Observational studyJournal of general internal medicine2026
Clinical Decision Support to Increase Naloxone Co-prescribing from the Inpatient Setting.
Observational study in Journal of general internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Leveraging the 72-Hour Rule Change to Support Transition From Hospital to Opioid Treatment Program.JAMA network open · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundCo-prescribing naloxone alongside opioid prescriptions reduces fatal opioid overdose risk in patients discharged from inpatient care, yet its adoption remains limited. Clinical decision support (CDS) tools are effective in increasing naloxone co-prescribing in emergency and primary care settings, but data from the inpatient setting is sparse.
objectiveTo evaluate the effectiveness of an electronic health record (EHR)-integrated CDS tool on rates of naloxone co-prescribing for patients discharged from inpatient care with high-risk opioid prescriptions.
designThis observational, pre-post study evaluated an EHR-embedded CDS tool implemented within an integrated health system between July 10, 2011, and July 15, 2023. STUDY SAMPLE: Adult patients discharged from inpatient care with opioid prescriptions that met the Centers for Disease Control and Prevention high-risk criteria for opioid prescribing.
interventionsA multidisciplinary team designed an interruptive CDS best practice alert to identify high-risk opioid prescriptions. The CDS offered prescribers a one-click option to add a naloxone co-prescription. MAIN MEASURES: Outcomes are organized under the RE-AIM implementation science framework, with the primary outcome, Effectiveness, measured by the proportion of patients receiving a naloxone prescription. Secondary outcomes include patient Reach, clinician Adoption, and fidelity to Implementation. Bayesian structural time-series models were used to evaluate differences in outcomes. KEY
resultsDuring the study period, there were 355,465 inpatient discharges. In the post-intervention period, the CDS was triggered in 2.2% (7799/355,465) of all discharges and 6.36% (7799/122,643) of all discharge opioid prescriptions. Compared to the pre-implementation period, CDS was associated with a weekly increase in inpatient naloxone co-prescribing by 4.7 prescriptions per 100 opioid prescriptions (95% CI 4.3-5, p = 0.001).
conclusionsImplementation of an EHR-embedded CDS was associated with increased naloxone co-prescribing for high-risk opioid prescriptions in the inpatient setting. This finding demonstrates the potential of targeted, interruptive CDS tools to enhance opioid safety efforts in the inpatient setting.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.