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

Abstract

This study was conducted at the National Health Laboratory Services (NHLS) in Paarl, located in the Western Cape region, a renowned diagnostic testing laboratory. In the wake of the COVID-19 pandemic’s emergence in 2020, healthcare systems were faced with unprecedented challenges, as laboratory testing was the primary means of diagnosing COVID- 19 in patients. The NHLS Paarl laboratory was mandated to test high volumes of samples in a short timeframe (within 12 hours), so patients would receive their results and follow isolation protocols promptly if required. This situation brought to light a multitude of laboratory errors, which impacted the COVID-19 testing and resulting process. The primary objective of this research study was to meticulously analyse and identify root causes of these errors, with the aim of reducing and ultimately eliminating them, thus enhancing the quality of patient healthcare. The conceptual framework underpinning this research employs the application of quality management tools such as: Pareto analysis, Ishikawa diagrams, the 5 Whys analysis, and the Failure Modes and Effects Analysis (FMEA). These tools are firmly rooted in the recognised quality management cycle known as the Plan Do Check Act (PDCA) model. The objective is to develop an optimised pre-analytic process enriched with preventative measures that ensures reduced laboratory errors in COVID-19 testing. The research methodology adopted for this research is a mixed methods approach, whereby both quantitative and qualitative data was collected and analysed. The quantitative data was collected by means of TrakCare rejection reports during the period 1st January 2021 until 31st December 2021. The qualitative data was collected by means of conducting semi-structured interviews with key stakeholders in the NHLS, namely, the regional quality assurance manager, the business manager, and the head phlebotomist. The quantitative data was analysed using the quality tools: pareto analysis, Ishikawa diagram, the 5 whys analysis, and FMEA. The qualitative data was analysed by using the ATLAS.ti software. The study’s findings revealed deficiencies in the pre-analytical COVID-19 testing process which needed improvement. This research found that vital processes needed to be implemented at specific steps in the pre-analytical COVID-19 testing process, as well as the appointment of key personnel at specified stages to overcome the errors found in this area. Consequently, this research led to the development of an optimised pre-analytical COVID-19 testing process, aimed to enhance the quality and reliability of test results. This study advocates for the implementation of pre-analytic process procedures and a structured deployment of training and education to health care professionals. Furthermore, it underscores the necessity of establishing check points at various stages, namely: check points prior to specimen collection, specimen and request form labelling, specimen handling, and specimen transportation to reduce and eliminate pre-analytical errors. Additionally, the study recommends annual performance reviews for nurses and clinicians and annual audits of the pre-analytic testing process. These mechanisms are deemed essential for achieving and sustaining continuous process improvement in healthcare.