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Updated: Jun 9, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Iterative Development of a Clinical Decision Support Tool to Enhance Naloxone Coprescribing
Richard Wu1, Emily Foster2, Qiyao Zhang2
1Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts, United States.
Background:
Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to coprescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low.
Objectives:
The objective of this study was to develop and evaluate a hospital-wide electronic health record (EHR)-based clinical decision support (CDS) tool designed to promote naloxone coprescription for high-risk opioids.
Methods:
We employed an iterative approach to develop a point-of-order, interruptive EHR alert as the primary intervention and assessed naloxone prescription rates, EHR efficiency metrics, and barriers to adoption. Data were obtained from our EHR's clinical data warehouse and analyzed using statistical process control with odds ratios calculated to quantify statistically significant differences in prescribing rates during the intervention periods.
Results:
The initial implementation phase of the intervention, spanning from April 2019 to May 2022, yielded a nearly 3-fold increase in the proportion of high-risk patients receiving naloxone, rising from 13.4% (95% confidence interval [CI], 12.9-13.8%) to 36.4% (95% CI, 35.2-37.5%; p = 10-38). Enhancements to the CDS design and logic during the subsequent iteration's study period, June 2022 and December 2023, reduced the number of CDS triggers by more than 30-fold while simultaneously driving an additional increase in naloxone receipt to 42.7% (95% CI, 40.6-44.8%; p = 2 × 10-5). The efficiency of the CDS demonstrated marked improvement, with prescribers accepting the naloxone coprescription recommendation provided by the CDS in 41.1% of the encounters in version 2, compared with 6.2% in version 1 (p = 6 × 10-9).
Conclusion:
This study offers a sustainable and scalable model to address low rates of naloxone coprescription and may also be used to target other opportunities for improving guideline-concordant prescribing practices.
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