Downsizing Big Data

While big data has been common in other industries for some time, it only recently has begun to become a factor in healthcare. It has applications that range from provider-specific business intelligence to scouring over an entire state’s health records to pinpoint people who are at risk for certain ailments. Many believe that big data can help target early warning signs and improve patient safety and cut costs.

 

Big data continues to grow, according to a recent Technavio report, global big data spending in healthcare is predicted to grow at a compound annual growth rate of about 42-percent from 2015 to 2019 as providers seek to derive insights from the vast amount of data generated by EHRs, bio-metric devices, social media, and other sources.

 

One of the challenges with using big data in healthcare writes Michelle Ronan Noteboom for Heatlhcare IT News, is to find ways to downsize it and make it relevant and of value to individual patients and their physicians.

While consumers today have more opportunities than ever to monitor their own health using wearables and smartphone apps that track exercise, sleep, diet, and other health behaviors about one third of users lose interest and abandon their trackers within six months. Meanwhile, physicians are often reluctant to download patient-collected data because they lack tools to disseminate and analyze the information.

Noteboom discusses the potential value of personalizing big data down to the patient level. At the rate that technology is developing it seems realistic that one day we’ll have a tracker that auto-magically captures all aspects of the wearer’s daily diet and exercise habits, monitors vitals, and provides predictions for such things as weight and cholesterol levels over the next 30 days. In other words, the device would not only capture data, but also consider big data insights and provide personalized information that might motivate the user to remain committed to healthy choices.

On the provider side, physicians would be equipped with enhanced tools for disseminating data from individual patients and gleaning insights based on big data analysis. Providers would arguably be more interested in patient-captured data if the information was more than just data points and could aid in the care process.

This wave of growing interest is leading to ground breaking work, often by partnerships between medical and data professionals, with the potential to peer into the future and identify problems before they happen. One recently formed example of such a partnership is the Pittsburgh Health Data Alliance — which aims to take data from various sources (such as medical and insurance records, wearable sensors, genetic data and even social media use) to draw a comprehensive picture of the patient as an individual, in order to offer a tailored healthcare package.

Another partnership that was announced last spring is between Apple and IBM. The two companies are collaborating on a big data health platform that will allow iPhone and Apple Watch users to share data to IBM’s Watson Health cloud healthcare analytics service. The aim is to discover new medical insights from crunching real-time activity and biometric data from millions of potential users.

“The problem with big data today, is that for the most part it is impact the health of the individual patient,” writes Noteboom. While she doesn’t believe big data can’t be beneficial there still needs to be some innovations that would focus on the health of one patient not just on population health, hopefully motivating more patients to remain engaged in healthy behaviors along the way.