Medical Apparatus Controller Data Management System
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Solution Overview
Problem
Current medical device data management systems are limited in their ability to effectively manage and control complex medical treatment environments, as they often operate with a restricted number of users, process limited types of data, and perform limited analyses, hindering their adoption and integration into comprehensive networks.
Innovation Solution
A computer-implemented method and system for controlling medical apparatuses in a data network, featuring a medical apparatus controller and data management system (MAC-DMS) with components like a streaming data processing engine, analytical engine, and enhanced data lake, which collects, analyzes, and securely relays medical apparatus data, enabling secure internet communication and preprogrammed analytical functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current medical device data management systems are used, then system simplicity is maintained, but the ability to manage and analyze complex medical treatment environments is limited
Solution Approach 1:
The system is divided into multiple functional modules including data collection module, data processing module, analysis module, and user interface module. Each module handles specific tasks independently, allowing the system to manage complex medical environments while maintaining modularity and ease of maintenance.
Solution Approach 2:
The medical device data management system is designed to handle multiple types of medical devices, data formats, and analysis methods through a unified platform. The system can process data from various sources including sensors, medical imaging devices, and electronic health records, making it adaptable to diverse medical treatment environments.
2Productivity
If comprehensive data collection and analysis capabilities are implemented, then data utilization is enhanced, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary data processing, validation, and categorization as data is collected from medical devices. This preprocessing work is done before comprehensive analysis is required, reducing the computational burden and time needed for subsequent analysis operations.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor data processing performance and adjust processing parameters dynamically. When processing time becomes excessive, the system can prioritize critical data streams or adjust analysis depth to maintain acceptable response times while still providing comprehensive data utilization.
Data Source
AI summary
Provided are new methods for controlling the operation of medical devices and related systems. Devices collect and relay sensor data via a secure internet connection in a streaming manner, but can also collect such data locally as cache data. When certain events occur, the devices also relay collected cache data. Device data is received by a network data system that analyzes the data and controls operation of the devices and other network devices based on such analysis. The medical devices can comprise multiple zones performing different data collection functions and being subject to different data relay processes. The system can segregate protected health information from commercial users that are allowed to access certain analytical data. In aspects, the system interacts with third party databases, e.g., customer relationship management systems, in generating analytical data. In aspects, machine learning processes are employed to improve the operation of such systems.