Literature DB >> 29297739

Measuring a Crisis: Questioning the Use of Naloxone Administrations as a Marker for Opioid Overdoses in a Large U.S. EMS System.

Joseph M Grover, Taibah Alabdrabalnabi, Mehul D Patel, Michael W Bachman, Timothy F Platts-Mills, Jose G Cabanas, Jefferson G Williams.   

Abstract

OBJECTIVE: The United States is currently experiencing a public health crisis of opioid overdoses. To determine where resources may be most needed, many public health officials utilize naloxone administration by EMS as an easily-measured surrogate marker for opioid overdoses in a community. Our objective was to evaluate whether naloxone administration by EMS accurately represents EMS calls for opioid overdose. We hypothesize that naloxone administration underestimates opioid overdose.
METHODS: We conducted a chart review of suspected overdose patients and any patients administered naloxone in Wake County, North Carolina, from January 2013 to December 2015. Patient care report narratives and other relevant data were extracted from electronic patient care records and the resultant database was analyzed by two EMS physicians. Cases were divided into categories including "known opioid use," "presumed opioid use," "no known opioid," "altered mental status," "cardiac arrest with known opioid use," "cardiac arrest with no known opioid use," or "suspected alcohol intoxication," and then further separated based on whether naloxone was administered. Patient categories were compared by patient demographics and incident year. Using the chart review classification as the gold standard, we calculated the sensitivity and positive predictive value (PPV) of naloxone administration for opioid overdose.
RESULTS: A total of 4,758 overdose cases from years 2013-15 were identified. During the same period, 1,351 patients were administered naloxone. Of the 1,431 patients with known or presumed opioid use, 57% (810 patients) received naloxone and 43% (621 patients) did not. The sensitivity of naloxone administration for the identification of patients with known or presumed opioid use was 57% (95% CI: 54%-59%) and the PPV was 60% (95% CI: 57%-63%).
CONCLUSION: Among patients receiving care in this large urban EMS system in the United States, the overall sensitivity and positive predictive value for naloxone administration for identifying opioid overdoses was low. Better methods of identifying opioid overdose trends are needed to accurately characterize the burden of opioid overdose within and among communities.

Entities:  

Keywords:  Emergency medical services; heroin; naloxone; opiate alkaloids; prehospital emergency care

Mesh:

Substances:

Year:  2018        PMID: 29297739     DOI: 10.1080/10903127.2017.1387628

Source DB:  PubMed          Journal:  Prehosp Emerg Care        ISSN: 1090-3127            Impact factor:   3.077


  9 in total

1.  Identifying high-risk areas for nonfatal opioid overdose: a spatial case-control study using EMS run data.

Authors:  Jeffrey Pesarsick; Melody Gwilliam; Olayemi Adeniran; Toni Rudisill; Gordon Smith; Brian Hendricks
Journal:  Ann Epidemiol       Date:  2019-07-03       Impact factor: 3.797

2.  Identification of Non-Fatal Opioid Overdose Cases Using 9-1-1 Computer Assisted Dispatch and Prehospital Patient Clinical Record Variables.

Authors:  Olufemi Ajumobi; Silvia R Verdugo; Brian Labus; Patrick Reuther; Bradford Lee; Brandon Koch; Peter J Davidson; Karla D Wagner
Journal:  Prehosp Emerg Care       Date:  2021-10-27       Impact factor: 2.686

3.  The changing epidemiology of opioid overdose in Baltimore, Maryland, 2012-2017: insights from emergency medical services.

Authors:  Chen Dun; Sean T Allen; Carl Latkin; Amy Knowlton; Brian W Weir
Journal:  Ann Med       Date:  2022-12       Impact factor: 5.348

4.  Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.

Authors:  Josie J Sivaraman; Scott K Proescholdbell; David Ezzell; Meghan E Shanahan
Journal:  Public Health Rep       Date:  2021 Nov-Dec       Impact factor: 2.792

5.  Using Surveillance With Near-Real-Time Alerts During a Cluster of Overdoses From Fentanyl-Contaminated Crack Cocaine, Connecticut, June 2019.

Authors:  Peter Canning; Suzanne Doyon; Sarah Ali; Susan B Logan; Aliese Alter; Katherine Hart; Raffaella Coler; Richard Kamin; Steven C Wolf; Kristin Soto; Lauren Whiteman; Mark Jenkins
Journal:  Public Health Rep       Date:  2021 Nov-Dec       Impact factor: 2.792

6.  Emergency Medical Services and Syndromic Surveillance: A Comparison With Traditional Surveillance and Effects on Timeliness.

Authors:  Peter J Rock; Dana Quesinberry; Michael D Singleton; Svetla Slavova
Journal:  Public Health Rep       Date:  2021 Nov-Dec       Impact factor: 2.792

7.  Administration of Naloxone by Prehospital Personnel: A Retrospective Analysis.

Authors:  Kaitlin M Bowers; Judd Shelton; Eric Cortez; Robert Lowe; John Casey; Andrew Little
Journal:  Cureus       Date:  2019-09-09

8.  The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance.

Authors:  José Tomás Prieto; Kenneth Scott; Dean McEwen; Laura J Podewils; Alia Al-Tayyib; James Robinson; David Edwards; Seth Foldy; Judith C Shlay; Arthur J Davidson
Journal:  J Med Internet Res       Date:  2020-01-03       Impact factor: 5.428

9.  Linking Emergency Medical Services and Emergency Department Data to Improve Overdose Surveillance in North Carolina.

Authors:  Jonathan Fix; Amy I Ising; Scott K Proescholdbell; Dennis M Falls; Catherine S Wolff; Antonio R Fernandez; Anna E Waller
Journal:  Public Health Rep       Date:  2021 Nov-Dec       Impact factor: 2.792

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.