Sample Quality Verification for Medical Analytical Testing
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Solution Overview
Problem
Existing laboratory testing methods often result in errors and invalid results due to poor sample quality, leading to wastage of resources, delayed medical interventions, and reduced laboratory throughput, primarily caused by issues during sample collection, handling, and processing.
Innovation Solution
A computer-implemented method and system that assesses the compliance of medical samples with analytical test specifications before processing, determining sample quality metrics and taking mitigation actions to reassign samples to appropriate tests, thereby reducing resource wastage and increasing valid test results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If laboratory testing is performed on all collected samples, then complete diagnostic coverage is achieved, but resource wastage increases and valid throughput decreases due to poor sample quality
Solution Approach 1:
The system performs preliminary assessment of sample quality metrics (hemolysis, icterus, lipemia indices) and evaluates compliance with test specifications before the actual analytical testing is conducted. This preliminary action identifies non-compliant samples that would produce invalid results, allowing them to be excluded from testing and thereby preventing resource wastage while maintaining high validity rates for tests that are performed.
2Loss of energy
If sample quality verification is performed before testing, then resource wastage is reduced, but processing time increases due to additional verification steps
Solution Approach 1:
The system automatically calculates sample quality metrics and determines compliance status without requiring manual intervention. The analytical testing management system autonomously assesses sample quality, identifies non-compliant samples, and excludes them from testing, thereby minimizing additional processing time while achieving resource efficiency. The verification process is integrated into the existing workflow rather than being a separate manual step.
3Productivity
If non-compliant samples are tested anyway, then diagnostic coverage is maintained, but invalid results increase and patient outcomes are delayed
Solution Approach 1:
The system provides feedback on sample compliance status by comparing measured quality metrics against test specification requirements. This feedback mechanism enables the system to identify non-compliant samples and exclude them from testing, ensuring that only samples with adequate quality proceed to analytical testing. This maintains high result validity while preserving diagnostic throughput by avoiding invalid results that would require retesting.
Data Source
AI summary
A computer-implemented method for optimising an assignment of one or more medical samples to one or more analytical tests to be conducted on those medical samples. The method comprises the steps of: obtaining an initial assignment of the one or more medical samples to the one or more analytical tests; determining a compliance status for the or each medical sample, the compliance status indicating: (i) whether a sample quality metric of the or each medical sample violates an analytical test specification of the medical sample's assigned analytical test(s) in the initial assignment and/or (ii) whether the or each medical sample is unprocessable; and performing a mitigation action if one or more compliance status indicate: (i) that the sample quality metric of a given medical sample violates the analytical test specification and/or (ii) a given medical sample is unprocessable.