Pre-Analytical Laboratory Errors Related to Nursing Practices in Conflict-Affected Hospitals in Yemen: A Quasi-Experimental Study from Al-Dhalea Governorate

This repository contains all data, analysis code, and supplementary materials for a hospital-based quasi-experimental study investigating pre-analytical laboratory errors attributable to nursing practices in major hospitals within Al-Dhalea Governorate, Yemen. Conducted between November 2025 and January 2026, this research addresses a critical gap in understanding diagnostic quality in humanitarian crises. Background The pre-analytical phase is the most vulnerable segment of the total testing process, contributing to up to 70% of laboratory errors. In conflict-affected Yemen—where healthcare systems face catastrophic collapse—this vulnerability is dramatically exacerbated. Nursing staff, responsible for frontline sample collection, often work with minimal training and under extreme duress. Despite global recognition of this issue, empirical data from active conflict zones remain scarce, hindering targeted quality improvement. Study Objectives This study aimed to: 1. Determine the prevalence and typology of pre-analytical laboratory errors in Yemeni conflict-zone hospitals. 2. Identify nursing-related factors (education, experience, training, shift) associated with increased error rates. 3. Analyze departmental and operational contributors to sample rejection. 4. Propose evidence-based, feasible intervention strategies tailored to resource-limited, conflict-affected settings. Methods We conducted a consecutive analysis of 600 laboratory samples collected by nursing staff across Emergency, Pediatrics, Internal Medicine, and Intensive Care Units. Samples were assessed for six pre-analytical errors: hemolysis, clotting, insufficient volume, wrong tube type, mislabeling, and transport delay. Comprehensive data on patient demographics, nursing factors, and sample handling were collected and analyzed using descriptive statistics, chi-square tests, and multivariable logistic regression. Key Findings · Overall Rejection Rate: 30.0% (180/600 samples). · Most Common Error: Hemolysis (28.0% of all samples). · Strongest Predictor: Absence of prior laboratory training (aOR = 3.45). · High-Risk Scenarios: Night shifts and Emergency Department settings showed significantly elevated error rates. · Systemic Issue: 62.2% of rejected samples had multiple co-occurring errors.