Who wants to live forever? Every one of us wishes to live a long life, but this is still not enough. It’s health and youth that we desire and with the advances of all modern technologies this dream might become true. With data-driven approaches coming closer to the health industry a lot of thing may change, including how this data should be handled. So where do those advances move us to? Some people, like P. Otero, W. Hersh and A. U. Jai Ganesh, see this opportunity from the skeptical point of view while others like Dr. Eric B. Larson look for further opportunities to enhance the lives of common people. Come join into this “scientific wanna-be debate” and decide for yourself. Oh, and how blockchain is actually related this time? Well, DYNOSTICS might have the answer!
Have we witnessed the future already?
Even in the “good ol’” 2014, the concept of accessible complex metabolic and health analysis machines were already present and in process of finding solutions. Even through the basis for these solutions has been prepared, the big data-driven aspects for such analytics were yet to come:
“Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in “deep analytical talent” as well as those who need knowledge to support such individuals.”
And those actions do not follow strictly academic interests. We may think that our time is an age of prosperity and longevity but looking at statistics and witness these delusion being too far from truth.
“There is a growing concern over waste and inefficiency in health care, in part due to poor use and integration of data. The US Institute of Medicine (IOM) has estimated annual excess costs of care in the US of around $750 billion (out of $2.5 trillion expended) and also resulting in approximately 75,000 annual premature deaths”
So there is an actual need for improvements in our healthcare system, and for this to be done first of all we need conclusions to base those actions on.
There is much to choose, so choose wisely
We all know that there is no cure-all solution to any given problem. In this regard, methods are only tools, but tools are primary things that differ a man from an animal. So there is no such thing as a perfect method, but some of them are more preferable than others.
“An array of methodologies is available to measure various aspects of energy metabolism and none is perfect under all circumstances. The choice of methods should be specific to particular research questions with practicality and quality of data the priorities for consideration. A combination of complementary measurements may be preferable. There is an imperative need to develop new methodologies to improve the accuracy and precision of energy intake assessments.”
Making a metabolic researcher is always a bargain (look at “Summary of methods to measure energy expenditure” chart in the article) between cost and accuracy, which forces people to always make a hard decision. With those realities in mind it leaves the systematic approach to health research even less realistic.
Man vs. Machine – 0:1
It’s already true that we live in a data driven economy with machine learning algorithms becoming a part of our everyday live. The industry of medicine and health is not an exception. So with the power of machines we can turn the tables about ages and diseases…
“Without a doubt, with the availability of more advanced algorithms and the mounting availability of data, machine learning will be increasingly relevant for the analysis of metabolism.”
But in reality can we? It’s not that hard to deal with data analysis today. You can easily find data science courses on Coursera and download pandas for Python for free. But it’s the actual data you lack, and the question of data sources is one of the most crucial here. Especially sources that you can actually trust.
“In 2006, Kell said: “By making mathematical models of the biological systems one is investigating (and seeing how they perform in silico) what is generally considered a minority sport, and one not to be indulged in by those who prefer (or who prefer their postdocs and students) to spend more time with their pipettes.” Over the last decade, there has been a major growth in the understanding of the value that computational biology models can bring to life sciences. Combining metabolomics with data-driven machine learning has a great potential in assessing the current or near future state of biological systems, but also, when combined with modelling methods, to predict future risks and events. There is no better time than the present to pick up this “minority sport”.
Not for theory, but for practice
As you’ve already seen, there are a lot of researchers that deal with metabolic data. But unlike theoretical physics, almost every one of them has a real application in our world. There are a lot of institutions that are trying to make our lives better and lots of research institutes focus their efforts on this subject. KP Washington is one of them:
“We’re continuing our commitment to work with health care teams to design and share innovative models of primary care inside and outside our system — including with safety net providers serving disadvantaged populations.“
As you can see, there are a lot of things they could achieve, but as we’ve already said, it’s medical data that they also lack. But if this is so heavily needed so much why can’t they just ask some government or private organization for this? Well, seems like this is not the best idea to realize…
Medical records as public property
Why Data Security is The Biggest Concern of Health Care by The University of Illinois at Chicago
We live in the age when personal information could easily be taken away once some big entity gains control over it. The case of Facebook and many more could make an easy example. With this in mind, our medical records could also turn out to be sold somewhere, and this kind of information is usually rather private.
“The risks and costs associated with healthcare data security breaches are too high, and the confidential, personal health data of millions are at risk. This makes data security health care’s biggest concern today, and a problem for which innovation and communication are of the utmost importance.”
With this in mind, there has to be a way to protect common people by preventing this data from lying unused while it could actually save lives.
…Blockchain to the rescue
Oh, and of course, as it comes with lots of other industries, it’s a blockchain solution that can handle this issue with moderate ease.
“With blockchain, healthcare systems could store medical records confidentially, updating patient data across multiple facilities and locations in real time and with security. This would free up time and resources in health facilities to be further dedicated toward patient care and innovation, rather than administration.”
And this is not just a hypothesis, there are already some projects present on the market that allow user to hold their data safe, use it for their own good, or even capitalize on it.
“Several companies have already made use of blockchain in an effort to enhance health care. None of these operations has taken off on a national scale as of yet, but they signal interest within the industry, as well as a theoretical openness to new technology.”
Though there are many ways this type of company could exist, among those there is a project that focuses not only on personal achievements, but on creating of ecosystem that allows encrypted and anonymized medical data to be exchanged.
“DYNOSTICS is a third such company. Catering toward individual users, DYNOSTICS helps individuals to determine their current state of fitness, providing instantaneous feedback and a single location for all data. Like both of the other companies above, DYNOSTICS is focused on data security and privacy.”
While being able to prove their data is true by using a DYNOSTICS apparatus and kept safe by using blockchain solution, users can also sell their anonymized data to any interested party for them to conduct research that could actually prove beneficial for not only them, but society as a whole.