Evidence map›Paper›PMID 32040923›Full record

ArticlePublic health reports (Washington, D.C. : 1974)

ICD-10-CM-Based Definitions for Emergency Department Opioid Poisoning Surveillance: Electronic Health Record Case Confirmation Study.

Svetla Slavova, Dana Quesinberry, Julia F Costich, Emilia Pasalic, Pedro Martinez, Julia Martin, Sarah Eustice, Peter Akpunonu, Terry L Bunn

Abstract read
In one paragraph

Article in Public health reports (Washington, D.C. : 1974). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
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  5. Article
  6. Racial, ethnic, and sex disparities in buprenorphine treatment from emergency departments by discharge diagnosis.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025
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  11. Article
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  13. Observational
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  15. Article
  16. Article
  17. Article
  18. Observational
  19. Defining indicators for drug overdose emergency department visits and hospitalisations in ICD-10-CM coded discharge data.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2021
    Article
  20. Article
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

9 authors.

Svetla SlavovaKentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, USA.ORCID 0000-0002-4541-6574
Dana QuesinberryKentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, USA.
Julia F CostichKentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, USA.
Emilia PasalicNational Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Pedro MartinezNational Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Julia MartinDepartment of Emergency Medicine, College of Medicine, University of Kentucky, Lexington, KY, USA.
Sarah EusticeKentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, USA.
Peter AkpunonuDepartment of Emergency Medicine, College of Medicine, University of Kentucky, Lexington, KY, USA.ORCID 0000-0002-6968-686X
Terry L BunnKentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, USA.

Funding

KENTUCKY PRESCRIPTION DRUG OVERDOSE PREVENTION PROGRAMU17CE002732 · CE · UNIVERSITY OF KENTUCKY · PI BUNN, TERRY LEE · 2015 to 2015
$940k
NCIPC CDC HHS U17 CE002732
6 · The paper itself

Abstract

objectivesValid opioid poisoning morbidity definitions are essential to the accuracy of national surveillance. The goal of our study was to estimate the positive predictive value (PPV) of case definitions identifying emergency department (ED) visits for heroin or other opioid poisonings, using billing records with

methodsWe examined billing records for ED visits from 4 health care networks (12 EDs) from October 2015 through December 2016. We conducted medical record reviews of representative samples to estimate the PPVs and 95% confidence intervals (CIs) of (1) first-listed heroin poisoning diagnoses (n = 398), (2) secondary heroin poisoning diagnoses (n = 102), (3) first-listed other opioid poisoning diagnoses (n = 452), and (4) secondary other opioid poisoning diagnoses (n = 103).

resultsFirst-listed heroin poisoning diagnoses had an estimated PPV of 93.2% (95% CI, 90.0%-96.3%), higher than secondary heroin poisoning diagnoses (76.5%; 95% CI, 68.1%-84.8%). Among other opioid poisoning diagnoses, the estimated PPV was 79.4% (95% CI, 75.7%-83.1%) for first-listed diagnoses and 67.0% (95% CI, 57.8%-76.2%) for secondary diagnoses. Naloxone was administered in 867 of 1055 (82.2%) cases; 254 patients received multiple doses. One-third of all patients had a previous drug poisoning. Drug testing was ordered in only 354 cases.

conclusionsThe study findings suggest that heroin or other opioid poisoning surveillance definitions that include multiple diagnoses (first-listed and secondary) would identify a high percentage of true-positive cases.

Indexed as

AdolescentAdultAnalgesics, OpioidChildDrug OverdoseElectronic Health RecordsEmergency Service, HospitalFemaleHeroinHumansInternational Classification of DiseasesKentuckyMaleNaloxoneAnalgesics, OpioidHeroinNaloxonecase definitionheroin poisoningopioid poisoningpositive predictive value

Identifiers

PMID32040923
PMCPMC7036606

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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.