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.
“Earlier, data warehousing and analytics was restricted to larger organizations because it was cost prohibitive. What big data has done has brought it down to smaller orgs. But the biggest challenge with these smaller markets and mid-tier organizations is resources,” Manmeet Singh, co-founder and CEO of Dataguise, told us. “Cloud is becoming very prevalent. They’re going to store a lot of data in the cloud. They’ll outsource a lot of that data to the cloud. Automation of compliance is important.”
Having witnessed the impact that big data and analytics have on other markets — and perhaps on competing healthcare organizations — healthcare CEOs want to know how their organizations can use these tools. In a PwC study, 95% of healthcare CEOs said they were exploring better ways to harness and manage big data.
Increasingly, CIOs can find similar organizations with pilot or full-blown projects. Forest Laboratories, for example, is collaborating with ConvergeHealth by Deloitte and Intermountain Healthcare on research to benefit patients with respiratory diseases. Using the collaborative, rapid-learning system developed by Intermountain and ConvergeHealth, Forest’s researchers use OutcomesMiner analytics software to develop new treatments and therapeutic products and improve patient outcomes.
The move to value-based payments means healthcare providers are taking on more risk, says Jeff Elton, managing director of Life Sciences for Accenture. To manage risk and treat patients most appropriately, providers need data — accurate data from a range of sources, he tells us.
Expanding use of big data across healthcare organizations should sound some alarms within C-level suites, Singh cautions. “From my perspective, security and compliance should be discussed from the get go. It should be part of their overall strategy.”
In the meantime, some healthcare organizations already have plunged into big-data analytics, with impressive results. Click through our slideshow to see some innovative uses of analytics in healthcare.
How are you using big data in healthcare projects? Let us know in the comments section.