Taming the Big Data frontier
In his keynote address at the Allscripts Client Experience, ACE13, Dr. Rasu Shrestha from University of Pittsburgh Medical Center said, “He who tames the data wins.”
As healthcare organizations manage evolving delivery and payment models, an analytics strategy is top of mind for many. Big Data is the next frontier for analytics and offers them access to rich data they can use for population health, research and consumer marketing and satisfaction.
Quickly emerging Big Data technologies augment traditional business intelligence technologies by efficiently and affordably acquiring and storing enormous amounts of data. Providers can query and re-query information without retooling the data model every time. This capability is particularly important with the mountains of data we have access to today.
3 opportunities to get value from Big Data
With so much data coming from so many different places, how can healthcare providers tame Big Data? There are different opportunities, depending on the type of information:
1. Join the conversations happening on the Internet.
Patients are posting status updates in Facebook, Twitter and other social media that give valuable information about their own health. They’re also talking about their experience with their hospitals and clinics.
Monitor these status updates to find out if patients are unhappy with wait times, how they were treated by staff, or overall condition of facilities. Chances are good that patients are “hash-tagging” your organization. Do you know what they are saying?
2. Mine clinical documentation for critical nuggets of information.
Even with the heavy adoption of electronic health record (EHR) technology, a significant amount of clinical documentation is still unstructured. Clinical notes and reports hold valuable information that providers can use to better measure quality, support research and feed predictive models.
Use Big Data technology to manage volumes of unstructured documentation in various formats. If you apply text mining techniques, you can drive near real-time clinical decision support. You can also use predictive algorithms to help understand what might indicate an adverse event before it occurs.
3. Harness and analyze device data.
Medical devices and smartphone applications are capturing a wealth of healthcare data that could easily become overwhelming. But think about the possibilities of capturing this data and applying analytics improve clinical interventions.
What if monitoring streaming device data in the hospital such as heart rate and respirations could feed predictive models for detecting sepsis? Or caregivers could monitor populations of diabetics using smartphone apps to report weight, glucose levels and blood pressure so that care teams can easily identify patients that may be trending out of control?
Health care is not lacking for data. But we must tame it to recognize its true value. Big Data technology and our partnership with Intel can help transform enormous amounts of data into insight that can ultimately result in better quality of care and more rapid interventions.