Medical Records Simulation Tool for Predictive Load Testing
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Solution Overview
Problem
Healthcare systems face challenges in managing uneven computational loads across networks of computing devices due to varying transaction volumes, leading to performance spikes and potential system failures or slowdowns, which are difficult to predict and resolve without disrupting live operations.
Innovation Solution
A simulated computing environment is generated to test network performance by monitoring transaction traffic and simulating CPU and memory usage, allowing for load testing to identify errors without causing them in a live environment, and diverting messages to devices with additional capacity to prevent downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load testing is performed in a live environment to identify performance issues, then system reliability can be improved, but it causes system failures and disruptions to normal operations
Solution Approach 1:
The patent creates a simulated computing environment that replicates the live medical records system's architecture, devices, and transaction patterns. This copy allows comprehensive load testing and performance validation without affecting the actual system operations, resolving the contradiction between testing reliability and maintaining availability
Solution Approach 2:
The system performs load testing and performance validation in advance within the simulated environment before deploying changes to the live system. This preliminary action identifies potential failures and optimizes performance without disrupting production operations, improving reliability while preserving system availability
2Reliability
If message volume is increased to test system capacity, then performance limits can be identified, but it causes computational bottlenecks and errors in the live system
Solution Approach 1:
The simulated environment replicates the live system's computing devices, transaction processing logic, and network architecture. By injecting test messages into this copy, the system can identify performance bottlenecks and capacity limits without consuming actual computational resources or causing errors in the production system
Solution Approach 2:
The system performs capacity testing and bottleneck identification in advance within the simulated environment. This allows optimization of message routing, load balancing, and system configuration before deploying to live operations, improving performance prediction accuracy without overloading production systems
3Measurement precision
If performance monitoring is continuously performed in the live system, then real-time issues can be detected, but it increases system complexity and resource consumption
Solution Approach 1:
The patent implements performance monitoring instrumentation within the simulated environment rather than the live system. This copy captures detailed performance metrics, transaction patterns, and system behavior under various loads, providing measurement precision without adding monitoring complexity to the production system
Solution Approach 2:
The simulated environment acts as an intermediary layer between testing requirements and the live system. It captures and analyzes performance data without requiring direct instrumentation of production devices, reducing system complexity while maintaining monitoring accuracy through realistic transaction replication
Data Source
AI summary
Systems for testing computing devices of a medical records system using a simulated environment are provided. The simulated environment is generated by identifying transaction traffic over the network, where the transaction traffic comprises messages of different transaction types. A computing device is configured to output a simulated status by extrapolating a performance of the computing devices upon receiving a series of messages indicating the transaction types. The output of the computing device may indicate an error in the simulated environment where the performance of a computing device exceeds a performance threshold. Based on the error indication, transaction traffic can be diverted from the computing device to another computing device having performance capacity.