Design Automated Medical Information and Analytical Management System for Large and Medium-Sized Organizations

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Advances in Artificial Systems for Medicine and Education VI (AIMEE 2022)

Abstract

The development of an automated medical document verification system has implemented the automation of the clinic’s business document management process, significantly speeding up and improving the interaction of medical staff in the workplace in order to provide better services. Efficient use of databases, and document-oriented data warehouses, including dual-use ones, allows certain operations to be performed efficiently and quickly, i.e. adding patient records, changing records, performing periodic or analytical data searches and operations to ensure quality decision management. The focus is on the interaction of distributed heterogeneous applications and independent institutional hardware, develo** professional medical client applications; thus, improving the quantity and quality of information data flows required for efficient patient care. The designed software application allows automatic patient record kee** with the needs of the medical staff, especially in the management of patient visits (scheduling) and the creation of patient medical records in accordance with current international standards. This work is basic for a smoother integration of medical records and data and effective prevention, diagnosis and prognosis. As the appropriate approaches and standards used have improved health information technology functions as well as the quality and safety of patient care, we have created a global architecture of specific medical automation systems, coordinating internationally regulated HL7 medical services to ensure system scalability in the global future.

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Correspondence to Nadiia Pasieka .

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Pasieka, N., Romanyshyn, Y., Chupakhina, S., Oliinyk, M., Kyrsta, N., Pitulei, A. (2023). Design Automated Medical Information and Analytical Management System for Large and Medium-Sized Organizations. In: Hu, Z., Ye, Z., He, M. (eds) Advances in Artificial Systems for Medicine and Education VI. AIMEE 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 159. Springer, Cham. https://doi.org/10.1007/978-3-031-24468-1_29

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