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Research Article Open access CC BY 4.0

Evaluation of Pre-Analytical Elements Affecting the Rejection of Hematology Samples at Masvingo Provincial Laboratory, Zimbabwe

Gracious Garira, Chukwuma J. Okafor, Emmanuel Ifeanyi Obeagu

Asian Hematology Research Journal · pp. 257–265 · Published 5 Nov 2025

10.9734/ahrj/2025/v8i4219

Abstract

Background: Pre-analytical errors are the leading source of laboratory inaccuracies worldwide, accounting for over 60% of all diagnostic testing errors. In hematology, sample quality is critically dependent on correct collection, labeling, and transport practices. Errors during this phase not only delay diagnosis but also waste resources and compromise patient safety. Despite ongoing laboratory quality improvement initiatives in Zimbabwe, limited data exist on the prevalence and causes of hematology sample rejection in provincial hospitals. Objective: The present study determine the prevalence, causes, and clinical implications of hematology sample rejection at Masvingo Provincial Hospital Laboratory, Zimbabwe, and to assess how pre-analytical variables influence sample rejection trends. Methods: A retrospective descriptive study was conducted using data from the hematology section of Masvingo Provincial Hospital Laboratory covering the period January–December 2024. Records from the sample rejection logbook and Laboratory Information Management System (LIMS) were reviewed. Parameters analyzed included total number of hematology samples received, number and reasons for rejection, source of samples, and time of occurrence. Results: A total of 6,364 hematology samples were processed during the study period, of which 72 were rejected, giving an annual rejection rate of 1.13%. Monthly rejection rates fluctuated between 0.2% and 3.0%, with the highest rates observed in June, July, and October 2024. The leading causes of sample rejection were clotted samples (28%), wrong sample tubes (18%), lipemic samples (14%), and insufficient volume (14%). Other causes included hemolysis (11%) and mismatched specimen details (13%). Most rejected samples originated from the Pediatric Ward (32%) and Antenatal Clinic (19%), indicating higher vulnerability among these clinical areas. Conclusion: Pre-analytical variables significantly affect hematology sample rejection at Masvingo Provincial Hospital Laboratory. While documentation and labeling practices appear satisfactory, technical errors—particularly clotting and use of incorrect tubes—remain a challenge. Strengthening staff competency through continuous professional training, regular quality audits, and improved transport logistics will help reduce rejection rates and improve the reliability of hematology results.

Pre-analytical errors hematology sample rejection laboratory quality Zimbabwe

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