How Big Data Could Save Billions For Healthcare

Big data doesn't discriminate — industries from manufacturing to retail and hospitality can benefit from this influx of information. When it comes to healthcare, however, there's huge potential not just for better decision making but significant cost reduction; here's how big data could save healthcare billions over the next few years.

Information Goldmine

For healthcare agencies to reap the benefits of big data, the first step is identifying available information sources. As noted by McKinsey and Company, these have diversified significantly over the last decade as pharmaceutical companies aggregate R&D data while government agencies and public stakeholders make healthcare data from clinical trials available upon request. There is also the huge amount of information available to doctors' offices and primary care facilities in the form of patient-driven data; this covers everything from quantitative information such as name, birthdate and specific symptoms; to more qualitative data regarding patient experiences, expectations and outcomes. In short, healthcare is sitting on an information goldmine — backed by the right analytics tools, health agencies can store and process this data to better inform patient prognosis, treatment and follow-up.

Potential Benefits

According to CIO, leveraging this data can do more than just improve service delivery. While it's difficult to find an exact number, recent studies suggest the healthcare industry could save between $348 and $493 billion by applying big-data analysis to existing data sets. It's worth noting that these savings aren't set in stone. To maximize savings, healthcare companies need better business intelligence management; while data alone is valuable, true ROI comes from the links forged with other unique data sets.

Specific Use Cases

While the promise of cost reduction is appealing to any company, specifics are what make the difference between pennies on the dollar and large-scale savings, for example:

  • Time Savings — Instead of filing out paper forms and going through the same questions each time a patient is admitted to a hospital or visits his/her primary physician, electronic health records (EHRs) save medical personnel a significant amount of time upfront. As secure sharing of these documents becomes commonplace among relevant agencies, expect these savings to increase.
  • Reduced Hospitalization — Armed with upfront knowledge about patient condition in addition to specifics about allergies, drug reactions and other relevant factors — such as missed appointments or recent medications — doctors can lower the possibility of patients entering the emergency-care stream and taxing public health resources.
  • Better Prognosis — As noted by Smart Data Collective, researchers have now created a tool which lets physicians enter characteristic patient data and look for comparisons along with specific treatment plans, letting them see in advance what worked and what didn't for patients with similar history.
  • Reduced Healthcare Fraud — Not all patients are genuine; some are looking to game the system and obtain powerful drugs or monopolize doctors' attention. By cataloging and correlating these incidents using a big data fraud management system it's possible to reduce the chances of losing time and money to scam artists.

Big data is a big deal for healthcare savings: Massive volume means billions potentially saved in treatment and medication costs, if companies are willing to embrace the big-data revolution.


  1. http://www.mckinsey.com/insights/health_systems_and_services/the_big-data_revolution_in_us_health_care
  2. http://www.cio.com/article/2993986/big-data/how-big-data-can-help-save-400-billion-in-healthcare-costs.html
  3. http://www.smartdatacollective.com/xanderscho/358180/how-healthcare-industry-can-save-400-billion-big-data