BACKGROUND: The relevance of the study is due to the insufficient study of the requirements for digitalization in healthcare.
 AIM: The aim of this research is the scientific substantiation of requirements for digitalization of optimization technologies in healthcare, and their approbation on the model of management decision-making in medical institutions.
 MATERIALS AND METHODS: An anonymous survey involved 32 teaching experts from organizational departments and the Department of Philosophy, Humanities and Psychology of Saratov State Medical University named after V.I. Razumovsky, where optimization technologies have been rapidly developed and introduced into teaching and practice. Experts were asked to use a 10-point scale to evaluate the list of requirements for digitalization of optimization technologies in healthcare, and their significance. As the data distribution did not correspond to the binomial Gauss–Newton curve, the assessment of the reliability of differences was performed using the nonparametric Mann–Whitney criterion.
 RESULTS: A list of seven requirements for the digitalization of optimization technologies in healthcare, relevant to information support, automated evaluation of the initial state, implementation of the provisions of flexible changes methodology, virtualization of the optimization goal, cyclic optimization process, unified information space, organization of professional training was designed. Since the significance of all these requirements is essential (more than 8.0 points), we can suggest that when assessing the compliance of a particular technology, the entire list should be implemented. It turned productive to use the results of designing the technology for optimization of managerial decision-making in medical institutions for approbation of reasonable requirements.
 CONCLUSION: The requirements for digitalization of optimization technology in healthcare have been substantiated. It has been proved that the technology of optimizing managerial decision-making in medical institutions is digitized. The findings of this study can be used in both assessing the degree of digitalization of optimization technologies in healthcare and the professional training of healthcare managers.