Medical Analyzer Condition Inference From Automatic Notifications
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Solution Overview
Problem
Managing the maintenance and monitoring of multiple Point of Care (POC) analytical devices is challenging due to the large number of automated notifications they generate, making it difficult to track the coherent status information of these devices.
Innovation Solution
A computer-implemented method and apparatus that processes automatic notifications from POC devices to infer their condition by applying identified characteristics to a model, and generates notifications reporting the inferred conditions, which can be used to improve maintenance scheduling and predict potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated notifications are generated for each POC device event, then device status information is captured comprehensively, but the volume of notifications becomes unmanageably large
Solution Approach 1:
Multiple individual notifications from different POC devices and various device components are merged into a single consolidated notification that provides a comprehensive overview of device status, reducing notification volume while maintaining monitoring reliability
Solution Approach 2:
The notification system is designed to handle multiple types of device events and status information through a universal notification format that can convey diverse information types in a single standardized message structure
2Loss of information
If all automatic notifications are processed and monitored individually, then complete device status information is obtained, but the complexity of monitoring increases significantly
Solution Approach 1:
The monitoring system segments device status information into hierarchical levels, processing detailed individual notifications at lower levels and aggregated summary information at higher levels, reducing overall system complexity while preserving information completeness
Solution Approach 2:
An intermediary processing layer is introduced between individual device notifications and the final monitoring output, which aggregates and synthesizes information from multiple sources before presenting it to users, simplifying the monitoring complexity
3Measurement precision
If detailed characteristics are extracted from each notification, then accurate device condition inference is achieved, but the processing time and computational resources increase
Solution Approach 1:
Notification characteristics and device condition patterns are pre-analyzed and stored during device operation, allowing for rapid condition inference when needed without performing complete real-time analysis, thus reducing processing time while maintaining accuracy
Solution Approach 2:
The system performs partial analysis of notification characteristics by focusing only on the most relevant features for condition inference rather than analyzing all possible notification attributes, reducing processing time while preserving sufficient accuracy
Data Source
AI summary
A computer-implemented method for inferring a condition of at least one analytical device based on at least one automatic notification received over a network from the analytical device is disclosed. The method comprises receiving, at a data processing agent, at least one automatic notification from at least one analytical device, processing, at the data processing agent, the at least one automatic notification, to thus identify one or more characteristics of the at least one automatic notification from the at least one analytical device, inferring, at the data processing agent, the condition of the at least one analytical device, by applying the one or more identified characteristics to a model; and generating, at the data processing agent, a notification reporting the inferred condition of the analytical device.