Clinical Analyzer Crossover Studies With Adaptive Sample Sizing
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Solution Overview
Problem
Current crossover studies in clinical diagnostic analyzers are inefficient and costly, requiring a fixed number of data points over a lengthy period, often leading to inaccurate mean and standard deviation calculations due to high error margins and labor-intensive manual data processing.
Innovation Solution
A system and method for conducting customized automated crossover studies that determine an optimal number of data points based on historical data from the instrument and its peer group, minimizing time, labor, and expense by using a processor to estimate relationships, confidence factors, and simulate sample sizes for desired accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed number of data points (at least twenty) is collected over a lengthy period to ensure statistical reliability, then the accuracy and reliability of mean and standard deviation calculations is improved, but the time required and cost incurred increases significantly
Solution Approach 1:
The patent changes the parameter of sample size from a fixed minimum (20) to a dynamically calculated optimal value based on historical data, peer group information, and desired confidence levels. This allows the study to use fewer data points when historical variability is low, reducing time while maintaining statistical reliability through adaptive parameter adjustment.
Solution Approach 2:
The system incorporates feedback from historical data and peer group performance to continuously improve the estimation of required sample sizes. By using feedback loops that analyze past crossover study results and instrument performance, the system refines its calculations to determine the minimum adequate sample size, reducing unnecessary data collection time.
2Ease of operation
If manual data processing using spreadsheets is used to calculate mean and standard deviation, then the ease of operation is improved, but the productivity and accuracy of data processing deteriorates due to labor intensity and error margins
Solution Approach 1:
The system performs self-service by automatically executing the entire crossover study protocol, including data collection, statistical analysis, and mean/standard deviation calculation. The analyzer autonomously processes data without requiring manual spreadsheet intervention, eliminating labor-intensive operations while maintaining high productivity and accuracy through built-in computational algorithms.
Solution Approach 2:
The patent replaces the mechanical manual processing system (spreadsheets and manual calculations) with an automated computational system integrated into the clinical diagnostic analyzer. This substitution uses electronic processing and programmed statistical algorithms to perform data analysis, significantly improving productivity while reducing human error.
3Measurement precision
If twenty data points are collected to determine standard deviation with desired accuracy, then the measurement precision is improved, but the loss of time and expense increases due to requiring eighty data points and lengthy collection periods
Solution Approach 1:
The system dynamically adjusts the required number of data points based on historical variability, peer group performance, and desired precision levels. When historical data indicates low variability, the system calculates that fewer data points are needed to achieve the same precision, reducing the quantity of samples required while maintaining measurement accuracy through adaptive statistical methods.
Data Source
AI summary
Systems and methods for conducting customized automated crossover studies for clinical diagnostic analyzers are disclosed. In disclosed embodiments, an optimal number of samples to run on a new QC material is determined based on historical information of the analyzer instrument and a peer group of similar instruments. Using the determined optimal number of samples, the crossover study is conducted, and the results are reported.