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Meaningful Health Care Informatics Blog

Aug 27 2012   8:11PM GMT

Big data, machine learning and powerful processing platforms in health care

Posted by: RedaChouffani

For the most part, big data continues to intrigue technology executives.  In the healthcare market it has the potential to make great use of some of the existing data sets that are available.

The interesting part about big data is that there are other technology advancements that will truly be a game changer when it comes to making good and significant use of all this digital information.  AI or artificial intelligence as we know it, is when machines can learn and adapt based on data inputs.  While machine learning has been around for a while within health care, combining machine learning, powerful computing platforms and big data will ultimately create an incredible platform that can soon transform our health care and work environment.

We can take some simple examples of how many of these technologies can be applied in a real life scenario:

Business workflow engines:

Traditionally when we attempt to automate specific business processes and tasks we find ourselves continuously adjusting and adding to our workflow branches.  With the increased complexity of today’s health care environment, whether it is dealing with payer payment rules, or simply the different diagnoses of a patient who came into the ER with specific symptoms, a machine-learning platform will be able to adapt and improve results over time by simply reviewing a past patient data. This is no different than some of the existing technologies and solutions available today, where computer assisted coding is able, through the analysis of audio files and medical charts, to correct or recommend the appropriate charge codes and helping hospitals avoid payment delays and reduce denials.

Predictive analytics:

Data scientists find themselves constantly working on complex forecast models, and other predictive analytics for disease outbreak scenarios, availability of supplies based on certain variables and simply identifying possible future outcomes of patients based on their DNA and the different treatments available.  With the combination of big data, clinical trials registries, and powerful analytics tools, systems will be able to forecast the outcome of specific treatments in cases of cancer and other diseases. They are will be able to do this based on a patient’s treatment history and their DNA.

Personal Health assistant and mobile coach:

There have been several startups and mobile apps in the marketplace that track the mobile users’ locations, habits, and are able to predict or suggest the next restaurant that the patients should visit based on analysis of historical data.  Taking this same model and providing a digital assistant to patients with a chronic disease, the assistant can relay the patient’s vitals and communicate with physicians by providing information on the patient’s condition.

These are just few simple existing and future applications made available through big data, machine learning, analytical tools and computer processes.  But, as some of the platforms continue to be available commercially and through open source licensing, more innovation will penetrate the health care segment and prove to help overall patient safety, improve efficiency and discover new insights toward cures that were not previously possible.

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