Context of Health Data Science - HDAT9100

Faculty: Faculty of Medicine

School: School of Medical Sciences

Course Outline: MSc Health Data Science

Campus: Sydney

Career: Postgraduate

Units of Credit: 6

EFTSL: 0.12500 (more info)

Indicative Contact Hours per Week: 9

CSS Contribution Charge: 3 (more info)

Tuition Fee: See Tuition Fee Schedule

Further Information: See Class Timetable

View course information for previous years.


This is a core course of the Graduate Certificate 7372, Graduate Diploma 5372 and Master of Science in Health Data Science 9372.

This course provides an outline of what a contemporary healthcare system looks like. It prompts the student to question what is 'health', what impacts upon it, and how is it ‘measured’? What influence does culture and/or geographical location play in this particular viewpoint? What is 'Evidence Based Medicine'? What role does ethics and patient confidentiality hold? What might healthcare systems and thus health research look like in the future? The strengths and limitations of big data will be introduced. Set against this background, the Health Data Science pipeline is introduced.

The over-arching goal is to foster a scientific, questioning attitude in the student, further growing their enthusiasm for Health Data Science.

Learning Outcomes

1. Discuss health delivery systems
2. Evaluate health outcome measures
3. Appraise the concept of Evidence Based Medicine
4. Judge ethical considerations in health research
5. Assess the role of technology in future health research
6. Describe the Health Data Science pipeline

Contact hours per week

Lecture/seminar: 2 hours
Tutorial: 1 hour
Web-based online learning activities: 6 hours

Study Levels

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