Healthcare Big Data

In this second instalment of Healthcare Big Data, let’s look at the multiple sources of data that are responsible for Healthcare Big Data.

The internal data found in existing paper-based medical records is one large source of Healthcare Big Data.

With more and more hospitals in the health care industry around the world turning to creating digital representations of existing data in paper-based medical records and acquiring everything that is new in the form of Electronic Medical Records, there is an infinite data growth rate in this internal data source.

Then there is also Big Data from other sources, those from external, private, and public sources.

The discovery process, both oral and written discovery initiated by the legal profession outside the healthcare industry which adds terabytes or even petabytes of information is one source of external Healthcare Big Data, when individual doctors, hospitals, and medical practice groups become defendants in malpractice lawsuits.

No matter the size of Healthcare Big Data, a known fact in healthcare is to improve patient care and reduce costs.

Thus to improve patient care and reduce costs through Healthcare Big Data, one of the biggest challenges for most healthcare organisations is to mine the data or dig for something of value from these multiple sources of data. Healthcare organisations must find i.e locate the appropriate data, identify useful data i.e determine whether the data set is appropriate for use, and aggregate all of the Big Data from the multiple sources and push through an analytics platform as part of their analytics processes.

Since I am running a blog for the general benefit of Health Information Management (HIM) / Medical Records (MR) practitioners, I shall not be diving deeper into big data sources, to avoid driving readers into the IT realm nor writing on the business analytics (BA) and business intelligence (BI) processes to determine how large-scale data sets can be used. I must say that all the posts on Big Data I have published on this website-blog , including this one is to facilitate HIM / MR practitioners to have a rudimentary understanding of Big Data.

Now that HIM / MR practitioner readers know that Big Data is out there, Frank (2013) states that “analytics is part science, part investigative work, and part assumption.” The idea is to capture as much as data the healthcare organisation deals with, so all of any data are located, included and gathered from as many data sources as possible so that the more data there will be to work with and bring all of these data into an analytics platform.

While the healthcare organisation locates, includes and gathers from as many data sources, healthcare organisations will find a vast wealth of external public information. This external data makes up the public portion of Big Data. This includes customer sentiments from research companies and social networking sites e.g Twitter, Facebook to geopolitical issues e.g. weather information and traffic pattern information, from government entities, e.g census data, and a multitude of other sources.

In the next instalment, I shall gather more information on how the multitude of sources of Healthcare Big Data must be integrated and managed to set priorities so that Big Data solutions could analyse and get the results into the right hands to improve patient care and reduce costs.

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