Introduction: Within the framework of the National Healthcare Project, personalization of a physician’s activity is very important,forming a demand for a Clinical Decision Support System. The available systems miss the functions of prompting a doctor during theclinical process or identifying possible contradictions between different types of medical treatment offered to the patient. Purpose:Development of a solution, free from the above-mentioned problems, for personalized support of the clinical process. Methods:Automata (state machine) approach presenting the clinical process as a set of automata states and possible transitions between them,and a set of design patterns, namely: Abstract Factory, Facade, Adapter and Visitor. Results: A solution for personalized supportof clinical processes is proposed, based on the automata approach and design patterns. The automata approach allows you to dividethe clinical process into separate stages and automatically control the possible transitions and conditions for their implementation,including checking for c ontraindications. The use of design patterns provides a sufficient degree of generalization, allowing you,without affecting the structure of the main application code, to promptly connect the system to the necessary sources of information,and to enter the data about contradictions of various origins, taking them into account when making decisions on the treatment of aparticular patient. Practical relevance: The developed solution, as compared to the available systems, is more efficient at promptingthe doctor during a clinical process, and at identifying possible contradictions between the various types of medical treatment offeredto the patient.
The existing medical information systems do not provide the possibility of operational fixation and storage of such associative information. The paper proposes a system for storing the creative associations of the doctor, which are of interest both from the point of view of personalizing the approach to treating a patient, and from the point of view of forming a personalized physician knowledge base. We have developed an association storage system consisting of three levels: timestamps, semantic labels from external plug-in dictionaries, and a dictionary of doctor's own associations, being dynamically filled in by the system.The ensembling of search results in all connected dictionaries allows the user to expand the coverage and enrich the results of search results (enrich search results). The proposed structure of storing associations is universal and allows the user to refer to any objects. It can be easily embedded in the database of a medical institution or a specific physician, as well as in other structures for storing medical information -for example, in the form of links to external files or the doctor's own files.paper must have an abstract.
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