“When mistakes happen, patients die. I remember thinking to myself ‘What is going on here?’ We can do better. We should do better.”
When Simon Kos practiced critical care medicine in intensive care and anaesthesia early on in his career, digital technology was not well established. “I saw mistakes – avoidable mistakes – happen all around me,” he states.
Now Chief Medical Officer at Microsoft, Kos is at the forefront of a medical revolution. His ambition is infectious, and his passion is fuelled by his first-hand experiences of the power that technological transformation, such as artificial intelligence (), can bring to our lives.
The term is thrown around a lot these days. For many, it conjures up images of a dystopian future where robots have infiltrated society and have replaced our jobs – a perception born out of silver screen fantasies.
“People think about artificial intelligence and immediately jump to the science fiction perceptions of robots,” Kos states. “Instead, when you distill it, it’s about using data in autonomous, mathematical ways, to deliver insights. For example, there are machine models that show you when you should discharge patients so that they don’t bounce back and have to be re-admitted.”
It’s these insights and technological capabilities, that were the missing link from Kos’ past. While he began his career observing the digitization of data, the real breakthroughs came with the advent of , alongside the infinite data storage and analytical processing power of the cloud.
With the introduction of this complementary technology, digitized data became more than just a way to save paper – it became a weapon to help fight disease, illness, and discomfort.
Today, machine models are capable of determining when a patient is deteriorating, so that medical intervention can occur before they need to be hospitalised. The outcome is improved patient care and health, and an increase in efficiency and costs saved for both the patient and hospital.
Oschner Health is one example of a company using to revolutionise healthcare. Its system is able to accurately track patients who are at risk of cardiac arrest, and can determine when there is a decline in their condition. This allows them to be admitted into intensive care hours earlier than they otherwise would have been. They are provided with potentially life-saving care, before their condition deteriorated to the point where medical care would have been less effective. […]