Analysis of hematology quality control using six sigma metrics

Author:

Goel Shreya1,Nisal Amit R.1,Raj Ankita1,Nimbargi Ravindra C.1

Affiliation:

1. Department of Pathology, Bharati Vidyapeeth Deemed to be University Medical College Hospital and Research Centre, Pune, Maharashtra, India

Abstract

ABSTRACT Introduction: Clinical laboratories serve a critical role in increasing the efficiency of patient care. Choosing the right test, getting trustworthy results and appropriate interpretation are of utmost importance in improving the patient’s well-being. Quality management strategies should be applied in routine patient care because laboratory errors have a major impact on the quality of patient care. In sigma metrics, errors identified are quantified as percentage errors or defects per million (DPM). It aims at improving the quality control (QC) process by forming an appropriate strategy. Aim and Objectives: To analyze the internal quality control (IQC) of hematology analytes using the sigma metrics method and to devise the frequency of IQC by the results of six sigma metric analysis. Materials and Methods: This study was conducted in a tertiary care center of western India. Internal quality control (IQC) data sets of five analytes- Red Blood Cell count (RBC), Hemoglobin (Hb), Hematocrit (Hct), White blood cell count (WBC), and Platelet count (PLT) were analyzed retrospectively of six months using Beckman Coulter DXH 800 hematology analyzers. Results: The observed sigma value was >6 for Hb, TLC, and PLT, indicating excellent results and requiring no modification in IQC. The Sigma value was between 3 and 4 for RBC and Hct suggested the need for improvement in quality control (QC) processes. No analytes showed a Sigma value of <3. Conclusion: Sigma metrics provide a quantitative framework that helps to assess analytic methodologies and can serve as an important self-assessment tool for quality assurance in the clinical laboratory.

Publisher

Medknow

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