Abstract
<jats:p>The healthcare system of Ukraine is undergoing structural transformation driven by the implementation of the Medical Guarantees Program and the transition to a patient-centered financing model. These changes significantly increase the role of data and analytical tools in the management of healthcare institutions, particularly in the context of interaction with the National Health Service of Ukraine. Under such conditions, the effectiveness of management decisions increasingly depends on the quality of data collection, processing, and interpretation. The aim of the study is to substantiate the role of analytical support in healthcare management within the framework of cooperation with the National Health Service of Ukraine and to develop a multi-level model of organizing analytical activities in healthcare institutions. The research is based on a combination of general scientific and special methods, including system analysis for identifying key elements of analytical support, comparative analysis for evaluating different organizational approaches, and a structural-functional approach to determine the roles and interactions of participants in the analytical process. The study identifies the main components of analytical support in healthcare institutions, including financial mechanisms, digital systems such as eHealth, and internal reporting tools. The key sources of data used for management decision-making are systematized. A multi-level model of analytical activity is proposed, integrating managerial, departmental, and individual levels. This model ensures the consistency of analytical processes and improves the quality of decision-making. It is demonstrated that the integration of data from different sources enhances the transparency and efficiency of healthcare management. The findings confirm that analytical support is a critical element of modern healthcare management. The proposed approach enables healthcare institutions to improve resource allocation, enhance service quality, and adapt to ongoing reforms. The implementation of a multi-level analytical model contributes to the development of data-driven management and supports the sustainability of healthcare systems in dynamic environments.</jats:p>