InstaMed Blog

As healthcare reform adds millions of new consumers to the U.S. healthcare system and deductibles continue to rise, providers must operate more efficiently to keep administrative costs low and collect more from patients.  Many industry experts believe that the recent influx of data and analytics due to innovation in healthcare technology, or Big Data, will give all healthcare organizations the ability to navigate the changes – and ultimately, to thrive.  In fact, a recent McKinsey report estimates that Big Data could save the healthcare industry $300 to $450 billion annually.

Is Big Data the key to efficiency in collections?

Big Data is exactly that – a large, cumbersome amount of information, not easily compressed for every day, real-time decisions or processes.  In an industry with billions of transactions per year flowing among millions of patients and thousands of payers and providers, healthcare organizations are not able to leverage massive amounts of data quickly to facilitate effective operational decisions.

In fact, the McKinsey report warns that the potential value and savings of Big Data will only be realized if the healthcare industry undergoes major changes to leverage Big Data, such as adopting new technology and processes to act quickly on data received.

What if Big Data got smart?

Big Data is made up of large, complex data sets collected over a long period of time and used to make strategic business decisions.  Collecting and analyzing Big Data can take months and even years, and the results generally are used only by C-level executives to make high-level plans and decisions.

For Big Data to improve efficiency in the healthcare industry, it needs to get smarter and go beyond the executive conference room.  There are opportunities for providers to use Big Data to trigger automated processes and real-time decisions at the staff level in daily operations.

Now, that would indeed be Smart Big Data.

Click here to read Finding Payment Assurance in the Healthcare Industry with Smart Big Data.

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