title: Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition.
abstract: BACKGROUND
  Although fatal opioid poisonings tripled from 1999 to 2008, data describing nonfatal poisonings are rare. Public health authorities are in need of tools to track opioid poisonings in near real time.
  
  
  METHODS
  We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid poisonings in a state-wide emergency department (ED) surveillance system. We sampled visits from four hospitals from July 2009 to June 2012 with diagnosis codes of 965.00, 965.01, 965.02 and 965.09 (poisoning by opiates and related narcotics) and/or an external cause of injury code of E850.0-E850.2 (accidental poisoning by opiates and related narcotics), and developed a novel case definition to determine in which cases opioid poisoning prompted the ED visit. We calculated the percentage of visits coded for opioid poisoning that were clinically significant and compared it to the percentage of visits coded for poisoning by non-opioid agents in which there was actually poisoning by an opioid agent. We created a multivariate regression model to determine if other collected triage data can improve the positive predictive value of diagnosis codes alone for detecting clinically significant opioid poisoning.
  
  
  RESULTS
  70.1 % of visits (Standard Error 2.4 %) coded for opioid poisoning were primarily prompted by opioid poisoning. The remainder of visits represented opioid exposure in the setting of other primary diseases. Among non-opioid poisoning codes reviewed, up to 36 % were reclassified as an opioid poisoning. In multivariate analysis, only naloxone use improved the positive predictive value of ICD-9-CM codes for identifying clinically significant opioid poisoning, but was associated with a high false negative rate.
  
  
  CONCLUSIONS
  This surveillance mechanism identifies many clinically significant opioid overdoses with a high positive predictive value. With further validation, it may help target control measures such as prescriber education and pharmacy monitoring.
authors: Division of Emergency Medicine, Duke University, 2301 Erwin Rd, Box 3935, Durham, NC, 27710, USA. Joseph.Reardon@alumni.duke.edu.
authors: Joseph M
authors: JM
authors: Reardon
authors: Carolina Center for Health Informatics and the Injury Prevention Research Center, University of North Carolina at Chapel Hill, 100 Market St, Chapel Hill, 27516, NC, USA.
authors: Katherine J
authors: KJ
authors: Harmon
authors: Department of Emergency Medicine, University of North Carolina at Chapel Hill, Box 7594, 170 Manning Dr, Chapel Hill, 27599, NC, USA.
authors: Genevieve C
authors: GC
authors: Schult
authors: Division of Emergency Medicine, Duke University, 2301 Erwin Rd, Box 3935, Durham, NC, 27710, USA.|Duke Global Health Institute, Duke University, 310 Trent Dr, Durham, 27710, NC, USA.
authors: Catherine A
authors: CA
authors: Staton
authors: Carolina Center for Health Informatics and the Injury Prevention Research Center, University of North Carolina at Chapel Hill, 100 Market St, Chapel Hill, 27516, NC, USA.|Department of Emergency Medicine, University of North Carolina at Chapel Hill, Box 7594, 170 Manning Dr, Chapel Hill, 27599, NC, USA.
authors: Anna E
authors: AE
authors: Waller
mesh_terms: D000293:Adolescent; D000328:Adult; D000701:Analgesics, Opioid / Q000506:poisoning*; D059019:Clinical Coding; D004636:Emergency Service, Hospital; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D000069342:Medical Overuse / Q000639:trends*; D008875:Middle Aged; D011159:Population Surveillance; D012189:Retrospective Studies; D014218:Triage; D055815:Young Adult
chemical_list: D000701:Analgesics, Opioid