ArticlePain reports
Naloxone prescribing practices in the Military Health System before and after policy implementation.
Article in Pain reports. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Opioid Prescriptions for Low Back Pain among Military-Connected Older Adults Across Multiple Care Systems.Drugs & aging · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Despite public health campaigns, policies, and educational programs, naloxone prescription rates among people receiving opioids remains low. In June 2018, the U.S. Military Health System (MHS) released 2 policies to improve naloxone prescribing. Objectives: The objective of this study was to examine whether the policies resulted in increased naloxone coprescription rates for patients who met the criteria for 1 or more risk indicators (eg, long-term opioid therapy, benzodiazepine coprescription, morphine equivalent daily dose ≥50 mg, and elevated overdose risk score) at the time of opioid dispense. Methods: Prescription and risk indicator data from January 2017 to February 2021 were extracted from the MHS Data Repository. Naloxone coprescription rates from January 2017 to September 2018 were used to forecast prescribing rates from October 2018 to February 2021 overall and across risk indicators. Forecasted rates were compared with actual rates using Bayesian time series analyses. Results: The probability of receiving a naloxone coprescription was higher for patients whose opioid prescriber and pharmacy were both within military treatment facilities vs both within the purchased-care network. Bayesian time series results indicated that the number of patients who met the criteria for any risk indicator decreased throughout the study period. Naloxone prescribing rates increased across the study period from <1% to 20% and did not significantly differ from the forecasted rates across any and each risk indicator (adjusted Conclusion: Future analyses are needed to better understand naloxone prescribing practices and the impact of improvements to electronic health records, decision support tools, and policies.
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