Data exchange in health analytics Steve Millward Chief Analytics - - PowerPoint PPT Presentation

Data exchange in health analytics

Steve Millward Chief Analytics Officer 22 October 2018 HISA

Contents

• 1. The case for greater liquidity in data
• 2. Examples of data exchange in the health sector
• 3. Components required for safe data exchange

The case for greater data liquidity

5%

What can be seen

95%

Diet Hobbies Spending patterns Retail Grocery Insurance Exercise Life and health insurance Online activity Location

Health outcomes Treatments What can’t be seen

The biggest, most useful datasets are still held in islands

Data has no liquidity Hard to move Hard to value Hard to control Hard to use

We need rails for data liquidity

Data Republic – Help the world decide wisely

Founded 2014 Sydney headquarters 60 staff Offices in Los Angeles and Singapore Investors include Westpac, ANZ, NAB, Qantas

Examples of data exchange in the health sector

Simon Kyaga Creativity and mental illness

Google AI

Google Deepmind AI

NSW Data Analytics Centre Grocery basket data

Inter-departmental data exchange

MBS datathon Second year NAB Qantas Medibank Victorian government Roy Morgan 250 data scientists

Mental health Exercise Social media

Insurance portfolio A

• r

Segment A Insurance portfolio B

• r

Segment B Data Exchange Data Exchange

8% 15%

Assessing cohort behaviour after individual matching

Components for safe data exchange

Data exchange cannot breach privacy rules

• 1. A common legal framework

“Can you imagine a world without lawyers?”

Govern the “permitted use” of data

• 2. Secure matching of PI

• 3. Senate governance platform

• 4. Secure analytics environment

• 5. Legislative traction

• 6. Giving back

• 7. Industry engagement

Ethics Use cases Processes

Any questions?