01 Apr What is Fast Analytics, and what can your hospital learn from it?
A Navy Seal-like analytics team at the University of Michigan Health System eliminated 10,000 hours of work and recovered $3 million in RAC money. Here’s how an experimental, try-and-fail approach helped them do it.
Jonathan Greenberg, director of the fast analytics program for the University of Michigan Health System, describes his small team’s approach to data crunching like this: “Break-it-down, have a quick success, have another quick success, build some momentum, and then start pulling things together in a larger way.”
If the academic medical center itself, with more than 26,000 employees, might be likened to the Navy, Greenberg said, the five-person Fast Analytics squad is akin to a Seal Team: an agile, mission-driven group of skilled specialists.
Its mission (to mix metaphors) is to “find and destroy low-hanging fruit,” he said. “We are able to focus on very specific tasks for a specific amount of time, using specific tools and staff and skills.”
By tapping into automation and data visualization techniques, the team has been able to notch some valuable tactical victories in recent years, driving operational efficiencies across the three-hospital, 990-bed health system.
“We’ve eliminated more than 10,000 hours of work by automating processes,” Greenberg explained. “We’ve recovered $3 million in RAC money. We’ve improved our mission of patients and families first by helping our end support group.”
Another mission has been to assist more than other divisions across UMHS implement dashboards, powered by Tableau Software, to do more with their own data. More than two dozen other departments are now able to share their visualizations and reports.
“Our original goals were really focused on just providing a better reporting environment,” Greenberg said. “In 2006, when I came into this role, we were printing 60,000 pages of reports and shipping them around the institution. Real early on, we moved that to a website, but it was still just sharing paper reports on the Web.