Each module contains 3 ECTS. You choose a total of 10 modules/30 ECTS in the following module categories:
- 12-15 ECTS in technical scientific modules (TSM)
TSM modules teach profile-specific specialist skills and supplement the decentralised specialisation modules. - 9-12 ECTS in fundamental theoretical principles modules (FTP)
FTP modules deal with theoretical fundamentals such as higher mathematics, physics, information theory, chemistry, etc. They will teach more detailed, abstract scientific knowledge and help you to bridge the gap between abstraction and application that is so important for innovation. - 6-9 ECTS in context modules (CM)
CM modules will impart additional skills in areas such as technology management, business administration, communication, project management, patent law, contract law, etc.
In the module description (download pdf) you find the entire language information per module divided into the following categories:
- instruction
- documentation
- examination
This course provides an in-depth overview of data management in digital healthcare.
First, the special features and challenges of medical documentation will be discussed followed by the underlying ontologies, classifications and scoring systems. Particular emphasis will be placed on a deeper understanding of different dimensions of interoperability. This knowledge will be used to address exemplary specific medical information systems. Challenges for software development in the context of the Medical Device Regulation (“MDR”) are covered.
Digitalization considerations will then open the next section which deals with the particular challenges of digital transformation in healthcare. In particular, the inclusion of patients in future data collection will be discussed and demonstrated, as well as the potential of the merging of lifestyle data, vital data and medical documentation. The topic of data reuse from the different medical applications combined with security issus within the emerging data science centers is also a subject of this module.
Prerequisites
This course requires knowledge about
- the electronic - also sensor-based - structured data acquisition,
- user centered design,
- a good understanding
- of database-concepts,
- of information systems and
- of general data analysis.
Learning Objectives
The aim of this lecture is to understand,
- how Data are collected in medicine,
- how these data are organized in a structured and interoperable way,
- the importance of information systems in this context,
- the role of these systems as a basis for digital transformation in the healthcare sector,
- how information systems can be linked with eHealth, mHealth (“mobile Health”), pHealth (“personalized Health”)
- how future active assisted living can be supported
- and the impact of MDR on the professionalization of medical software and apps.
Contents of Module
First Part (6 weeks):
- Medical & Health Data Documentation (1 week)
- Hospital & Health Care Information Management Systems (1 week)
- Medical Ontologies and Classification (2 weeks)
- Dimensions of Interoperability in Health Care Systems (2 weeks)
Second Part (8 weeks):
- Device Connectivity, FHIR, MDR for software (1 week)
- Digitalization & Transformation in Treatment Pathways (1 week)
- mHealth & App – Ecosystems (1 week)
- eHealth & EPD (1 week)
- pHealth and Data Science Center (1 week)
- From Data to Predictive Models (2 weeks)
- Home Monitoring (1 week)
Teaching and Learning Methods
Lectures and practical work on computer.
Literature
Slides and lecture notes will be available in addition to recommended book chapters.
Download full module description
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