Optimizing Health Care With Big Data

For big data enthusiasts, healthcare is a goldmine for disruption. Right from the patient demographic data to their medical reports, the recommended treatment, their retention rates and treatment success rates – the information gathered from all this could help unravel a number of patterns and interpretations that could potentially startle you.

For big data enthusiasts, healthcare is a goldmine for disruption. Right from the patient demographic data to their medical reports, the recommended treatment, their retention rates and treatment success rates – the information gathered from all this could help unravel a number of patterns and interpretations that could potentially startle you.

Over the past few years, companies like IBM have invested quite heavily in healthcare to leverage the benefits of big data. Intel recently partnered with the Michael J Fox Foundation for Parkinson’s Research to mine data obtained from wearable devices to identify patterns in the progression of the disease. Similarly, the Jersey City Medical Center recently partnered with Bradshaw Consulting Services to help improve the response time for medical emergencies through big data. The result – the average response time is now lower than six minutes; quite lower than the national average of nine minutes.The opportunities and the potential gains are massive in healthcare and tech companies are rightly interested.

While such news-making big data partnerships in healthcare are on, there are also opportunities for independent healthcare businesses to make use of big data to optimize their operations. For instance, a number of medical units today utilize the IBM Smarter Care big data solution to identify and reduce potentially expensive patient readmission as well as decrease mortality rates. IBM’s Smarter Care is an effective tool because it uses Natural Language Processing to interpret both structured and unstructured data to identify patterns and clues that could help healthcare workers understand the causes for patient readmissions and thus help them prevent them.

Besides core healthcare, hospitals also need intelligence to tackle their business operation needs. According to Solution Reach, a patient relationship management company, practices lose 50% of their base every five years presumably due to the perceived indifference. While a lot of this may be tackled through a better system for setting appointment reminders and gathering patient feedbacks, big data can help identify patterns in patient attrition – a tool that is extremely critical to maintaining the financial health of a healthcare business.

In a nutshell, here are the three ways big data can help optimize healthcare:

Managing Patient Records : No two patients are the same and therefore managing patient history is a nightmare even with the best spreadsheet programs. Big data helps manage the records of thousands of patients with ease.

Predicting Ailments : There are often medical cases that can stump even the experienced doctors. This often leads to a wild goose chase and by the time the right cause of an ailment is deciphered, it may be too late. With big data, it is possible to map the patient’s data with millions of existing patient records to help identify patterns – this helps in quickly rounding in on possible causes and thus helps save precious time.

Prevent Readmissions : Readmissions are often a symptom of wrongful diagnosis or insufficient treatment. Big data helps identify the reasons for readmissions and helps hospitals tackle them efficiently. This is also valuable from a business point of view considering that US Medicare have come up with new rules that penalize hospitals in case patients are readmitted within 30 days of being released.