University of Technology, Sydney

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92491 Health Analytics

6cp; 5 x 7hrs workshops; pre-learning 2hrs per workshop
Requisite(s): 92489 Foundations of Health Information Management AND 90 credit points of completed study in spk(s): C10360 Bachelor of Health Science


Once the digitisation of healthcare is complete, the volume and complexity of the clinical and administrative data generated is likely to exceed the capacity of the human brain to absorb and derive conclusions. Healthcare is rapidly becoming an information-driven entity, and the challenge is to link clinical outcomes with accountable business intelligence. Rather than continue collecting data, health services now need to analyse multiple disparate datasets to discover meaningful information that will influence clinical practice. This subject illustrates how analytics contributes to and drives rapid-cycle improvement processes in healthcare. Students are exposed to common techniques and tools used for health data analytics, including spreadsheets, statistical programs, database management systems and business intelligence applications, and are informed about descriptive, predictive and prescriptive analytics. Lastly, students have the opportunity to view future-oriented analytical methods such as predictive analytics, machine learning and data visualisation, and appreciate how healthcare data analysts plays a central role not only in the transformation of healthcare but also in the future provision of health services.

Typical availability

Autumn session, City campus

Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.