The healthcare sector has always been at the forefront of technological innovation, but as capabilities increase and data volumes grow, it is becoming vital that organizations are better able to harness the data in order to apply emerging technologies such as artificial intelligence (AI).
The rise of artificial intelligence is set to have a transformative effect on the sector. This topic is also flavoring Microsoft Health Innovation Summit arranged in Brussel this week. We are joining there together with other experts from across the healthcare and technology sectors to hear and discuss more about the progress being made on this and help put in place steps to build an industry-wide ecosystem to support developments.
Bringing the data together
A coherent approach is vital as the number of health and well being data sources available for both consumers and healthcare professionals have increased hugely over the last years. This has been driven by advance in technology and start-up culture such as special applications, mobile devices, personal gadgets and Internet of Things sensors that can more accurately track an individual’s activities and this is just the beginning.
At the moment, for example, a normal blood test may provide clinicians with a handful of biomarkers on things like cholesterol levels. But already, the same test could give information on as many as 200 biomarkers. Therefore, one of the biggest challenges for the sector will be collating all this data in a location from where it can be analyzed.
We’ve been working to achieve this by building a data lake service that enables healthcare organizations to pool data from a wide range of disparate sources. This will help overcome the issue of large amounts of unstandardized data and create a great foundation from which to perform critical analytics tasks.
Moving to machine learning
While AI is certainly set to transform how we think about health and well being in the coming years, it’s still a work in progress. At the moment, the first stage of any development is being able to apply relatively simple analytics to this data in order to gain insight about patients.
The next phase brings in technologies such as machine learning and advanced AI solutions that can examine vast quantities of data, such as genomic information, in order to perform calculations and identify correlations that can be passed on to the doctor. In three or four years, I envisage AI enables the change of the whole face of healthcare from a reactive one to a proactive one and at the same time from hospital centric to human centric.
In the first phase care professionals will be able to easily identify patients who may be at risk of a particular condition, allowing them to put in place preventative steps that tackle risk factors before they become a serious problem. In the later phases preventive guidance can be given to individuals automatically by AI.
Not only does this lead to better patient outcomes, but it will also be much cheaper in the long run for healthcare organizations, as it will reduce the need for costly treatment programs and at the same time keeping citizens more well being tax payers.
The right partnerships for the future
With so much data emerging in the healthcare sector, it will be essential for organizations to work together to harness this. That’s why I’m pleased that Tieto will be part of Microsoft’s AI in Healthcare Alliance Program. Being able to share research and expertise with other companies and work together on developing improved AI and machine learning solutions for healthcare is the key to improving the use of data in healthcare, and I’m very excited about what it promises for the future.