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Abstract: 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.  

Abstract:

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

Abstract:

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

Abstract:

Background: The National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) has supported clinical trials of substance use disorder (SUD) interventions for 25 years. This review describes the use of implementation outcomes across CTN trials, characterizes outcomes included, and identifies gaps and potential opportunities to strengthen implementation research within the CTN and the field of SUD treatment.

Methods: This systematic review included active or completed studies listed on the CTN Dissemination Library webpage as of August 18, 2021, and approved by the CTN for development by January 1, 2022. Study summaries and protocols were reviewed if they: 1) measured at least one implementation outcome and 2) examined a practice change, intervention, or process. Extracted data elements included trial design characteristics, implementation frameworks, and outcome assessment domains informed by the RE-AIM and Proctor Implementation Outcomes Frameworks.

Results: 114 protocols were considered, 42 full-text protocols were screened, and 25 were included for data extraction. Start dates of trials spanned a 20-year period (2004–2024) with latter studies including more implementation outcomes. Fidelity (n = 29) and reach/penetration (n = 26) were the most included implementation outcomes. Equity was not identified in any protocols. Methods of defining, capturing, and evaluating outcomes data varied across trials and outcomes.

Conclusions: The inclusion of implementation outcomes increased over time, perhaps reflecting a growing emphasis on implementation research. Incorporating measures of equity could advance knowledge about differential receipt or effectiveness of SUD interventions. Future research should seek to improve the consistency and comprehensiveness in descriptions of implementation science elements.

Related protocols: CTN-0016, CTN-0056, CTN-0062-Ot, CTN-0064, CTN-0065, CTN-0069, CTN-0074, CTN-0074-A-1, CTN-0075, CTN-0076-Ot, CTN-0079, CTN-0079-A-1, CTN-0088, CTN-0090, CTN-0091, CTN-0095, CTN-0096, CTN-0097, CTN-0098, CTN-0099, CTN-0102, CTN-0103, CTN-0107, CTN-0116, CTN-0121

Abstract:

This presentation featured the work of CTN-0095: Clinic-Randomized Trial of Clinical Decision Support for Opioid Use Disorders in Medical Settings. Drs. Rebecca Rossom, Stephanie Hooker, and Gavin Bart shared their study approach, key findings, and lessons learned from implementing this pragmatic trial.

Abstract:

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

Abstract:

Opioid-related deaths continue to rise in the U.S. A shared decision-making (SDM) system to help primary care clinicians (PCCs) identify and treat patients with opioid use disorder (OUD) could help address this crisis.

In this cluster-randomized trial (CTN-0095, COMPUTE 2.0), primary care clinics in three healthcare systems were randomized to receive or not receive access to an OUD-SDM system. The OUD-SDM system alerts PCCs and patients to elevated risk of OUD and supports OUD screening and treatment. It includes guidance on OUD screening and diagnosis, treatment selection, starting and maintaining patients on buprenorphine for waivered clinicians, and screening for common comorbid conditions. The primary study outcome is, of patients at high risk for OUD, the percentage receiving an OUD diagnosis within 30 days of index visit. Additional outcomes are, of patients at high risk for or with a diagnosis of OUD, (a) the percentage receiving a naloxone prescription, or (b) the percentage receiving a medication for OUD (MOUD) prescription or referral to specialty care within 30 days of an index visit, and (c) total days covered by a MOUD prescription within 90 days of an index visit.

The intervention started in April 2021 and continues through December 2023. PCCs and patients in 90 clinics are included; study results are expected in 2024.

Conclusion: This protocol paper describes the design of a multi-site trial to help PCCs recognize and treat OUD. If effective, this OUD-SDM intervention could improve screening of at-risk patients and rates of OUD treatment for people with OUD.

Related protocols: CTN-0095

Abstract:

Both patients and clinicians have described discussions of potential opioid risks as challenging. This study, part of CTN-0095, “Clinic-Randomized Trial of Clinical Decision Support for Opioid Use Disorders in Medical Settings,” aimed was to understand patient perspectives on discussing opioid risks with primary care clinicians (PCCs).

Patients identified to be at elevated risk for problems with opioids (i.e., opioid use disorder [OUD] diagnosis, taking a medication for OUD, or having = 3 opioid prescriptions in the last year) were recruited from an integrated, Upper Midwest health system to participate in semi-structured qualitative interviews. Interview questions aimed to better understand patient views on conversations about opioid risks with PCCs and perceptions of OUD screening and treatment in primary care. Interviews were analyzed using an inductive thematic analysis approach.

A total of 20 patients participated (mean age: 53.5 years; 65% male). Six themes emerged: 1) archetypes of patient relationships with opioids (long-term opioid use, acute opioid use, OUD in treatment, OUD no treatment) require different approaches in discussing opioid risks; 2) patients may develop their own archetypes about PCCs and opioids; 3) these archetypes may help guide how conversations about opioids are conducted (e.g., PCC demeanor, terminology); 4) most patients believe that primary care is an appropriate setting for opioid risk discussions; 5) patients may have limited awareness of the availability and value of overdose rescue medications; and 6) handouts are more acceptable if perceived to come from the PCC’s assessment instead of a computer.

Conclusions: Results suggest that patients generally perceive discussing opioid risks with PCCs acceptable. PCCs should tailor opioid risk conversations to patients’ specific situations and needs.

Related protocols: CTN-0095

Abstract:

Addressing the opioid epidemic would benefit from primary care clinicians identifying and managing opioid use disorder (OUD) during routine clinical encounters, but current rates are low. Clinical decision support (CDS) systems are a promising way to facilitate such interactions, but will clinicians use them?

For this study, related to CTN-0095 (COMPUTE 2.0), researchers iteratively conducted semi-structured interviews with 8 purposively sampled primary care clinicians participating in a pilot OUD-CDS study to identify attitudes toward discussing OUD and preferences for support in doing so. Five of them had used a pilot version of the CDS for 6 months, while the others were in comparison clinics. Interviews were recorded, transcribed, and analyzed by a multi-disciplinary group of experienced researchers, using an editing organizing style where the analysts independently highlighted relevant text and then discussed to reach a consensus on themes.

Five themes were identified: 1. Primary care is the right place to address OUD. 2. Both clinician-patient and clinician-clinician relationships affect how and whether clinicians address OUD in a particular patient encounter. 3. The main challenges are limited time and competing priorities for these complex patients. 4. Although a CDS for OUD could be very helpful, it must meet different needs for different clinicians and clinical situations and be simple to use. 5. For optimal benefit, the CDS needs to be complemented by supportive organizational policies and systems as well as local clinician encouragement.

Conclusions: With the right design and a supportive organization, these primary care clinicians believe a CDS could help them regularly identify and address OUD among their patients as long as it incorporates their concerns about relationships, competing priorities, patient complexity, and user simplicity.

Related protocols: CTN-0095

Abstract:

The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research that leverages digital technologies to glean new insights into SUDs and provide science-based therapeutic tools to a diverse array of persons with SUDs.

This article provides an overview of the breadth and impact of research conducted in the realm of digital health within the CTN. This work has included the CTN’s efforts to systematically embed digital screeners for SUDs into general medical settings to impact care models across the nation. This work has also included a pivotal multi-site clinical trial conducted on the CTN platform, whose data led to the very first “prescription digital therapeutic” authorized by the U.S. Food and Drug Administration (FDA) for the treatment of SUDs. Further CTN research includes the study of telehealth to increase capacity for science-based SUD treatment in rural and under-resourced communities. In addition, the CTN has supported an assessment of the feasibility of detecting cocaine-taking behavior via smartwatch sensing. And, the CTN has supported the conduct of clinical trials entirely online (including the recruitment of national and hard-to-reach/under-served participant samples online, with remote intervention delivery and data collection). Further, the CTN is supporting innovative work focused on the use of digital health technologies and data analytics to identify digital biomarkers and understand the clinical trajectories of individuals receiving medications for opioid use disorder (OUD).

This paper concludes by outlining the many potential future opportunities to leverage the unique national CTN research network to scale-up the science on digital health to examine optimal strategies to increase the reach of science-based SUD service delivery models both within and outside of healthcare.

Related protocols: CTN-0044, CTN-0059, CTN-0073-Ot, CTN-0076, CTN-0083, CTN-0084-A-2, CTN-0090, CTN-0095, CTN-0101, CTN-0102