Applying the DMAIC Approach to Reduce Pre-Analytical Errors - Evidence from a Moroccan Medical Laboratory Case Study

Q: What problem does the DMAIC approach target in this study?

It targets pre-analytical errors in a medical laboratory, including hemolysis, labeling mistakes, and sample transport problems.

Q: How was the DMAIC intervention evaluated in the Casablanca laboratory?

Through a quasi-experimental study comparing 162 patients before the intervention (September 2023) and 162 after (February 2024), using laboratory information system data, internal audits, and incident reports.

Q: What were the main results after applying DMAIC?

The proportion of patients with at least one pre-analytical error dropped from 43.8% to 17.9%, while labeling, transport issues, and hemolyzed samples decreased, and the sigma level increased from 3.03 to 3.86.

Oct 26, 2026

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Pre-analytical errors represent the most frequent failures in medical laboratories and can undermine patient safety while distorting diagnostic accuracy. This study evaluates whether the DMAIC method (Define, Measure, Analyze, Improve, Control) can reduce such errors in a private Casablanca laboratory with limited resources. A quasi-experimental design compared 162 patients before (Sep 2023) and 162 after (Feb 2024) intervention. Hemolysis, labeling mistakes, and transport problems were tracked through audits, incident reports, and the laboratory information system, showing a substantial and sustained improvement.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages7

Reading Time18 min

AccessFree to download

Introduction

Methods

Results

Conclusion

ORIGINAL ARTICLE Applying the DMAIC Approach to Reduce Pre-Analytical Errors: Evidence from a Moroccan Medical Laboratory Case Study Application de l’approche DMAIC pour réduire les erreurs pré-analytiques dans un laboratoire médical : Une étude de cas du Maroc Mohamed Omari Higher Institute of Nursing Professions and Health Techniques of Casablanca, Morocco. Research laboratory: care, health and sustainable development (2s2d), team 3: health sciences, education and management (2sem) . AbstrAct Background: Pre-analytical errors are the most common mistakes in medical laboratories and can directly affect patient safety and the accuracy of test results. Typical problems include hemolysis, mislabeling, and issues with sample transport. In Morocco, few studies have looked closely at these errors or tested structured improvement approaches such as DMAIC (Define, Measure, Analyze, Improve, Control) . Aim: This study aimed to see whether the DMAIC method could reduce pre-analytical errors in a private laboratory in Casablanca, and whether it could provide practical guidance for similar low-resource laboratories. Methods: We conducted a quasi-experimental study with 324 patients—162 before (September 2023) and 162 after (February 2024) the intervention. Data came from the Laboratory Information System, internal audits, and incident reports. Key indicators included hemolysis, labeling mistakes, and transport problems. We used Pearson’s Chi-square test to compare groups, with p ≤ 0.05 considered significant. Results: The percentage of patients with at least one pre-analytical error dropped from 43 .8%(71/162) to 17 .9%(29/162) (χ² = 24 .67; df = 1; p < 0.001) . Labeling mistakes fell from 29 to 8 cases, transport issues from 24 to 11, and hemolyzed samples from 12 to 3. The sigma level rose from 3.03 to 3 .86, showing clear improvement in process reliability. The improvements remained stable over time. Conclusion: Applying the DMAIC method significantly reduced pre-analytical errors and improved laboratory processes. This structured, step-bystep approach can help similar laboratories improve patient safety and test reliability, even with limited resources. Key words: DMAIC methodology, Lean Six Sigma, Pre-analytical errors, Process improvement, Medical laboratory résumé Contexte : Les erreurs pré-analytiques constituent une source majeure d’erreurs de laboratoire et peuvent compromettre considérablement laprécision diagnostique et la sécurité des patients. Les problèmes fréquents incluent l’hémolyse des échantillons, des erreurs d’étiquetage et des problèmes de transport. La méthodologie DMAIC, qui fait partie du cadre Lean Six Sigma, propose une approche structurée et basée sur les données pour réduire ces erreurs. Objectif : Cette étude a évalué l’efficacité de l’approche DMAIC pour réduire les erreurs pré-analytiques dans un laboratoire médical privé à Casablanca, au Maroc. Méthodes : Une étude de cas quasi-expérimentale a été réalisée sur 324 patients — 162 avant (septembre 2023) et 162 après (février 2024) del’intervention. Les données ont été obtenues à partir du Laboratoire Information System, des audits internes et des rapports d’incident. Chaque échantillon a été évalué pour détecter des non-conformités pré-analytiques, notamment l’hémolyse, les erreurs d’étiquetage et les problèmes de transport. L’analyse des causes profondes, utilisant des outils comme les graphiques de Pareto et les diagrammes d’Ishikawa, a guidé les actions d’amélioration. Les statistiques descriptives mesuraient les résultats. Résultats : Des erreurs pré-analytiques ont été enregistrées chez 43,8 % des patients avant l’intervention, pour chuter à 17,9 % par la suite. Les casd’hémolyse sont passés de 12 à 3, les erreurs d’étiquetage de 29 à 8, et les problèmes de transport de 24 à 11. Le nombre de cas sans erreur est passé de 91 à 133. Le niveau sigma est passé de 3,03 à 3,86, indiquant une amélioration des performances du

FAQs

What problem does the DMAIC approach target in this study?

It targets pre-analytical errors in a medical laboratory, including hemolysis, labeling mistakes, and sample transport problems.

How was the DMAIC intervention evaluated in the Casablanca laboratory?

Through a quasi-experimental study comparing 162 patients before the intervention (September 2023) and 162 after (February 2024), using laboratory information system data, internal audits, and incident reports.

What were the main results after applying DMAIC?

The proportion of patients with at least one pre-analytical error dropped from 43.8% to 17.9%, while labeling, transport issues, and hemolyzed samples decreased, and the sigma level increased from 3.03 to 3.86.

Oct 26, 2026

Upload by Tirek