eHealth

Electronic health records | Public health | Evidence-based medicine | Software as a medical device | Clinical decision support | Artificial intelligence | IT management | Data management in clinical research | Privacy and security

Rapid technological developments and progressive digitalisation in the health and social care sectors are changing the demands on academic training. In response, the eHealth Master’s degree programme has been completely redesigned to reflect these current developments. In the 2nd and 3rd semester, students can specialise in one of the following three fields:

• Software Engineering
• Machine Learning
• IT Management

You can further supplement your selected field of expertise by choosing two additional subjects from a list of eight electives. You also have the opportunity to complete your Master’s project and Master’s thesis while working with potential employers. This allows each student to create a course of study which matches their own personal interests and strengths and is relevant to a future career in the growing eHealth profession. Ideally applicants will be graduates with a Bachelor’s degree in computer sciences. However, graduates of health or business degree courses are also eligible to apply, provided that they can demonstrate a strong affinity for IT. During the 1st semester the Introduction to the Master’s course will give you an initial overview of each of the three specialisations so that you can make an informed choice. The lecturers on the eHealth programme provide active support in this selection process.

Health Informatics

You will become familiar with the relationship between medical documentation (ICD-10, LOINC, DICOM, DRG, CDISC, ICPC-2, NANDA, ICF, ATC, …), semantic interoperability (HL7-CDA, FHIR, SNOMED-CT, IHE, …) and modern eHealth and mHealth applications in the fields of public health or clinical research. Students have access to a free Cochrane library for more intensive study and evidence-based analysis. We also give you an overview of international trends and common medical standards concerning electronic health records and introduce you to the Austrian ELGA system. The course regularly invites specialists from the sector to give guest lectures. Business intelligence and sophisticated data privacy and security topics such as blockchaining, technical implementation of the GDPR or cryptography round off the health informatics portfolio.

Health Sciences

The specialist subjects of public health, evidence-based medicine and epidemiology will give you a profound overview of general public health topics ranging from prevention and health promotion to acute and long-term care. You will learn how to deal with questions of clinical research and public health and how to plan and implement research and development projects. The topics covered include the design of clinical studies as well as regulatory and ethical aspects. Based on the new guidelines of the General Data Protection Regulation, you will be introduced to the principles of data management both in the clinical environment and when dealing face to face with people.

Health Management

In addition to introducing you to general management subjects, the course will also make you familiar with the key requirements of quality management in terms of Good Manufacturing Practice and Good Laboratory Practice. This will prepare you for a career in specialist companies of the pharma and biotech sectors. You will also learn to assess the effects of basic concepts on change processes and eHealth applications as well as medical interventions and drugs using health technology assessment.

Software Engineering

This specialisation is aimed at students who wish to specialise in medical software engineering and develop products for the healthcare market. In the field of smart eHealth technologies you will be introduced to classical and agile methods of medical software development. You will become familiar with the entire development cycle of eHealth applications, from requirement analysis, usability design and human-centred interaction through to product development taking into account the regulatory requirements of data protection and the Medical Devices Act. You will acquire advanced technical knowledge of modern software architectures, the integration of mobile end devices and sensors via radio technologies (NFC, RFID, Bluetooth, …) and advanced network protocols (Internet of Medical Things).

Machine Learning

This specialisation is suitable for students who wish to work as data analysts in the health and social care sector. You will focus on multivariate statistical methods such as variance, regression and cluster analysis as well as big data analysis. You will also become familiar with enhanced knowledge-based information systems and clinical decision support systems including methods of fuzzy logics and Arden syntax. You will learn to use common methods of artificial intelligence such as deep learning, machine learning, support-vector machines and CART and apply them to topics related to the health and social care sector. The specialisation also covers topics of advanced medical image processing. We use R and Matlab as tools and Python for programming.

IT Management

This specialisation is aimed at students who wish to take on management responsibility for IT applications in companies in the healthcare sector. You will deal with the tasks and duties of management and the different requirements of all stakeholders in the healthcare sector. This requires identifying the strategic objectives of companies in the healthcare sector and monitoring their implementation in regular business operations. The curriculum includes corporate controlling, HR management, quality and risk management as well as current legal topics (company law, copyright law, procurement law, etc.).

The topics include IT project management according to IPMA, SCRUM, etc. and IT service management, such as ITIL. You will also become familiar with the methods of business process management (BPM) in relation to clinical and intersectoral paths based on evidence-based guidelines.

Study mode

The programme is designed to be work-friendly with lectures being held on Wednesdays, Thursdays and Fridays during the first, second and third semesters. In the fourth semester the students write their Master’s thesis and, apart from occasional seminars, are not required to attend classes on campus. This allows students to combine a part-time job with the course. E-learning units are not available.

Attendance

In principle, students are expected to attend all lectures at FH JOANNEUM. Final judgement on the implications of absence and on exceptions to the attendance requirement (for example, as the result of illness, or where elective subject courses overlap) will be made by the head of degree programme.