AUTOMATION OF LABORATORY TESTING: ADVANTAGES AND LIMITATIONS - Asirova Malika; Asirova Malika (JOURNAL OF NEW CENTURY INNOVATIONS, 2026)
Modern medical development is impossible without a highly effective laboratory diagnostics system, which plays a key role in the prevention, early detection, and monitoring of diseases. According to the World Health Organization, laboratory test results are used in up to 70–80% of clinical decisions, which underscores their exceptional importance in the healthcare system [1, 2]. With the rise in disease incidence, increased life expectancy, and more complex clinical protocols, the workload on clinical diagnostic laboratories is growing significantly. In recent decades, there has been a steady increase in the volume of laboratory tests, an expansion in the range of parameters measured, and higher requirements for accuracy, reproducibility, and speed of results [3]. Traditional, predominantly manual methods of performing laboratory analyses are in some cases unable to fully meet the modern needs of clinical practice, due to the high probability of pre-analytical and analytical errors, the dependence of results on human factors, and limited scalability [4, 5]. In this regard, the automation of laboratory research is considered one of the priority areas for the development of laboratory medicine. The introduction of automated analytical systems, robotic complexes, and laboratory information systems is aimed at optimizing work processes, standardizing research methods, and increasing the overall efficiency of laboratory activities [6, 7]. Automation minimizes the influence of subjective factors, ensures strict quality control at all stages of laboratory analysis, and reduces the time required to perform tests, which is especially important in emergency and intensive care settings [8]. Automation plays a special role in the pre-analytical stage, which, according to numerous studies, is the source of up to 60–70% of all laboratory errors [9]. The use of automated systems for sorting, centrifuging, dosing, and identifying samples contributes to a significant reduction in the frequency of errors associated with incorrect labeling, contamination, and violation of biomaterial storage conditions [10].