Cloud-Local Medical Data Sync and Version Control
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Solution Overview
Problem
Existing cloud-based Picture Archiving and Communications Systems (PACS) face challenges in maintaining continuous workflow and data synchronization across healthcare facilities, especially during network disconnections and version mismatches, which can lead to downtime and inconsistencies in medical image and data sharing.
Innovation Solution
A cloud-to-local, local-to-cloud synchronization system that automatically updates medical data and checks for application version mismatches, allowing healthcare facilities to switch to local repositories during disconnections and synchronize data upon reconnection, ensuring continuous access to up-to-date medical images and data without requiring all data to be synchronized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud-based PACS is used to improve accessibility and efficiency of medical images, then data sharing between healthcare facilities is improved, but system reliability deteriorates during network disconnections
Solution Approach 1:
The system divides the centralized cloud PACS into distributed components: local PACS servers at each healthcare facility and a central cloud repository. Each local server can independently store and access medical images, enabling facilities to continue operating during network disconnections while maintaining the ability to share data when connected.
Solution Approach 2:
The patent introduces synchronization mechanisms as intermediaries between local PACS servers and the cloud repository. These synchronizers automatically transfer and reconcile data between distributed locations, ensuring consistency across the network while allowing independent operation when disconnected.
2Stability of the object's composition
If automatic update synchronization is implemented across all local servers, then version consistency is improved, but system complexity and update time increase
Solution Approach 1:
The update synchronization system implements feedback mechanisms where local servers report their application versions to the cloud server. The cloud server tracks version information and automatically identifies which servers need updates, creating a self-regulating update distribution system that reduces manual coordination complexity.
Solution Approach 2:
The system performs preliminary version checking and update preparation before actual deployment. The cloud server pre-configures update packages and prepares synchronization instructions in advance, allowing for coordinated rolling updates that minimize disruption and reduce the complexity of simultaneous multi-server updates.
Data Source
AI summary
A method for updating a system that synchronizes medical data between a cloud repository on a cloud server and a plurality of local repositories on a plurality of local servers of healthcare facilities connected to the cloud server is provided. The method includes, by the cloud server: receiving a request to update a medical synchronization application stored on the cloud server and each of the local servers of the healthcare facilities using an update file; transmitting an instruction to each local server to update the medical synchronization application determining a version information of the medical synchronization application on all of the local servers; and executing the update file to update the medical synchronization application on the cloud server only in the event that cloud server determines that the medical synchronization application of all of the local servers have been updated.