Health Event Workflow Server Priority Processing
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Solution Overview
Problem
Current healthcare systems face challenges in efficiently processing and prioritizing health events from network-aware devices, such as IoT sensors, which require effective classification and reclassification of health events based on biometric data to ensure timely and appropriate patient care.
Innovation Solution
A method and system utilizing a workflow server with interconnected processing nodes and consumers, where each node executes multiple consumers for processing high, medium, and low priority health events, allowing for reclassification and prioritization of health events based on severity, type, and patient characteristics, enabling efficient processing and notification to care providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If health events are processed using a single queue and consumer system, then system complexity is reduced, but processing speed and latency for high-priority health events deteriorate
Solution Approach 1:
The patent segments the single consumer system into multiple priority-based consumers (high-priority consumers and low-priority consumers) that operate on separate queues. This segmentation allows high-priority health events to be processed independently and immediately by dedicated high-priority consumers, eliminating the bottleneck of a single shared queue and significantly improving processing speed for critical events.
Solution Approach 2:
The patent applies local quality by assigning different processing characteristics to different parts of the system. High-priority queues are configured with higher processing priorities and are serviced by dedicated high-priority consumers that can immediately process critical health events, while low-priority queues use standard consumers. This localized optimization ensures that critical processing paths have the quality needed for rapid response without making the entire system overly complex.
2Productivity
If multiple priority-based consumers are implemented, then processing efficiency and latency reduction are improved, but system complexity and difficulty of management worsen
Solution Approach 1:
The patent implements dynamic consumer management where consumers can be added, removed, or adjusted based on system workload and priority requirements. The system dynamically routes health events to appropriate consumers based on their priority level, and the consumer pool can be flexibly configured to match varying processing demands. This dynamic approach allows the system to maintain high productivity while adapting to changing conditions without requiring complete system redesign.
Solution Approach 2:
The patent introduces an intermediary event processing system that includes priority queues and a consumer management layer. This intermediary layer sits between event sources and the processing consumers, providing intelligent routing and load distribution. The intermediary manages the complexity by automatically determining which consumer should handle which event based on priority, thereby improving processing efficiency while shielding users from the underlying system complexity.
3Measurement precision
If health events are reclassified based on processing results, then accuracy of event classification is improved, but processing time and system complexity worsen
Solution Approach 1:
The patent applies preliminary action by performing initial classification of health events before they enter the main processing queues. Events are pre-sorted into priority categories based on their characteristics, allowing them to be routed to appropriate priority queues in advance. This preliminary classification reduces the need for extensive reclassification during processing, thereby improving classification accuracy while minimizing additional processing time.
Solution Approach 2:
The patent implements feedback mechanisms where processing results are used to validate and potentially reclassify events. When events are processed, the system evaluates the results and can trigger reclassification if new information indicates a different priority or type is appropriate. This feedback loop improves classification accuracy by incorporating real-time processing information, while the automated nature of the feedback mechanism prevents significant time loss.
Data Source
AI summary
Collecting biometric data from a patient provides numerous opportunities for a care provider to monitor the health of the patient. In one embodiment, the biometric data is used to identify health events that are processed in a workflow that includes a plurality of interconnected processing nodes and queues. In one embodiment, the workflow processes the health events using a priority assigned to the health events. The priority may be assigned based on a severity of the event, the type of the health event, a characteristic of the patient whose biometric data generated the health event, and the like. Each processing node in the event engine may execute multiple consumers for processing health events with different priorities. The health event can further be re-classified based on processing by a consumer.