CS979 - Decision Support and Health Analytics

Aims and Objectives

The class will provide students with a robust understanding of the technologies and principles underpinning predictive modelling, complex health data visualisation, clinical coding and clinical document architecture, knowledge representation, decision support system and data linkage.

Learning Outcomes

After completing this class participants will be able to:

• understand healthcare data, data quality and information systems quality;
• understand a range of techniques and technologies to aggregate and interrogate complex healthcare data and synthesize results in a meaningful way;
• use data visualisation principles and techniques to present healthcare data for meaningful use;
• understand clinical knowledge management methodologies and clinical knowledge models, representation and reasoning;
• understand the structuring of knowledge and data for computer-based processing;
• understand how clinical guidelines can be used for developing clinical decision-support algorithms and systems.

Syllabus

Each of the following will consist of a 2-hour lecture, with corresponding lab and personal work:

• Introduction to Analytics & Decision Support
• Sensors, wearables and Environmental Triggers
• Patient reported experience and outcomes
• Making sense of Complex Data
• Predictive Modelling
• Displays, Notifications and Visualisations
• Clinical Coding Systems
• Clinical Document Architecture
• eHealth Knowledge Representation
• Clinical Decision Support Systems
• Epidemiology / Data Linkage

Recommended Reading

This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.

Healthcare Data Analytics. Reddy, C.K. and Aggarwal, C.C. Chapman and Hall / CRC Press, 2015. ISBN-13: 978-1482232110 | Stocked at Amazon (Other retailers are available)

Handbook of Medical Informatics. van Bemmel, J.H. and Musen, M.A. Springer-Verlag, Heidelberg. 1997. | Stocked at Amazon (Other retailers are available)

Last updated: 2022-09-09 13:45:09