Cloud Service System for Clinical Research Data Conversion
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Solution Overview
Problem
Small hospitals face significant costs and operational burdens in managing clinical research trials due to the need for multiple clinical research management systems and varying document formats, which hinders efficiency and workload management for researchers and coordinators handling multiple projects from different clients.
Innovation Solution
A clinical research information cloud service system comprising application servers, data transfer servers, and a data conversion server that connects researcher terminals to research client systems, allowing for metadata-based conversion of communication data structures between different systems, enabling seamless information sharing and management across multiple projects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a small hospital installs multiple clinical research management terminals for different research clients, then the hospital can participate in multiple clinical research projects, but the operational burden and training requirements for staff increase significantly
Solution Approach 1:
The patent implements a universal terminal design where a single clinical research management terminal can access and manage multiple clinical research projects from different clients. The system uses a unified interface and operation method that works across all projects, eliminating the need for separate terminals for each client while maintaining full functionality for participating in multiple research initiatives.
Solution Approach 2:
The patent combines multiple clinical research management functions into a single integrated terminal system. Instead of having separate terminals for different research clients, the system merges access to multiple projects, data management, and coordination functions into one unified platform that staff can operate without needing to learn multiple different systems.
2Productivity
If a clinical research management system is introduced to improve research efficiency, then information sharing and document management are enhanced, but the system cost becomes prohibitive for small hospitals
Solution Approach 1:
The patent implements a cloud-based system where the research clients (pharmaceutical companies, medical device manufacturers) host and maintain the management systems on their own servers. Small hospitals can access these systems through standard terminals without needing to purchase or maintain expensive local infrastructure. The system providers serve themselves by offering access to multiple research institutions, reducing the burden on small hospitals.
Solution Approach 2:
The patent introduces a cloud service platform as an intermediary between research clients and participating hospitals. This platform enables small hospitals to access clinical research management capabilities through standardized interfaces without directly bearing the full cost of system deployment and maintenance. The intermediary model allows resource sharing and cost distribution across multiple institutions.
3Adaptability or versatility
If different document formats are used for different research clients, then each client's specific requirements are met, but the workload for creating and managing documents increases for research staff
Solution Approach 1:
The patent implements preliminary standardization of document formats and templates during system setup. Common document structures, fields, and formats are pre-configured based on each research client's requirements. When a new project starts, the appropriate pre-configured templates are automatically applied, eliminating the need for staff to manually create and format documents from scratch for each different client requirement.
Solution Approach 2:
The patent uses parameter-based document management where document formats are defined by configurable parameters rather than fixed rigid structures. The system can dynamically adjust document parameters (such as format type, required fields, validation rules) based on the specific research client and project requirements, while maintaining a consistent underlying document model that reduces manual formatting work.
Data Source
AI summary
A data conversion server mutually converts a structure of a communication data transmitted and received between a data transfer server and an application server, based on a metadata which makes a structure of a communication data defined for each research client system associate with a structure of a communication data commonly used by a plurality of the application servers connected to a researcher terminal.