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

Journal: Public health reports (Washington, D.C. : 1974)
PMID: 34726978

Abstract

OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (EMS) data, with flexible methodology for application to other states' data.

Authors

  • Josie J Sivaraman
    2331 Department of Epidemiology, University of North Carolina at Chapel Hill, NC, USA.
  • Scott K Proescholdbell
    Epidemiology, Surveillance and Informatics Unit, Injury and Violence Prevention Branch, Chronic Disease and Injury Section, Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC, USA.
  • David Ezzell
    6800 Division of Health Service Regulation, Office of Emergency Medical Services, North Carolina Department of Health and Human Services, Raleigh, NC, USA.
  • Meghan E Shanahan
    Injury Prevention Research Center, University of North Carolina at Chapel Hill, NC, USA.

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