AI Hemodialysis Data Processing System for HL7 Format Translation
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Solution Overview
Problem
Current hemodialysis data processing systems face challenges in interpreting and accurately recording patient data due to differences in file formats between hemodialysis devices and electronic medical record systems, leading to potential medical errors from information errors or omissions.
Innovation Solution
An AI-based hemodialysis data processing method and system that extracts patient identification and health status information, predicts dry weight data, and adjusts hemodialysis demand based on AI models, while monitoring vital signs and detecting health anomalies to provide real-time clinical event data and response recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hemodialysis device transmits data in HL7 format, then data can be transmitted between devices, but the file format is difficult for humans to read and interpret
Solution Approach 1:
The patent introduces an AI-based data processing system as an intermediary between the hemodialysis device and the electronic medical record system. This intermediary automatically translates HL7 format data into interpretable formats, eliminating the need for manual interpretation while maintaining data compatibility across different systems.
Solution Approach 2:
The patent replaces manual data interpretation and transcription processes with an AI-based automated processing system. The AI model automatically extracts, maps, and transforms data from HL7 format to the electronic medical record system format, eliminating human intervention in the data translation process.
2Ease of operation
If medical staff manually records patient data, then data can be entered into the system, but information errors or omissions may occur
Solution Approach 1:
The patent implements a self-service data processing system where the AI model automatically extracts, validates, and maps patient data from the hemodialysis device to the electronic medical record system without requiring manual intervention. This automated self-service process eliminates human errors while maintaining data accuracy.
Solution Approach 2:
The patent incorporates feedback mechanisms where the AI model continuously validates data against predefined criteria and clinical guidelines. If data anomalies are detected, the system provides feedback for correction, ensuring high data accuracy while maintaining operational flexibility.
3Productivity
If continuous monitoring of patient data is performed, then real-time data can be captured, but data processing complexity increases
Solution Approach 1:
The patent extracts and isolates the data processing functionality into a separate AI-based processing layer, separating the monitoring function from the processing complexity. The monitoring system continuously captures data while the AI model handles the complex transformation and mapping operations independently, maintaining real-time capability without increasing overall system complexity.
Data Source
AI summary
The present disclosure relates to an artificial intelligence-based hemodialysis data processing method, device, and system. The method of the present disclosure may comprise the steps of: extracting pre-stored identification information of a patient; acquiring health status information measured for the patient; mapping the extracted identification information and the acquired health status information; acquiring information of the amount of blood required for dialysis for that day, calculated for the patient on the basis of the mapped identification information and health status information; and outputting the acquired information of the amount of blood required for dialysis for that day.