Automated quality control for the haematology laboratory

Area of Science:

• Clinical Laboratory Science
• Statistical Quality Control

Background:

• Intralaboratory quality control is crucial for reliable diagnostic testing.
• Sophisticated statistical methods can improve the analysis of quality control data.
• Existing methods for monitoring laboratory instruments may lack efficiency.

Purpose of the Study:

• To describe two simple, statistically-driven methods for analyzing intralaboratory quality control data.
• To provide an automated quality control solution for the Coulter S blood counter.
• To explore the potential for developing simple, dedicated apparatus for quality control.

Main Methods:

• Utilized cumulative sum (cusum) graphing with a plastic grid for visual assessment of quality control data.
• Developed an equivalent computer-based procedure for automated, on-line quality control.
• Applied statistical techniques to analyze intralaboratory quality control data from laboratory instruments.

Main Results:

• The cusum graph method provides a straightforward way to assess quality control trends.
• The automated computer procedure offers efficient on-line quality control for the Coulter S blood counter.
• Both methods demonstrate the utility of statistical analysis in enhancing laboratory quality control.

Conclusions:

• Simple statistical methods can effectively analyze intralaboratory quality control data.
• Automated and computer-assisted quality control improves laboratory efficiency and reliability.
• Further development of simple apparatus for quality control is feasible and recommended.