Evidence map›Paper›PMID 23734988›Full record

ArticlePrehospital emergency care

EMS runs for suspected opioid overdose: implications for surveillance and prevention.

Amy Knowlton, Brian W Weir, Frank Hazzard, Yngvild Olsen, Junette McWilliams, Julie Fields, Wade Gaasch

Abstract read
In one paragraph

Article in Prehospital emergency care. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed.

  1. BMJ open · 2026
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  8. Prediction of naloxone dose in opioids toxicity based on machine learning techniques (artificial intelligence).Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2024
    Article
  9. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Amy KnowltonJohns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205 , USA. aknowlto@jhsph.edu
Brian W Weir
Frank Hazzard
Yngvild Olsen
Junette McWilliams
Julie Fields
Wade Gaasch

Funding

Informal Caregiving & Medical Adherence Among HIV+ IDUsR01DA019413 · NIDA · JOHNS HOPKINS UNIVERSITY · PI KNOWLTON, AMY · 2006 to 2009
$2.2M
Enhanced brief Intervention for linking opiate abusing EMS patients to treatmentR34DA034314 · NIDA · JOHNS HOPKINS UNIVERSITY · PI KNOWLTON, AMY · 2012 to 2013
$680k
Event-level correlates of substance use, violence, and HIV risk behaviorF31DA026763 · NIDA · JOHNS HOPKINS UNIVERSITY · PI WEIR, BRIAN WILSON · 2009 to 2011
$124k
NIDA NIH HHS F31 DA026763NIDA NIH HHS R01 DA019413NIDA NIH HHS R01DA019413NIDA NIH HHS R34 DA034314
6 · The paper itself

Abstract

backgroundOpioid (including prescription opiate) abuse and overdose rates in the United States have surged in the past decade. The dearth and limitations of opioid abuse and overdose surveillance systems impede the development of interventions to address this epidemic. Objective. We explored evidence to support the validity of emergency medical services (EMS) data on naloxone administration as a possible proxy for estimating incidence of opioid overdose.

methodsWe reviewed data from Baltimore City Fire Department EMS patient records matched with dispatch records over a 13-month time period (2008-2009) based on 2008 Census data. We calculated incidence rates and patient demographic and temporal patterns of naloxone administration, and examined patient evaluation data associated with naloxone administration. Results were compared with the demographic distributions of the EMS patient and city populations and with prior study findings.

resultsOf 116,910 EMS incidents during the study period for patients aged 15 years and older, EMS providers administered naloxone 1,297 times (1.1% of incidents), an average of 100 administrations per month. The overall incidence was 1.87 administrations per 1,000 residents per year. Findings indicated that naloxone administration peaked in the summer months (31% of administrations), on weekends (32%), and in the late afternoon (4:00-5:00 pm [8%]); and there was a trend toward peaking in the first week of the month. The incidence of suspected opioid overdose was highest among male patients, white patients, and those in the 45-54-year age group. Findings on temporal patterns were comparable with findings from prior studies. Demographic patterns of suspected opioid overdose were similar to medical examiner reports of demographic patterns of fatal drug- or alcohol-related overdoses in Baltimore in 2008-2009 (88% of which involved opioids). The findings on patient evaluation data suggest some inconsistencies with previously recommended clinical indications of opioid overdose.

conclusionsWhile our findings suggest limitations of EMS naloxone administration data as a proxy indicator of opioid overdose, the results provide partial support for using these data for estimating opioid overdose incidence and suggest ways to improve such data. The study findings have implications for an EMS role in conducting real-time surveillance and treatment and prevention of opioid abuse and overdose.

Indexed as

Analgesics, OpioidBaltimoreDrug OverdoseEmergency Medical ServicesFemaleHumansIncidenceMaleNaloxoneNarcotic AntagonistsRetrospective StudiesRisk FactorsSubstance-Related DisordersTreatment OutcomeAnalgesics, OpioidNaloxoneNarcotic Antagonists

Identifiers

PMID23734988
PMCPMC3682796

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Registered trials

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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.