Predictive analytics techniques aid hospitals that treat data properly Posted on : May 28 - 2015

Hospitals are under pressure to cut costs and to restore patients to good health without readmissions. Predictive analytics can help, but providers need a solid plan for using their data.

In 2014, Cleveland Clinic wanted to get a better handle on controlling the cost of knee replacement surgeries done at its surgery centers. The health system performs about 2,600 of the procedures annually, so even a small cost reduction on each one could add up to huge savings for the clinic and patients. To find what it was looking for, the provider turned to predictive analytics techniques and tools — but its analytics team also had to spend time convincing surgeons to base treatment plans on what the data was telling them.

Steven Spalding, Cleveland Clinic’s medical director for enterprise information management and analytics, said his team developed assessments built into the organization’s electronic health record system that score knee-replacement patients on their likely length of stay and their probability of being discharged to someplace other than home, an indication of surgical complications. The analysts, in partnership with surgical specialists, also developed recommended care strategies for surgeons to follow based on individual patients’ risk factors.

It’s the people and the process — and unless you have those things lined up, who cares if you’ve integrated big data and produced an awesome model?

Steven Spalding

medical director for enterprise information management and analytics, Cleveland Clinic View more