Algorithm for the development and architecture of a prototype information-analytical system for supporting management decisions in a medical organization operating under biological, technological, and geopolitical challenges

IThe article examines the development algorithm and architecture of a prototype information-analytical decision support system (IADSS) integrating data on a network of medical organizations, their resources, and patient flows. The system is designed to operate both in routine mode and in emergency situations, providing forecasting, optimization of resource allocation, and coordination between departments and medical organizations.

The IADSS prototype was developed using a modular approach and a service-oriented architecture. Geoinformation services, modern programming languages, frameworks, analytical libraries, and visualization tools were used in the development.

The architecture includes a geoinformation module for displaying and analyzing medical infrastructure, a BPMN business process editor, a simulation and optimization modeling module, calculators for computing integral sustainability indices, as well as tools for reporting, monitoring key performance indicators (KPI), managing resource inventories and information security.

The implemented IADSS prototype combines more than ten interconnected microservices, ensuring flexibility, scalability, and the ability to integrate with external information and analytical systems. The viability of the architectural approach was verfied through functional testing on synthetic datasets simulating biological, technogenic (man-made), and geopolitical threats scenarios. The comprehensive integration of geoinformation technologies, business process modeling, analytics, and optimization tools improves the preparedness of healthcare organizations to respond to emergencies, minimizes the impact of external threats, and reduces decision-making time. The proposed architecture can serve as the basis for the further development of regional decision support systems in healthcare, enhancing the system’s resilience and operational efficiency in the face of global challenges.

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