Medical Device Status Information Handling System
Solution Overview
Problem
Users face difficulties in understanding error messages from medical device status information due to varying error codes from different conditioners, making it challenging to identify the nature and severity of errors, differentiate between machine and human errors, and predict potential device failures.
Innovation Solution
A method that receives status information from medical devices, determines error conditions, associates global error categories, and outputs fault information including identification, status, and severity levels, using machine learning algorithms to analyze patterns and predict future errors, thereby facilitating user understanding and proactive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If different types of conditioners provide different error codes, then device-specific monitoring capability is improved, but user understanding of error nature and severity deteriorates
Solution Approach 1:
The system introduces an intermediary layer (central control system) that translates device-specific error codes into standardized global error categories. This mediator converts the heterogeneous error information from multiple conditioners into a unified format that users can easily understand, resolving the contradiction between maintaining device-specific monitoring precision and improving user comprehension.
Solution Approach 2:
The system transforms error information by changing its parameter representation - converting from device-specific error codes (original parameter format) to global error categories with standardized severity levels (transformed parameter format). This parameter transformation allows the same error information to be expressed in multiple ways: preserving the original device-specific details while also providing a standardized, user-friendly classification.
2Measurement precision
If device-specific error codes are used, then error identification accuracy is improved, but differentiation between machine and human error deteriorates
Solution Approach 1:
The system segments error information into multiple hierarchical levels: device-specific error codes (identifying the specific error), global error categories (classifying the type of error), and severity levels (indicating the impact). This segmentation allows each piece of information to serve a specific purpose - device codes maintain identification accuracy while global categories and severity indicators provide context about whether the error is machine-related or user-related.
Solution Approach 2:
The global error category system serves multiple functions simultaneously: it standardizes error classification across different devices, indicates severity levels, and provides information about error causes (machine vs. human). This multi-functional approach allows a single standardized framework to address multiple information needs that would otherwise require separate systems.
3Reliability
If comprehensive status information is collected, then device monitoring capability is improved, but system complexity deteriorates
Solution Approach 1:
The central control system acts as an intermediary that manages the complexity of collecting and processing comprehensive status information from multiple conditioners. It provides a unified interface for data collection, standardizes the information format, and implements the error categorization logic, thereby isolating the complexity from the user side while maintaining high monitoring capability.
Solution Approach 2:
The system manages complexity by transforming heterogeneous status information parameters from different devices into a standardized parameter structure. By changing the parameter representation to a universal format with consistent data types and structures, the system can collect comprehensive information without proportionally increasing system complexity.
Data Source
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AI summary
This provides a method for handling medical device status information, comprising the steps of: receiving status information data from one or more medical devices, wherein the status information data is received in a data format specific to each medical device; determining that the status information data indicates a fault condition of the one or more medical devices; assigning one or more global fault categories from a predetermined list of global fault categories to each fault condition, wherein the global fault categories are not specific to any particular medical device; and outputting fault information data, comprising: identification data identifying a particular medical device; status information data received from the particular medical device; and the one or more global fault categories assigned to the detected fault condition.