Reducing Preanalytical Errors in Clinical Laboratories Through Automation and Standardization
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Abstract
Preanalytical errors are a major source of laboratory diagnostic errors that undermine patient safety and quality of care. This literature review examines the prevalence, types, causes and impact of preanalytical errors in clinical laboratories. Additionally, it evaluates evidence-based strategies focused on workflow automation, standardization of procedures, and quality management to reduce preanalytical errors. Findings indicate that 46-68% of total laboratory errors occur in the preanalytical phase. Misidentification, improper test ordering, inadequate specimen quality, and mishandling are leading sources of preanalytical errors which lead to misdiagnosis, treatment delays, redundant testing, and patient harm. Implementing barcode specimen labeling, computerized provider order entry, specimen tracking systems, and automation of processing can significantly reduce preanalytical errors. Standardizing phlebotomy, handling protocols, and storage procedures also decreases errors. Continuous monitoring of quality indicators is essential for identifying problematic steps and enabling corrective actions. Further research is needed, but significant evidence indicates that optimizing work processes through automation, standardization, training, and quality control in the preanalytical phase is critical to improving patient safety by enhancing diagnostic accuracy in clinical laboratories.
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