Securing FHIR Servers: Security Evaluation and AI-Driven Medical Data Analysis and Simulations for Enhanced Healthcare Services

Our project collaboration between the Goce Delcev University (UGD), and the University of Applied Sciences Upper Austria (UASUA) has a dual focus on enhancing healthcare security and utilizing AI-driven data analysis techniques for medical data, using the HL7 FHIR standard. The security aspect is done via a stenographic analysis of the standard and identifying vulnerabilities in FHIR servers. In addition, we plan to explore the application of AI algorithms and techniques to analyse medical data, especially for the purposes of improving treatment pathways and data quality. This is done primarily in two areas, Process Mining to identify pathways from logs, and then conformance checking them, as well as AI-driven medical data analysis and matching free text to machine-readable codes (e.g., SNOMED-CT), for the purpose of automatic data analysis. We plan to create mathematical models and perform simulations based on clinical guidelines and demographic data from both North Macedonia and Austria, to verify these goals. The integration of security measures and advanced AI-driven data analysis would contribute to a comprehensive approach for strengthening healthcare security while harnessing the power of AI in medical data analysis.