Martin Kohn, Chief Medical Scientist at Sentrian, the first Remote Patient Intelligence Company, recently stated that randomised medical research trials have been resulting in poor healthcare strategies, which has led to one third of health spending going to waste.
At WIRED Health in London Kohn stated: “Between 21 percent and 47 percent of what we spend on healthcare in the US is on things of no value. This equates to between $900 billion to a trillion dollars of waste every year.” He attributed much of this wastage to everything from fraud to overtreatment and emphasised the absolute need for better decisions to be made and a new system to be put in place.
$900 billion to a trillion dollars of waste every year
Often considered to be the “gold standard” in medical research, the comments from the former Chief Medical Scientist of IBM, may come as a shock to many. However, to those who are big data advocates, Kohn’s belief that the only way to cut this wastage and improve healthcare, is to move towards a system where we use big data to resolve health issues, will come as no surprise.
Kohn believes the system should involve personalised decisions being made for each and every patient, an idea which has existed for nearly half a century! However, this idea has been impossible to put in place because the healthcare information needed for such treatment only existed in paper record format and was therefore slow and cumbersome.
Kohn emphasised that understanding more about an individual patient will enable better healthcare decisions to be made for that patient, rather than a reliance on solutions being produced for an individual from randomised controlled studies; such studies do not tell you anything specific about the individual. He said we must: “work in the real world because that’s where you live — you don’t live in a controlled study. This is where big data comes in.”
In the UK, the NHS system could provide a huge amount of its big data
In the UK, the NHS system could provide a huge amount of its big data, which has been collected over many years, to help medical professionals identify patterns and similar medical issues for their patients. This big data can help professionals gain insight into the progress made in treatments or even identify treatment plans for patients experiencing like-for-like health problems.
As with most technologies, there will always be a few niggles to work through, such as random associations. However, Kohn believes that these niggles are worth the ultimate benefit that big data can bring to the party.
He explained how using analytics engines will provide a better chance of creating a personalised treatment plan for a patient than using results from a randomised trial would do because the analytics engines search through the huge amounts of big data that the random trials don’t.
using analytics engines will provide a better chance of creating a personalised treatment plan for a patient than using results from a randomised trial
There might well be a few people out there who believe using such analytics and computers means that we can replace physical doctors. However, Kohn does not go that far, even though he admits some things are beyond our contemplation: “The interesting part about big data is that there are patterns within the big data that go beyond our ability as humans to understand.”
He went on to say that there will always be flawed data in healthcare so we cannot therefore put 100% of our trust either in randomised medical trials or in big data analytics. Kohn believes the healthcare industry needs a combination of big data analytics and dedicated experts to do the work that’s needed. He believes this would make both medical and economic sense and that ultimately, increasing our reliance on big data it is the only way forward.