Statistical process control methods for quality inspection of blood component samples: a case study

Abstract

Objective To explore the analytical methods for detecting data in the process of quality inspection of blood component samples. Methods The quality inspection data of blood component samples from 2018 to 2022 in our center were collected. Based on the principles of statistical process control, control charts were created using Minitab software to analyze key test items. Results The P control chart was used to analyze the pass rate of platelet content and revealed one out-of-control point. The normality test was performed on plasma protein content to analyze the causes of data fluctuations for further improvement. The mean and range control chart was utilized for hematocrit measurement, with abnormal data trends detected. Further analysis of the normality test and process capability analysis was conducted, resulting in a Cpk value of 0.67. Conclusion By applying statistical process control methods, the study employed P control charts to analyze count data in the quality inspection of blood component samples, conducted normality tests for measurement data, and utilized mean and range control charts to identify abnormal data trends. For data conforming to a normal distribution, the process capability index (Cpk) was calculated to explore effective monitoring methods for ensuring stability in the blood supply process.

Keywords

• quality inspection of blood component samples
• statistical process control
• control charts
• minitab software