The data economy: The future of health care is data based - II

An interesting reading, the book "The patient will see you now" by Eric Topol, reverse today's practice of medicine with patients being ever more informed about their health state as result of technology putting vital parameters at their fingertips. Credit: YouTube

That we will have more data about our "physical state" is a given. They will no longer be sought when we feel sick, rather they will represent a continuous stream, day after day. By the end of this decade sensors present in our homes, embedded in our smart phones, "glued" on our body and even "embedded" in our body will provide data on temperature, blood pressure, calories consumption, metabolic rate and much more.

The transition is likely to be so slow, in terms of penetration (number of people having them) and variety (number and diversity of data captured), that we will not notice what is happening, each single step below the thresholds of awareness.

Your smart watch will start providing data on blood pressure and oxygenation, a curio to show your friends the first few days and then to fade away from your perception. Calories burnt is another one, and so is the first indication of your metabolic rate, and then the record of your sleeping rhythm, the gait, the heart ECG and so forth. Before realising it sensors will be tracking as many vital signs as the ones that today are being harvested in an advanced hospital life support environment.

It is not inconceivable that in the next decade we will see our doctor bringing along a set of data that will match the ones we collect today AFTER the doctor has prescribed a number of tests. This is basically the starting consideration of an intriguing book by Eric Topol, The Patient will see you now.

This will, in a way, turn the relation between the patient and the doctor upside down. Already today, thanks to the Web, sometimes doctors are seeing patients that are more informed than they are about their pathology. 

Today's medicine is by far the result of statistical analyses, rather than 1+1=2, particularly in terms of cure (drugs effectiveness). But also, in a way, in terms of detecting what is wrong. True, a diagnoses of cancer looks like a scientific result: a surgeon takes a biopsy of suspected tissue, a biologist looks at it under a microscope and there is scientific certainty that it is a small cell lung cancer. However, this is just part of the story. It doesn't tell why you got it. Was it the smoke inhaled at the workplace, the pollution in the air, a specific gene combination in your genome, a side effect of your diet ...? Health care is related to science via statistics. And statistics gets more and more precise the more data you have and the better relations among them.

This is where the personal sensors will bring a revolution in health care. In 2014, according to MobileHealthNews, over 150 million sensors to detect health parameters were shipped; this figure will grow to over 500 million in 2017. We will start to have statistics about ourselves! By monitoring in a continuous way our biological parameters we will accrue sufficient data to make statistical analyses meaningful. As an example the dream of an artificial pancreas is on sight thanks to software algorithm that are personalised and can predict when the glucose will go up to the point of requiring insulin injection and this will take into account the time, that in your specific case, it will take the insulin to reach the liver to command glucose absorption.

More than that. Already today we are seeing communities of people suffering from a specific, sometimes unusual, pathology that exchange information on line. Give it a few more years and these communities will be sharing hard data related to the physical condition and drugs taken by their members . This will provide a much more accurate data set for evaluating the effectiveness of a therapy and its possibile side effects. Since we are talking about the next decade it is not unrealistic to assume that those members will also share, in some way, their sequenced genome and that will provide further data to move to the next level: analytics and inference.

Author - Roberto Saracco

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