The course is connected to the following study programs

Teaching language

English

Recommended prerequisites

IKT462 Digital Health: Fundamentals", or equivalent courses.

Course contents

The goal of this course is to provide the students with detailed theoretical and hands-on knowledge and with practical methods and competences needed for the development of future Digital Health solutions. The focus is particularly on two perspectives - "Digital Health Applications" and "Digital Health Data".

"Digital Health Applications" relates to the role of a solution designer and developer of user applications for the health and care sector, dealing with aspects of Human-Computer-Interaction (HCI) and user-centered design (UCD) of solutions involving different stakeholder groups. "Digital Health Data" relates to the role of a data engineer, designing and developing the data model from data collection by eHealth devices and applications, data integration, communication, and storage to processing, evaluation, and provisioning.

The course will in the first part provide all students with a common theoretical overview over both perspectives. In the second part, the students will specialize for one perspective, based on their background and interests, and will proceed with supervised eLearning, including self-study and micro-assignments.

The course will cover

  • Methodologies and methods for user-centered and multi-disciplinary co-design of digital health applications and services.
  • Skills for planning and execution of test, verification and evaluation of eHealth solutions.
  • Identification and application of AI in digital health solutions and services.
  • Structuring and representation of digital health data in ontologies, and their implementation in standardized terminologies and classifications.

Learning outcomes

After the course, the student will

  • be able to assess user needs, opportunities and limitations when applying new ICT solutions in the health and social sector, specify requirements and define development approaches
  • be able to identify key principles, design requirements and evaluation methods for user-system interaction
  • have general competence in concepts of Clinical Decision Support Systems (CDSS) and Natural Language Processing (NLP)
  • have a general understanding of the functionality of AI, and the potential strengths and limitations for eHealth solutions
  • have knowledge of the main terminologies and classifications of the healthcare sector, and their use and relevance in eHealth solutions
  • specific for "Digital Health Applications":
    • have knowledge and practical skills in User-Centered Design (UCD) and multi-disciplinary co-design of new and innovative solutions for the healthcare sector
    • be able to plan, prepare and conduct the test, verification and evaluation of eHealth devices, applications and services, considering usability, efficacy, efficiency and other key performance indicators (KPI)
  • specific for "Digital Health Data":
    • have in-depth knowledge of ontologies relevant for the structuring of eHealth data
    • have competence and skills in the relevance and application of AI Learning Automata, Probabilistic Reasoning and Pattern Recognition in eHealth solutions for decision support

Examination requirements

  •  
  • min. 75% participation in compulsory lectures (i.e. min 3 out of 4)
  • min. 75% submission of weekly self-study assignment (i.e. 3 out of 4)

Teaching methods

  •  
  • Lectures (compulsory teaching: 2 lectures á 4 lecture-hours on "Digital Health Applications", and 2 lectures á 4 lecture-hours on "Digital Health Data"; physical on-site, alternatively digitally on-line);
  • Self-studies with books and scientific paper publications, combined with 4 weekly exercises to write short reports/essays related to lecture topics
  • Self-study group assignment on pre-defined or student-proposed topic from the "Digital Health Applications" or the "Digital Health Data" fields, involving deepening self-studies with books and scientific paper publications
  • Expected total extent of workload corresponding to 7.5 ECTS is 200 hours

Evaluation

The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Offered as Single Standing Module

Yes, if there are places available

Admission Requirement if given as Single Standing Module

Admission requirements for the course are the same as for the master’s programme in ICT.

Assessment methods and criteria

Graded essay / report on group assignment. Group is graded as a whole (all group members receive the same group-grade).

Last updated from FS (Common Student System) June 30, 2024 1:55:45 AM