Utilizing Quality Indicators to Detect and Reduce Pre-Analytical Errors in Laboratory Testing

Abstract

Pre-analytical errors are the most frequent type of errors encountered in clinical laboratory testing, accounting for approximately 46-68% of all laboratory-related mistakes. These errors occur during the stages of patient preparation, sample collection, handling, transport, and processing, often resulting in compromised test accuracy and negatively impacting patient outcomes. The clinical implications of pre-analytical errors can be serious, leading to misdiagnosis, inappropriate treatments, delays in patient care, and increased healthcare costs. The introduction of quality indicators (QIs) offers laboratories a systematic approach to identifying, monitoring, and reducing pre-analytical errors. QIs measure critical aspects of the pre-analytical phase, such as specimen rejection rates, hemolysis index, patient identification accuracy, sample transport conditions, and phlebotomy success rates. By tracking these indicators, laboratories can detect weaknesses in their processes, implement targeted interventions, and ensure consistent improvements in quality. Studies have demonstrated that the implementation of QIs significantly reduces error rates, leading to enhanced diagnostic accuracy and improved patient safety. This review discusses the common pre-analytical errors, the role of QIs in mitigating these errors, and the impact of quality management on overall laboratory performance, with evidence drawn from recent research and clinical practice.