Evaluación del desempeño de la calidad analítica mediante la aplicación de la métrica Sigma en el área de hematología clínica: Estudio en la Unidad Técnica de Patología Clínica del Hospital de Especialidades Carlos Andrade Marín

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Authors: Lenin Ramiro Villalta-Guzmán, Maricela Alexandra Chacha García, Ingrid Dannae Briones-Ramírez
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Abstract

INTRODUCTION: Clinical laboratories seek to standardize processes that guarantee accurateand reliable results. The Sigma metric has established itself as an effective tool for evaluating analytical performance by identifying defects that traditional quality control methods failto detect. A Sigma value ≥6 is considered world-class performance; however, its application inhematology is still limited. OBJECTIVES: To evaluate the analytical performance of hematological parameters using theSigma metric in Mindray® CAL 6000 and BC 6200 analyzers, in order to identify opportunitiesfor improvement and optimize the frequency of quality control. MATERIALS AND METHODS: A retrospective (cross-sectional) observational study was conductedusing internal quality control (IQC) data recorded between July and December 2024on Mindray›s Innolab HCP platform. The Sigma calculation was performed using the formula: Sigma = (ETa% value - Bias%)/CV%, taking the total allowable error (ETa) limits from the CLIA guide. The bias and coefficient of variation were calculated. RESULTS: The parameters white blood cells (WBC), hemoglobin (HGB), and platelets (PLT)achieved a Sigma ≥6, reflecting world-class performance. Red blood cells (RBC) obtained a Sigma ≥5, considered good, with a need for adjustment, while hematocrit (HCT) showed a Sigma≥3, corresponding to marginal performance. CONCLUSIONS: Parameters such as hemoglobin, leukocytes, and platelets showed highperformance, while hematocrit and erythrocytes revealed correctable random and systematicerrors. These results justify adjusting the frequency of quality control according to the Sigma obtained,improving efficiency, reducing costs, and promoting evidence-based decisions throughintegration with models such as the Deming cycle.

Fields of Study & Subjects

Clinical Laboratory Practices and Quality Control Healthcare Quality and Management Management Systems and Quality Improvement

Publication details

Publication date
3 February 2026
Language
ES
Document type
Dataset