Date of Award
January 2022
Document Type
Thesis
Degree Name
Medical Doctor (MD)
Department
Medicine
First Advisor
Jeanette M. Tetrault
Abstract
AbstractBackground: Office-based opioid treatment (OBOT) is an evidence-based treatment model for opioid use disorder (OUD) offered by both addiction and general primary care providers (PCPs). Calls exist for more PCPs to offer OBOT. Few studies have been conducted on the primary care characteristics of OBOT patients. Objective: To characterize medical conditions, medications, and treatment outcomes among patients receiving office-based opioid treatment (OBOT) with buprenorphine for OUD, and to describe differences among patients by age and by time in care. Methods: This study is a retrospective review of medical records on or before 4/29/2019 at an outpatient primary care clinic within a non-profit addiction treatment setting. Inclusion criterion were all clinic patients actively enrolled in the OBOT program. Patients not prescribed buprenorphine or with no OBOT visits were excluded. Results: Of 355 patients, 42.0% had another primary care provider (PCP). Common comorbid conditions included chronic pain and psychiatric diagnosis. Few patients had chronic viral hepatitis or HIV. Patients reported a median of 4 medications. Common medications were cardiovascular, antidepressant, and non-opioid pain agents. Older patients had a higher median number of medications. There was no significant difference in positive opioid urine toxicology (UT) based on age, chronic pain status, or psychoactive medications. Patients retained >1 year were less likely to have positive opioid UT. Conclusion: Primary care needs of many patients receiving OBOT are similar to those of the general population, supporting calls for PCPs to provide OBOT.
Recommended Citation
Du, Xinxin, "Primary Care Characteristics And Medication Management Among Patients Receiving Office Based Opioid Treatment With Buprenorphine" (2022). Yale Medicine Thesis Digital Library. 4065.
https://elischolar.library.yale.edu/ymtdl/4065
Comments
This thesis is restricted to Yale network users only. It will be made publicly available on 06/29/2023