Assessment of Pre-Analytical Errors in Hematology Laboratory Testing Processes

Thesis Abstract

Pre-analytical errors represent a significant challenge in hematology laboratory testing, contributing substantially to inaccurate diagnoses, delayed patient management, and increased healthcare costs. Recognizing that a considerable proportion of laboratory inaccuracies originate before analytical procedures—particularly during sample collection, handling, and transportation—this study aims to systematically assess the prevalence, types, and determinants of pre-analytical errors within hematology laboratories in a tertiary healthcare setting. The specific objectives include quantifying the incidence of individual pre-analytical errors, identifying key procedural and operational factors associated with these errors, evaluating the level of staff adherence to standard operating procedures (SOPs), and exploring the impact of these errors on test reliability and patient outcomes. Adopting a descriptive cross-sectional design guided primarily by the socio-technical systems theory and the human factors theory, the study intends to provide a comprehensive understanding of the factors influencing pre-analytical errors. The population encompasses all hematology laboratory samples processed within the hospital over a six-month period, comprising approximately 10,000 samples collected from adult outpatient and inpatient departments. A stratified random sampling technique will select a representative sample of 1,200 samples to investigate the occurrence and nature of pre-analytical errors. Data collection instruments will include structured observation checklists, error reporting forms, staff questionnaires, and review of laboratory information system (LIS) records. The validity of these instruments will be established through expert consultations, while reliability will be assessed via Cronbach's alpha for questionnaires and inter-rater reliability for observational checklists. Quantitative data analysis will employ descriptive statistics to determine the frequency and distribution of different pre-analytical errors (e.g., hemolysis, clotting, labeling errors, inadequate sample volume). Inferential statistical techniques such as chi-square tests and logistic regression analysis will identify associations between errors and variables including staff qualification, sample transportation time, sample type, and adherence to SOPs. A multivariate regression model will further elucidate predictors of errors, controlling for potential confounders. Qualitative data from staff questionnaires will undergo thematic analysis to uncover contextual insights into procedural challenges and perceptions related to sample handling. Expected findings anticipate a pre-analytical error rate of approximately 15%, with hemolysis (40%) and inadequate labeling (25%) being the most prevalent. The study is projected to reveal significant associations between errors and variables such as staff training levels (p<0.01), transportation time exceeding 30 minutes (p<0.05), and non-compliance with SOPs (p<0.001). These findings will provide empirical evidence on critical operational deficiencies and behavioral factors contributing to errors, filling existing gaps in the literature limited to isolated hospital settings. The research will contribute to the theoretical understanding of human and systemic factors influencing pre-analytical errors in hematology laboratories, informing the development of targeted interventions. Specifically, it will offer a validated error classification framework tailored to hematology testing and a predictive model for error occurrence based on operational parameters. The main conclusion emphasizes the urgent need to improve staff training, process standardization, and sample transportation protocols. Based on these findings, recommendations include implementing continuous staff education programs, strengthening quality assurance systems, adopting barcode-based sample identification, and establishing real-time error tracking mechanisms. The study advocates for integrated quality improvement initiatives to mitigate pre-analytical errors, thereby enhancing test accuracy, patient safety, and overall laboratory performance.