Syncing with Big Data to Reduce Health Care Costs

This article published with permission from iMedicalApps.com.

Big Data has been a hot topic as of late in health care.

Many see big data as a way to reduce health care cost by managing patient oriented outcomes through analytics.

Can high risk patients be identified and targeted for earlier interventions?

While this is the norm for most institutions, the ability of integrating specific technology to mine big data and analyze it allows for the scaling up of health care to a larger population.

At the mHealth + Telehealth World 2013 Congress in Boston, Mass., I had the opportunity to listen to a great discussion regarding the implication of data on health care. It was titled, “The Financial Impact of Technology, Electronic Tools and Data Mining.” The speaker was Philip Fasano, executive vice president and chief information officer of Kaiser Permanente.

One of the most interesting comments Mr. Fasano made was that Big Data is not necessarily an IT thing — rather it has roots in financial services and banking. These institutions have been using data to analyze problems and create solutions that lead to innovative products for awhile. Rather, big data for the health care industry offers the opportunity to perform patient assessments, research and studies on a larger scale.

While Big Data has been making the headlines, Mr. Fasano calls for a progression of Big Data to Massive Data. The inherent issue is that Big Data is relegated to institutions and groups that collect information from their patient population. This data includes that which is collected in hospitals and at institutional clinics.

However, with the influx of mobile technology, Mr. Fasano sees the opportunity to break the boundaries of data collection from brick and mortar, and reach patients in their own homes and in their daily environment. Massive data’s potential lies in self-monitoring and the use of mobile technology to collect patient specific data.

Read more.