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Published on: September 16, 2012
Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing
Yanchun Lin1, Nicholas C Spies1, Kimberly Zohner2
1Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA.
Clinical laboratory errors, particularly pre-analytical ones, remain a significant concern. This study highlights the high frequency of pre-analytical errors, emphasizing the need for improved detection and mitigation strategies in laboratory testing.
Area of Science:
- Clinical Laboratory Science
- Patient Safety
- Healthcare Quality Improvement
Background:
- Clinical laboratory errors can compromise patient safety.
- Pre-analytical errors are consistently identified as the most frequent type of laboratory error.
- Understanding error patterns in contemporary practice is crucial for quality improvement.
Purpose of the Study:
- To determine the types and frequency of errors in clinical laboratory testing.
- To analyze the distribution of errors across pre-analytical, analytical, and post-analytical phases.
- To identify the most common error types in a core laboratory setting.
Main Methods:
- Retrospective analysis of errors in a core laboratory from January 2022 to May 2023.
- Data collection through technologist interventions, incident reports, and laboratory information system (LIS) reports.
- Errors were categorized into pre-analytical, analytical, and post-analytical phases; total test volumes were assessed.
Main Results:
- Over 37 million billable results and 11 million specimens were analyzed, with 87,317 errors recorded.
- Pre-analytical errors constituted 98.4% of all errors, with hemolysis being the most common (69.6%).
- Excluding hemolysis, pre-analytical errors still represented 94.6% of the remaining errors.
Conclusions:
- The study confirms that pre-analytical errors are the predominant type of error in clinical laboratory testing.
- Findings are consistent with previous research, underscoring the persistent challenge of pre-analytical variability.
- Enhanced tools and strategies are necessary for effective detection and mitigation of pre-analytical errors.
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