UnitLevel 5Postgraduate

EPM5029 Introduction to health data analytics

Faculty of Medicine, Nursing and Health Sciences

EPM5029 Introduction to health data analytics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences, offered in 2024 in Semester 1 at Alfred Hospital. It has no prerequisites and unlocks 1 unit.

Credit points
6
Offered in 2024
Semester 1
Alfred Hospital
Assessment
No exam
4 tasks

This is the 2024 handbook entry. See the 2027 entry.

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Requisites

Before EPM5029

No prerequisites or corequisites besides the enrolment rules below.

After EPM5029

1 unit list EPM5029 as a prerequisite or corequisite.

Enrolment rules

Must be enrolled in M6036 Master of Health Data Analytics, M6024 Master of Public Health, M6030 Master of Biotechnology, M6008 Master of Health Management, or M6028 Master of Clinical Research.

Overview

This unit provides you with a foundation for the study of Health Data Analytics by introducing key health, statistical and machine learning concepts. The unit commences with a discussion of the scope of health data analytics, to introduce you to the key ethical and privacy issues, provide you with a review of basic statistics and give you an overview of machine learning techniques and their applications.  You will be presented with the classification of health data analytics tasks into description, prediction and explanation. 
You will be introduced to the different sources of health data, including linked data, together with the appropriate methods for analysis and strengths and weaknesses surrounding their use. You will be involved in a discussion about the fast-changing nature of data analytics and current topics of major interest including precision and evidence-based medicine and the surge in data-driven evaluation and policy.

Offerings in 2024

Teaching periodCampusMode
First semesterAlfred HospitalOn campus

Assessment

  • Written assessment: Health data sources (Equivalent 2,100 words)
    35%
  • Written assessment: Literature review (Equivalent 2,100 words)
    35%
  • Written assessment: Ethics and Privacy (Equivalent 900 words)
    15%
  • Quizzes x 3 (10 questions per quiz each worth 5%)
    15%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Explain the appropriate use of health data analytics in health research.

  2. 2

    Describe the importance of ethics and privacy with health data analytics.

  3. 3

    Evaluate different health data sources for health data analytics.

  4. 4

    Differentiate between descriptive, predictive and explanatory research problems, and statistical compared with machine learning models.

  5. 5

    Evaluate the different uses of linked health data and explain their strengths and weaknesses.

  6. 6

    Describe the steps in data analytics.

Workload and teaching

  • Tutorials2 hours

Twelve hours per week, consisting of (on average)

  • 4 hours per week for reading core material
  • 1-hour online lecture materials (multiple videos)
  • 2-hour face-to-face tutorial
  • 2 hours per week for online communication via online moderated discussions, and
  • 3 hours per week for assignment and quiz preparation

No residential component is required.

Contacts

Unit Coordinators
Dr Joanna Dipnall
Chief Examiners
Dr Joanna Dipnall

Common questions

What are the prerequisites for EPM5029?

EPM5029 has no prerequisites, but enrolment rules apply.

What can I take after EPM5029?

EPM5029 is a prerequisite or corequisite for 1 unit, including EPM5032.

When is EPM5029 offered?

In 2024, EPM5029 runs in Semester 1 at Alfred Hospital.

Does EPM5029 have an exam?

No. EPM5029 has 4 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Medicine, Nursing and Health Sciences
Organisational unit
Department of Epidemiology and Preventive Medicine
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
202220232024202520262027