School of Population Health

Digital Health - Principles, Practice and Evidence (PHCM9790)

This course is offered in two modes: face-to face (on-campus) and fully online by distance mode.


Digital health is “a broad umbrella term encompassing eHealth as well as developing areas of computing sciences in the fields of “big data”, genomics and artificial intelligence (AI)”. It emphasises digital consumers, with a wider range of smart-devices and connected equipment used through the Internet of Things (IoTs) and personalized health and medicine. Digital health will drive the transformation of the healthcare industry especially with the increasing role of the health care consumer, mobile technology and AI-driven precision medicine. The exponential growth of digital health requires the next generation of health professionals to be equipped with the knowledge and skills to successfully adopt and use appropriate digital solutions in their health settings. The focus is on the implementation and evaluation of digital health technologies on the heath system, health organisations, health professionals and citizens. The course will stimulate critical appraisal and understanding of the indicators of successful implementation, outputs and impacts of digital health tools and applications, data quality and interoperability standards, governance and social, legal and ethical challenges. These will be viewed through a framework for digital health maturity and the principles in evaluation of digital health interventions.

Interested students, who are not enrolled in a Masters program offered by the School of Population Health will need to contact the course convenor, who will assess whether they have the appropriate background, before enrolling in this course.

Credit points

This course is an elective course of the Master of Public Health, Master of Global Health and the Master of Health Leadership and Management comprising six units of credit towards the total required for completion of each study program. There are no pre-requisites for this course.

Mode of study

External (Distance, fully online) and Internal (Face-to-Face) classes on campus.

Course aim

This course aims to enable students to critically appraise digital health tools, understand the development, implementation, adoption and evaluation of currently available digital health solutions and determine its cost-effectiveness in clinical and/or population health practice. The student should consider the sociotechnical principles, validity and evidence, ethical challenges, legal and governance issues, utility and relevance in diverse local and international contexts.

Course Outcomes

By the end of this course you should be able to:

  • Discuss the strengths, weaknesses, opportunities and threats of digital health and artificial intelligence in society and the health system at macro, meso and micro levels.
  • Explain what user, technical, conceptual and contextual factors contribute to successful implementation of digital health and artificial intelligence tools.
  • Critically review the importance of evaluation and the determinants of successful evaluation from the perspective of single site effectiveness studies, multisite comparative effectiveness research and large scale-up of evidence-based digital health interventions.
  • 4.    Identify and justify what data quality benchmarks and interoperability standards are required, its importance and implications, and how it may be achieved and sustained to support health care and outcomes in context.
  • Discuss the governance, ethical, legal and social issues associated with digital health and artificial intelligence and the implications for health stakeholders and systems locally and internationally.
Teaching strategies and rationale

The course will highlight applications in digital health, critically evaluate and appraise these tools in healthcare delivery. The course will also introduce students to the design thinking concepts and methodological principles adopted in current digital health practices. The course will have a focus on the understanding and evaluation of the standards and interoperability frameworks and incorporating these in the design of efficient digital health systems.

We recognize that candidates in this course are graduates and/or employed in health services sector, and many will be studying part-time while working full-time. The course has therefore been designed to provide opportunities to critically engage with the key ideas and concepts and with each other via both face-to-face sessions and online environment (with discussions), develop an understanding of the fundamental principles in design and evaluation of digital health practice both individually (via reading, the preparation of assignments) and collaboratively (group discussions in face-to-face/online and peer review). The learning activities of the course has been designed to be hands-on and immersive in nature and include self-directed reading, face-to-face sessions, online activities including support for feedback after the workshop, reflective pieces, preparation of written assignments and peer review processes linked to the assignments.


Assessment 1 - Short Answer Questions
Weighting: 15%

Assessment 2 - Report
Weighting: 35%
Length: 800 words

Assessment 3 - Essay
Weighting: 50%
Length: 2000 words