Recommended prerequisite for participation in the module

The module builds on knowledge, skills and competences obtained in the course module: Dataflow, Databases and Data Quality or knowledge, skills and competences equivalent to this.

Content, progress and pedagogy of the module

The course introduces with examples the role of decision support and decision support systems in clinical practice. Simple tools for decision analysis are introduced with examples as well as how to identify important attributes for a decision problem and how to ascertain the preference structure of a decision maker for a given decision. The course then introduces the basic elements and structure of a decision support system followed by theoretical and practical introduction to various knowledge-based methods for decision support systems. 

Learning objectives

Knowledge

• Can account for basic elements and structure of a decision support system. 

• Can account for and relate different methods for decision support system knowledge base. 

• Can account with examples for the role of decision support systems in clinical practice. 

Skills

• Can apply selected methods for visualizing a clinical decision problem. 

• Can apply selected methods for identifying appropriate attributes and decision maker’s preferences for a decision problem. 

• Can apply selected knowledge-based methods for decision support including rule-based methods, decision theory-based methods and model-based methods and Bayesian networks. 

• Can apply selected methods for decision support system inference engine including forward/backward chaining, fuzzy inference, basic numerical optimization, and probabilistic inference. 

Competences

• Can identify appropriate combination of methods for knowledge base and inference engine for a decision support system in relation to a clinical decision support problem. 

• Can combine understanding of methods for knowledge base and inference engine to design, implement and evaluate a simple decision support system. 

Type of instruction

This course focuses on the role of decision support systems in clinical practice and the software implementation of knowledge-based methods for decision support systems, supporting participants in handling development tasks in relation to clinical decision support systems. 

The teaching format is blended learning based on self-study of both written material and video clips, working with exercises, working with software implementation of methods for decision support systems, discussion in study groups and online seminars. 

Exam

Exams

Name of exam	Decision Support for Clinical Practice
Type of exam	Written or oral exam
ECTS	5
Permitted aids	See semester description
Assessment	Passed/Not Passed
Type of grading	Internal examination
Criteria of assessment	The criteria of assessment are stated in the Examination Policies and Procedures