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MAPRS: An intelligent approach for post-prescription review based on multi-label learning
Guangfei Yang1, Ziyao Zhou2, Aili Ding3
1Central Hospital of Dalian University of Technology (Dalian Municipal Central Hospital), Dalian 116033, China; Institute of Systems Engineering, Dalian University of Technology, Dalian 116024, China.
Artificial Intelligence in Medicine
|September 12, 2024
Summary
Antimicrobial resistance (AMR) is a global health threat. A new Multi-label Antimicrobial Post-Prescription Review System (MAPRS) uses NLP and machine learning to identify inappropriate prescriptions and explain their causes, improving antimicrobial stewardship.
Area of Science:
- Medical Informatics
- Public Health
- Computational Biology
Background:
- Antimicrobial resistance (AMR) poses a significant global health risk.
- Post-Prescription Review (PPR) is crucial for antimicrobial stewardship but often uses simplified binary classification.
- Existing PPR methods lack explanations for inappropriate antimicrobial use, hindering targeted improvements.
Purpose of the Study:
- To develop an intelligent system for reviewing antimicrobial prescriptions.
- To address the multi-label nature of prescription classification.
- To identify and explain the reasons behind inappropriate antimicrobial prescriptions.
Main Methods:
- Collected antimicrobial prescriptions and clinical data from clean surgery patients.
- Developed a Multi-label Antimicrobial Post-Prescription Review System (MAPRS) using Natural Language Processing (NLP).
- Employed Classifier Chains fused with machine learning for multi-label classification and SHAP for explainability.
Main Results:
- MAPRS achieved high performance on a six-category multi-label task.
- Demonstrated a subset accuracy of 90.7% and an average AUROC of 94.3%.
- Successfully explained causes of inappropriate antimicrobial prescriptions.
Conclusions:
- MAPRS offers an effective solution for intelligent antimicrobial prescription review.
- The system enhances antimicrobial stewardship by identifying and explaining prescription issues.
- This approach can aid hospitals in improving antimicrobial usage and combating AMR.
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