Precision Medicine

Andrew Rebhan, consultant at The Advisory Board, discusses new advances in "digital frontiers" such as artificial intelligence, internet of things, 3D printing, augmented reality and more.

Delivered by UNSW's Entrepreneurship Unit, the 20-week programme will include five health startups providing products and services focused on chronic diseases.

SNUH serves more than 8,000 cancer patients per year across 16 cancer specialty centres, 10 multidisciplinary cancer treatment centres, and a cancer clinical trials centre.

Kate Birch, head of data and technology at Melbourne Genomic Health Alliance in Australia, discusses how rare conditions are being identified and successfully treated through pediatric gene testing.

Finding the best care for a patient can be a constantly moving target. The number of stakeholders, the constant advance of new information and treatment options and the nuanced demands of different payers make for a maze of complexities to navigate. In the field of oncology, for example, nobody but a specialist could be expected to keep up with the growing wealth of knowledge in the treatment of individual cancers. Yet most patients are treated by general oncologists who may not be abreast of every best course of action for specific conditions. These practices might not know which treatments a patient could be pre-approved for, or which payers are most likely to compensate and for what. As the practice of tailoring precision medicine plans for each patient takes hold, physicians are being asked to make more specific treatment decisions than ever before. "You have labs, you have payers, you have providers and you have pharma – and they’re all interested in what the doctor is about to do with a patient," said Clynt Taylor, CEO of Intervention Insights, which makes a tool called Trapelo that helps streamline treatment and payment options. Taylor says that giving an oncologist "an opportunity to see what they should be ordering based on the clinical scenario" empowers them to make the best decision for the patient. Information is inspiration "Most doctors have a good idea of what they want to do," said Taylor. "It’s information access that’s really holding up the process: ‘I didn’t know the lab could do that, I didn’t know these genes should be tested.’" Effective deployment of an IT system that can gather all of this information and put it at an oncologist’s fingertips, integrated into their workflow, helps align the interests of everyone involved. In precision medicine, every decision has to be tailored to the patient at hand. This requires significant knowledge about everything in a field where treatment options and knowledge about the disease are advancing rapidly. Doctors need to know their options in a way that relates to the patient and which a payer will approve. "If I order a test, will I get a treatment option that is supported by clinical evidence?" said Taylor. "Or will I get treatment options I can’t use?" Taylor notes that health plans "will pay if there’s evidence." But that puts the onus on providers to have conversations with the payer at the beginning of the care process to build a case for a specific treatment regimen. Integrating payers into the treatment option plan helps form a more granular narrative of care. "Payers not usually involved until the end of treatment selection process," said Taylor. "Docs go through the process, made treatment decisions, submitted to payer and the payer says ‘what’s going on?’ Involving them earlier in the process avoids the situation where payer prior authorization is a holdup." Having a picture at the onset of care of how to proceed and the likely outcomes enables a much better relationship with the payer and delivers the most effective care possible for an individual. Deep insights have been helping physicians predict the best treatment course in a number of fields; tying the process to the payer conversation makes for a more streamlined transition from treatment to payment. Taylor notes that as more data is amassed about precision health, the more seamless the whole process will become. "The more we can streamline communications through automation, the faster a decision can be made," he said. Benjamin Harris is a Maine-based freelance writer and former new media producer for HIMSS Media. Twitter: @BenzoHarris.

Garvan Institute of Medical Research scientists hope the method, called RAGE-seq, could have powerful applications for precision medicine.

Researchers are working with digital therapeutics specialist Biofourmis, using machine learning technology and the Apple Watch to analyze dozens of physiology biomarkers.

The 10-year initiative will focus on workforce development, education and training for next-generation care delivery.

A multi-year agreement with the machine learning company will start with a tool to identify high-risk GI patients, eventially expanding to other high-burden diseases.

Nearly 20% of Estonia's citizens are gene donors, which is useful when it comes to implementing precision medicine, says Kalle Killar, deputy secretary general at the Ministry of Social Affairs.