SIX SIGMA EVALUATION OF 17 BIOCHEMISTRY PARAMETERS USING BIAS CALCULATED FROM INTERNAL QUALITY CONTROL AND EXTERNAL QUALITY ASSURANCE DATA PROCENA 17 BIOHEMIJSKIH PARAMETARA METODOM SIX SIGMA NA OSNOVU KORIŠĆENJA I PODATAKA UNUTRAŠNJE I SPOLJAŠNJE KONTROLE KVALITETA


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Çevlik T., HAKLAR G.

Journal of Medical Biochemistry, cilt.43, sa.1, ss.43-49, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 43 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.5937/jomb0-43052
  • Dergi Adı: Journal of Medical Biochemistry
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, Central & Eastern European Academic Source (CEEAS), Veterinary Science Database, Directory of Open Access Journals
  • Sayfa Sayıları: ss.43-49
  • Anahtar Kelimeler: bias, imprecision, quality goal index, quality management, Six Sigma method
  • Marmara Üniversitesi Adresli: Evet

Özet

Background: Six Sigma is a popular quality management system that enables continuous monitoring and improvement of analytical performance in the clinical laboratory. We aimed to calculate sigma metrics and quality goal index (QGI) for 17 biochemical analytes and compare the use of bias from internal quality control (IQC) and external quality assurance (EQA) data in the calculation of sigma metrics. Methods: This retrospective study was conducted in Marmara University Pendik E&R Hospital Biochemistry Laboratory. Sigma metrics calculation was performed as (TEa−bias)/CV). CV was calculated from IQC data from June 2018 – February 2019. EQA bias was calculated as the mean of % deviation from the peer group means in the last seven surveys, and IQC bias was calculated as [(laboratory control result mean–manufacturer control mean)/ manufacturer control mean) x100]. In parameters where sigma metrics were <5; QGI=bias/1.5 CV) score of <0.8 indicated imprecision, >1.2 pointed inaccuracy, and 0.8–1.2 showed both imprecision and inaccuracy. Results: Creatine kinase (both levels), iron and magnesium (pathologic levels) showed an ideal performance with ≥6 sigma level for both bias determinations. Eight of the 17 parameters had different sigma levels when we compared sigma values calculated from EQA and IQC derived bias% while the rest were grouped at the same levels.