SummaryBackgroundThe most common sources of error in the preanalytical phase are considered to be at the stage of patient preparation and sample collection. In order to reduce the preanalytical errors, we aimed to determine the level of phlebotomists knowledge about the preanalytic phase before and after planned trainings in the study.MethodsTraining about preanalytical processes was given to the 454 health professionals and the majority of them were employed as nurse. Questionnaires before and after training were conducted. In order to assess the effect of the training into the process, preanalytical error rates were calculated before and after training.ResultsThe total correct answer rates of vocational school of health diplomaed were statistically lower than the total correct answer rates of other. It was observed significantly increase in the rate of correct answers to questionnaire and significantly decrease in preanalytical error rates after training.ConclusionsThe results of the survey showed that the attitudes of the phlebotomists were diverse in the preanalytical processes according to the levels of education and their practices. By providing training to all staff on a regular basis, their information about preanalytical phase could be updated and hence, it may possible to significantly reduce the preanalytical errors in health practice and nursing science.

Digitalization and artificial intelligence in laboratory medicine interpretation will further increase the effectiveness of laboratory diagnostics in the process of intensive dialogue/ consultation and clinical decision-making. Medical laboratories may play an active role in the future as a "nerve center of diagnostics" and joining the patient and physician to form a "Diagnostics 4.0" triangle. As the big data continue to grow in healthcare, the need for implementing AI and ML techniques into laboratory medicine is inevitable. In this new AI-supported era, clinical laboratories will move towards a more specialized role in translational medicine, advanced technology, management of clinical information, and quality control of results generated outside the laboratory. The field of laboratory medicine should consider such a development sooner rather than later.

No abstract