СLINICAL DECISION SUPPORT SYSTEMS: FOREIGN EXPERIENCE (LITERATURE REVIEW)

Abstract

The article analyzes the foreign experience of using various clinical decision support systems. Clinical decision support systems are computing or technology systems designed to meet specific healthcare requirements. A traditional clinical decision support system consists of software designed to directly aid clinical decisions, in which individual patient characteristics are matched against a computerized clinical knowledge base, and patient-specific assessments and recommendations are then provided to the clinician for decision-making. Their advantages related to facilitating the work of a medical worker, opportunities to reduce the workload, optimizing the amount of time for diagnosis and treatment of diseases, and choosing the most optimal ways of solving the tasks are considered. Clinical decision support systems, when used correctly, can significantly improve the work of hospitals and accelerate the establishment of the correct diagnosis. The importance of information and technological progress and cybernetic opportunities for the implementation of clinical procedures is clarified. The “critical points” of using artificial intelligence and machines capable of self-learning are discussed, because data from clinical decision support systems is full of problems, including problems with understanding the logic used by artificial intelligence to create recommendations (black boxes), as well as problems with data availability. In our opinion, the moderate and professional attitude of the medical staff towards clinical decision support systems is important, as well as opportunities to improve their knowledge and skills in the “smart” use of computer technologies. We believe that it is expedient to train medical workers in new medical informatics by conducting courses and internships to implement clinical decision-making support systems in all healthcare institutions of Ukraine. The development and analysis of already existing domestic clinical decision-making support systems for the implementation of the abovementioned conclusions remains a promising direction.