As a society, we are more diverse than ever, we are more informed than ever, we are aware and proud of our individuality. Now, more than ever, consumers seek experiences that reflect their preferences, style and needs. The one size fits all approach just doesn’t work anymore.
In many consumer offerings the shift from one size fits all to personalisation is already the case. Daily, we experience personalised recommendations and insights from the likes of Facebook, Spotify, Google, Netflix and Amazon. Also in healthcare and wellbeing, patients are more and more interested in understanding their own health. And they expect, due to their experience with consumer offerings, a personalised approach to help them achieve better results. Digital technology can create more personalised health experiences and empower people to take greater control of their health and wellbeing.
Understanding which aspects of the healthcare experience can be innovated, and which can be personalised, is a huge part of moving forward successfully. For patients and consumers, healthcare isn’t just a collection of tests, therapies and procedures, but a journey towards better outcomes or ‘just’ an easier life. The journey - that every human being undertakes many times – is deeply personal.
What makes or breaks a course of treatment and outcomes isn’t the drug or the exercise, but the personal considerations around it: when and how long the drug is taken, which lifestyle changes will you adopt, how carefully do you track outcomes, how engaged are you in the long term.
One of the most promising technologies to achieve a personalised health approach is Artificial Intelligence (AI), in particular one specific method called: Reinforcement Learning (RL). RL has shown impressive results, e.g. it is the technology behind computers playing complex computer games, driving cars, optimising your Facebook feed, recommending your next Netflix series to watch, and it is now showing promise to enable personalised medicine and care.
You can read more about Reinforcement Learning in Personalised Healthcare in our white paper. The paper provides both a high level and more technical description of RL, our approach, applications and last but not least 5 key learnings to follow when developing your personalised healthcare solution.
