Project Summary/Abstract Buprenorphine is a life-saving treatment for people with opioid use disorder (OUD), yet only 1 in 5 people with OUD receive this medication. Telehealth-delivered buprenorphine (tele-buprenorphine) is one of the most promising interventions to increase treatment and retention, yet there is limited data on comparative effectiveness and no prior randomized controlled trials (RCTs) to support implementation. This dearth of evidence represents a major challenge for clinicians and policymakers when weighing questions around risks versus benefits and how to deploy telehealth to improve patient outcomes. In addition to overall effectiveness, there are additional real-world questions, including: 1) is tele-buprenorphine effective in potentially higher risk groups (e.g. using other substances), 2) can tele-buprenorphine address existing treatment disparities, and 3) in this new era where telehealth is an option alongside in-person visits, are hybrid approaches effective? Traditional RCTs would be impractical and take years to address the array of important clinical questions, and clinical and policy landscapes are evolving quickly. Emulated target trials are an innovative causal inference approach that use existing data to emulate RCTs by carefully pre-specifying aspects of the protocol, including: eligibility, treatment assignment, outcome and follow-up assessments, and analytic strategies. We will harness our team’s unique expertise in causal inference, telehealth and mixed methods research to systematically gather needed data to develop clinical guidance to optimize tele-buprenorphine care. Quantitative aims focus on emulated target trials using national Veterans Health Administration and Medicaid data across states, comprising the largest U.S. provider and payer for OUD services respectively, to compare effectiveness of telehealth to in-person care, in patients starting and continuing buprenorphine. We will first develop the target trial framework and apply this framework to analysis evaluating overall effectiveness of tele-buprenorphine on retention and other key outcomes. We will then apply this framework to address additional clinically relevant questions about effectiveness of tele-buprenorphine in high-risk groups and in groups experiencing OUD treatment disparities. We will also conduct qualitative interviews with buprenorphine patients and clinicians to obtain a nuanced understanding of experiences with telehealth compared to in- person care to explain, contextualize and extend the quantitative findings. Finally, we will summarize quantitative and qualitative findings, integrate with existing literature, and create joint displays that will be provided to patient and clinician experts who will engage in an adapted Delphi process to form consensus recommendations. Findings will be summarized and disseminated via publications and development of Consensus Guidance on tele-buprenorphine care for clinicians and policymakers. This project will have high public health impact by providing critical new insights on comparative effectiveness of tele-buprenorphine treatment in order to directly inform best practice and policies to improve real-world care for patients with OUD.

Project Narrative Telehealth is one of the most promising tools to help increase buprenorphine treatment for people with opioid use disorder (OUD), yet we know little about effectiveness of telehealth compared to traditional in- person care, which limits use and poses a major barrier to developing evidence-based policies and implementing high-quality care. The overall goal of this project is to generate clinical guidance to optimize buprenorphine care by evaluating effectiveness of telehealth-delivered buprenorphine, including for high-need and high-risk populations, using novel target trial methods, and incorporating stakeholder perspectives and expert consensus. This study will use national data from the Veterans Health Administration and Medicaid, encompassing the largest U.S. provider and payer for OUD services, and incorporate novel methods to systematically inform best practices for tele-buprenorphine care.