Aim. The presented study aims to create a business model of a medical institution where the data-driven decision-making concept is implemented.Tasks. The authors define the data-driven concept; analyze successful cases of implementation of the data-driven concept in various organizations, including medical organizations; identify the technical requirements of this concept; develop business models of budgetary and commercial medical institutions with the with the introduction of the data-driven concept.Methods. This study uses such research methods as description, theoretical and comparative analysis, construction of business models, and systematization.Results. The concept of the data-driven approach to managerial decision-making is explored. Excerpts from foreign analyses of this approach are presented. The authors provide examples of successful implementation of the data-driven concept in organizations operating in various fields, including marketing, management, and medicine. The cases of PJSC Sibur Holding, PJSC SberBank, Seoul National University Bundang Hospital, and Memorial Sloan Kettering Cancer Center are considered. Technical requirements for the implementation of the data-driven concept are indetified. The business models of budgetary and commercial medical institutions operating according to this concept are described and analyzed in detail.Conclusions. The scope of application of the data-driven approach in managerial decisionmaking is extensive: this concept can be successfully applied in marketing, management, and medicine. In most cases, the company’s field of activity does not limit the applicability of this management approach. However, the implementation of the data-driven concept in the organization’s management will inevitably lead to high financial and labor costs. The authors believe that this concept can be used to successfully manage budgetary and commercial medical institutions in Russia in view of the steps toward implementing the data-driven approach provided in this study. The introduction of data-driven management will allow medical institutions to develop a personalized approach to patients and increase the level of work efficiency.
