Pre-analytical errors in a high-volume Bangladeshi diagnostic centre: Prevalence, workload impact, and mitigation strategies - Indrajit Sarkar; Kona Rani Sarkar (PLoS ONE, 2026)
Background Pre-analytical errors are the most frequent cause of laboratory mistakes, accounting for nearly half of all diagnostic inaccuracies worldwide. These errors can invalidate test results, delay clinical decisions, and waste valuable healthcare resources, particularly in resource-limited, high-volume diagnostic laboratories. This study aimed to assess the prevalence, contributing factors, and severity of pre-analytical errors in a large diagnostic centre in Bangladesh. Methods An observational, cross-sectional study was conducted over two months in the Biochemistry and Immunology Laboratories of a high-volume diagnostic centre in Dhaka, Bangladesh. Data from 195 documented pre-analytical errors and a structured survey of 27 laboratory staff were analysed. Errors were classified into minor, moderate, or major using definitions adapted from ISO 15189:2022 and WHO guidelines. Descriptive statistics and Chi-square tests were performed to explore associations between workload level (≥ 931 samples/day) and error frequency, with p < 0.05 considered statistically significant. Results The most frequent errors were sample misplacement (38.5%) and incorrect labelling (17.9%). The sample collection (42.6%) and pick-and-drop (38.5%) units contributed the majority of errors. Morning shifts (65.1%) and high-workload days (70.8%) showed higher error frequencies, with a statistically significant association between workload and error occurrence (χ² = 121.093, p < 0.001). Major errors accounted for 37.4% of incidents. Conclusion Pre-analytical errors remain a critical threat to diagnostic accuracy in resource-limited laboratories. Improving workflow organization, implementing barcoding and automation, and strengthening staff training and workload management can substantially reduce error rates and enhance patient safety in high-throughput clinical settings.