• Author: Teresa J. Hudson
Clear all

Development and validation of machine-learning algorithms predicting retention, overdoses, and all-cause mortality among US military Veterans treated with buprenorphine for opioid use disorder

Abstract: Aim: The aim of this study was to develop and validate machine-learning algorithms predicting retention, overdoses, and all-cause mortality among US military veterans …

Are gaps in rates of retention on buprenorphine for treatment of opioid use disorder closing among Veterans across different races and ethnicities? A retrospective cohort study

Abstract: Introduction: The U.S. Veterans Health Administration has undertaken several initiatives to improve veterans' access to and retention on buprenorphine because it prevents …

Development and validation of machine-learning algorithms predicting retention, overdoses, and all-cause mortality among U.S. military Veterans treated with buprenorphine for opioid use disorder

Abstract: Background: Buprenorphine for opioid use disorder (B-MOUD) is essential to improving patient outcomes; however, retention is essential. Objective: To develop and validate …

Telemedicine-Based Collaborative Care for Posttraumatic Stress Disorder A Randomized Clinical Trial

Abstract: Importance: Posttraumaticstressdisorder (PTSD)is prevalent, persistent, and disabling. Although psychotherapyandpharmacotherapyhaveprovenefficaciousinrandomized clinical …

Veterans Self-Reported Reasons for Non-Attendance in Psychotherapy for Posttraumatic Stress Disorder

Abstract: This study explored rates of non-attendance (i.e., non-initiation, inconsistent attendance, early discontinuation) in cognitive processing therapy (CPT) and other …