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Using natural language processing and VetCompass to understand antimicrobial usage patterns in Australia
B Hur1,2, L Y Hardefeldt1, K Verspoor2,3
1Asia-Pacific Centre for Animal Health, Melbourne Veterinary School, University of Melbourne, Parkville, Victoria, Australia.
Australian Veterinary Journal
|June 19, 2019
Summary
Understanding antimicrobial use in Australian veterinary clinics is crucial for stewardship. VetCompass Australia used natural language processing (NLP) to analyze millions of records, revealing usage patterns with high accuracy.
Area of Science:
- Veterinary Medicine
- Data Science
- Pharmacology
Background:
- Antimicrobial usage patterns in Australian veterinary clinics are not well understood.
- Knowledge of these patterns is essential for effective antimicrobial stewardship programs.
Purpose of the Study:
- To analyze and understand antimicrobial usage patterns in Australian veterinary clinics.
- To develop and validate natural language processing (NLP) techniques for this analysis.
Main Methods:
- Utilized VetCompass Australia, a database of medical records from 181 Australian clinics.
- Applied natural language processing (NLP) and machine learning to analyze 4,394,493 veterinary consultation records (2013-2018).
- Focused on free-text fields within consultation records to identify antimicrobial dispensing.
Main Results:
- Successfully collated and analyzed a large dataset of companion animal (dogs and cats) veterinary records.
- Developed NLP algorithms capable of identifying antimicrobial mentions in clinical records.
- Achieved 96.7% accuracy and an F1 Score of 0.85 in matching antimicrobials, as validated by expert annotations.
Conclusions:
- The developed NLP algorithms accurately identify antimicrobial usage in veterinary clinical records.
- The VetCompass Australia dataset provides a valuable resource for querying and understanding antimicrobial usage patterns in companion animal practices across Australia.
- This work supports the monitoring and implementation of antimicrobial stewardship initiatives.
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