Related Experiment Video
Updated: Mar 19, 2026

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
Published on: October 10, 2025
Management of non-conformities in the pre-analytical phase of the medical analysis laboratory
Hind Kechkar1, Jihad Boukhaldi1, Abderrazak Sabri1
1Faculty of Medicine and Pharmacy, Clinical Immunology, Infection and Autoimmunity Laboratory, Hassan II University of Casablanca, Casablanca, Morocco.
Purpose:
The pre-analytical phase is a critical step in medical biology analyses, encompassing all stages from test ordering to sample presentation on the analyzer. The aim of this study is to propose a quality management approach for handling non-conformities in the pre-analytical phase of a medical analysis laboratory.
Design/Methodology/Approach:
This study investigated various pre-analytical non-conformities in a medical biology laboratory in Casablanca over an 8-month period. To address the primary causes of these non-conformities, we employed several quality tools, including FMECA, Ishikawa diagram, Pareto diagram, and brainstorming. Our work was structured according to the Plan-Do-Check-Act cycle. Excel was used for data processing and diagram creation, while Zotero managed bibliographic references.
Findings:
Two non-conformities were classified as high-criticality: the first concerned sampling errors (incorrect patient identification and non-compliant labeling), and the second involved non-compliant subcontracting samples. After determining the root causes of these two nonconformities, we implemented corrective actions and achieved a 46% improvement for the non-conforming during sampling and a 49% improvement for the non-conforming subcontracting samples.
Originality/Value:
After the first PDCA cycle, we achieved a significant improvement in the two non-conformities studied. Using quality tools, we prioritized the most critical non-conformities for immediate action. In addition, other methods enabled us to identify all the potential causes of these two non-conformities, pinpointing those responsible for 80% of their occurrence. A second PDCA cycle will be implemented to further improve the results obtained in the first cycle.
More Related Videos
Related Concept Videos
Data Validation
Key parameters for method validation include:
Quality Control
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Sample Handling
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...

