The use of quality indicators (QIs) and risk assessment are valuable tools for maintaining the quality of laboratory tests. Both are requirements of ISO 15189: 2012 and are usually based on standard statistical and empirical data. In this chapter, the authors focus on evaluating clinical laboratory quality indicators in the era of the COVID-19 pandemic. The goal is to pose and discuss, based on the authors' experience, the quality evaluation and risk assessment through the collection, study, and analysis of quality indicators covering the pre-analytical, analytical, and post-analytical phases of the laboratory testing process. QIs were evaluated using the Six Sigma method. Moreover, FMEA risk analysis was performed, and the degree of risk priority was assessed using the Pareto method. The results show that in the analytical phase, the laboratory's performance is satisfactory, while the pre-and post-analytical phases need further preventive/corrective actions.
TopIntroduction
Clinical laboratories produce test results that must be relevant, accurate and reliable for the prognosis,diagnosis, treatment, hospital admission and discharge of patients. Approximately 70-85% ofclinical decisions are based upon information derived from laboratory test results. Quality in clinicallaboratories is defined as the guarantee that the entire testing process is correctly performed, thusensuring valuable decision making and effective patient care. Clinical laboratories have always beenforerunners in quality. Moreover, the implementation of quality assessment programs has alwaysbeen a routine in clinical laboratory work. Automated innovations have contributed to a significantimprovement in the quality of laboratory results, but despite all the automation, errors, which canlead to inappropriate patient care decisions, still occur (Plebani, 2015; Najat, 2017; Lao et al., 2017).
These errors occurring may have a negative impact on patient outcomes, suchas time lost, patient revisits, increased costs, erroneous therapies, diagnostic delays and increasedrisk of patient debility (Epner et al., 2013; Blick, 2013; Warade, 2015; Mourtzikou&Stamouli, 2017).
The ongoing new coronavirus pandemic COVID-19, caused by the SARS-CoV-2 virus, is a severe global health crisis withmany social and economic consequences (Austin &Kachalia, 2020; Reeves et al., 2020).
It started in December 2019, when a cluster of pneumonia cases was observed in Wuhan City, China (Wu F et al.,2020).Since then, no country has been left untouched by theoutbreak, and up to now, more than3,5million people have died. However, we observe a high heterogeneity in death rates among countries andbetween regions within a country. The World Health Organization declared COVID-19 to be a pandemic on March 11th 2020.
According to the phase of the testing process during which they are observed, clinical laboratory errors are classified as preanalytical, analytical, and post-analytical.Strategies used to reduce laboratory errorsinclude certification and accreditation by professional bodies, internal quality control procedures,external quality assessment programs, certification of education programs, risk assessment, as wellas the implementation of quality indicators for the evaluation of laboratory performance (Jones et al.,2017; Mourtzikou&Stamouli, 2017; De la Salle et al., 2017).The preanalytical phase includes all components of the laboratory testing process before specimen analysis; test ordering, specimen collection, specimen transportation to thelaboratory, specimen accessioning in the laboratory centrifugation and specimen preparation foranalysis. The analytical phase involves the analysis of the specimen. The post-analytical phase includesevaluation, release and report of results. According toscientific literature, laboratory errors occurmainly in the preanalytical phase, which is the most vulnerable to errors due to many non-laboratory professionals, such as physicians, phlebotomists, medical interns and nursingstaff (Plebani et al., 2017; Najat, 2017). The preanalytical phase has the highest error rates, accountingfor up to 70% of all errors in laboratory diagnostics.
Moreover, preanalytical and post-analyticalerrors account for 93% of the total errors encountered in the laboratory. Reviews on available data onlaboratory errors indicate significant heterogeneity in the studies, where the data collection methodis the factor that influences the prevalence and type of errors (Najat, 2017; Sushma&Shrikant, 2019; Stamouli et al., 2019).Total quality management, which encompasses all the steps involved in sample processing,beginning from test order to the final interpretation of results by the clinicians, must be evaluatedperiodically to reduce or eliminate the errors that may arise during the various steps (Kaul, 2020; Austin &Kachalia, 2020; Reeves, 2020).