Distributed Medical Software Platform for Containerized Device Integration
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Solution Overview
Problem
Healthcare facilities face complex, costly, and inefficient integration and management of medical software and systems due to regulatory verification and validation requirements, leading to potential hardware and software failures that cascade throughout the facility, jeopardizing patient safety.
Innovation Solution
A distributed medical software platform leveraging clustered architectures, utilizing cloud technology and Kubernetes systems to scale compute resources, host containerized medical applications, and provide an API data model framework for orchestration, enabling scalable and redundant hosting of medical applications while maintaining compliance with clinical regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a patchwork of medical software and systems is used to meet diverse clinical needs, then adaptability and versatility are improved, but device complexity and integration difficulty worsen
Solution Approach 1:
The patent implements a universal container orchestration platform that can host multiple medical applications with different functional requirements. The system provides a common infrastructure layer that supports diverse clinical applications through standardized interfaces and resource management, allowing one platform to serve multiple purposes without requiring separate dedicated systems for each application.
Solution Approach 2:
The patent segments medical applications into containerized units that can be independently deployed, managed, and scaled. Each application is encapsulated in its own container with defined resource requirements, allowing the system to manage complexity by dividing the overall system into manageable, isolated components while maintaining adaptability through flexible composition of these segments.
2Reliability
If regulatory verification and validation requirements are strictly followed for each medical application, then reliability and safety are improved, but integration time and cost worsen
Solution Approach 1:
The patent implements preliminary validation of the container orchestration platform and its infrastructure components before deploying medical applications. By pre-verifying the platform's security, reliability, and compliance features, the system reduces the validation time required for individual applications while maintaining regulatory standards. The platform itself undergoes rigorous verification to establish trust boundaries.
Solution Approach 2:
The patent uses containerization to create isolated, reproducible environments for medical applications. Each container is a self-contained copy of the application with its dependencies, allowing for consistent validation across different deployment scenarios. This copying approach enables validation results to be reused and replicated, reducing redundant verification efforts while maintaining safety standards.
3Reliability
If hardware and software redundancy is implemented to prevent failures, then reliability is improved, but device complexity and resource requirements worsen
Solution Approach 1:
The patent merges redundancy management into the container orchestration platform, combining multiple failure prevention mechanisms (resource monitoring, health checks, automated recovery) into a unified system. The orchestration layer consolidates redundancy functions that would otherwise require separate systems, reducing overall complexity while maintaining reliability through integrated resource management and coordinated failover procedures.
4Productivity
If compute resources are scaled up to handle peak medical workloads, then productivity and service quality are improved, but resource allocation efficiency and cost worsen
Solution Approach 1:
The patent implements dynamic resource allocation where compute resources are automatically adjusted based on real-time workload demands. The container orchestration platform monitors resource utilization and dynamically scales, migrates, or reallocates containers across available hardware resources. This dynamic approach allows the system to maintain high productivity during peak workloads while optimizing resource efficiency during lower utilization periods, avoiding the need for permanently over-provisioned infrastructure.
Data Source
AI summary
Intelligent, distributed medical software management (e.g., using a computerized tool) is enabled. A system can comprise a processor, and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising determining requirement information representative of one or more requirements of a medical application of a group of medical applications, wherein the medical application is associated with a medical device, based on the requirement information, allocating elements of a cluster employable to host and run the medical application in a medical application container, wherein the elements of the cluster are determined to satisfy the requirement information, and in response to allocating the elements of the cluster, hosting the medical application in the medical application container, wherein hosting the medical application comprises communicatively coupling the medical application to the medical device.