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AI and Machine Learning transform healthcare in the next decade

Consumer technology companies have fundamentally changed our expectations, adding value and integrating nearly every aspect of our daily lives — from how we shop to how we join a meeting. In 5 years time the idea that a vendor will be able stand in front of you and to tell that I have an AI or Machine Learning in my software will be as laughable as me saying that I have a database behind my technology.

What exactly is AI ? Most companies are not creating robots to replace humans. They are embedding learning and improvement in their daily operations. AI is just advanced math. Math that allows us to collect millions of data points and to learn from that, analyse, optimize, to predict, to personalise our recommendations etc. Thats a very fundamental improvement. We have the ability to learn from a lot of data in ways we couldn’t in the past and companies are revolutionising this space by using this new capability in ways others had not thought to do. But in healthcare, we mostly use data to prove compliance. In healthcare over 90% of our analytic capabilities are dedicated to demonstrating to a third party that we are achieving value by their definitions. Demonstrating compliance is not equivalent to learning and improving. Could you imagine if Google dedicated 90% of its data to prove they are compliant with Sarbanes-Oxley Act. It is just outrageous.

Increasingly, patients are demanding this same experience in healthcare and traditional technology companies are making big bets on their ability to integrate tech platforms, analytics and most importantly UX into digital health tools that will provide consumers a more complete, accessible picture of their health data. However, moving into healthcare for tech companies won’t be easy, and they will need partners. The US healthcare system is complicated and regulated by a web of state and federal laws. Increasingly, partnerships are forming between companies to leverage expertise. Tech companies are looking to leading payers and provider systems to inform and support development of platforms and apps. The big question is whether health-related companies can garner enough trust. Technology companies already do: customers exchange data for value and convenience everyday.

Heathcare spending will be the fastest growing item of government expenditure in the coming decades due to ageing societies, evolving technology, and widening coverage. By mid-century healthcare costs will account for 11.1 per cent of GDP, up from 6.3 per cent in 2010. Soon every device used on heart patients will connect to the Internet. Pacemakers, defibrillators, stents, valves … will all be connected to the Internet. The industrial Internet of Things — where machines connect directly to servers and each other — is a subset of the larger Internet of Things. These devices will transmit data in real time that’ll be stored on a server. All this collected data — which is called Big Data — contains information gold.

During the late 1990s, telecommunication companies started thinking of future necessity because they knew that with the introduction of the Internet to the common man would come with a higher demand for accessing the Internet quickly and easily, these companies bought hundreds of thousands of high capacity optic cable in order to meet those demands. While this was a good idea, the fiber optic cables lay dormant for years — and this is where the medical data currently is now. It’s stuck in a stasis, waiting for someone to finally utilize it the way it should be utilized. As it stands, we can talk about medical big data in four words: volume, velocity, variability and value. The first three speak for themselves, and are something of a staple in the world of all big data, but the fourth V is something that’s recently been thought of when it comes to both data and healthcare. Retailers in particular stand to increase their operating margins by more than 60 percent, while the United States healthcare sector could reduce costs by 8 percent through data analytics efficiency and quality improvements.

General consensus is that healthcare needs to catch up with other industries in terms of application of ML. As more data becomes available, analytics capabilities have become a higher priority for all healthcare organisations, and public clouds like Amazon Web Services (AWS) have matured to the point where they can pass the most rigorous compliance concerns and find efficiencies in healthcare process improvement. The companies that market them have also matured in their understanding of the business relationships required (such as a BAA for HIPAA) to support them. Cloud services are scalable, flexible and supported with a wide range of ML tools. Storage and computing power can be scaled up or down as soon as the need arises. The Federal government is also steering the industry in a direction that could mean hospitals would take on more responsibility for service and risk than insurance companies. Such a move would heighten the need to manage data from multiple sources that include pharmacies, labs, demographic data on patients, and social determinants of health.


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