Research and Policy Repository

  • Author: Corey J. Hayes
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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 …

Physical Health Peer reviewed

Medications for opioid use disorder: Predictors of early discontinuation and reduction of overdose risk in US military Veterans by medication type

Abstract: Aim: This study: (1) estimated the effect of early discontinuation of medication for opioid use disorder (MOUD) on overdose probability and (2) measured the relationship …

Physical Health Peer reviewed

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 …

Physical Health Peer reviewed

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 …

Mental Health Peer reviewed

Systemic lupus erythematosus initially presenting as acute motor and sensory axonal neuropathy variant of Guillain-Barre syndrome in a healthy active duty female

Abstract: Guillain-Barre syndrome (GBS) is an acute monophasic immune-mediated polyradiculoneuropathy characterized by rapidly evolving ascending weakness, mild sensory loss, and …

Physical Health Peer reviewed