Blood Analyzer Calibration via Performance Trend Visualization
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Solution Overview
Problem
Ensuring consistency and reproducibility of analysis results from automated blood analyzers is challenging due to variations in instrument performance over time and among multiple systems, making it difficult to assess and maintain accurate calibration.
Innovation Solution
The system and methods allow for the display and analysis of performance measurement data from control samples and calibrators using graphical user interfaces, enabling visualization of trends and variability in CBC parameter measurements over time, allowing technicians to assess instrument performance and detect drift or inconsistencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control samples and calibrators are processed by automated blood analyzers, then analysis results are obtained, but instrument performance varies over time and among multiple systems making consistency difficult to maintain
Solution Approach 1:
The system calculates performance metrics (such as bias, precision, and accuracy) by comparing measured values from control samples and calibrators against target values, then provides feedback to the user interface to display these metrics. This feedback mechanism enables users to monitor instrument performance over time and identify trends that indicate degradation in consistency or reproducibility, allowing for timely calibration adjustments to maintain reliable results across multiple systems.
2Loss of information
If performance measurement data from multiple lots and time points is displayed, then instrument performance can be assessed over time, but data complexity increases making it difficult to quickly identify issues
Solution Approach 1:
The user interface segments the performance measurement data by organizing it into structured components: control samples are separated into different lots, each with its own measured values and performance metrics. The data is displayed in an organized format that groups related information (measured values, target values, and calculated metrics) together, making it easier to navigate and interpret performance trends across multiple time points without being overwhelmed by raw data complexity.
Solution Approach 2:
The system transforms raw measured values into derived performance parameters such as bias (difference from target value), precision (standard deviation), and accuracy. By presenting data in terms of these pre-calculated performance parameters rather than raw measurements, the system reduces the cognitive load on users and simplifies the identification of performance issues, as the transformed parameters directly indicate whether the instrument is performing within acceptable ranges.
3Manufacturing precision
If detailed performance metrics are calculated and displayed for each control sample, then instrument calibration can be maintained, but time required for analysis increases
Solution Approach 1:
The system performs preliminary calculations of performance metrics (bias, precision, accuracy) automatically during the analysis process, before the user needs to interpret the results. The computer automatically compares measured values against target values, calculates the performance parameters, and prepares the data for display. This preliminary processing eliminates the need for manual calculation and review, significantly reducing the time required for performance assessment while maintaining high calibration accuracy through detailed metric calculation.
Data Source
AI summary
Systems and methods for displaying measured values of a complete blood count (“CBC”) parameter include displaying the measured values of the CBC parameter obtained from a plurality of samples from a first lot of a quality control composition, where the displaying includes displaying a marker corresponding to each measured value from the first lot on a plot that includes a two dimensional coordinate system, and where the two dimensional coordinate system includes a first dimension corresponding to a time at which measured values of the CBC parameter were obtained, and a second dimension corresponding to a numerical value of the CBC parameter.