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Big Data, Analytics, and the Steady Rise of Precision Medicine

If you follow healthcare data management, health data reporting or healthcare news at all one term you might have seen popping up over and over again is precision medicine, or “personalized medicine” as it is known to the general public. The idea being that individual characteristics: DNA, lifestyle, environment, personal medical history, etc. can be used to customize treatments for maximum effect. The term personalized medicine can be a bit misleading though as it gives the wrong impression. A quote from Hanno Ronte, partner at the healthcare and life sciences team at Deloitte, sums it up nicely:

Personalized medicine gave rise to the notion that different treatments and drugs would be used for each individual – and that may happen, but it’s a very long way away. Precision medicine is preferred as it refers to groups of people with the same genes that you can develop treatments for. It acknowledges that even for relatively common diseases, treatments don’t work equally well for everyone, but better for some than others. So ultimately it’s about using huge data assets to help understand how to create better interventions.”

What are some examples of this precision medicine in action? Some of the best and most recent examples come from Spain, at the Barcelona Supercomputing Center. Using bioinformatics (a fusion science that combines biology, mathematics, engineering, and computer science to analyze biological data), they have created a method for predicting how mutations in HIV will affect its resistance to different drugs (specifically amprenavir and darunavir). How did they do it? Using patient obtained informational data, which they have made available for free on the web, along with an automatic platform through which other researchers can enter a patient’s pertinent information to predict the effectiveness of prescribing the drugs in question. An amazing revolution in treatment, which comes on the heels of a previous advance they made in 2014 in which they created another computational method for detecting genetic changes responsible for the onset of tumors.

This isn’t the only advance. In less than a week’s time, the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) will be meeting. A large topic of discussion during the meetings will be using data analysis to improve patient outcomes. Using analytics to better characterize patients, and tailoring drugs to groups of patients and perhaps even individual patients will be on everyone’s minds. Combining data with genetic and environmental information to determine a person’s risk of kidney disease and predict outcomes from various treatments is fast becoming a real possibility. Indeed, one of the lectures featured is even titled, “Is It Time for One-Person Trials”. It’s hard to get more personal and specific than that!’

Precision medicine is even being eyed as a possible solution for mental health issues as well. In a recent interview with Psychiatric Times, Peter Buckley, a psychiatrist and expert on schizophrenia, spoke in detail about the potential application of precision medicine in treating mental illness:

“In psychiatry, we are also advancing these approaches. We are now aware, due to the work of Dr. Charles Nemeroff and many others, that genetic susceptibility to stress powerfully contributes to whether people develop depression when exposed to life stressors during adulthood. In another exciting initiative, Dr. Carol Tamminga and colleagues have conducted a comprehensive study of the neurobiology (or “neurobiologies”) of psychoses—across schizophrenia, schizoaffective disorder, and bipolar disorder.”

In other words, just like cancers and other diseases which are well known to be affected by large ranges of factors which can be recorded and analyzed so too can a range of mental conditions. Considering these and many other recent announcements, it seems that precision medicine is on the upswing. It appears poised to become an everyday feature across healthcare settings, with an ever growing percentage of healthcare professionals reporting that precision medicine is already positively impacting patient outcomes at their organizations.

 

How are they able to accomplish all of this? The reliance on technology to improve healthcare. Professionals are using data capture, cloud storage, interoperability capabilities, predictive analytics, and decision-support tools to create actionable insights out of raw data. Healthcare data management is crucial if you intend to be at the forefront of a global revolution in healthcare. Organization and management of big data in healthcare and coming up with precise conclusions is the next frontier.

John:
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