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A "Patch" to the NYU Emergency Department Visit Algorithm.

Kenton J Johnston1, Lindsay Allen2, Taylor A Melanson2

  • 1Department of Health Management & Policy and Center for Outcomes Research, Saint Louis University, St. Louis, MO.

Health Services Research
|July 21, 2017
PubMed
Summary
This summary is machine-generated.

The Emergency Department (ED) visit algorithm's classification accuracy declined due to new diagnosis codes. An updated algorithm significantly improves classification rates, enhancing its utility in health services research.

Keywords:
Emergency department visit algorithmemergency department usehealth services research

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Area of Science:

  • Health Services Research
  • Emergency Medicine
  • Data Science

Background:

  • The Emergency Department (ED) visit algorithm is crucial for health services research.
  • Changes in diagnostic coding systems can impact the algorithm's accuracy over time.

Purpose of the Study:

  • To evaluate the erosion in the ED visit algorithm's classification capability.
  • To develop an improved algorithm (a "patch") to address classification inaccuracies.

Main Methods:

  • Utilized the Nationwide Emergency Department Sample.
  • Employed bivariate models to assess the impact of ICD-9 code changes on unclassifiable visits.
  • Updated the algorithm incorporating ICD-9 and ICD-10 codes added since 2001.

Main Results:

  • The proportion of unclassifiable ED visits rose from 11.2% in 2006 to 15.5% in 2012 (p < .01).
  • The algorithm update enhanced the classification rate by 43% in 2012 (p < .01).

Conclusions:

  • The developed algorithm patch significantly enhances the precision of the ED visit classification system.
  • This improvement increases the usefulness of a widely adopted tool in health services research.