Identifying and Mitigating Human Errors in Laboratory Quality Control Systems

Abstract

Background: Errors in laboratory quality control can compromise patient safety, increase costs, and erode confidence in clinical decision-making. While technological and procedural factors are frequently addressed, human factors (staff behavior, training, communication, workload) remain underexplored. Objectives: To identify the types and prevalence of human-factor–related errors in clinical laboratories of tertiary care hospitals in Chennai; to assess their root causes; and to propose mitigation strategies suitable for the local context. Methodology: A cross-sectional observational study was conducted in three tertiary care hospitals in Chennai between January and June 2025. Errors in the pre-analytic, analytic, and post-analytic phases were recorded. Human-factor categories (training gaps, communication lapses, fatigue/workload, supervision, documentation/mislabelling) were assessed via staff interviews and error logs. Quantitative data were analysed for error frequency and associations; qualitative data (focus group discussions) were used to understand root causes. Results: Among approximately 30,000 laboratory tests analyzed, the overall error rate was about 1.8%. Pre-analytical, analytical, and post-analytical phases accounted for 60%, 25%, and 15% of these errors, respectively. Nearly 75% of all errors involved at least one human-factor component, with mislabelling (25%), sample collection mistakes (20%), insufficient staff training (18%), communication lapses during handovers (12%), and fatigue or workload (10%) being the most common. Laboratories with stronger internal quality control (IQC) practices and well-integrated laboratory information systems (LIS) demonstrated significantly fewer transcription and post-analytical errors (p < 0.05). Conclusion: Human factors are major contributors to laboratory quality control errors in Chennai hospitals. Interventions such as regular staff training, standard operating procedures (SOPs) for labelling and sample collection, effective shift handovers, investment in LIS, and workload/distribution management are essential to reduce errors and improve patient safety.