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[Application of Medical Record Quality Control System Based on Artificial Intelligence]
Yu Wen1, Xiong Li1, Feifei Zeng1
1（ 514000） Meizhou People's Hospital, Meizhou 514000, China.
Summary
Artificial intelligence (AI) significantly improves medical record quality control, detecting 2.97 times more issues than manual methods. This AI system enhances accuracy and efficiency in healthcare documentation.
Area of Science:
- Health Informatics
- Artificial Intelligence in Healthcare
- Medical Record Management
Context:
- Manual quality control of medical records is labor-intensive and prone to errors.
- Standardizing medical record documentation is crucial for patient care and research.
- Existing quality control methods struggle with the volume and complexity of electronic health records.
Purpose:
- To develop and evaluate an artificial intelligence (AI)-based system for automated medical record quality control.
- To compare the effectiveness of AI-driven quality control against traditional manual methods.
- To standardize medical record documentation processes and improve overall data integrity.
Summary:
- An AI-powered system was developed using a rule base derived from expert opinions and standards.
- The system processed 2,918 medical records, automatically identifying quality issues across five key areas.
- AI quality control demonstrated 89.57% accuracy, significantly outperforming manual review in detecting errors (2.97x more) and achieving high AUC values (≥0.9).
Impact:
- The AI system substantially increases the detection rate of medical record quality problems.
- Implementation of AI-based quality control leads to significant manpower savings.
- Enhanced accuracy and efficiency in medical record documentation improve overall healthcare data quality.
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