title: Performance Measures of Diagnostic Codes for Detecting Opioid Overdose in the Emergency Department.
abstract: OBJECTIVE
  Opioid overdose mortality has tripled in the United States since 2000 and opioids are responsible for more than half of all drug overdose deaths, which reached an all-time high in 2014. Opioid overdoses resulting in death, however, represent only a small fraction of all opioid overdose events and efforts to improve surveillance of this public health problem should include tracking nonfatal overdose events. International Classification of Disease (ICD) diagnosis codes, increasingly used for the surveillance of nonfatal drug overdose events, have not been rigorously assessed for validity in capturing overdose events. The present study aimed to validate the use of ICD, 9th revision, Clinical Modification (ICD-9-CM) codes in identifying opioid overdose events in the emergency department (ED) by examining multiple performance measures, including sensitivity and specificity.
  
  
  METHODS
  Data on ED visits from January 1, 2012, to December 31, 2014, including clinical determination of whether the visit constituted an opioid overdose event, were abstracted from electronic medical records for patients prescribed long-term opioids for pain from any of six safety net primary care clinics in San Francisco, California. Combinations of ICD-9-CM codes were validated in the detection of overdose events as determined by medical chart review. Both sensitivity and specificity of different combinations of ICD-9-CM codes were calculated. Unadjusted logistic regression models with robust standard errors and accounting for clustering by patient were used to explore whether overdose ED visits with certain characteristics were more or less likely to be assigned an opioid poisoning ICD-9-CM code by the documenting physician.
  
  
  RESULTS
  Forty-four (1.4%) of 3,203 ED visits among 804 patients were determined to be opioid overdose events. Opioid-poisoning ICD-9-CM codes (E850.2-E850.2, 965.00-965.09) identified overdose ED visits with a sensitivity of 25.0% (95% confidence interval [CI] = 13.6% to 37.8%) and specificity of 99.9% (95% CI = 99.8% to 100.0%). Expanding the ICD-9-CM codes to include both nonspecified and general (i.e., without a decimal modifier) drug poisoning and drug abuse codes identified overdose ED visits with a sensitivity of 56.8% (95% CI = 43.6%-72.7%) and specificity of 96.2% (95% CI = 94.8%-97.2%). Additional ICD-9-CM codes not explicitly relevant to opioid overdose were necessary to further enhance sensitivity. Among the 44 overdose ED visits, neither naloxone administration during the visit, whether the patient responded to the naloxone, nor the specific opioids involved were associated with the assignment of an opioid poisoning ICD-9-CM code (p ≥ 0.05).
  
  
  CONCLUSIONS
  Tracking opioid overdose ED visits by diagnostic coding is fairly specific but insensitive, and coding was not influenced by administration of naloxone or the specific opioids involved. The reason for the high rate of missed cases is uncertain, although these results suggest that a more clearly defined case definition for overdose may be necessary to ensure effective opioid overdose surveillance. Changes in coding practices under ICD-10 might help to address these deficiencies.
authors.affiliation: Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Rowe
authors.affiliation: School of Medicine, Department of Epidemiology and Biostatistics, San Francisco, CA.
authors.forename: Eric
authors.initials: E
authors.lastname: Vittinghoff
authors.affiliation: Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA.|School of Nursing, Department of Community Health Systems, San Francisco, CA.
authors.forename: Glenn-Milo
authors.initials: GM
authors.lastname: Santos
authors.affiliation: Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA.|Department of Global Health Sciences, San Francisco, CA.
authors.forename: Emily
authors.initials: E
authors.lastname: Behar
authors.affiliation: Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA.
authors.forename: Caitlin
authors.initials: C
authors.lastname: Turner
authors.affiliation: Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA.|School of Medicine, Division of HIV, ID, and Global Health, University of California San Francisco, San Francisco, CA.
authors.forename: Phillip O
authors.initials: PO
authors.lastname: Coffin
mesh_terms: D000328:Adult; D000701:Analgesics, Opioid / Q000506:poisoning*; D002140:California; D003951:Diagnostic Errors / Q000517:prevention & control*; D062787:Drug Overdose / Q000175:diagnosis*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D012680:Sensitivity and Specificity
chemical_list: D000701:Analgesics, Opioid