Application of R-charts to detection of random errors: a computer simulation study

Area of Science:

• Clinical Chemistry
• Statistical Process Control
• Quality Control

Background:

• R-charts are utilized in statistical process control to monitor data variability.
• Their application in clinical chemistry quality control requires further investigation.
• Traditional methods may not always effectively differentiate between error types.

Purpose of the Study:

• To investigate the utility of R-charts for quality control in clinical chemistry.
• To evaluate the effectiveness of R-charts in identifying systematic versus random errors.
• To assess the cost-effectiveness of R-charts in different analytical run lengths.

Main Methods:

• A computer simulation program was developed to model R-chart performance.
• The study considered a set of five control serums.
• R-chart performance was analyzed for its sensitivity to systematic errors.

Main Results:

• The R-charts demonstrated a power function insensitive to systematic errors.
• R-charts showed potential in discriminating between systematic and random errors when used with Levey-Jennings' charts.
• The technique requires multiple control samples, impacting cost-effectiveness for short runs.

Conclusions:

• R-charts can be a valuable tool for troubleshooting in clinical chemistry quality control.
• Concurrent use with Levey-Jennings' charts enhances error discrimination.
• The method's cost-effectiveness is limited for short analytical runs.