Clearing Big Hurdles in Healthcare 

If you’ve ever spent half an hour filling out paperwork in your physician’s waiting room, you know that the amount of information doctor’s offices face every day can be overwhelming. Now, a growing number of of healthcare organizations say that it is having too much data rather than too little that can bog down decision-making.

Within doctors’ notes, registration and discharge papers, phone calls, CT scans and MRIs lies 80 percent of the information that doctors use to make decisions, and it’s all unstructured. To help turn this data into a benefit instead of a burden, organizations like UNC Health Care are turning to big data and analytics.

According to UNC, the result is that cancer patients waiting on biopsy results or those waiting to hear back about screenings such as pap smears, mammograms and colonoscopies will hear back from their doctor more quickly, which can lead to getting treated more quickly, or simply getting peace of mind sooner.

In addition, UNC Health Care expects the system to reduce readmission rates since it will help doctors to arrive at the correct diagnosis and optimal treatment plan the first time around. Twenty percent of patients in the U.S. will be readmitted currently, which takes up six percent of Medicare’s $102.6 annual budget.

Although two-thirds of healthcare organizations already have similar tools in place, only twenty percent actually use them across operations. Perhaps even more telling is a recent IBM survey from its Institute of Business Value, which found that only 34 percent of the 555 medical organizations polled thought that analytics would help them to improve decision-making.

“One major obstacle for healthcare organizations today is how to manage all their data when it comes in many different formats and can be difficult to find in various parts of an organization,” said Dr. Michael Weiner, director of Healthcare Strategic Services at IBM in an article for the Washington Post. IBM has provided UNC Health Care with its Smarter Care analytics system, which helps to sift through these types of unstructured data through natural language processing similar to human understanding of language.