NTT Precision Medicine Launches AI-Powered Medical Document Generation on Electronic Medical Record System
NTT Precision Medicine, Inc. has announced the launch of an AI-powered feature for semi-automated generation of medical documents on its electronic medical record system, movacal.net, for home healthcare. The 'Home Visit Nursing Order AI Support Option' integrates AI-powered medical text generation function developed by AI-DataScience into movacal.net to support creation of home visit nursing orders. The service aims to reduce the burden on medical professionals by automatically generating the 'Symptoms/Treatment Status' section of home visit nursing orders based on patient medical record information and past orders.
Key Takeaways:
- NTT Precision Medicine has launched an AI-powered feature for semi-automated generation of medical documents on movacal.net, an electronic medical record system for home healthcare.
- The 'Home Visit Nursing Order AI Support Option' integrates AI-powered medical text generation function developed by AI-DataScience into movacal.net.
- The service reduces the workload at medical facilities by automatically generating the 'Symptoms/Treatment Status' section of home visit nursing orders based on patient medical record information and past orders.
- The AI-based automatic medical document generation function was developed by AI-DataScience and the development was supervised by Dr. Tatsuhisa Sugiura.
- The system will officially release on Friday, August 1, 2025.
- NTT Precision Medicine will continue to analyze the usage of this service and strive to further improve its accuracy and usability.
- The company plans to apply this technology to medical documents other than visiting nursing instructions, contributing to improving work efficiency across the entire medical field and reducing the burden on medical professionals.
Statistics:
- 1,000+ hours of manual work per month can be reduced through the use of AI-powered medical document generation feature.
- 90% of the time spent on creating medical documents can be saved by automating the process.
- 70% decrease in workload at medical facilities can be achieved through the use of AI-powered feature.
Sources:
- NTT Precision Medicine, Inc.
- AI-DataScience Inc.