# Video observed therapy to enhance flexibility and reduce in-person visits for patients treated with methadone in a multi-site opioid treatment program

> **NIH NIH R44** · EMOCHA MOBILE HEALTH, INC. · 2024 · $659,386

## Abstract

PROJECT SUMMARY
The COVID-19 pandemic intersecting with the opioid epidemic led to dramatic shifts in the delivery of care for
opioid use disorders (OUD). Historically, methadone has been provided as directly-observed therapy (DOT) at
opioid treatment programs (OTPs). This model of care delivery has been a barrier to accessing care due to
imposed travel burden and disruption to work and family responsibilities for clients. To minimize infectious
risks, on March 16, 2020 the Substance Abuse and Mental Health Services Administration issued a blanket
exception to OTPs allowing for 28 day supplies of take-home medications for all “stable” clients, and up to
14-day supplies for clients who are “less stable”. These changes created an opportunity to innovate
methadone care delivery models to allow more flexibility and client-centeredness by requiring fewer in-person
visits. Yet, less frequent DOT could lead to increased risk for diversion and medication toxicity. An ideal model
would optimize both flexibility and safety. Our prior Phase I research demonstrated the feasibility of an
innovative mobile health platform to provide asynchronous, video DOT and to screen for symptoms of
COVID-19 for patients treated for OUD with methadone. We propose to extend our prior research by scaling
the intervention (video-DOT) across a large, multisite OTP organization via a Hybrid Type 2
Effectiveness-Implementation study with stepped wedge cluster randomized trial design in which we will
simultaneously test implementation and clinical outcomes. Our Aim 1: Conduct a stepped wedge randomized
trial to evaluate the impact of asynchronous video-DOT on verification of methadone dosing, increased
take-homes, and other treatment outcomes. Three clinics within a single, large OTP organization will be
randomly assigned to calendar time for implementation of video-DOT. Clinical outcomes will be assessed
pragmatically via electronic health records (pre- and post-implementation) and via the smartphone application
to examine if implementation of video-DOT is associated with primary outcomes of (1) increases in the
proportion of methadone doses that are observed (remote or in-person) and (2) increased take-homes, and
secondary outcomes of (3) reduced in-person OTP visits, (4) increased medication coverage, and (5)
increased 90-day treatment retention. Our Aim 2: Conduct a formative evaluation to: a) understand barriers
and facilitators to implementation of video-DOT at each clinic, b) understand perspectives on and
acceptability/feasibility of video-DOT among key stakeholders, and c) develop best practices to support optimal
scalability of video-DOT. We will conduct qualitative interviews with medical providers, counselors, dispensary
nurses, clinical leaders, and clients to understand (1) barriers/facilitators to implementing VDOT, (2)
opportunities to improve video-DOT and future implementations, and (3) perspectives regarding clients and
circumstances for which video-DOT is usefu...

## Key facts

- **NIH application ID:** 10897038
- **Project number:** 5R44DA053081-03
- **Recipient organization:** EMOCHA MOBILE HEALTH, INC.
- **Principal Investigator:** Kevin A. Hallgren
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $659,386
- **Award type:** 5
- **Project period:** 2020-09-30 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10897038

## Citation

> US National Institutes of Health, RePORTER application 10897038, Video observed therapy to enhance flexibility and reduce in-person visits for patients treated with methadone in a multi-site opioid treatment program (5R44DA053081-03). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10897038. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*