DOI:https://doi.org/10.15407/kvt207.01.059
Cybernetics and Computer Engineering, 2022, 1(207)
O.S. Kovalenko, DSc (Medicine), Professor,
Head of the Medical Information Systems Department
ORCID 0000-0001-6635-0124
e-mail: askov49@gmail.com
L.M. Kozak, DSc (Biology), Senior Researcher,
Leading Researcher of the Medical Information Systems Department
ORCID: 0000-0002-7412-3041
e-mail: lmkozak52@gmail.com
M. Najafian Tumajani,
Junior Researcher of the Medical Information Systems Department,
ORCID:
e-mail: najafian@mail.ru
O.O. Romanyuk,
Junior Researcher of the Medical Information Systems Department
ORCID:0000-0002-6865-1403
e-mail: ksnksn7@gmail.com
International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
40, Glushkov ave., Kyiv, 03187, Ukraine
EXPERIENCE AND PROSPECTS OF CREATING MEDICAL INFORMATION SYSTEMS AND INFORMTION TECHNOLOGIES TO SUPPORT MEDICAL CARE
Introduction. One of the four flagship initiatives identified by the WHO as health priorities for the coming years is the Flagship Initiative to enable citizens for receive quality health care through digital health care. The use of digital medical technologies to provide health care will serve for strengthening the health care system, empowering patients and achieving the principle of “health for all”.
The purpose of the paper is to summarize the experience and latest results of the scientists of the Medical Information Systems Department of the International Center for Research and Development of Medical Information Systems and Information Technologies of Digital Medicine against the background of the general process of digital transformation in medicine.
Results. The main characteristics and principles of building modern medical information systems (MIS) as components of the digital medicine ecosystem are determined. Internal and external information flows of MIS are analyzed. To further differentiate the representative attributes of these documents, three similar but different technologies associated with the patient card were identified: electronic medical records, electronic health records and electronic patient health passport, each of which is differentiated based on the level of patient orientation. Based on one of the principles of “5Ps medicine”, the principle of personalization, the structure of personal medical storage is determined, which according to modern challenges is needed by all participants in digital medicine infrastructure (patients, doctors, laboratories and functional diagnostics departments, etc.). To ensure the interconnection of such repositories, models of business processes of accumulation and exchange of digital medical data have been created and based on them mobile applications, modules for accumulation and exchange of digital medical data between different users in the process of diagnostic data analysis have been developed. The interaction of mobile applications with the local information environment of the health care institution is analyzed and its features are taken into account in the created specialized mobile software modules of accumulation and analysis of personal medical data.
Conclusion. The developed model of digital transformation in medicine, which includes digital methods of obtaining and analyzing biomedical signals, digital medical images, methods of forming electronic medical records and documents, allowed to create methods and tools for building the digital medicine ecosystem using global intellectual resources to provide the necessary level for analysis Big Data and decision support for doctors at all stages of medical care. The use of developed mobile applications of accumulation, analysis and exchange of personal medical data allows to review the accumulated data, assess and predict human health according to the developed Data Mining models and implement medical data exchange of different origins between patient and doctor.
Keywords: medical information systems, digital medicine ecosystems, medical information technologies, mobile applications, classification models Data Mining.
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Received 14.01.2022