Modular Health Study Management System for Clinical Data Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing health monitoring systems for clinical studies are inflexible and costly due to the need for bespoke mobile applications and server-side infrastructure, and they struggle with integrating diverse health monitoring devices and sensors, which limits their adaptability to new diseases and evolving technologies.
Innovation Solution
A modular health study management system that includes a data ingestion subsystem with extensible interface modules for various data sources and a data processing subsystem for deriving health indicators, allowing for dynamic configuration and simultaneous management of multiple studies across different devices and diseases, with data collection and processing optimized for real-time data transmission and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bespoke mobile applications and server-side infrastructure are developed for each health monitoring application, then the system can collect and process health data for specific diseases, but the cost and complexity of development become prohibitively high
Solution Approach 1:
The patent implements a universal health monitoring platform that can support multiple diseases and studies through a common infrastructure. The system uses a standardized data collection framework that can be configured for different clinical studies without requiring bespoke applications, thereby reducing development complexity while maintaining reliable health data collection capabilities across multiple use cases
Solution Approach 2:
The system segments the health monitoring functionality into modular components including configurable data collection modules, standardized data models, and flexible analysis frameworks. This segmentation allows the same core platform to be adapted to different disease areas through configuration rather than custom development, reducing overall system complexity
2Reliability
If bespoke mobile applications are developed for each health monitoring application, then the system can be tailored to specific diseases, but the adaptability to new diseases and evolving technologies is reduced
Solution Approach 1:
The patent creates a universal platform with standardized data models and configurable analysis modules that can accommodate multiple diseases and evolving technologies. The system maintains disease-specific monitoring accuracy through configurable parameters and protocols while adapting to new diseases through the same infrastructure, eliminating the need for separate bespoke applications for each disease area
Solution Approach 2:
The system implements dynamic configurability allowing study protocols, data collection parameters, and analysis methods to be adjusted for different diseases and evolving research requirements. This dynamic architecture enables the platform to adapt to new diseases and technologies without requiring fundamental system changes
3Productivity
If device manufacturers' devices and APIs generate data in incompatible formats, then each device can be optimized for its specific function, but the integration of diverse devices into a health monitoring system becomes complicated
Solution Approach 1:
The patent introduces a standardized data model and interface layer that acts as an intermediary between diverse device APIs and the central health monitoring system. This intermediary layer translates incompatible device formats into a unified data structure, allowing optimized device functionality to be maintained while simplifying integration into the health monitoring platform
Data Source
AI summary
A computer-implemented method performed at a health study management system collects health-related data from data sources, including sensors monitoring system users. A modular data ingestion subsystem includes interface modules adapted to receive health-related data from a respective type of data source. A modular data processing subsystem includes processing modules, processing health-related data to determine derived health indicators. The system receives configuration information for a health study using the health study management system, the configuration information specifying data collection activities, for collecting respective health-related data. The data collection activities include sensor-based data collection activities associated with a sensor type for collecting sensor data, and processing collected sensor data. The data ingestion subsystem and data processing subsystem are configured for the health study. Health-related data is collected from the data sources via the configured data ingestion subsystem and processed using the configured data processing subsystem. A study dataset is generated and output.