# ADAPT: Adaptive Decision support for Addiction Treatment

> **NIH NIH R33** · YALE UNIVERSITY · 2024 · $1,214,921

## Abstract

Project Summary
The opioid crisis is dynamic. To overcome barriers to addiction treatment, implementation research must keep
pace with the changing landscape of the opioid crisis by more rapidly adapting to emerging evidence. Clinical
decision support (CDS) offers a promising implementation strategy to more efficiently operationalize and scale
evidence-based practices. Patients are motivated to initiate addiction treatment after sentinel events, such as
an emergency department (ED) visit for opioid overdose. Unfortunately, clinicians rarely initiate addiction
treatment. To that end, we recently conducted the EMBED pragmatic cluster-randomized trial. This trial
evaluated the effectiveness of non-interruptive electronic health record (EHR)-based CDS to facilitate patient
assessment and automate EHR activities to implement ED-initiation of buprenorphine in the routine care of
people with opioid use disorder (OUD). The EMBED CDS increased the proportion of physicians who initiated
buprenorphine leading to national dissemination of EMBED. Post-trial analysis identified disparities in
treatment as well as opportunities to increase reach and adoption. However, CDS interventions typically
remain unchanged while being studied and traditional methods for evaluation are time-consuming, resulting in
missed opportunities for progress and delays in implementing effective interventions. These limitations must be
addressed to speed the implementation of evidence-based solutions to the opioid crisis in general and the the
nationally scaled EMBED CDS specifically. The EHR can both deliver CDS interventions and offer a non-
obtrusive, rigorous way to study care delivery at scale utilizing EHR use measurement with automated log data
capture. Current quantitative CDS use and usability metrics are limited to alert dismissal rates and descriptive
measures of CDS characteristics but are not capable of evaluating CDS interfaces and workflows such as
granular assessment of CDS uptake and usability. Therefore, we will adapt CDS of best practices in the care of
people with OUD using a Multiphase Optimization STrategy (MOST) framework including rapid, serial
randomized testing, measured by scalable, pragmatic EHR use metrics to achieve the following specific aims:
(1) Refine and validate reproducible, scalable outcome measures for assessing CDS uptake and usability to
implement ED-initiation of buprenorphine for OUD and (2) Refine and evaluate a multicomponent CDS
intervention to improve ED-initiation of buprenorphine in patients with OUD via increased CDS uptake,
usability, and equity. Achievement of these specific aims will offer a pathway to scalable, equitable
interventions for the opioid crisis by innovating data-driven, adaptive approaches that increase treatment
access and engagement for people with OUD. With expertise in emergency medicine, addiction medicine,
clinical decision support, pragmatic evaluation, biostatistics, health equity, and data, measurement, and
im...

## Key facts

- **NIH application ID:** 10932975
- **Project number:** 5R33DA059884-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Edward Robert Melnick
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,214,921
- **Award type:** 5
- **Project period:** 2023-09-30 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10932975

## Citation

> US National Institutes of Health, RePORTER application 10932975, ADAPT: Adaptive Decision support for Addiction Treatment (5R33DA059884-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10932975. Licensed CC0.

---

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