Course - Clinical Information and Knowledge Systems - IT6122
Clinical Information and Knowledge Systems
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About the course
Course content
The course will give a theoretical and practical introduction to different kinds of decision support, modelling of clinical information and knowledge, clinical recommendations and guidelines, evaluation and quality.
Learning outcome
By completing this course, you will have
knowledge about:
- clinical decision support
- history of development of decision support systems
- the role of knowledge modelling in decision support
- common forms of decision support like rule-based reminders, clinical guidelines and recommendations, on-demand cases and data-driven decision aids.
- the relationship between decision support and health records.
cababilities in:
- modelling information and knowledge in UML, OWL and similar formalisms
- making simple rule-based systems
- using Protégé
general competency in:
- opportunities and limitations for clinical decision support
- experience with clinical decision support
- representations of clinical recommendations
- norms and standards related to decision support software
Learning methods and activities
The course is project- and laboratory-oriented and develops practical capabililties through experiments, programming, modelling, testing and evaluation.
Collaborative group effort combined with lectures and participant work experience enables multidisciplinary methods and student-driven learning.
Further on evaluation
The exam is portfolio assessment and consists of the following:
- Two individual assignments that each count ¼ of the portfolio. Each of the assignments can include both programming, multiple choice answers, and open texts.
- One group assignment that counts 1/2 of the portfolio. The group assignment consists of an implementation project and a project report.
All assignments must be submitted in Inspera. In the group assignment, the students must create and submit an agreement and a self-declaration on cooperation and each student's own effort. Everyone in the group gets the same score for the joint answer. Each part of the portfolio is given points between 0 and 100. Letter grade is given individually on the total portfolio and on the basis of points and weighting of the parts included.
Specific conditions
Admission to a programme of study is required:
Healthcare Informatics (MHI)
Recommended previous knowledge
Basic knowledge and practice in software engineering and programming. Ability to read english academic literature.
Required previous knowledge
Applicants should have passed IT6101 Introduction to Health Informatics and IT6102 Programming, or document similar formal or practical competency.
Course materials
Will be specified at start of course.
Coiera: The Guide to Health Informatics, 3ed, 2015. Robert A. Greenes: Clinical Decision Support: the road to broad adoption, 2ed, 2014. Forskningsartikler.
Other pages about the course
Subject areas
- Technological subjects
Contact information
Course coordinator
Lecturers
Department with academic responsibility
Department of Computer Science