SIGMA METRICS AS A TOOL FOR EVALUATING THE PERFORMANCE OF INTERNAL QUALITY CONTROL IN A CLINICAL CHEMISTRY LABORATORY OF A TERTIARY HOSPITAL
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Keywords
Quality Control; Clinical Chemistry Tests; Laboratories, Hospital; Quality Assurance, Health Care; Statistics as Topic; Tertiary Healthcare
Abstract
Sigma metrics provide a quantitative approach to assess analytical performance by integrating total allowable error, bias, and imprecision. Limited evidence exists regarding sigma-guided quality control optimization in resource-constrained laboratory settings with poor baseline performance.
Aim: To evaluate analytical performance of twelve biochemical parameters using sigma metrics methodology and assess the effectiveness of enhanced quality control rules for analytes with sigma values below 3 in a tertiary care hospital laboratory.
Methods: This prospective study evaluated sigma metrics for Albumin, Beta HCG, Calcium, Chloride, Creatinine, Ferritin, Magnesium, Potassium, Sodium, Total Bilirubin, Total Protein, and TSH across three quality control levels over six months (August 2022-January 2023). Sigma values were calculated using σ = (TEa - |Bias|) / CV formula. Enhanced quality control rules were implemented for analytes with sigma <3 during February-April 2023, and pre- and post-implementation outcomes were compared.
Results: Of 26 analyte-level combinations, 24 (92.31%) demonstrated poor performance (σ <3), with only Beta HCG Level 1 achieving good performance (σ = 4.45) and TSH Level 1 reaching marginal performance (σ =3.41). Following enhanced quality control implementation, 11 of 22 combinations (50%) showed improvement while 11 (50%) deteriorated. Beta HCG Level 2 achieved the greatest improvement (167.1% increase,σ =2.07 to 5.53), while Magnesium levels showed substantial gains (173.7% and 110.9%). However, albumin and creatinine demonstrated significant deterioration (55-67% decreases).
Conclusion: Sigma metrics effectively identify analytical deficiencies and guide quality control optimization. The mixed outcomes following enhanced rule implementation emphasize the need for individualized rather than uniform optimization strategies in laboratories with predominantly poor baseline performance.
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Anusree M
Indiana Institute of Allied Health Sciences, Mangaluru, Karnataka
Dr.Suriyan.S.Nair
A.J.Institute of Medical Sciences and Research Centre, Mangaluru, Karnataka
Dr.Reshma Kiran
P.E.S University Institute of Medical Sciences, Electronic City, Bengaluru, Karnataka
Dr.Janice D’Sa
A.J.Institute of Medical Sciences and Research Centre, Mangaluru, Karnataka
Dr.Prathima M.B
A.J.Institute of Medical Sciences and Research Centre, Mangaluru, Karnataka
Dr Kiran Kumar PK
A.J.Institute of Medical Sciences and Research Centre, Mangaluru, Karnataka