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Effect of Applying a Real-Time Medical Record Input Assistance System With Voice Artificial Intelligence on Triage
Ara Cho1, In Kyung Min2, Seungkyun Hong3
1Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
JMIR Medical Informatics
|August 31, 2022
Summary
Real-time medical record input assistance with voice artificial intelligence (RMIS-AI) speeds up emergency department triage tasks. While RMIS-AI enhances promptness, further research is needed to improve its reliability for comprehensive record completion.
Area of Science:
- Clinical informatics
- Artificial intelligence in healthcare
- Natural language processing
Background:
- Medical studies often use retrospective analysis of manually entered text.
- Limited research applies NLP and speech-to-text to raw clinical voice data.
- Voice AI for real-time medical record input is an emerging area.
Purpose of the Study:
- To evaluate the speed and reliability of a voice AI system for medical records (RMIS-AI).
- To compare RMIS-AI with manual methods for emergency department triage.
- To assess the system's performance in clinical practice.
Main Methods:
- Prospective application of RMIS-AI in a clinical triage unit.
- Machine learning engine trained on 1717 triage cases.
- Analysis of 1063 triage tasks performed by 19 nurses.
Main Results:
- RMIS-AI significantly reduced triage task time (204s vs. 231s, P<.001).
- Higher completion rates for chief concerns and past medical history with RMIS-AI.
- Manual method had higher completion rates for most variables; RMIS-AI showed lower accuracy for categorical data.
Conclusions:
- RMIS-AI enhances promptness in triage tasks compared to manual input.
- Further technical improvements and research are necessary for RMIS-AI reliability.
- Voice AI shows potential but requires refinement for comprehensive clinical documentation.
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