I started to work in data modelling 15 years ago. My company at that time was a pioneer in building technological solutions based on data, mathematical models and extracting knowledge to make better decisions.
Big data is transforming the way that companies compete amongst, this paradigm has also arrived in the health industry which is good news for our ageing hearts.
In my opinion, this approach can be based on 4 pillars. 4 Ps using data for a healthy heart: Participation, Personalization, Prediction and Prevention.
Anyone over 21 who has an iPhone or more importantly an Apple Watch can join other people committed to improving their health, sharing their heart´s activity; Apple and Stanford Medicine facilitate this participation.
The development of new wireless devices that record our health data, as well as an exponential growth in our computing capacity, will greatly boost data-driven research. More data leads to more discoveries that will save more lives and /or make them healthier.
Large projects are being developed to improve our knowledge of very prevalent diseases and in 2017 for example BigData@Heart launched a five-year project which consists of patient networks, pharmaceutical companies and academia to name but a few which focuses on sharing important information with the relevant people who might need this vital data to make better decisions.
The availability of this new information, superior to clinical and administrative databases, will allow the development of diagnostic and therapeutic strategies that will improve both medical care and our quality of life, offering benefits previously unknown until now.
Cardiovascular disorder is a complicated entity, which is influenced by numerous individual factors such as genetic inheritance, life habits of each person or personal adherence to treatment, amongst others. Therefore, the collection of personal data and its subsequent use is essential for the generation of patterns and markers of individual behaviour that explain patients according to their risk profile.
Access to massive data sets of cardiological information, allows us to:
Classify patients into different categories clinically recognisable by patterns, such as: different response to medications or medical therapies, different types of physical or work activity, different types of nutrition and even different environmental-regional settings and locations.
Comparing different databases with a generous historical data series will allow us to describe the phenomena, explain past events, understand trends and establish relationships on a specific time horizon.
The objective will be to advance in a more precise medicine that will impact on an improvement of the medical results of each patient.
One of the most influential doctors in the United States, considered a Rockstar in his field, cardiologist Eric Topol says, **”It’s not just data, it’s analytical capacities”
We have always had data, of course in smaller amounts, but all that data was there and is now being analysed and interpreted. This is the most radical change in the study of healthy aging.
What do these datasets and the application of advanced analytics tools brings us?
They offer us the ability to predict, to anticipate, to see in advance.
The research lead by Dr. Tariq Ahmad and Dr. Nihar Desai, both professors at the Yale Cardiovascular Medicine Section, analyse health data from more than 40,000 patients, using statistical techniques of “machine learning.” The result predicted their medical results one year after diagnosis.
Researchers at the hospital in Ottawa, using data collected from 104,219 residents in Ontario and using mathematical models linked to hospitalization data, made predictions about the risk of admission for cardiovascular disease over the next five years.
Therefore, advanced analytics cannot forecast when a person will suffer a heart problem as such, but it will help to find signs that better anticipate likely occurrence of some alteration in the short or medium term.This is the way to improve premature detection and early diagnosis.
Cardiac problems are in the top 10 of chronic diseases that result in higher costs for healthcare systems. Reversing this trend involves taking cardiovascular prevention measures based on data with a focus on a positive impact on our quality of life.
Highlighting the importance of the information we have available, analysing it properly and extracting knowledge is of little use to us, if we do not finally put it into practice with an improvement in decision making.
For this, the development of technological platforms, and data visualization tools, which in addition to the storage and dissemination of information, will facilitate a better and easier interpretation of them not only by the cardiologist, but also the patient and family.
The great promise of data-based cardiovascular prevention is that a timely decision for a specific patient may be made by the right person, with the right information, and at the right time.
We are transforming this world and our way of living in it.
With the health and heart to enjoy it.
Dedicated to my friend, Romulo, who survived a heart attack a few weeks ago.