The allocation of public health services is no guessing game. The government relies on vast datasets – and the analysts who can identify patterns within them – to understand the health of our population and where services are most needed.
In this episode, David is joined by Professor Suzanne Robinson, from Curtin University’s School of Public Health, and Professor Andrew Rohl, from the Curtin Institute for Computation, to discuss health economics in the digital age.
- How do the worlds of economics, health and supercomputing combine to make us healthier? [0.30]
- How do health authorities get their data and how do they keep it private? [1.33]
- What sort of information are we learning from big data that we didn’t know before? [4.03]
- How do computers find patterns? [8.06]
- How is machine learning applied in a health context? [10.07]
- What are we learning about our health from the data that’s been gathered? [13.43]
- Are we any closer to learning why Indigenous Australians and those in regional areas have poorer health outcomes? [14.41]
- What’s next with health data analytics? [16.15]
- What impact will the changes to My Health Record have? [20.08]
- Curtin News: Data mining to combat chronic kidney disease
- The Conversation: Youngest in class twice as likely to take ADHD medication
- Curtin University Health Research and Data Analytics Hub
Got any questions, or suggestions for future topics?
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Music: OKAY by 13ounce Creative Commons — Attribution-ShareAlike 3.0 Unported — CC BY-SA 3.0 Music promoted by Audio Library
You can read the full transcript for the episode here.