Quality Indicators for the Performance Evaluation at a Biochemistry Laboratory: QIs for a Biochemistry Laboratory

Quality Indicators for the Performance Evaluation at a Biochemistry Laboratory: QIs for a Biochemistry Laboratory

Zoi S. Athanasiadou (Ippokrateio General Hospital of Thessaloniki, Thessaloniki, Greece), Antonia Mourtzikou (University General Hospital “ATTIKON”, Chaidari, Greece), Marilena Stamouli (Naval and Veterans Hospital of Athens (NNA), Athens, Greece) and Petros Karkalousos (University of West Attica, Athens, Greece)
Copyright: © 2020 |Pages: 16
DOI: 10.4018/IJRQEH.2020040102

Abstract

The use of quality indicators and risk evaluation are valuable tools for maintaining the quality of laboratory tests. There are both requirements of ISO 15189: 2012 and are usually based on common statistical and empirical data. The purpose of the present study was the quality quantification and risk evaluation through the collection, study, and analysis of quality indicators covering the pre-analytical, analytical, and post-analytical phases of the laboratory testing process. Statistical data was collected for the period from 1/12/2017 to 28/2/2018, using the LIS of Biochemical Laboratory. QIs were evaluated using the Six Sigma method and the Pareto statistical tool. FMEA risk analysis was performed, while the degree of risk priority with the Pareto method. The results show that in the analytical phase the QIs give us satisfactory values, while those in the pre- and post- analytical phases need further preventive/corrective actions in order to overcome the problems raised by the QIs. Thus, the fully automatization and computerization of the laboratory is needed.
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Introduction

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% of clinical decisions are based upon information derived from laboratory test results. Quality in clinical laboratories is defined as the guarantee that the entire testing process is correctly performed, thus ensuring valuable decision making and effective patient care. Clinical laboratories have always been forerunners in quality issues. Moreover, the implementation of quality assessment programs has always been a routine in clinical laboratory work. Automated innovations have contributed to a significant improvement in the quality of laboratory results, but despite all the automation, errors, which can lead to inappropriate patient care decisions, still occur (Plebani, 2015; Najat, 2017; Lao et al., 2017).

Errors occurring in the laboratory practice may have a negative impact on patient outcomes, such as time lost, patient revisits, increased costs, erroneous therapies, diagnostic delays and increased risk of patient debility (Epner et al., 2013; Warade, 2015; Mourtzikou and Stamouli, 2017). Clinical laboratory errors are classified as pre-analytical, analytical, and post-analytical, according to the phase of the testing process during which they are observed. Strategies used to reduce laboratory errors, include certification and accreditation by professional bodies, internal quality control procedures, external quality assessment programs, certification of education programs, risk assessment, as well as implementation of quality indicators for the evaluation of laboratory performance (Jones et al., 2017; Mourtzikou and Stamouli, 2017; De la Salle et al., 2017).

The pre-analytical phase includes all components of the laboratory testing process that take place before specimen analysis; test ordering, specimen collection, specimen transportation to the laboratory, specimen accessioning in the laboratory centrifugation and specimen preparation for analysis. The analytical phase involves the analysis of the specimen. The post-analytical phase includes evaluation, release and report of results. According to scientific literature, laboratory errors occur mainly in the pre-analytical phase, which is the most vulnerable to errors, due to the involvement of many non-laboratory professionals, such as physicians, phlebotomists medical interns and nursing staff (Plebani et al., 2017; Najat, 2017). The preanalytical phase has the highest error rates, accounting for up to 70% of all errors in laboratory diagnostics. Moreover, pre-analytical and post-analytical errors account for 93% of the total errors encountered in the laboratory. Reviews on available data on laboratory errors indicate significant heterogeneity in the studies, where the data collection method is the most influential factor that influences the prevalence and type of errors (Najat, 2017; Sushma and 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 evaluated periodically to reduce or eliminate the errors that may arise during the various steps. For a patient-centered approach, there is the need to assure that every step of the entire testing process is correctly performed, that weaknesses are recognized, and that corrective and preventive actions are designed and implemented (Schneider et al., 2017; Lippi et al., 2017). The current study aimed at investigating the most common causes of errors in the biochemistry laboratory of a tertiary hospital in Greece and evaluating the relevant quality indicators.

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