Literature Collection

INTRODUCTION: Patients with opioid use disorder (OUD) have a heightened need for quality health care, including access to evidence-based medications to reduce cravings and prevent overdose. However, primary care providers (PCPs) are reluctant to work with patients with OUD and implement medication prescribing into primary care practice. Previous studies have sought to identify potential ways to overcome these barriers, but often utilize interventions that facilitate both positive contact with as well as empathy for patients with OUD. In this study, we jointly assess positive contact and empathy to determine their unique impact on treatment attitudes and behaviors among PCPs, after controlling for other known predictors. METHODS: We surveyed 409 PCPs currently practicing in Ohio in 2022. Our primary dependent variables were willingness to work with patients with OUD, receipt of an X-waiver to prescribe buprenorphine, and interest in receiving an X-waiver. Our primary independent variables were positive contact and empathy toward patients with OUD. We computed bivariate correlations and multivariable linear regression (for continuous dependent variables) and logistic regression (for binary dependent variables) to understand the relationship between positive contact, empathy, and our outcome variables while accounting for other known predictors and relevant participant demographics. RESULTS: Positive contact was positively correlated with willingness to work with patients with OUD, receipt of the X-waiver, an interest in receiving the X-waiver, more frequent checking with patients about the need for naloxone, and higher odds of naloxone prescribing. These relationships held after accounting for PCP demographics, explicit bias toward patients with OUD, and overall levels of contact with patients with OUD. Empathy, conversely, was not a significant predictor of any treatment outcomes in the fully adjusted models. CONCLUSION: Interventions and medical education programs aimed at improving treatment outcomes for patients with OUD should facilitate positive contact between PCPs and patients with OUD.

The Practice Guidelines for the Administration of Buprenorphine for Treating Opioid Use Disorder provides eligible physicians, physician assistants, nurse practitioners, clinical nurse specialists, certified registered nurse anesthetists, and certified nurse midwives, who are state licensed and registered by the DEA to prescribe controlled substances, an exemption from certain statutory certification requirements related to training, counseling and other ancillary services (i.e., psychosocial services).

Medications such as buprenorphine-naloxone are among the most effective treatments for opioid use disorder, but limited retention in treatment limits long-term outcomes. In this study, we assess the feasibility of a machine learning model to predict retention vs. attrition in medication for opioid use disorder (MOUD) treatment using electronic medical record data including concepts extracted from clinical notes. A logistic regression classifier was trained on 374 MOUD treatments with 68% resulting in potential attrition. On a held-out test set of 157 events, the full model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% CI: 0.64-0.90) and AUROC of 0.74 (95% CI: 0.62-0.87) with a limited model using only structured EMR data. Risk prediction for opioid MOUD retention vs. attrition is feasible given electronic medical record data, even without necessarily incorporating concepts extracted from clinical notes.

OBJECTIVE:  Our objective was to examine the biomedical and sociodemographic factors associated with the prescription of naloxone among pregnant people with opioid-use disorder (OUD) who were admitted for initiation of medications for OUD (i.e., buprenorphine-containing medications or methadone) following the implementation of a statewide initiative focused on reducing adverse perinatal health outcomes. STUDY DESIGN:  This is a single-site, retrospective cohort study of pregnant people admitted for the management of OUD at an urban, tertiary care center between 2013 and 2020. The primary outcome is evidence of a prescription of naloxone, ascertained from the electronic medical record. Bivariate and multivariable logistic regression modeling was performed to evaluate biomedical and sociodemographic variables associated with a prescription for naloxone. Covariates for inclusion in the multivariate logistic regression model were selected based on a p < 0.05 on bivariate analysis. Statistical significance was set at p < 0.05. RESULTS:  One hundred and thirty-nine participants met the inclusion criteria. On bivariate analysis, people who received naloxone were more likely to be admitted after the initiation of a statewide initiative focused on reducing adverse perinatal outcomes associated with perinatal OUD. Those individuals reporting intravenous drug use (IVDU) were less likely to receive naloxone. On multivariate logistic regression, after controlling for IVDU and epoch of admission, both IVDU (adjusted odds ratio [aOR]: 0.27, 95% confidence interval [CI]: 0.11-0.70) and epoch of admission (aOR: 3.48, 95% CI: 1.28-9.50) were independently associated with receipt of prescription of take-home naloxone. CONCLUSION:  Naloxone prescription was independently associated with the epoch of admission and route of drug administration. These data can be useful in the evaluation and development of clinical practices to increase rates of naloxone prescription in pregnant people with OUD admitted for inpatient management. KEY POINTS: · Thirty four percent of individuals with perinatal OUD were prescribed take-home naloxone (THN).. · Epoch of admission and route of drug administration were independently associated with THN.. · These data can be used to guide public health and clinical programming for pregnant people..