Healthcare organizations hope big data and analytics projects can help reduce costs and improve care. Consider these innovative examples.
With the mandated adoption of electronic health records (EHRs), many healthcare professionals for the first time got centralized access to patient records. Now they’re figuring out how to use all this information. Although the healthcare industry has been slow to delve into big data, that might be about to change. At stake: not only money saved from more efficient use of information, but also new research and treatments — and that’s just the beginning.
For instance, data from wireless, wearable devices such as FitBits is expected to eventually flood providers and insurers; by 2019, spending on wearables-data collection will reach $52 million, according to ABI Research. Another source of health data waiting to be analyzed: social media. Monitoring what people post can help fight insurance fraud and improve customer service.
These are just two ways big data can be used to improve care while cutting costs, experts say.
“We, as a society, need to start creating our own metrics for how healthcare quality is defined. In the sense of looking at costs, we know where there’s avoidable cost in healthcare. We just need to get folks the data they need to avoid those pitfalls,” said Dr. Anil Jain, senior VP and chief medical officer at Explorys, in an interview. Explorys, which is an innovation spinoff from Cleveland Clinic, is powering Accenture’s Predictive Health Intelligence in a collaboration intended to help life sciences companies determine the combination of treatments and services that can lead to better patient, provider, and economic outcomes for diabetics.
Hosted analytics, partnerships and collaborations, and lower-cost internal applications open the door for smaller organizations to use big data, too.