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Provider-specific quality measurement for ERCP using natural language processing.

Timothy D Imler1, Stuart Sherman2, Thomas F Imperiale3

  • 1Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Biomedical Informatics, Regenstrief Institute, LLC. Indianapolis, Indiana, USA.

Gastrointestinal Endoscopy
|May 7, 2017
PubMed
Summary
This summary is machine-generated.

Natural language processing (NLP) can track adherence to ERCP quality measures for individual providers. This method offers accurate quality metric tracking without manual review, improving endoscopic procedure quality.

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Area of Science:

  • Endoscopic procedures
  • Medical informatics
  • Health services research

Background:

  • Endoscopic retrograde cholangiopancreatography (ERCP) is a high-risk procedure.
  • No systematic methods exist to track ERCP quality measure adherence.
  • Individualized provider quality tracking is needed for ERCP.

Purpose of the Study:

  • To demonstrate the feasibility of using Natural Language Processing (NLP) to measure adherence to ERCP quality indicators.
  • To enable individualized tracking of ERCP providers for quality metrics.

Main Methods:

  • Utilized NLP and data mining (ICD9-CM codes) to extract quality measures from 23,674 ERCPs (2006-2014).
  • Defined 13 quality measures (pre-, intra-, and post-procedure) based on guidelines and expert opinion.
  • Validated NLP extraction against manual record review, assessing precision and accuracy.

Main Results:

  • NLP demonstrated high precision (84%-100%) and accuracy (90%-100%) in extracting ERCP quality measures.
  • Intraprocedure measures showed slightly lower precision (84%) and accuracy (90%) compared to other categories.
  • Analysis covered 13 quality measures across 23,674 ERCPs from 6 providers.

Conclusions:

  • NLP combined with data mining effectively tracks ERCP quality metrics per provider, eliminating manual review.
  • This approach can be scaled to multiple centers for national registry quality monitoring.
  • Facilitates objective assessment and improvement of ERCP procedural quality.