Precision medicine is the use of all available information about a patient to produce the most informed care plan possible. This is often associated with using genetic or other “-omics” information to help doctors select which medicine to prescribe for their patient. For example, testing a cancer patient for specific biomarkers can tell doctors which chemotherapy will work best.
But it’s much bigger than that. If you look at what contributes to premature death, around 30% is thought to be genetic. The rest is a combination of our environment, diet, exercise, work, mental health, social interactions and other exogenous factors. So why limit ourselves to genetic data alone?
As healthcare is now in the information era, the challenge is to pull together the vast quantity of data that exists and aggregate it in a way that allows health services to be tailored to each patient.
There is already a wealth of data and this is expected to increase 50-fold in the next eight years. There is no way any physician can cope with this volume of information. That’s why software companies are playing an increasing role in healthcare. Information overload is essentially an IT challenge: how do we access and surface these data in a way that makes them accessible and actionable? How do we acquire and aggregate data, then reason against it to help manage populations and drive insights?
Healthcare is unique but software experts have already overcome huge challenges in areas such as e-commerce and financial services to deliver a more tailored and user-friendly experience while safeguarding data privacy.
In fact, the public is so used to this kind of customised intelligence that some patients find it quite surprising that healthcare has been slow to catch up. For example, your GP holds some of your medical records; if you’ve attended a hospital they also have some information; social services might have another package of data and so on.
There is no shortage of information but it is scattered in all directions. Our task is to pull this together so that, irrespective of where in the system you turn up next, all of your information is accessible to the health professional who is trying to treat you so that there is an informed episode of care.
Having access to a full medical record is useful if you are rushed to hospital and a doctor needs to know if you have allergies or are on medication. But it’s not just about emergencies. GPs should be able to use precision medicine, based on medical, social and other data, to predict which of their patients may be highest risk of needing urgent care such that proactive steps can be taken to manage the risk. Patients with chronic disease, for example, might need early interventions to avoid more catastrophic events that require hospital admission.
This requires time and resources but delivers considerable value to the health system. By avoiding the costs of urgent care, a data-driven approach offers the opportunity of building a health service that is proactive rather than reactive – which we believe is better for everyone.
Even relatively minor things, like avoiding repeat blood tests by ensuring the results of recent diagnostic tests are accessible, can save time, money and stress for patients. When you join information systems together, waste like this disappears, allowing managers to devote resources where they can deliver better outcomes.
Our experience working in this area with, for example, health authorities in Northern Ireland, shows that long-standing challenges such as data access, security and privacy can be overcome while delivered significant benefits. Around half the population has been treated within the Electronic Care Record (ECR) system we developed in Northern Ireland. One user of the integrated system described it as the best invention since the stethoscope!
Make no mistake, this is where the future is going. Indeed, for some, it is already a reality today. With open standards, greater interoperability between systems and the power of cloud computing, our ability to unlock the full potential of data will only grow. Regions have been building their information foundations, the data has been standardised and can be mobilised. The full potential of precision medicine will ultimately come from a scalable data platform in the cloud, with open API’s and machine learning to surface new insights. But there is a lot we can do today. For example picture the scene where a man walks into a restaurant. Without prompting, his phone talks to a beacon on the ceiling, flagging his severe peanut allergy from his medical record to their in-house app which is accredited to receive this data. The waiter appears with a suitably tailored menu and can advise caution in the preparation of his food. Science fiction or Star Trek? Not at all, this exists today.
This blog originally appeared on the MedTech Views site, after Colin spoke at the MedTech forum 2016.
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