Evaluation of Pre-analytical Errors in the Histopathology Laboratory at a Tertiary Care Hospital in Kenya
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Josephine N Rioki1, Rency Lel2, Allan T Kirrima1
1Department of Medical Laboratory Sciences, University of Nairobi, Nairobi, KEN.
Background:
Pre-analytical errors comprise inappropriate performance and procedures executed before sample analysis. These nonconformities compromise report quality, consequently impeding optimal patient management and clinical outcomes. Awareness of these errors within histopathology laboratories is crucial for maintaining diagnostic integrity.
Objective:
This study aimed to characterize the frequency, nature, and distribution of documented demographic, accessioning, and specimen-rejection errors recorded in the Kenyatta National Hospital (KNH) histology laboratory registers between December 2017 and December 2019.
Methodology:
A retrospective cross-sectional study was conducted reviewing data from the general laboratory register and the sample rejection register recorded between December 2017 and December 2019. Assessment focused on two major domains: demographic/accessioning errors and sample rejection criteria. Analysis was performed using IBM SPSS Statistics software, version 20 (IBM Corporation, Armonk, NY, USA).
Results:
A total of 757 missing patient information records were recorded during the study period. Missing patient age was the most prevalent demographic error among the missing data events, accounting for 52.2% (24/46) in December 2017, 58.6% (286/488) in 2018, 57.4% (128/223) in 2019, and overall 57.9% (438/757). Within the sample rejection category, a missing request form was the most frequently specified reason for rejection (16.0%; 8/50 in December 2017, 40.0%; 2/5 in 2018, and 60.0%; 3/5 in 2019) and overall, 21.7% (13/60). Crucially, in December 2017, 66.0% (33/50) of the samples were rejected without documentation of the specific reason for rejection.
Conclusion:
Requisition forms were systematically underfilled, with missing patient age representing the predominant demographic discrepancy. Missing requisition forms reported with the highest frequency in this study were strongly associated with sample rejection. Furthermore, a severe lack of structured documentation regarding the reasons for specimen rejection was identified.
