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Iscoe MS, Diniz Hooper C, Levy DR, Buchanan L, Dziura J, Meeker D, Taylor RA, D'Onofrio G, Oladele C, Sarpong DF, Paek H, Wilson FP, Heagerty PJ, Delgado MK, Hoppe J, Melnick ER. Adaptive decision support for addiction treatment to implement initiation of buprenorphine for opioid use disorder in the emergency department: protocol for the ADAPT Multiphase Optimization Strategy trial. BMJ Open 2025; 15:e098072. [PMID: 39979056 DOI: 10.1136/bmjopen-2024-098072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2025] Open
Abstract
INTRODUCTION Despite the current opioid crisis resulting in tens of thousands of deaths every year, buprenorphine, a medication that can reduce opioid-related mortality, withdrawal, drug use and craving, is still underprescribed in the emergency department (ED) for treatment of opioid use disorder (OUD). The EMergency department-initiated BuprenorphinE for opioid use Disorder (EMBED) trial introduced a clinical decision support (CDS) tool that improved the proportion of ED physicians prescribing buprenorphine but did not affect patient-level rates of buprenorphine initiation. The present trial aims to build on these findings by optimising CDS use through iterative improvements, refined interventions and clinician feedback to enhance OUD treatment initiation in EDs. METHODS AND ANALYSIS The Adaptive Decision support for Addiction Treatment (ADAPT) trial employs the Multiphase Optimization Strategy (MOST) framework to refine a multicomponent CDS tool designed to facilitate buprenorphine initiation for OUD in ED settings. Using a pragmatic, learning health system approach in three phases, the trial applies plan-do-study-act cycles for continuous CDS refinement. The CDS will be updated in the preparation phase to reflect new evidence. The optimisation phase will include a 2×2×2 factorial trial, testing the impact of various intervention components, followed by rapid, serial randomised usability testing to reduce user errors and enhance CDS workflow efficiency. In the evaluation phase, the optimised CDS package will be tested in a randomised trial to assess its effectiveness in increasing ED initiation of buprenorphine compared with the original EMBED CDS. ETHICS AND DISSEMINATION The protocol has received approval from our institution's institutional review board (protocol #2000038624) with a waiver of informed consent for collecting non-identifiable information only. Given the minimal risk involved in implementing established best practices, an independent study monitor will oversee the study instead of a Data Safety Monitoring Board. Findings will be submitted to ClinicalTrials.gov, published in open-access, peer-reviewed journals, presented at national conferences and shared with clinicians at participating sites through email notification. TRIAL REGISTRATION NUMBER NCT06799117.
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Affiliation(s)
- Mark S Iscoe
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Carolina Diniz Hooper
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Deborah R Levy
- Department of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Veterans Affairs, VA Connecticut Healthcare System-West Haven Campus, West Haven, Connecticut, USA
| | - Laurel Buchanan
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - James Dziura
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Yale University School of Public Health, New Haven, Connecticut, USA
| | - Daniella Meeker
- Department of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Richard Andrew Taylor
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Gail D'Onofrio
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Yale University School of Public Health, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Carol Oladele
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Equity Research and Innovation Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Daniel F Sarpong
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Equity Research and Innovation Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Hyung Paek
- Digital & Technology Solutions, Yale New-Haven Health, New Haven, Connecticut, USA
| | - Francis P Wilson
- Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut, USA
- Section of Nephrology, Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Patrick J Heagerty
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Mucio Kit Delgado
- Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jason Hoppe
- Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Edward R Melnick
- Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, USA
- Yale University School of Public Health, New Haven, Connecticut, USA
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Heerman WJ, Perrin EM, Yin HS, Schildcrout JS, Delamater AM, Flower KB, Sanders L, Wood C, Kay MC, Adams LE, Rothman RL. The Greenlight Plus Trial: Comparative effectiveness of a health information technology intervention vs. health communication intervention in primary care offices to prevent childhood obesity. Contemp Clin Trials 2022; 123:106987. [PMID: 36323344 DOI: 10.1016/j.cct.2022.106987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 10/17/2022] [Accepted: 10/26/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND The first 1000 days of a child's life are increasingly recognized as a critical window for establishing a healthy growth trajectory to prevent childhood obesity and its associated long-term comorbidities. The purpose of this manuscript is to detail the methods for a multi-site, comparative effectiveness trial designed to prevent childhood overweight and obesity from birth to age 2 years. METHODS This study is a multi-site, individually randomized trial testing the comparative effectiveness of two active intervention arms: 1) the Greenlight intervention; and 2) the Greenlight Plus intervention. The Greenlight intervention is administered by trained pediatric healthcare providers at each well-child visit from 0 to 18 months and consists of a low health literacy toolkit used during clinic visits to promote shared goal setting. Families randomized to Greenlight Plus receive the Greenlight intervention plus a health information technology intervention, which includes: 1) personalized, automated text-messages that facilitate caregiver self-monitoring of tailored and age-appropriate child heath behavior goals; and 2) a web-based, personalized dashboard that tracks child weight status, progress on goals, and electronic Greenlight content access. We randomized 900 parent-infant dyads, recruited from primary care clinics across six academic medical centers. The study's primary outcome is weight for length trajectory from birth through 24 months. CONCLUSIONS By delivering a personalized and tailored health information technology intervention that is asynchronous to pediatric primary care visits, we aim to achieve improvements in child growth trajectory through two years of age among a sample of geographically, socioeconomically, racially, and ethnically diverse parent-child dyads.
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Affiliation(s)
- William J Heerman
- Vanderbilt University Medical Center, Department of Pediatrics, 2200 Children's Way, Suite 2404, Nashville, TN 37232, United States of America.
| | - Eliana M Perrin
- Johns Hopkins University, Department of Pediatrics, Schools of Medicine and Nursing, 200 N. Wolfe St, Rubenstein Building-2071, Baltimore, MD 21287, United States of America.
| | - H Shonna Yin
- New York University School of Medicine, Departments of Pediatrics and Population Health, 550 First Avenue, New York, NY 10016, United States of America.
| | - Jonathan S Schildcrout
- Vanderbilt University Medical Center, Department of Biostatistics, 1161 21st Ave S # D3300, Nashville, TN 37232, United States of America.
| | - Alan M Delamater
- University of Miami Miller School of Medicine, Department of Pediatrics, 1601 NW 12(th) Ave., Miami, FL 33136, United States of America.
| | - Kori B Flower
- University of North Carolina at Chapel Hill, Division of General Pediatrics and Adolescent Medicine, 231 MacNider Building, CB# 7225, 321 S. Columbia Street, UNC School of Medicine, Chapel Hill, NC 27599-7225, United States of America.
| | - Lee Sanders
- Stanford University School of Medicine, United States of America.
| | - Charles Wood
- Duke University School of Medicine, Department of Pediatrics, Division of General Pediatrics and Adolescent Health, 3116 N. Duke St., Durham, NC 27704, United States of America.
| | - Melissa C Kay
- Duke University School of Medicine, Department of Pediatrics, Division of General Pediatrics and Adolescent Health, 3116 N. Duke St., Durham, NC 27704, United States of America.
| | - Laura E Adams
- Vanderbilt University Medical Center, Department of Pediatrics, 2200 Children's Way, Suite 2404, Nashville, TN 37232, United States of America.
| | - Russell L Rothman
- Vanderbilt University Medical Center, Institute of Medicine and Public Health, 1161 21st Ave S # D3300, Nashville, TN 37232, United States of America.
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