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Lecturer(s)
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Krystyník Ondřej, MUDr.
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Kolář Milan, prof. MUDr. Ph.D.
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Vaněk Jakub, MUDr. Ph.D.
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Gergely Ondrej, Mgr.
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Slaninová Nikola, Ing.
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Král Jakub, Ing.
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Matějka Filip, Mgr.
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Heřman Miroslav, prof. MUDr. Ph.D.
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Táborský Miloš, prof. MUDr. CSc., FESC, MBA
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Klásková Eva, doc. MUDr. Ph.D.
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Hlavinka Antonín, Ing.
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Kučera Petr, MUDr.
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Kolář Martin, Mgr.
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Genzor Samuel, MUDr. Ph.D.
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Štýbnar Michal, Mgr.
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Doleček Zdislav, Mgr.
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Wita Martin, MUDr.
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Mazalová Romana, PhDr. PhD.
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Mizera Jan, MUDr.
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Havelka Ladislav, Ing.
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Course content
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Cybersecurity, GDPR. eHealth (mHealth), Interoperability. Legal aspects of eHealth and public procurement in healthcare. Hospital and outpatient information systems in healthcare. BigData, ML and AI (Machine Learning and Artificial Intelligence) - Healthcare applications. Imaging - PACS and teleradiology. Registries and central data - IHIS. Social networks, PR and user experience (UX) in healthcare. Assistive technologies. Telemedicine, mHealth applications for medical use, sensors and IoT.
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Learning activities and teaching methods
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Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
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Learning outcomes
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The aim of the course is to acquaint students of the General Medicine with the basic principles of digital medicine of the third millennium. Emphasis is placed on mastering the basic IT principles, including IT security, legal and technical aspects, as well as on the use in everyday clinical practice in fields and diagnoses where digital medicine, resp. telemedicine brings clear benefits to the patient, healthcare facilities and healthcare payers.
The aim of the course is the student's ability to work with standard hospital and outpatient information systems, registries and other data sources, to use digital forms of education within the Faculty of Medicine and later in postgraduate education. Furthermore, the student will be able to work with various peripherals that measure and interpret the physiological values of the patient, evaluate them and respond in a timely manner to major changes in health. Knowledge of the use of artificial intelligence and large data for the design of patient diagnosis and treatment algritms will also be standard.
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Prerequisites
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The condition for completing the course is the completion of the 3rd year of study.
PAT/VAB11 and PFY/VAB11
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Assessment methods and criteria
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Written exam, Student performance
The requirement for completing the course is a minimum of 80% attendance and further completion of the electronic final test with a minimum of 80% correct answers.
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Recommended literature
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Táborský, M., Kautzner, J., Linhart, A. a kol. (2021). Kardiologie. Grada Publishing.
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