Does the word ‘psychohistory’ mean anything to you? If it does then it is likely you have at least a passing interest in mankind’s ability to predict the future.
The term is taken from the Foundation series by Isaac Asimov and refers to mathematical models that analyse historical data to predict what will happen. Widely regarded as classic works of literature, the Foundation books were of course science fiction.
The exciting thing is that when it comes to modern healthcare, Asimov’s fancies are fast becoming science fact.
But let’s stick with the general theory for a moment longer. The predictive power of data is not a concept that is confined to the world of literary discussion. Throughout history, a broad range of scientists, mathematicians, philosophers, business leaders and politicians have touted the idea that with a deep enough pool of information, we can understand and predict the future ten or twenty years from now.
The key phrase here is ‘deep enough pool’ – divining the future with data requires a lot of information for it to be feasible, even in theory. That hurdle has been insurmountable – until now.
Life BG (before Google) was very different. Google is perhaps the closest thing we have to a mathematical soothsayer of human behaviour, a fact linked entirely to the unprecedented scale and scope of the data sets available to it.
While Google is perhaps the most successful modern predictor, it is by no means alone. The technologies now at our disposal mean we have entered an era of ‘Big Data’ analytics and that is opening up some very interesting doors – including a portal to predictive and more personalised, healthcare.
Here is a case in point: two risk prediction tools, launched just last month, capable of identifying diabetic patients at high risk of blindness and amputation.
The tools use algorithms developed from analysing electronic records of around 455,000 diabetic patients from 763 GP practices in England (known as the QResearch clinical database – a joint venture between EMIS Health and the University of Nottingham), and take into account risk factors such as ethnicity, smoking BMI, cholesterol and blood pressure.
The tools were tested and validated on a pool of patients from a further 611 practices. Based on this research a web calculator has been produced that enables GPs to enter a specific patient’s data to determine the likelihood of their developing these complications within the next 10 years. You can read more about this innovation in the British Medical Journal.
When you consider that diabetic eye disease is now the second biggest cause of blindness for people of working age in the UK, and that around 7000 diabetes related amputations take place in England ever year, this really is a significant development.
Projects like this are only possible with sizeable data-sets - one of the reasons EMIS Health is ideally positioned to collaborate with the researchers involved. We’re proud to have helped develop tools that can identify patients likely to get conditions that threaten the collective future health of Britain; conditions such as cancer, heart disease, thrombosis and mental health issues.
What excites me most about all this is what it means for bespoke care planning and also for the future of preventative medicine.
Scrutinizing patient data from the past enables doctors, wherever they work in the health service, to make more accurate diagnoses and therefore quickly implement more tailored treatment plans. Potentially, this removes a layer of appointments, medication trialling and resource wastage – improving health outcomes for the patient, and reducing demand on the NHS (a significant benefit given current strains on our healthcare system).
What will it mean for preventative medicine?
Accurately predicting risk within a ten year timescale will enable doctors to intervene much earlier, while patients will have a clearer grasp of their own risk factors. Essentially, they will have more time to do something to prevent ill health.
Taken with the rise of health apps, innovations such as the Personalised Health Record, and other tools that give patients greater control over their own health and wellbeing, it is clear how patients and doctors can work together much more effectively. There is huge potential here for data to change all our lives for the better.
Isaac Asimov once said: “No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be”. With predictive healthcare we have the opportunity to change the world ‘as it will be’, by making more accurate, data-driven decisions in the here and now.