Automated Quality Control Validation for Biological Analyzers
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Solution Overview
Problem
The existing methods for managing quality control in analyzing devices configured to perform analysis of biological samples are time-consuming and error-prone, requiring manual input of acceptance ranges and validation processes for new quality control sets.
Innovation Solution
A computer-implemented method and system for managing quality control, which involves receiving quality control data, evaluating results against validation requirements, storing acceptance ranges, and providing them to analyzing devices, with the option to receive updates from a remote quality control update service, reducing the need for manual input and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual input of acceptance ranges and validation processes is used for quality control sets, then quality control management can be performed, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system enables automatic self-validation of quality control sets by comparing received quality control results against stored validation requirements. The analyzing device autonomously determines whether a quality control set is valid without requiring manual operator intervention for validation processes, thereby reducing time consumption while maintaining reliability through systematic automated checking.
Solution Approach 2:
Acceptance ranges and validation requirements are pre-configured and stored in the system before quality control operations begin. This preliminary setup allows the system to automatically validate quality control sets against predetermined criteria, eliminating the need for time-consuming manual input during actual quality control processes while ensuring consistent and accurate validation.
2Reliability
If manual input of acceptance ranges is required for each quality control set, then quality control parameters can be validated, but the complexity of operation increases
Solution Approach 1:
The system automatically retrieves and validates quality control acceptance ranges against pre-stored validation requirements without requiring manual operator input. The analyzing device performs self-validation by comparing received quality control results with stored criteria, significantly improving ease of operation while maintaining rigorous validation standards through automated systematic checking.
3Reliability
If validation processes are performed manually for new quality control sets, then quality control requirements can be ensured, but productivity decreases
Solution Approach 1:
Validation requirements and acceptance ranges are pre-configured and stored in the system before quality control sets are implemented. When new quality control sets are introduced, the system automatically compares them against these predetermined criteria, enabling rapid validation that ensures requirement compliance without sacrificing productivity. This preliminary setup allows multiple quality control sets to be validated quickly and consistently.
Solution Approach 2:
The system performs automated self-validation of quality control sets by comparing received results against stored validation requirements, eliminating the need for manual validation processes. This automated approach maintains strict compliance with quality control requirements while dramatically increasing productivity by validating multiple sets in rapid succession without human intervention.
4Adaptability or versatility
If acceptance ranges are not pre-stored, then flexibility in quality control set selection is maintained, but errors increase due to manual input
Solution Approach 1:
The system automatically retrieves and validates acceptance ranges for quality control sets without requiring manual operator input. By performing self-service validation against pre-stored criteria, the system eliminates human error in data entry while maintaining flexibility in quality control set selection. The automated process adapts to different quality control sets by retrieving their specific acceptance ranges and validating results accordingly.
Data Source
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AI summary
A computer-implemented method is disclosed for managing quality control of analyzing devices configured to perform analysis of biological samples. Each of the analyzing devices is configured to perform measurements on biological samples and provide parameter values based on the measurements. Quality control of an analyzing device comprises provision of quality control parameter values by performing measurements on samples of a quality control set, and comparison of the quality control parameter values to acceptance ranges associated with the quality control set. The method comprises receiving (from one of the analyzing devices) quality control data comprising quality control results associated with a quality control set identifier, and evaluating the received quality control results in relation to requirements for quality control set validation responsive to an initial reception of quality control data for the quality control set identifier. Responsive to the received quality control results passing the evaluation, the method comprises storing acceptance ranges for the quality control set in association with the quality control set identifier, for further quality controls with the quality control set identifier. Corresponding computer program product, computer-based data processing system, server node, arrangement, and use are also disclosed.