OBJECTIVES: This study aimed to develop and implement an integrated informatics platform to harmonize sample collection quality indicators (QIs) monitoring across a regional medical laboratory center (RMLC), and to systematically characterize the frequency and distribution of four key pre-analytical QIs using platform-generated data. METHODS: A standardized dictionary of rejection types and reasons was configured into the laboratory information system sample rejection menu. The web-based QIs management system (iLab system) was developed with key functions including automated data collection, QIs calculation, visual analytics, and a corrective action implementation module. A 24-month retrospective analysis was performed on four sample rejection QIs. RESULTS: The iLab QIs management system was successfully implemented across the RMLC network. In total, 7,437,716 biological samples were received, with 4235 (0.057%) rejected based on four QIs criteria. Clotted samples (43.61% of total rejections) and incorrect sample volume (24.46%) were the leading causes, with "inadequate mixing" accounting for 62.25% of clotting incidents. Primary sample volume issues included insufficient volume in urine and empty tubes in stool. Nasopharyngeal swab, urine, and secretion samples collectively represented over 50% of incorrect container incidents, while sputum incorrectly collected as stool or urine was the most common sample type error. P-control charts were utilized for continuous rejection rate monitoring, and electronic forms for process automation supported collaborative non-conformity rectification. CONCLUSION: The iLab platform successfully harmonized pre-analytical QIs monitoring, demonstrating that an integrated informatics framework enables standardized, automated data capture and precise, network-wide root cause attribution for sample rejection.
Chen et al. (Tue,) studied this question.