From Data to Quality: Using Six Sigma to Assess Lab Performance

DOI

10.2991/978-94-6239-756-9_6How to use a DOI?

Keywords

Six sigma; Bias; Total allowable error; Standard deviation; Lab performance

Abstract

Since doctors’ decisions are primarily based on laboratory results, accurate test results are essential to the healthcare system. Maintaining accurate laboratory results requires regular performance evaluations. The most recent iteration of total quality management is called Six Sigma. The study’s main goal was to comprehend the benefits of Six Sigma as a performance metric and use it to measure the caliber of outcomes in a clinical biochemistry lab. We examined IQC data from the clinical biochemistry lab. For over 15 years, our lab has been accredited by the NABL. For Siemens Dimension EXL 200 fully automated chemistry analyzers for both levels of IQC control (BR1 & BR2), data of 23 parameters were retrospectively examined over a 6-month January 2025 to June 2025.The results were plotted on a Levey-Jennings chart, were analyzed statistically. Alkaline Phosphatase, CRP, Iron, Magnesium, HDL & Triglycerides, satisfactory sigma values (>6), indicating less strict QC guidelines and low false rejection. The sigma values for parameters were found to be between 3 &6: albumin, total bilirubin, direct bilirubin, calcium, creatinine, glucose, phosphorus, protein, AST, ALT, uric acid, sodium, potassium, chloride, and glycosylated hemoglobin. It`s acceptable, but it indicates that additional QC guidelines need to be put in place. Parameters urea and cholesterol had poor sigma scores (<3), indicating that these procedures need to be improved. The IQC process would be greatly improved by the application of six sigma principles, which also offer the justification for the precise amount of QC that is required. The Six Sigma methodology is the best option for resolving managerial and analytical issues in laboratory and reducing errors.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Pratik Poladia
AU  - Rashmi Tupe
AU  - Preeti Chavan
AU  - Chital Naresh
AU  - Avianash Pagdhune
PY  - 2026
DA  - 2026/08/31
TI  - From Data to Quality: Using Six Sigma to Assess Lab Performance
BT  - Proceedings of the Conference on Bioengineering for Global Health (SYMRESEARCH 2.0 2025)
PB  - Atlantis Press
SP  - 62
EP  - 71
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6239-756-9_6
DO  - 10.2991/978-94-6239-756-9_6
ID  - Poladia2026
ER  -