Dynamic Reference Ranges for Medical Lab Quality Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing laboratory testing systems fail to account for newly observed variations in analyte values, leading to flawed quality control procedures and inefficiencies, as they rely on static reference ranges that do not reflect temporal or demographic changes in patient populations.
Innovation Solution
A computer-based quality control system that calculates a grade for test batches by factoring in time-periodic and demographic variations, using reference ranges adjusted for parameters like age, sex, and location, to determine whether tests need retesting or can be released, thereby avoiding false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static reference ranges are used for quality control, then the quality control procedure is simple and efficient, but the reliability of quality control deteriorates because newly observed variations in analyte values are not reflected
Solution Approach 1:
The patent transforms static reference ranges into dynamic reference ranges that automatically adjust based on newly observed analyte variations. The system continuously updates reference ranges using statistical methods (e.g., moving averages, control charts) that incorporate recent test results, allowing the quality control system to adapt to temporal variations in analyte values while maintaining automated operation.
Solution Approach 2:
The system implements feedback loops where test results are continuously monitored and fed back into the reference range calculation process. When variations in analyte values are detected, the system automatically adjusts reference ranges and notifies relevant personnel, creating a closed-loop quality control system that responds to actual performance data.
2Productivity
If static reference ranges are used, then the system is easy to operate, but false positives increase causing unnecessary retesting
Solution Approach 1:
The patent changes the parameters of reference ranges from fixed values to dynamically adjustable values based on statistical analysis of test results. The system monitors parameters such as mean, standard deviation, and coefficient of variation, and automatically adjusts reference ranges when these parameters indicate genuine shifts in analyte values, thereby reducing false positives while maintaining operational efficiency.
3Measurement precision
If dynamic reference ranges incorporating temporal and demographic variations are implemented, then the accuracy of quality control improves, but the complexity of the system increases
Solution Approach 1:
The patent segments the population into demographic subgroups (e.g., age groups, sex, ethnicity) and establishes separate dynamic reference ranges for each segment. This allows the system to account for demographic variations in analyte values without requiring an overly complex monolithic model, as each segment can be analyzed and updated independently.
Solution Approach 2:
The system adds temporal and demographic dimensions to the reference range model, transforming it from a single static value to a multi-dimensional framework that varies by time, population segment, and analyte type. This dimensional expansion enables more accurate quality control while using standardized statistical methods that can be implemented through automated software.
4Reliability
If traditional quality control methods are used, then the process is fast and simple, but unnecessary retesting occurs reducing productivity
Solution Approach 1:
The system performs preliminary statistical analysis and dynamic reference range updates before final quality control decisions are made. By proactively adjusting reference ranges based on observed variations and notifying personnel in advance, the system prevents false positive flags that would otherwise trigger unnecessary retesting, thereby saving time while maintaining reliability.
Data Source
AI summary
Laboratory testing plays a significant and growing role in the delivery of medical services. Fresh analysis of past test results has led to discovery of previously unknown correlations between statistical properties of analyte values and parameters such as age, sex, and region. Observed values in patient populations have also newly been discovered to show both secular and regular periodic variations over time. Embodiments of the invention may use information about these correlations to improve quality control and other statistical analysis of patient samples by applying adjusted reference ranges to quality control methodologies, and providing a quality control grade for patient samples based on the adjusted reference ranges.