What parameters do automated hematology analyzers use moving averages to monitor as part of internal quality control in clinical laboratories, specifically in Hematology (Hematology)

Automated Hematology Analyzers Use Moving Averages for RBC Parameters

Automated hematology analyzers use moving averages to monitor the instrument's performance in determining RBC parameters. 1

Understanding Moving Averages in Hematology Analyzers

Moving averages are a statistical technique used in automated hematology analyzers to monitor instrument performance and ensure quality control. This technique is particularly important for:

RBC Parameters Monitoring

Moving averages are specifically applied to red blood cell (RBC) parameters as indicated in the Journal of Thrombosis and Haemostasis guidelines 1. These parameters include:

• Red cell count
• Hemoglobin concentration
• Hematocrit
• Mean corpuscular volume (MCV)
• Mean corpuscular hemoglobin (MCH)
• Mean corpuscular hemoglobin concentration (MCHC)

How Moving Averages Work in Hematology Analyzers

1. The analyzer continuously collects data from patient samples
2. It calculates a running average of specific parameters over time
3. This moving average serves as an internal quality control mechanism
4. Deviations from established ranges trigger alerts for potential instrument malfunction

Why RBC Parameters Are Monitored with Moving Averages

RBC parameters are particularly suited for moving average monitoring because:

• They have relatively stable distributions in the general patient population
• They demonstrate predictable statistical behavior
• Significant shifts in these parameters often indicate analyzer malfunction rather than true population changes
• The stability of these parameters makes them ideal for ongoing quality assessment

Comparison with Other Cell Parameters

While the question asks specifically about which parameters are monitored using moving averages, it's worth noting how RBC parameters compare to other options:

• Reticulocyte parameters (Option A): These are less commonly monitored with moving averages due to their greater biological variability and lower testing frequency.

• RBC parameters (Option B): These are indeed monitored using moving averages as discussed above.

• PLT parameters (Option C): While platelet parameters can be monitored, they show greater biological variability than RBC parameters, making them less ideal for moving average monitoring.

• WBC parameters (Option D): White blood cell parameters typically show too much biological variability between patients to serve as reliable indicators for moving average monitoring.

Clinical Significance and Quality Control Implications

The use of moving averages for RBC parameters is critical for:

• Detecting subtle shifts in analyzer performance before they become clinically significant
• Ensuring accuracy of patient results without requiring additional control materials
• Providing continuous quality monitoring between formal quality control checks
• Complying with laboratory accreditation requirements for internal quality control

This approach to quality control is part of a broader system of quality assurance in clinical laboratories that ensures accurate and reliable test results for optimal patient care.