Making Big Data Sustainable in Healthcare

Big data is now being used by the University of Mississippi Medical Center to determine whether patients are more or less likely to suffer from a heart attack in the future. Other initiatives based on big data include using geo-mapping in what’s been called a system of deep machine learning which is fully automated, a system which was rolled out across hospitals in December.

There are many hospitals across the country applying big data analytics to patient care. This has lead to a situation where there are many sources of data coming together in a database for researchers and clinicians to analyze and extract any information that they find important.

It’s a big step away from the previous system of data warehousing to utilizing the atomic level data and metadata now available from the big data systems, allowing the healthcare organizations to employ a minimalistic data analysis model.

This means that the data can be transferred into new metrics and algorithms very quickly. The flexibility of the new model means that it is possible to extract more predictive insights from any data they can acquire.

This change in system means that healthcare organizations now require workers with the skill-set that will allow them to work with medical experts and develop a level of expertise that is shared between experts and data scientists.

These changes have, in the past, been initiated by executive boards, however, in this case, it is being driven throughout the healthcare system, with technology experts, revenue cycle managers, chief transformation officers and clinical champions all pushing the analytical initiatives forward.

It is also recommended that engineers should be included in this list, in order to move the development of systems forward faster. They need to be in the workplace with the patients, in a real space where it is much easier to see where exactly the big data system needs to be tweaked.

One of the big questions facing big data technology in healthcare is how to make it financially sustainable. This is especially difficult, as the systems are still under development and executives are unsure where exactly to commit the money in order to achieve the best results. There are plenty of rewards at the end of the process, such as arising from better treatments, more efficient operations and other cost savings, but there is still a lot of work to do in order to get the most out of big data systems.