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Orion Health releases report: Introduction to Machine Learning in Healthcare
Precision Driven Health initiative launched at University of Auckland

Whether they practice medicine in a hospital or a community clinic, healthcare workers are facing an exponential increase in the amount of patient information needed to effectively treat their patients. This will require the application of sophisticated ‘big data’ techniques such as machine learning to process, analyse and surface information that will assist in creating more personalised healthcare plans.

That’s according to Orion Health CEO Ian McCrae, whose company has today released a report on the application of machine learning in healthcare. The report’s publication coincides with the official launch at the University of Auckland of Precision Driven Health – one of the largest data science research initiatives to be undertaken in this country, which aims to position New Zealand at the forefront of precision health globally.

“The electronic health record is fast becoming the most powerful tool in the medical toolkit. Today it contains a patient’s medical record, soon it will include genetic, environmental and social data and will be critical in the application of precision medicine or personalised healthcare,” Mr McCrae says.

“For all this information to be accessible it will need to be stored in the cloud because the size of the electronic file for each individual will be so large.  Some estimates suggest the average electronic health record could include as much as six terabytes of data – that’s a quarter of the whole of Wikipedia (24 terabytes)!”

Mr McCrae says healthcare workers will be unable to process all this new information in a timely way and will rely on high-powered computing, using insights from machine learning – a type of artificial intelligence that enables computers to find hidden insights without being programmed.

“Algorithms will interrogate vast data sets and present recommended treatment plans tailored to individuals,” Mr McCrae says.

“Essential to the application of machine learning are intelligent algorithms and rich data sets. At Orion Health we are at the forefront of developing both areas. We have invested in the Precision Driven Health initiative, and our software manages over 100 million patient records globally, making us one of the few health software companies in the world capable of carrying out machine learning analysis at scale.”

As a founding partner in the Precision Driven Health initiative Waitemata District Health Board is at the forefront of implementing health informatics and analytics capabilities to deliver enhanced healthcare for it’s growing population in Auckland’s North and West.

Waitemata DHB Chief Executive Dr Dale Bramley says the joint initiative with Orion Health and the University of Auckland promotes a better understanding of its patient population and will result in an improved suite of decision-support tools for healthcare professionals, that should lead to better health outcomes.

“Knowledge-driven healthcare supports our clinicians to make sound clinical decisions at the frontline of our hospitals and communities. It enables streamlined, personalised care and ultimately results in better care plans, outcomes and experiences for our patients,” says Dr Bramley.

The Introduction to Machine Learning in Healthcare report is co-authored by Dr Kevin Ross (PhD in Management Science & Engineering from Stanford University) and Dr Kathryn Hemstalk (PhD in Computer Science from Waikato University), with an introduction by Orion Health CEO Ian McCrae (Masters in Engineering Science from University of Auckland). It covers the following:

  • Data that is useful for the practice of precision medicine, and which will become part of an electronic health record
  • An introduction to different types of machine learning models
  • A real-life example of how the application of machine learning can improve patient outcomes
  • A time-line on the development of machine learning
  • A short glossary of key ideas associated with machine learning.

To download the report, visit the Orion Health website.