Goal 1: Capability and culture

​​​A data culture that equips, empowers and expects our people to use data and information

What will this mean?

Goal 1 is about enabling and empowering our people across NSW Health to contribute to better decisions, better outcomes, and a more connected health system.

  • Individuals and teams across NSW Health have the skill and will to handle data and information, responsibly.
  • NSW Health staff have better access to opportunities that grow their data and analytics expertise.
  • There are clearer accountabilities for data and analytics across NSW Health. We get the balance right between adapting to local needs and centrally coordinating NSW Health's data and analytics effort and investment.
  • Transdisciplinary teams combine different perspectives to support collaborative action in data and analytics across the NSW Health system.
A group of figures with linked arms, surrounding text: 'Diverse perspectives collectively driving action in data and analytics'. The figures are identified as clinical, data consumer, governance and risk, business operations, other technical expertise, data and analytics expertise and patients, carers and communities.
Transdisciplinary teams.

Why does this matter?

At NSW Health, our people are our greatest asset. Each of us relies on data and information in our day-to-day, whether it's making clinical decisions in real-time, documenting care, reviewing performance data, or deciding what, where and how best to act. This means that each of our people have a role to play in ensuring that data are meaningful, actionable and handled responsibly.

The challenge is that data held by NSW Health are complex - because of who we share it with, the many types of data we hold, and the many purposes for which we collect and share data and information. Understanding and navigating this complexity is key to ensuring our people do the right thing with the data and information that we are privileged to hold.

What is the work to be done?

  • Data and analytics capability.
  • Data and analytics talent.
  • Data culture.
  • Data and analytics operating models.
Current as at: Monday 2 March 2026