Laboratory Specimen Rejection: Pre Analytical Errors, Trends, Quality Indicators, and Improvement Strategies – A Comprehensive Review

  • Unique Paper ID: 190467
  • PageNo: 2199-2204
  • Abstract:
  • Background: Clinical laboratory results are central to clinical decision-making and patient management. Although analytical technologies have advanced considerably, errors occurring in the pre-analytical phase continue to pose significant challenges to laboratory quality systems. Specimen rejection remains a critical quality indicator reflecting failures in patient identification, sample collection, labeling, transport, storage, and processing. Objectives: This review aims to consolidate evidence from international and regional studies on laboratory specimen rejection, focusing on its causes, trends, clinical impact, and quality improvement strategies, with particular emphasis on specimen referral networks in resource-limited settings and the application of Six Sigma metrics.Methods: A narrative review of published literature was conducted, including studies, surveillance reports, and guidelines addressing specimen rejection rates, pre-analytical errors, and laboratory quality management. Emphasis was placed on evidence related to referral laboratories and the use of Six Sigma methodology for performance evaluation. Results: The reviewed literature consistently identifies pre-analytical errors as the leading cause of specimen rejection, with improper labeling, hemolysis, insufficient sample volume, and transport-related issues being most frequent. High rejection rates were associated with delayed diagnosis, repeated phlebotomy, increased healthcare costs, and compromised patient safety. Studies employing Six Sigma metrics demonstrated improved standardization and benchmarking of laboratory performance. Discussion: Specimen rejection reflects systemic weaknesses in pre-analytical workflows, particularly in resource-limited and high-volume referral settings. The adoption of standardized quality indicators, staff training, improved referral systems, and Six Sigma-based monitoring can significantly reduce rejection rates and enhance overall laboratory efficiency. Conclusion: Specimen rejection remains a preventable yet persistent challenge in clinical laboratories. Strengthening pre-analytical practices through evidence-based interventions and integrating Six Sigma metrics into laboratory quality management systems are essential for minimizing errors, improving patient safety, and ensuring reliable diagnostic services.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{190467,
        author = {Bharathi B and Lakshaya P and Deepa C.Philip},
        title = {Laboratory Specimen Rejection: Pre Analytical Errors, Trends, Quality Indicators, and Improvement Strategies – A Comprehensive Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {2199-2204},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190467},
        abstract = {Background: Clinical laboratory results are central to clinical decision-making and patient management. Although analytical technologies have advanced considerably, errors occurring in the pre-analytical phase continue to pose significant challenges to laboratory quality systems. Specimen rejection remains a critical quality indicator reflecting failures in patient identification, sample collection, labeling, transport, storage, and processing. Objectives: This review aims to consolidate evidence from international and regional studies on laboratory specimen rejection, focusing on its causes, trends, clinical impact, and quality improvement strategies, with particular emphasis on specimen referral networks in resource-limited settings and the application of Six Sigma metrics.Methods: A narrative review of published literature was conducted, including studies, surveillance reports, and guidelines addressing specimen rejection rates, pre-analytical errors, and laboratory quality management. Emphasis was placed on evidence related to referral laboratories and the use of Six Sigma methodology for performance evaluation. Results: The reviewed literature consistently identifies pre-analytical errors as the leading cause of specimen rejection, with improper labeling, hemolysis, insufficient sample volume, and transport-related issues being most frequent. High rejection rates were associated with delayed diagnosis, repeated phlebotomy, increased healthcare costs, and compromised patient safety. Studies employing Six Sigma metrics demonstrated improved standardization and benchmarking of laboratory performance. Discussion: Specimen rejection reflects systemic weaknesses in pre-analytical workflows, particularly in resource-limited and high-volume referral settings. The adoption of standardized quality indicators, staff training, improved referral systems, and Six Sigma-based monitoring can significantly reduce rejection rates and enhance overall laboratory efficiency. Conclusion: Specimen rejection remains a preventable yet persistent challenge in clinical laboratories. Strengthening pre-analytical practices through evidence-based interventions and integrating Six Sigma metrics into laboratory quality management systems are essential for minimizing errors, improving patient safety, and ensuring reliable diagnostic services.},
        keywords = {Specimen rejection; Pre analytical errors; Laboratory quality indicators; Six Sigma; Referral laboratory systems.},
        month = {January},
        }

Cite This Article

B, B., & P, L., & C.Philip, D. (2026). Laboratory Specimen Rejection: Pre Analytical Errors, Trends, Quality Indicators, and Improvement Strategies – A Comprehensive Review. International Journal of Innovative Research in Technology (IJIRT), 12(8), 2199–2204.

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