ArticleJMIR medical informatics2024
Clinical Decision Support to Increase Emergency Department Naloxone Coprescribing: Implementation Report.
Article in JMIR medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Emergency Departments Leading the Transformation of Alzheimer's and Dementia Care: Emergency Care Redesign.Journal of the American Geriatrics Society · 2026Article
- Scalable and Privacy-Conscious End-to-End Processing of Large-Scale Clinical Data for Precision Medicine: Empirical Evaluation Study.JMIR medical informatics · 2026Article
- A Naloxone Best Practice Advisory That Failed to Signal: A Real‑World Evaluation of an Emergency Department.Cureus · 2026Article
- Pragmatic Integration of User-Centered Design and Implementation Science: A New Methodological Approach for Clinical Decision Support Implementation in EHRs.Applied clinical informatics · 2025Article
- Application of Nudges to Design Clinical Decision Support Tools: Systematic Approach Guided by Implementation Science.Journal of medical Internet research · 2025Article
- A Measurement Science Framework to Optimize CDS for Opioid Use Disorder Treatment in the ED.Applied clinical informatics · 2025Article
- Reduced Taurine Synthesis Underlies Morphine-Promoted Lung Metastasis of Triple-Negative Breast Cancer.Cancers · 2025Article
- Academic Detailing to Enhance Adoption of Clinical Decision Support for Patients at Risk of Opioid Overdose.Applied clinical informatics · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Background: Coprescribing naloxone with opioid analgesics is a Centers for Disease Control and Prevention (CDC) best practice to mitigate the risk of fatal opioid overdose, yet coprescription 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. Objective: This study aimed to rigorously evaluate and quantify the impact of CDS designed to improve emergency department (ED) naloxone coprescribing. We hypothesized CDS would increase naloxone coprescribing and the number of naloxone prescriptions filled by patients discharged from EDs in a large health care system. Methods: Following user-centered design principles, we designed and implemented a fully automated, interruptive, electronic health record-based CDS to nudge clinicians to coprescribe naloxone with high-risk opioid prescriptions. "High-risk" opioid prescriptions were defined as any opioid analgesic prescription ≥90 total morphine milligram equivalents per day or for patients with a prior diagnosis of opioid use disorder or opioid overdose. The Reach, Effectiveness, Adoption, Implementation, and Maintenance (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 coprescriptions 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; R Core Team). Unlabelled: Between November 2019 and July 2023, there were 1,994,994 ED visits. CDS reached clinicians in 0.83% (16,566/1,994,994) of all visits and 15.99% (16,566/103,606) of ED visits where an opioid was prescribed at discharge. Clinicians adopted CDS, coprescribing naloxone in 34.36% (6613/19,246) of alerts. CDS was effective, increasing naloxone coprescribing from baseline by 18.1 (95% CI 17.9-18.3) coprescriptions per week or 2,327% (95% CI 3390-3490). Patients filled 43.80% (1989/4541) of naloxone coprescriptions. The CDS was implemented simultaneously at every ED and no adaptations were made to CDS postimplementation. CDS was maintained beyond the study period and maintained its effect, with adoption increasing over time (τ=0.454; P<.001). Conclusions: Our findings advance the evidence that electronic health record-based CDS increases the number of naloxone coprescriptions and improves 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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