Validation of the Enhanced Opioid Identification and Co-occurring Disorders Algorithms

Details

• Personal Author:
  Brown, Amy, M. ; White, Donielle, G. ; Adams, Nikki, B. ; Badwe, Rihem ; Shaikh, Salah ; Guluma, Lello
• Corporate Authors:
  National Center for Health Statistics (U.S.)
• Description:
  Public health report presenting the results of a validation study conducted to assess the reliability of two algorithms applied to the 2016 National Hospital Care Survey. One algorithm identifies opioid-involved and opioid overdose hospital encounters, and the other identifies encounters ; with patients that have substance use disorders and selected mental health issues. These algorithms use both medical codes and natural language processing to identify encounters.
• Subjects:
  • Statistical Models
  • Data Collection
  • Vital Statistics
• Keywords:
  • mental health issues, substance use disorders, natural language processing, National Hospital Care Survey
• Source:
  National Hospital Care Survey
• Series:
  NCHS Vital and Health Statistics Series
• Document Type:
  Text
• Genre:
  Report ; Statistics
• Place as Subject:
  United States
• Pages in Document:
  31 Pages
• Volume:
  2
• Issue:
  205
• Download URL:
  https://stacks.cdc.gov/view/cdc/134958/cdc_134958_DS1.pdf
• File Type:
  [PDF - 1.71 MB]
• Collection(s):
  National Center for Health Statistics
• Main Document Checksum:
  urn:sha-512:fc87c5555e179d530d461065f4d57a67ba947982ed75f68e57a30f6474f7c18c4a2e22f1a96fd99f9abdce1a48388d244c04cf9ba88d8aeb192e8a35f2c3c382