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Analysis of hematology quality control using six sigma metrics
Shreya Goel1, Amit R Nisal, Ankita Raj
1Department of Pathology, Bharati Vidyapeeth Deemed to be University Medical College Hospital and Research Centre, Pune, Maharashtra, India.
Indian Journal of Pathology & Microbiology
|February 23, 2024
Summary
Sigma metrics analysis revealed excellent internal quality control for Hemoglobin, White Blood Cell count, and Platelet count. Red Blood Cell count and Hematocrit require improved quality control processes.
Area of Science:
- Clinical Laboratory Science
- Hematology
- Quality Management
Background:
- Clinical laboratories are vital for patient care efficiency and well-being.
- Laboratory errors significantly impact patient care quality.
- Sigma metrics quantify errors to improve quality control (QC) processes.
Purpose of the Study:
- To evaluate internal quality control (IQC) for hematology analytes using sigma metrics.
- To determine optimal IQC frequency based on sigma metric analysis.
Main Methods:
- Retrospective analysis of six months of IQC data for five hematology analytes (RBC, Hb, Hct, WBC, PLT).
- Utilized Beckman Coulter DXH 800 hematology analyzers.
- Applied sigma metrics to quantify analytical performance.
Main Results:
- Sigma values >6 for Hemoglobin (Hb), White Blood Cell count (WBC), and Platelet count (PLT) indicate excellent performance.
- Sigma values between 3 and 4 for Red Blood Cell count (RBC) and Hematocrit (Hct) suggest a need for QC improvement.
- No analytes demonstrated a sigma value <3.
Conclusions:
- Sigma metrics offer a quantitative method for assessing analytical methodologies in clinical laboratories.
- This approach serves as a valuable self-assessment tool for quality assurance.
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