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Medical Informatics Meets Medical Education: the Croatian Experience

Author(s): Josipa Kern, Kristina Fišter

Objectives: The purpose of this paper is to describe the medical informatics program and training at the University of Zagreb, School of Medicine (Croatia).

Methods: We reviewed the medical informatics program, training and research for medical students at the integrated pre-graduate and graduate level, as well as at the postgraduate education and research level.

Results: We present three approaches to teaching and training medical students in medical informatics at the integrated pre-graduate and graduate level. These are (1) Basics of medical informatics taught early in the medical curriculum, (2) Medical informatics which uses students’ clinical knowledge and is taught towards the end of the medical curriculum, and (3) individualized research programs. Both Basics of medical informatics and Medical informatics are courses tailored in line with the IMIA Recommendations on Medical Informatics Education for IT users, and adjusted to students’ attitudes to medical informatics issues and the position of the courses in the medical curriculum. Postgraduate studies, as the higher level of education at the School of Medicine, also include several mostly elective medical informatics courses dealing with general medical informatics methodology and health information system management in both clinical medicine and public health. Included are also simulation modeling, methods of machine learning and knowledge discovery in medical domains, as well as medical statistics and methods oriented towards free textual data analysis. The postgraduate level includes in addition telemedicine, electrophysiological methods in research, and evidence based medicine.

Conclusions: Medical students are starting to recognize the role of information in their future profession. They require medical informatics applications to support their professional work with patients, as well as their research. In particular they express interest in machine learning, simulation modeling, medical decision making, data security, e-learning, and evaluation of ICT based medical applications.


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