary care clinicians (PCCs) screen for, diagnose, or treat OUD. Clinical decision support tools (CDS) integrated into the electronic health record improve process and outcome measures across a variety of conditions. We evaluated PCC perspectives on an OUD CDS tool (Opioid Wizard) deployed through a clinic-randomized trial.

Methods: This is a secondary analysis of CTN-0095, a trial evaluating the effectiveness of Opioid Wizard on OUD process and outcome measures. In short, 92 primary care clinics across three health systems were randomized to Opioid Wizard or usual care. PCCs completed online surveys pre- and 9-month post-Opioid Wizard’s go-live date. Survey items measured PCC self-reports on their confidence and ability to manage OUD, and for PCCs in Opioid Wizard clinics, perceptions about the tool. Generalized linear mixed models with Poisson distribution estimated change in survey response from baseline to follow-up within each treatment group (risk ratios) and in intervention relative to control clinics (ratio of risk ratios).

Results: 361 PCCs (n = 180 Opioid Wizard, n = 181 usual care, 63% female) answered at least one survey. Confidence in screening (RR 1.32, 95% CI 1.07, 1.62), diagnosing (RR 1.24, 95% CI 1.02, 1.50), and referring (RR 1.17, 95% CI 1.02, 1.34) patients for OUD care significantly increased in Opioid Wizard clinics only. Confidence in treating OUD with buprenorphine did not increase in either setting. Of 55 PCCs who used Opioid Wizard at least once, 80% agreed Opioid Wizard made tasks easier and 70% agreed using Opioid Wizard was time “well spent,” but only 44% were likely to recommend it to colleagues.

Conclusion: Opioid Wizard increased PCC confidence across a variety of OUD care measures yet enthusiasm for and use of the tool was limited. Efforts to increase Opioid Wizard use may improve OUD care measures.

Related protocols: CTN-0095

Background: Most people with opioid use disorder (OUD) do not receive evidence-based treatment. To increase treatment rates, primary care clinics may choose to implement risk prediction tools available in the electronic health record (EHR) to identify patients with a high risk of OUD or overdose.

Objective: To externally validate Epic’s cognitive computing model to predict the Risk of Opioid Abuse or Overdose (referred to as the Opioid Risk Score; ORS) in three large integrated health systems.

Design: Prospective cohort study secondary to an ongoing clinical trial.

Participants: Patients (N = 704,764) aged 18-75 who had a primary care encounter during the study period (April 2021-December 2022) and did not have an OUD diagnosis at index.

Main measures: Data were extracted from the EHR. The index date was defined as the first date within the study period where the patient met eligibility criteria and had an ORS calculated by the EHR. The binary outcome variable was whether the patient was diagnosed with OUD or experienced an opioid overdose within 12 months of the index date.

Key results: Most patients were classified as low risk on ORS (99.6%). Few patients experienced an OUD diagnosis or overdose in the 12-month follow-up period (0.3%). The model correctly classified 185 of 2362 patients who experienced an event (sensitivity 0.0783, 95% CI 0.0675, 0.0892) and 699,926 of 702,406 patients who did not experience an event (specificity 0.9965, 95% CI 0.9963, 0.9966). Few patients with high ORS experienced the event (PPV 0.0694, 95% CI 0.0598, 0.0791). The model had excellent discrimination (c-statistic = 0.815) but was poorly calibrated, underestimating risk for patients who experienced the outcomes.

Conclusions: Epic’s ORS demonstrated excellent discrimination but very low sensitivity across three large integrated health systems. Health systems should exercise caution before implementing vendor risk prediction models without validating their use in their patient populations.

Related protocols: CTN-0095

Introduction:
Primary care patients with opioid use disorder (OUD) may receive treatment in primary care clinics or co-located specialty addiction treatment models. To help guide operational leaders in organizing OUD care delivery systems, we described rates of OUD medication treatment among primary care patients in PRimary care Opioid Use Disorders treatment (PROUD, CTN-0074) trial intervention clinics and four primary care clinics not in the trial because they already had OUD treatment programs in place (exemplar clinics).

Methods:
Primary care patients seen at six PROUD trial intervention clinics that implemented the Massachusetts model of office-based addiction treatment (PROUD clinics) and four exemplar clinics (two co-located specialty models; two primary care models with universal prescribing, in which all primary care providers were expected to treat OUD) were compared. Primary outcomes were person-years (PY) of medication treatment for OUD with buprenorphine or extended-release naltrexone during follow up (3/2018–2/2020) and changes from baseline (3/2016–2/2018).

Results:
Baseline primary care samples included 109,196 patients in PROUD clinics and 101,631 patients in exemplar clinics. Baseline OUD treatment rates varied across exemplar clinics (range: 10.9 to 328.7 PY per 10,000 primary care patients) but were higher than in PROUD clinics at baseline (3.9 PY per 10,000), with exemplar clinics with primary care models (established 2005 and 2017) providing the highest treatment rates to their primary care patients. During follow-up, PROUD clinics nearly tripled treatment, to 14.4 PY per 10,000, whereas most exemplar clinics increased treatment by less than 10% but still had higher treatment rates (range: 12.0 to 359.4 PY per 10,000).

Conclusions:
Primary care OUD treatment rates varied markedly. Exemplar clinics in which all primary care providers were expected to treat OUD had the highest treatment rates at baseline and follow-up, suggesting that universal prescribing is a promising approach to increasing OUD treatment in primary care.

Related protocols: CTN-0074

This cohort study, partially supported by the CTN Greater Intermountain Node, evaluates changes in prescribing of buprenorphine treatment for opioid use disorder at primary care, mental health, and pain clinics and substance use disorder clinics in Stepped Care for Opioid Use Disorder Train the Trainer (SCOUTT) and non-SCOUTT facilities.

This is the primary outcomes article for CTN-0095.

Nearly 727,000 individuals in the US died of opioid overdoses between 1999 and 2022. The current workforce of addiction medicine specialists is inadequate to address the scale of this crisis, and primary care clinicians (PCCs) do not feel sufficiently supported to treat opioid use disorder (OUD).

Objective: To evaluate whether an electronic health record–integrated clinical decision support system (CDSS) increases OUD diagnosis and treatment in primary care.

Design, Setting, and Participants: This pragmatic cluster randomized clinical trial was conducted from April 2021 to December 2023. Primary care clinics in 3 health systems in 4 US states were randomized to receive or not receive an electronic health record–integrated CDSS aimed at improving OUD diagnosis and treatment. Eligible patients were aged 18 to 75 years, visited a randomized clinic, and had an OUD diagnosis in the last 2 years, opioid overdose in the last 6 months, or risk score indicating high risk of OUD or opioid overdose. Data were analyzed from September 2023 to October 2024.

Interventions: The OUD CDSS provided personalized treatment recommendations to patients and PCCs in intervention clinics.

Main Outcomes and Measures: Primary outcomes were likelihood to receive (1) an OUD diagnosis (among high-risk patients without a baseline OUD diagnosis), (2) a naloxone prescription, or (3) a prescription of a medication for OUD (MOUD) or specialty referral, all within 30 days of first eligible (index) visit, and (4) days covered by a MOUD prescription in the 90 days after index.

Results: Among 10,891 patients meeting eligibility criteria, 5918 (54.3%) were female, and the mean (SD) age was 48.0 (13.9) years. There was no difference in OUD diagnoses within 30 days between groups. Patients in the intervention group had more naloxone orders (80 of 5538 [1.4%] vs 40 of 5353 [0.7%]; odds ratio, 1.76; 95% CI, 1.14-2.72) and orders for MOUDs or treatment referral (775 of 5538 [14.0%] vs 503 of 5353 [9.4%]; odds ratio, 1.48; 95% CI, 1.05-2.08) within 30 days. There were no differences in median (IQR) days covered by MOUD over 90 days postindex between intervention (84 [55-90] days) and usual care (83 [55-90] days; rate ratio, 1.00; 95% CI, 0.93-1.08) or in overdose or death rates during the intervention period.

Conclusions and Relevance: In this cluster randomized clinical trial, the intervention improved rates of naloxone orders and OUD treatment in primary care but did not affect days covered by a MOUD over 90 days postindex or overdose or death rates. These findings demonstrate an OUD CDSS can help increase access to OUD treatment in primary care.

Related protocols: CTN-0095

Background: A majority of the 8.9 million Americans with opioid misuse have mild or no symptoms of opioid use disorder (OUD), but they may be at elevated risk of developing more severe OUD, overdose, or other health consequences of opioid use. The “Subthreshold Opioid Use Disorder Prevention”(STOP) Trial is evaluating a collaborative care intervention for risky opioid use in primary care. Here, we describe baseline characteristics of participants to understand their needs and assess the generalizability of the sample.

Methods: Recruitment at five primary care sites spanned March 2021-May 2023. Adult patients who screened positive for subthreshold OUD (current illicit or non-medical opioid use without meeting DSM-5 criteria for moderate-severe OUD) were eligible. Baseline assessments measured self-reported demographic characteristics, other substance use, pain, and physical and mental health symptoms. Descriptive statistics summarize characteristics of the enrolled sample across sites.

Results: Among the 202 participants, the majority identified as female (63.4%), white (70.8%), and non-Hispanic (96.5%), with mean age 55.7 (SD: 12.7) years. Nearly half (49.0%) had problem or high-risk use of prescription opioids, and most received a prescription for opioid medication in the past six months (74.8%). Many participants reported current problem use or high-risk use of alcohol (47.0%) or cannabis (31.2%). Approximately one-third endorsed mental health symptoms, including moderate-severe anxiety (35.6%), depression (31.2%), or sleep disturbance (29.7%), and 20.3% reported a past suicide attempt. In the prior six months, 14.7% had experienced a nonfatal overdose. Moderate-severe pain was reported by 63.4%, and 60.4% rated their general health as fair or poor.

Conclusions: Patients with subthreshold OUD had high rates of polysubstance use and comorbidities that may present challenges to reducing risky opioid use. The STOP trial presents an opportunity to detect and address subthreshold OUD in a cohort with considerable medical and social needs, within primary care settings.

Related protocols: CTN-0101

While approximately one in five Americans with substance use disorder (SUD) receives treatment in addiction treatment programs, a majority have seen a primary care medical provider in the past year. Recognizing the critical role of primary care in addressing prevention and treatment of unhealthy substance use, for over a decade the National Drug Abuse Treatment Clinical Trials Network (CTN) has supported research to build the tools and evidence needed to support the integration of SUD care, while remaining realistic about the barriers to doing so. Authored by primary care and addiction medicine physician researchers, this commentary provides an overview of CTN primary care-focused research, from developing and implementing substance use screening tools to advancing evidence-based SUD treatment delivery in primary care settings. We identify three priority areas for research and practice innovations: 1) identifying effective treatment interventions to address polysubstance use; 2) improved screening and treatment for cannabis use; and 3) building the evidence base for substance use interventions among non-treatment seeking patients who have unhealthy drug use identified through screening. Addressing these areas can help primary care fulfill its potential as a key component of the substance use services continuum of care.

Introduction: Understanding conditions in which interventions succeed or fail is critical. The PRimary care Opioid Use Disorders treatment (PROUD) trial, a cluster-randomized hybrid study, tested whether implementation of office-based addiction treatment supported by a nurse increased medication of OUD. Six health systems each provided two primary care (PC) clinics that were randomly assigned to implement the intervention or usual care. This secondary, exploratory study used an innovative mixed methods approach to understand contextual factors that consistently distinguished intervention clinics that increased OUD treatment from those that did not.

Methods: The study collected contextual information through field notes, health system debriefs, and nurse interviews. Rapid qualitative analysis using a template based on the Practical, Robust Implementation and Sustainability Model identified themes reflecting the external environment, recipients, and implementation infrastructure. The study used qualitative themes to create binary factors reflecting barriers and facilitators potentially critical to implementation success and assigned clinics a factor value of 1 if present and 0 if absent. Two clinic-level outcomes were defined: 1) significant increase in patient-years of OUD treatment from baseline to two-year follow-up; and 2) high rate of OUD treatment at two-year follow-up (=20 per 10,000 patient-years). Coincidence analysis, a cross-case configurational method, identified difference-makers for both OUD outcomes across intervention clinics.

Results: Qualitative analysis yielded 11 themes which were dichotomized and consolidated into 9 factors. Two factor values perfectly distinguished between intervention clinics with and without increased OUD treatment (outcome #1): (a) presence of strong support from PC staff and providers and (b) lack of OUD treatment in the community. Intervention clinics increased OUD treatment when either factor value was present; when both were absent, clinics did not increase treatment. Strong support from PC staff and providers was independently sufficient to achieve high rates of OUD treatment (outcome #2) while the absence of support explained low rates of treatment. Importantly, strong support from leadership was not sufficient for either outcome.

Conclusions: Strong support from staff and providers consistently differentiated between clinics with increased OUD treatment across both outcomes in the PROUD trial from those without. OUD programs should consider increasing support across clinic roles.

Related protocols: CTN-0074

Background: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.

Objective: Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.

Participants: Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019-9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.

Main measures: We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.

Key results: Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3-19.2%) and 0.9% (0.0-2.7%) for < monthly to 44.6% (41.4-47.7%) and 20.3% (17.8-22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.

Conclusions: Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.

Related protocols: CTN-0077-Ot

Rural primary care clinics can expand their medication treatment for opioid use disorder (MOUD) capacity by coordinating care with external telemedicine (TM) vendors specializing in addiction medicine. This study used mixed methods to identify factors that influence patient referrals from rural primary care clinics to TM vendors for MOUD.

Between July/August 2020 and January/February 2021, 582 patients with OUD were identified across six primary care sites; that included 68 referred to an external TM vendor to receive MOUD. Mixed effects logistic regression identified individual and site-level factors associated with being referred to the TM vendor. Clinic providers and staff participated in in-depth interviews and focus groups to discuss their considerations for referring patients to the TM vendor.

Patient referrals were positively associated with local household broadband coverage (OR=2.55, p<0.001) and negatively associated with local population density (OR=0.01, p=0.003) and the number of buprenorphine prescribers in the county (OR=0.85, p<0.001). Clinic personnel expressed appreciation for psychiatric expertise and the flexibility to access MOUD brought by the TM vendor. Perceived concerns about TM referral included a lack of trust with external providers, uncertainty about TM service quality, workflow delays, and patients’ technological and insurance challenges.

Conclusions: This study revealed several clinic-level factors that may potentially influence patient referral to TM vendor services for MOUD. To facilitate the referral process and utilization of TM vendors, efforts should be made to foster open communication and trust between clinic providers and TM vendors, streamline workflows, and improve Internet access for patients.

Related protocols: CTN-0102

Importance: The Primary Care Opioid Use Disorders (PROUD) treatment trial was a 2-year implementation trial that demonstrated the Massachusetts office-based addiction treatment (OBAT) model of nurse care management for opioid use disorder (OUD) increased OUD treatment in the 2 years after implementation began (8.2 more patient-years of OUD treatment per 10 000 primary care patients). The intervention was continued for a third year, permitting evaluation of 3-year outcomes.

Objective: To compare OUD medication treatment in intervention and usual care clinics over 3 years of implementation.

Design, setting, and participants: This is a preplanned secondary analysis of a cluster randomized implementation trial, conducted in 6 health systems in 5 states (2 primary care clinics per health system) with clinic randomization stratified by system (assignment notification February 28, 2018 [August 31, 2018, in 1 system]). Data were obtained from electronic health records and insurance claims. Eligible patients were those aged 16 to 90 years visiting intervention or usual care clinics from 3 years before to 2 years after randomization. Patients new to clinics during the third year after randomization could not be included because COVID-19-era transitions to virtual care precluded assignment of patients to clinics. Data analysis occurred from November 2023 to September 2024.

Intervention: Clinics were randomized to intervention or care as usual. Intervention included 3 implementation components: salary for 1 full-time OBAT nurse per intervention clinic; training and ongoing technical assistance for nurses; and 3 or more primary care buprenorphine prescribers.

Main outcome and measures: Patient-years of OUD treatment (buprenorphine or extended-release naltrexone) per 10,000 primary care patients in the 3 years postrandomization. Mixed-effect models adjusted for baseline values of the outcome and included a health system-specific random intercept to account for correlation of clinic pairs within a system.

Results: Prerandomization, a total of 290,071 primary care patients were seen, including 130,618 in intervention clinics (mean [SD] age, 48.6 [17.7] years; mean [SD] female, 59.3% [4.0%]) and 159 453 in usual care clinics (mean [SD] age, 47.2 [17.5] years; mean [SD] female, 64.0% [5.3%]). Over 3 years postrandomization, intervention clinics provided 19.7 (95% CI, 11.1-28.4) more patient-years of OUD treatment per 10 000 primary care patients compared with usual care clinics.

Conclusions: In this secondary analysis of the PROUD cluster randomized trial, after an added year of the intervention, OUD treatment continued to increase in intervention clinics compared with usual care. The treatment increase over 3 years exceeded that of the first 2 years, suggesting that implementation of the Massachusetts OBAT model leads to ongoing increases in OUD treatment among primary care patients in the third year of implementation.

Related protocols: CTN-0074