Analysis of risks associated with laboratory error rates of covid-19 testing at the NHLS Paarl laboratory

Abstract

The emergence of the novel coronavirus (COVID-19) in 2020 posed a significant global health crisis, leading to a heightened demand for effective laboratory testing. This study focuses on the COVID-19 laboratory testing process at the NHLS Paarl laboratory in the Western Cape, employing a two-phase mixed-method examination. The initial phase utilizes Deming's PDCA cycle, incorporating quality tools such as Pareto analysis, Ishikawa diagram, 5 Whys analysis, and Failure Modes and Effect Analysis (FMEA) to enhance the efficiency of the COVID-19 testing process. The second phase involves qualitative research through semi-structured interviews to validate the outcomes of the first phase. The study identifies errors in the pre-analytic phase as a major challenge in laboratory testing, specifically rejected specimens. By applying the PDCA cycle, the research aims to formulate an optimized pre-analytic process to minimize errors. Laboratory errors, in the pre-analytic phase, are crucial quality indicators (QIs) that impact patient care and safety. The analysis reveals common pre-analytic errors, including invalid samples, insufficient specimens, and mismatched information. The consequences of these errors extend to delayed diagnostic results, hindering disease prevention and containment strategies. The study emphasizes the need for stringent measures to ensure accurate and reliable laboratory results in the context of COVID-19. The optimized pre-analytic process includes interventions such as standardized procedures, education and training programs, and check points to verify patient details and specimen handling. In conclusion, this research addresses the critical role of laboratory testing in the context of the COVID-19 pandemic, focusing on the pre-analytic phase to minimize errors and enhance the accuracy of results.