Medical organization management processes optimization through prototyping algorithms definition

Relevance. In today’s competitive environment, project management can ensure higher speed and quality of achieving strategic goals set for the healthcare industry at minimal cost and risk. Due to the need to implement regional projects with higher speed and quality, the problems of algorithmization of project management processes become relevant. The aim of the study was to find a prototype model for managing the processes of a medical organization project, built on formalized data of the functional components of the project and algorithms obtained during stage-by-stage modeling of the system. Materials and Methods. The research materials included scientific developments, manuals and works of Russian and foreign authors devoted to the economic and mathematical model of decision support in organizations of various types, the adaptive abilities of medical organizations implementing national projects in healthcare. Results and Discussion. The complex multi-­level system of project implementation in the healthcare industry, the instability of the external environment and the diversity of stakeholder needs require finding an algorithm for the implementation of management processes. As part of the research question, in the process of constructing, formalizing the operation of the system, its elements, the presentation of data on the prototype of the medical organization project is iteratively refined — in accordance with the data, the algorithms are simultaneously refined. To build a model of a prototype of management processes in a medical organization in the region for the purpose of subsequent digitalization, it is necessary to formalize the variables, determine in accordance with the size of the range of values ​​that this variable can take, for subsequent effective algorithmization of management processes. The authors consistently correlated the stages of project management processes with the classification characteristics of models to establish the stages of their construction and modeling of the working model of the project prototype. Conclusion. Having established an optimal (effective) prototype of the project’s management processes, it can be immediately integrated into the project environment of a medical organization using machine learning methods.