Published 01-08-2024
Keywords
- Clinical documentation improvement,
- Electronic health records,
- AI,
- Natural language processing,
- Machine learning
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
Abstract
Clinical documentation is crucial for accurate billing, quality reporting, and patient care. However, maintaining complete and accurate documentation can be challenging for healthcare providers. This paper explores the implementation of AI-driven solutions for clinical documentation improvement in electronic health records (EHRs). These solutions leverage natural language processing (NLP) and machine learning (ML) to analyze clinical notes and suggest improvements to enhance documentation quality. By automating documentation processes, AI can reduce errors, improve efficiency, and ensure compliance with regulatory requirements. This paper discusses the benefits, challenges, and future directions of AI-powered clinical documentation improvement in EHRs.
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References
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