PHIL519 - Ethical Practice in Digital Health

Year

Credit points

Campus offering

Teaching organisation

This unit will be delivered in online mode using an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn. Students are encouraged to contribute to asynchronous weekly discussions. Active learning opportunities provide students with opportunities to practice and apply their learning in situations similar to their current or future professions. Activities encourage students to bring their own examples to demonstrate understanding, application and engage constructively with their peers. Students receive regular and timely feedback on their learning, which includes information on their progress.

Unit rationale, description and aim

Given its increasing reliance on advanced digital technologies and data accessibility, contemporary healthcare practice is faced with a range of complex ethical and legal challenges that need to be carefully understood and addressed. Ranging from issues concerning the ownership and secure use of patient data, to issues in research ethics, and the uses of artificial intelligence in therapeutic decision making, powerful new and emerging technologies raise many issues that require careful consideration. This unit names and explores such challenges with the aim of equipping students with the knowledge and skills to think, judge and respond appropriately on the basis of clear ethical principles, to current and emerging challenges in professional practice, thereby ensuring respect for human dignity whilst working for the common good. In so doing, it also provides insights into the larger social and commercial contexts within which clinical and healthcare management decisions are made.

Learning outcomes

To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.

Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.

Explore the graduate capabilities.

On successful completion of this unit, students should be able to:

LO1 - Analyse key aspects of the social, clinical and management contexts that are affected by new and emerging developments in digital health, and evaluate the relevance of ethics to their application in practice (GA1, GA2)

LO2 - Critically analyse the benefits and associated ethical risk of new and emerging technologies and data applications in healthcare provision (GA1, GA2, GA4)

LO3 - Apply understanding of the benefits and risks of digital health developments, and the key ethical principles and challenges involved, to common clinical and/or management situations in healthcare (GA1, GA2, GA3, GA4, GA6) 

Graduate attributes

GA1 - Demonstrate respect for the dignity of each individual and for human diversity

GA2 - Recognise their responsibility to the common good, the environment and society

GA3 - Apply ethical perspectives in informed decision making

GA4 - Think critically and reflectively

GA6 - Solve problems in a variety of settings taking local and international perspectives into account

Content

Topics will include:

• Key concepts such as privacy, confidentiality, anonymity and deidentification, and general principles relating to the ethical and legal use of patient data;
• Measuring the value of health information, and the justification for the storage/use of data;
• Complexities concerning health data security issues (e.g., concerning opt ins and opt outs relating to databases);
• Ownership, use and confidentiality of genetic profiles;
• The ‘dual-use’ dilemma issue, particularly as it pertains to public health and the reuse of data acquired for other purposes;
• The use of individual and agglomerated data in healthcare research ethics;
• The use of pharmaceutical and substance abuse information;
• Issues raised by the use of artificial intelligence (e.g., machine learning and predictive modelling) in digital healthcare contexts, including the deferral of human judgement and the algorithmic design of ethical values into systems;
• Tensions between confidentiality and appropriate transparency relating to adoption records;

Learning and teaching strategy and rationale

ACU Online

This unit will be delivered in online mode using an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn. Students are encouraged to contribute to asynchronous weekly discussions. Active learning opportunities provide students with opportunities to practice and apply their learning in situations similar to their future professions. Activities encourage students to bring their own examples to demonstrate understanding, application and engage constructively with their peers. Students receive regular and timely feedback on their learning, which includes information on their progress.

Assessment strategy and rationale

This unit’s assessment strategy is to facilitate and examine understanding of key concepts, principles and theories, and to then encourage and assess the application of this material to workplace healthcare contexts. The assessment tasks enable participants to synthesise and deepen their learning, while also assessing their success in doing so.

The first assessment task requires participants to take their understanding of early unit material and to utilise this as they enter into dialogue with some of the scholarly literature in the field. The focus here is on understanding, analysis and reflection. The second task requires them to integrate and apply this learning to challenging workplace realities. Both assessments provide a strong, practical connection between unit learning outcomes and participants’ professional roles.

Overview of assessments

Representative texts and references

Arora, C. (2019). Digital health fiduciaries: Protecting user privacy when sharing health data.’ Ethics and Information Technology 21, 181-196.

Baric-Parker, J., & Anderson, E. E. (2020) Patient data-sharing for AI: Ethical challenges, Catholic solutions. The Linacre Quarterly, (87)4, 471–81. https://doi.org/10.1177/0024363920922690

Cohen, I. G., Gasser, U., Fernandez Lynch, H. & Vayena, E. (2018). Big Data, Health Law, and Bioethics. Cambridge, Cambridge University Press.

Hasselberger, W. (2020). Ethics beyond computation: Why we can't (and shouldn't) replace human moral judgment with algorithms. Social Research: An International Quarterly, (86)4, 977-999.

Celi, L. A., Ordóñez, P., Paik, K. E., Somai, M., Osorio, J., S. & Mujumder, M., S. (2020). Leveraging data science for global health. New York, NY: Springer.

Househ, M. (2019). Big Data, Big Challenges: A Healthcare Perspective. Background, Issues, Solutions and Research Firections. Springer.

Krutzinna, Jenny and Luciano Floridi. (2019). The Ethics of Medical Data Donation. Cham: Springer.

Richterich, Annika, (2018).The Big Data Agenda: Data Ethics and Critical Data Studies. London: University of Westminster Press.

Rivas, H. & Wac, K. (2018). Digital Health: Scaling Healthcare to the World. Springer.

Sinibaldi, E. et al. (2020). Contributions from the Catholic Church to ethical reflections in the digital era. Nature Machine Intelligence, (2), 242–244 doi.org/10.1038/s42256-020-0175-4