Handbook home
Digital Health and Informatics Methods (INFO90001)
Graduate courseworkPoints: 12.5Online
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
Semester 1
Semester 2
Overview
Availability | Semester 1 - Online Semester 2 - Online |
---|---|
Fees | Look up fees |
This subject offers an overview of major health informatics research areas and methods that contribute to quality improvement, scientific research, and technological innovation in healthcare and biomedicine. The subject sets out the scientific foundations of digital health, and disciplined approaches to understanding the implications of digital health for health system performance.
The subject is arranged in blocks of study that examine methods for: (a) Undertaking digital health research and innovation projects, including: justifying a project in pragmatic and conceptual terms; drawing on existing practice and knowledge; specifying and staging work packages; meeting needs for partnerships and resources; assuring socially and ethically responsible conduct; reporting on progress rigorously and communicating for impact; (b) Managing exponential growth in health and biomedical knowledge, including: increasing openness in research data life cycle management; automating processes of generating, synthesising, and translating evidence; assuring the quality of electronic decision support systems for clinicians and patients; producing sophisticated forecasts and scenarios of the future of health; (c) Analysing structured and unstructured health data, including: wrangling phenome, exposome and other omics data; scaling up clinical, translational and population health research on platforms; approaching artificial intelligence in medicine through data analytics techniques and machine learning; (d) Modelling and simulating the dynamics of health conditions and health services, including: building personalised and population-level models of health and disease; mapping patient journeys, clinical workflows, and health supply chains; creating immersive environments for healthcare system learning and research.
Intended learning outcomes
On completion of this subject, students should be able to:
- Associate a range of real-world health research and development needs with appropriate health informatics methods
- Identify, access and apply essential, selected health informatics tools
- Assess claims made in digital health research and innovation reports in terms of the quality of evidence
- Form and communicate a view of medium and long term trends in a specific area of health information and communication technology
Generic skills
- locating and critiquing scientific, industry and policy literature from multiple disciplines
- framing, designing and planning a research project
- structuring oral and written presentations of a research project
- participating in the production, dissemination and application of evidence
Last updated: 6 March 2024
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
This subject assumes that participants are aware of basic information resources in digital health and informatics, such as those shown at https://unimelb.libguides.com/healthinformatics . Prior experience with using these resources is not essential.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 6 March 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Two written reports of individual work on assigned practical activities. Students will be able to choose from four topics. Each report will be 1000 words (20% each)
| During the teaching period | 40% |
Individual Oral Presentation
| Week 12 | 20% |
Major Project Report
| During the examination period | 40% |
Last updated: 6 March 2024
Dates & times
- Semester 1 - Online
Coordinator Kathleen Gray Mode of delivery Online Contact hours 2 hours per week of active participation in scheduled online tutorials. Students unable to attend a tutorial may submit their contribution beforehand and review proceedings afterward. 10hours per week of independent study and participation in asynchronous Total time commitment 164 hours Teaching period 26 February 2024 to 26 May 2024 Last self-enrol date 8 March 2024 Census date 3 April 2024 Last date to withdraw without fail 3 May 2024 Assessment period ends 21 June 2024 Semester 1 contact information
- Semester 2 - Online
Coordinator Kathleen Gray Mode of delivery Online Contact hours 2 hours per week of active participation in scheduled online tutorials. Students unable to attend a tutorial may submit their contribution beforehand and review proceedings afterward. 10hours per week of independent study and participation in asynchronous Total time commitment 164 hours Teaching period 22 July 2024 to 20 October 2024 Last self-enrol date 2 August 2024 Census date 2 September 2024 Last date to withdraw without fail 20 September 2024 Assessment period ends 15 November 2024 Semester 2 contact information
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 6 March 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Subject notes
LEARNING AND TEACHING METHODS
This subject is offered in semester 2 each year, as a 3 hour class one evening each week over a 12 week period, including lectures, tutorials and small group activities. Opportunities are provided for online interaction during class using students’ personal internet-connected devices.
Classroom teaching is complemented by a subject website in the University Learning Management System. Students unable to attend class on campus can participate each week, by going online to access lecture slides and recordings, undertake practical activities, and complete assessable work.INDICATIVE KEY LEARNING RESOURCES
This subject has no textbook. Students have access to electronic full-text of recommended readings, including current journal articles, government documents and industry reports. Examples:
Dahlin, S., Eriksson, H., & Raharjo, H. (2019). Process mining for quality improvement: propositions for practice and research. Quality Management in Healthcare, 28(1), 8-14.
Enam, A., Torres-Bonilla, J., & Eriksson, H. (2018). Evidence-based evaluation of eHealth interventions: systematic literature review. Journal of Medical Internet Research, 20(11), e10971. Full-text open access URL: https://www.jmir.org/2018/11/e10971
Gianfrancesco, M. A., Tamang, S., Yazdany, J., & Schmajuk, G. (2018). Potential biases in machine learning algorithms using electronic health record data. JAMA Internal Medicine, 178(11), 1544-1547.
Van de Velde, S., Kunnamo, I., Roshanov, P., Kortteisto, T., Aertgeerts, B., Vandvik, P. O., & Flottorp, S.(2018). The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support. Implementation Science, 13(1), 86.
Wong, A., Young, A. T., Liang, A. S., Gonzales, R., Douglas, V. C., & Hadley, D. (2018). Development and validation of an electronic health record–based machine learning model to estimate delirium risk in newly hospitalized patients without known cognitive impairment. JAMA Network Open, 1(4), e181018. Full-text open access URL: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2695078
CAREERS/INDUSTRY LINKS
This subject provides advanced knowledge and practical skills to work in digital health. This subject is offered jointly by the Faculty of Engineering and the Faculty of Medicine, Dentistry and Health Sciences, and makes local and international links with accomplished researchers and with experts from public and private sector organisations.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Certificate in Health Informatics and Digital Health Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 6 March 2024