Better use of large datasets in health and medicine offer enormous potential to improve the effectiveness, safety and efficiency of health care.

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Big Data & Research

The massive amounts of available patient data are fundamentally changing the way healthcare is designed and delivered. Data collected from wearable devices, medical claims, routinely collected patient data, hospitals and laboratories can inform us about health trends and patterns with a scope that has not been possible using traditional research methods.

Using big data will also help us to ensure that improvements in healthcare are value-driven. It’s been estimated that big data could reduce Australia’s national health expenditure by more than $11 billion annually.

From molecular analysis through to genetic and clinical research, health systems analysis and population-level research, big data has played a crucial role.

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The Centre for Big Data Research in Health

The Centre for Big Data Research in Health (CBDRH) is the first Australian centre dedicated to health research using big data. The CBDRH maximises the use of health big data to research pressing health questions, for Australians and the global community.

The CBDRH has four research units:

  • Health Services and Outcomes Unit
  • Medicines Policy Research Unit
  • Cancer Epidemiology Research Unit
  • National Perinatal Epidemiology Statistics Unit (a joint unit with the School of Women’s and Children’s Health).

The Centre is the hub for collaborative interdisciplinary big data research across UNSW Medicine. It actively fosters a broad community of researchers. The Centre’s researchers are agile in adopting new techniques, adept in advanced analytic methods, and embody the best in data security and privacy protection.

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Big Data & UNSW Medicine

Some of the research areas where large-scale data is used across UNSW Medicine include:

The UNSW Schools of Computer Science and Engineering and Mathematics and Statistics also have major research strengths in a range of relevant methodologies and technologies, including;

  • biostatistics
  • bioinformatics
  • data mining
  • visualisation
  • natural language processing
  • cloud computing
  • high-performance computing.
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Case Study: The Use & Safety of Quit-Smoking Medications

Quitting smoking is one of the most important things we can do to safeguard our health. Studies have found that older Australians with chronic health conditions were up to 700% more likely to go to hospital if they smoked.

UNSW Medicine is using big data to evaluate the safety of prescription medications that are now available to help people to stop smoking.

Our NHMRC-funded project has investigated the use and safety of medications during pregnancy. It has brought together 10 different data collections, resulting in a linked dataset containing almost 35 million records, belonging to over 2 million individuals.

The study is investigating the maternal and neonatal safety of nicotine replacement therapy, bupropion and varenicline use during pregnancy, as well as inequalities in the use of these medications in disadvantaged populations, and whether their use has changed in response to pharmaceutical policy reforms and changes in clinical guidelines.