Clinical laboratories are critical to patient care, with accurate diagnostics essential for effective management. The preanalytical phase is particularly prone to errors, accounting for up to 70% of lab mistakes. These can distort results, increase costs, and compromise patient safety. Quality indicators (QIs) help monitor and minimize such errors, especially in hematology testing. This study focuses on assessing preanalytical QIs and proposes strategies—including staff training and workflow audits—to improve laboratory accuracy and overall performance. Aim: To evaluate preanalytical quality indicators (QIs) in hematology laboratory settings and implement targeted strategies—such as staff training and workflow audits—to enhance diagnostic accuracy and overall laboratory performance. Study Protocol: All samples received by the Hematology Laboratory of the Maternity and Pediatric Hospital in Hail were retrospectively reviewed for preanalytical issues using predefined QIs. Blood samples (n-10000) were analyzed from January 2023 to December 2023. Results: Of 10,000 hematology samples assessed in 2023, 9.3% showed preanalytical errors—predominantly clotted specimens (502) and unreceived samples (3.5%). While quality indicators largely reflected moderate to low performance against benchmarks, sigma analysis affirmed acceptable levels in key processes. Notably, error rates declined from 11.6% to 6.5% over the year, highlighting the impact of continuous quality improvement measures. Conclusion: Minimizing preanalytical errors is essential for accurate hematology reporting. Standardized protocols, staff training, sample tracking, and continuous audits strengthen quality assurance and promote diagnostic reliability. Embedding these safeguards into routine workflows ensures consistent clinical value and patient safety.
Naveena et al. (Wed,) studied this question.
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