Clinical Decision Support to Increase Emergency Department Naloxone Co-prescribing: Implementation Report (Preprint)

Abstract

Co-prescribing naloxone with opioid analgesics is a Centers for Disease Control and Prevention best practice to mitigate the risk of fatal opioid overdose (OD), yet co-prescription by emergency medicine clinicians is rare, occurring less than 5% of the time it is indicated. Clinical decision support (CDS) has been associated with increased naloxone prescribing; however, key CDS design characteristics and pragmatic outcome measures necessary to understand replicability and effectiveness have not been reported.

This study aimed to rigorously evaluate and quantify the impact of CDS designed to improve emergency department (ED) naloxone co-prescribing. We hypothesized CDS would increase naloxone co-prescribing and the number of naloxone prescriptions filled by patients discharged from EDs in a large healthcare system.

Following user-centered design (UCD) principles, we designed and implemented an interruptive, electronic health record (EHR)-based CDS to nudge clinicians to co-prescribe naloxone with high-risk opioid prescriptions. “High-risk” opioid prescriptions were defined as any opioid analgesic prescription > 90 total morphine milligram equivalents (MMEs) per day or for patients with a prior diagnosis of opioid use disorder (OUD) or opioid overdose (OD). The RE-AIM framework was used to evaluate pragmatic CDS outcomes of reach, effectiveness, adoption, implementation, and maintenance. Effectiveness was the primary outcome of interest and was assessed by: 1) constructing a Bayesian structural time-series model of the number of ED visits with naloxone co-prescriptions before and after CDS implementation, and 2) calculating the percentage of naloxone prescriptions associated with CDS that were filled at an outpatient pharmacy. Mann-Kendall tests were used to evaluate longitudinal trends in CDS adoption. All outcomes were analyzed in R (version 4.2.2).

Between 11/2019 and 7/2023, there were 1,994,994 ED visits. CDS reached clinicians in 0.83% (16,566/1,994,994) of all visits and 16% (16,566/103,606) of ED visits where an opioid was prescribed at discharge. Clinicians adopted CDS, co-prescribing naloxone in 34% (6,613/19,246) of alerts. CDS was effective, increasing naloxone co-prescribing from baseline by 18.1 (95% CI 17.9-18.3) co-prescriptions per week or 2,327% (95% CI 3,390-3,490). Patients filled 44% (1,989/4,541) of naloxone co-prescriptions. The CDS was implemented simultaneously at every ED and no adaptations were made to CDS post-implementation. CDS was maintained beyond the study period and maintained its effect, with adoption increasing over time (tau=0.454, p<<0.001).

Our findings advance the evidence that EHR-based CDS increase the number of naloxone co-prescriptions and improve the distribution of naloxone. Our time series analysis controls for secular trends and strongly suggests that minimally interruptive CDS significantly improves process outcomes.

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