Startseite Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing
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Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing

  • Yanchun Lin , Nicholas C. Spies , Kimberly Zohner , Diane McCoy , Mark A. Zaydman und Christopher W. Farnsworth EMAIL logo
Veröffentlicht/Copyright: 5. Mai 2025
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Clinical Chemistry and Laboratory Medicine (CCLM)
Aus der Zeitschrift Clinical Chemistry and Laboratory Medicine (CCLM) Band 63 Heft 9

Abstract

Objectives

Clinical laboratory errors pose a threat to patient safety and previous studies have demonstrated that pre-analytical error is the most common error type. Our study aimed to determine the types and frequency of errors occurring in clinical laboratory testing in contemporary practice.

Methods

Errors occurring in a core laboratory between 01/2022 and 05/2023 were recorded retrospectively. Errors were quantified using multiple data-streams including real-time manual technologist intervention, incidence reports filed by hospital staff/physicians, and retrospective assessment using automated reports from the lab information system (LIS). Errors were adjudicated and binned into pre-analytical, analytical, and post-analytical phases. Total test volumes were assessed in the LIS and electronic medical record.

Results

There were 37,680,242 billable results reported from approximately 11,000,000 specimens during the study period. In total, 87,317 errors occurred impacting 0.23 % (2,300 ppm) of billable results and approximately 0.79 % (7,900 ppm) of specimens. Among these errors, 85,894 (98.4 %, 984,000 ppm) were in the pre-analytical, 451 (0.5 %, 5,000 ppm) were in the analytical, and 972 (1.1 %, 11,000 ppm) occurred in the post-analytical phase. Hemolysis impacting specimen integrity (60,748/87,317, 69.6 %, 696,000 ppm) was the most common error. When excluding hemolysis, there were 26,569 errors documented (0.06 %, 600 ppm of billable results), among which 94.6 %, 1.7 % (17,000 ppm) and 3.7 % (37,000 ppm) were in the pre-analytical, analytical and post-analytical phase respectively.

Conclusions

Observed error rates were consistent with previous studies with pre-analytical errors comprising most errors. High prevalence of pre-analytical errors implies a need for enhanced tools for error detection and mitigation in the pre-analytical phase of testing.

Keywords: laboratory error; error rate; pre-analytical error; hemolysis; specimen integrity
Corresponding author: Christopher W. Farnsworth, Department of Pathology and Immunology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO 63110, USA, E-mail:

  1. Research ethics: Deemed non-human subjects research by Washington University in St. Louis IRB.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors declare the following conflicts of interest: Research Funding: CF – Roche, Abbott, Siemens, Beckman coulter, Cepheid, Biomerieux. MZ – BIomerieux. Financial Support – MZ: ALDM – speaker honoraria on topics related to predictive analytics, ADLM support for travel to annual scientific meeting, API support for travel to annual summit. Consulting – abbott, werfen, cytovale. Others – CF – Editorial Board, clinical chemistry. MZ – ADLM Data analytics steering committee. Patents: MZ – Patent regarding analysis of immunoassays. Patent regarding analytical methods for analyzing bacteria proteomes. Planned patent for metabolic cage modeling software. All other authors declare no conflicts of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2025-0190).

Received: 2025-02-17
Accepted: 2025-04-25
Published Online: 2025-05-05
Published in Print: 2025-08-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2025-0190
Schlagwörter für diesen Artikel
laboratory error; error rate; pre-analytical error; hemolysis; specimen integrity

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Macroprolactinaemia – some progress but still an ongoing problem
  4. Review
  5. Understanding the circulating forms of cardiac troponin: insights for clinical practice
  6. Opinion Papers
  7. New insights in preanalytical quality
  8. IFCC recommendations for internal quality control practice: a missed opportunity
  9. Genetics and Molecular Diagnostics
  10. Evaluation of error detection and treatment recommendations in nucleic acid test reports using ChatGPT models
  11. General Clinical Chemistry and Laboratory Medicine
  12. Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing
  13. Improving the efficiency of quality control in clinical laboratory with an integrated PBRTQC system based on patient risk
  14. IgA-type macroprolactin among 130 patients with macroprolactinemia
  15. Prevalence and re-evaluation of macroprolactinemia in hyperprolactinemic patients: a retrospective study in the Turkish population
  16. Defining dried blood spot diameter: implications for measurement and specimen rejection rates
  17. Screening primary aldosteronism by plasma aldosterone-to-angiotensin II ratio
  18. Assessment of serum free light chain measurements in a large Chinese chronic kidney disease cohort: a multicenter real-world study
  19. Beyond the Hydrashift assay: the utility of isoelectric focusing for therapeutic antibody and paraprotein detection
  20. Direct screening and quantification of monoclonal immunoglobulins in serum using MALDI-TOF mass spectrometry without antibody enrichment
  21. Effect of long-term frozen storage on stability of kappa free light chain index
  22. Impact of renal function impairment on kappa free light chain index
  23. Standardization challenges in antipsychotic drug monitoring: insights from a national survey in Chinese TDM practices
  24. Potential coeliac disease in children: a single-center experience
  25. Vitamin D metabolome in preterm infants: insights into postnatal metabolism
  26. Candidate Reference Measurement Procedures and Materials
  27. Development of commutable candidate certified reference materials from protein solutions: concept and application to human insulin
  28. Reference Values and Biological Variations
  29. Biological variation of serum cholinesterase activity in healthy subjects
  30. Hematology and Coagulation
  31. Diagnostic performance of morphological analysis and red blood cell parameter-based algorithms in the routine laboratory screening of heterozygous haemoglobinopathies
  32. Cancer Diagnostics
  33. Promising protein biomarkers for early gastric cancer: clinical performance of combined detection
  34. Infectious Diseases
  35. The accuracy of presepsin in diagnosing neonatal late-onset sepsis in critically ill neonates: a prospective study
  36. Corrigendum
  37. The Unholy Grail of cancer screening: or is it just about the Benjamins?
  38. Letters to the Editor
  39. Analytical validation of hemolysis detection on GEM Premier 7000
  40. Reconciling reference ranges and clinical decision limits: the case of thyroid stimulating hormone
  41. Contradictory definitions give rise to demands for a right to unambiguous definitions
  42. Biomarkers to measure the need and the effectiveness of therapeutic supplementation: a critical issue
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