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:
  Data Collection Statistical Models 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
• Collection(s):
  National Center for Health Statistics
• Main Document Checksum:
  urn:sha-512:fc87c5555e179d530d461065f4d57a67ba947982ed75f68e57a30f6474f7c18c4a2e22f1a96fd99f9abdce1a48388d244c04cf9ba88d8aeb192e8a35f2c3c382
• Download URL:
  https://stacks.cdc.gov/view/cdc/134958/cdc_134958_DS1.pdf
• File Type:
  [PDF - 1.71 MB ]