Artificial Intelligence to Predict Billing Code Levels of Emergency Department Encounters

To use artificial intelligence (AI) to predict billing code levels for emergency department (ED) encounters. We accessed ED encounters from our health system from January to September 2023. We developed an ensemble model using natural language processing and machine learning techniques to predict bi...

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Bibliographic Details
Published in:Annals of emergency medicine 2025-01, Vol.85 (1), p.63-73
Main Authors: Morey, Jacob, Winters, Richard, Jones, Derick
Format: Article
Language:English
Subjects:
Adult
Artificial Intelligence - economics
Clinical Coding - standards
Current Procedural Terminology
Emergency Service, Hospital - economics
Emergency Service, Hospital - statistics & numerical data
Female
Humans
Machine Learning
Male
Middle Aged
Natural Language Processing
ROC Curve
Citations: Items that this one cites
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Summary:To use artificial intelligence (AI) to predict billing code levels for emergency department (ED) encounters. We accessed ED encounters from our health system from January to September 2023. We developed an ensemble model using natural language processing and machine learning techniques to predict billing codes from clinical notes combined with clinical characteristics and orders. Explainable AI techniques were used to help determine the important model features. The main endpoint was to predict evaluation and management professional billing codes (levels 2 to 5 [Current Procedural Terminology codes 99282 to 99285] and critical care). Secondary endpoints included predicting professional billing codes at different decision boundary thresholds and generalizability of the model at other EDs. There were 321,893 adult ED encounters coded at levels 2 (
ISSN:0196-0644
1097-6760
1097-6760
DOI:10.1016/j.annemergmed.2024.07.011