Background: Opioid overdose is a well-established cause of morbidity and mortality in the United States1. Naloxone is an opioid antagonist and harm-reducing treatment with a complex history of prescribing behaviors, attitudes, availability and reimbursement2. Interventions to increase appropriate co-prescription of naloxone include government mandates3 and Electronic Health Record (EHR) clinical decision support4. Our institution used EHR clinical decision support to help increase statewide co-prescriptions >400%4 historically, but the sustainability and impact of that decision support has not been studied long-term.
Methods: This abstract reports naloxone co-prescribing events over 6 years of time (36 months prior to EHR clinical decision support implementation in August 2021 and 36 months after), percentage of outpatient opioid prescriptions and percentage of unique patients with an active prescription for naloxone. All outpatient opioid prescriptions (including those written at hospital discharge) at our institution are included in this analysis. A co-prescription is defined by an active prescription for naloxone written during the same encounter as the opioid (or written previously and has not been discontinued or expired). Data was extracted from a standard EHR opioid prescription data model.
Results: In the 36 months prior to EHR clinical decision support implementation 193,807 prescriptions for outpatient opioids were written on 70,165 unique patients. 2,305 (1.2%) of these prescriptions, written for 302 (0.43%) unique patients, included a naloxone co-prescription. In the 36 months after EHR clinical decision support implementation 191,051 prescriptions for outpatient opioids were written on 67,557 unique patients. 61,763 (32.3%) of these prescriptions, written for 15,696 (23.2%) unique patients, included a naloxone co-prescription.
Conclusions: Observational analysis of pre/post data over 6 years and 384,858 prescribing events shows a sustained increase in naloxone co-prescription at both the prescription and patient level of detail following implementation of EHR clinical decision support.
