A recent survey indicates that federal IT officials think big data analytics will save money and spare patients’ lives.
A SAP-sponsored survey released by the TechAmerica Foundation found that 83 percent of about 200 public IT officials believe that big data has the potential to save the U.S. healthcare system $380 billion from the federal budget annually or about $1,200 per American. The survey was conducted by the pollster firm Penn Schoen Berland.
Similarly 87 percent of federal IT officials and three out of four state IT officials believe real-time big data analytics will save many lives each year. Among the initiatives they suspect will accomplish that goal are the aggregation of data on healthcare outcomes, which officials believe can reveal patterns that will help detect epidemics and point the way to more effective treatment.
IT officials are clamoring for big data tools, the survey found, because traditional database queries take too much time to perform when faced with the large data collection sets organizations are increasingly using. But cost has been a roadblock.
“One of the challenges in the past with big data has been the cost of computation, and storage was fairly high,” said Anil Jain, MD, CMIO of the data analytics firm Explorys. Recruiting the help of analysts with the skills to interpret these mountains of data also was expensive and the needed skills were rare. However, those barriers are coming down, Jain said.
“All of a sudden, the value proposition for leveraging big data to solve real-world challenges is now realizable.”
But not everyone in healthcare is sold on the big data trend.
Rebecca Armato, executive director, physician and interoperability services, Huntington Hospital, Pasadena, Calif., sees the value of data analytics and believes it can lower healthcare costs and save lives, but she’s not taken in by the fad called big data. “Big data is no different from smart, intelligent data,” she said. “Who cares how big it is? I care how smart and accurate it is.”