Evaluation of quality indicators in pre-analytical phase of testing in clinical biochemistry laboratory of a tertiary care hospital in India

Authors : Nishtha Wadhwa

DOI : 10.18231/j.ijcbr.2020.076

Volume : 7

Issue : 3

Year : 2020

Page No : 354-356

Introduction: Preanalytical errors account for nearly 70% of the total number of laboratory errors. Hence,
controlling them is a big challenge. Quality Indicators expressed as sigma metrics provide a convenient
way to objectively quantify errors.
Aim: To quantify performance in the preanalytical phase of the testing process in Clinical Biochemistry
laboratory of a tertiary care hospital in India using quality indicators.
Materials and Methods: Study period: January to September 2016. Quality Indicators (QIs) used: samples
lost–not received (QI-8); samples collected in an inappropriate blood collection tube (QI-9); haemolyzed
samples (QI-10); clotted samples (QI-11); samples with insufficient sample volume (QI-12); improperly
labelled (QI-15); damaged in transport (QI-14). Sigma metric was calculated for the above mentioned QIs.
Results: The total number of samples received during the study period was 5,73,694 and the total number
of preanalytical errors was 1,782. Among the preanalytical errors, 43.9% were samples with insufficient
volume (sigma: 4.5), 33.2 % were haemolyzed samples (sigma: 4.6), 11.3% were samples collected in an
inappropriate blood collection tube (sigma: 4.9), 6.7% were samples not received in the laboratory (sigma:
5.1), 4.2% were clotted samples (sigma: 5.2), 0.7% were improperly labelled (sigma: 5.6), only one sample
(0.06%) was lost over 9 months period due to spill in pneumatic chute.
Conclusion: QIs serve as a tool to monitor process performance in the laboratory. In this study, insufficient
sample volume and haemolysis were the major causes of preanalytical errors. All QIs had acceptable sigma
value. Regular training of phlebotomists regarding the preanalytical errors needs to be conducted to achieve
six sigma performance.

Keywords: Preanalytical errors, Quality indicators, Insufficient sample volume, Hemolysis.


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