by Uday Tekumalla

Predictive analytics are used by companies for everything from customer retention and direct marketing to forecasting sales. But at the University of Iowa Hospitals and Clinics, predictive analytics are serving a far more noble purpose - to decrease post-surgical infections.

By utilizing  a number of different data points that were gathered from 1,600 patients, each of whom has had colon surgery performed at the University's hospitals, the medical teams have dramatically reduced the number of patients inflicted with post-surgical infections. In fact, over a two-year period, those infections were slashed by an impressive 58-percent.

That is an impressive feat. There are, after all, a multitude of variables that can lead to an infection. This analysis considered several different data points - patients’ medical history, data from monitoring equipment, data from national registries, and real time data collected while the surgery is being performed like blood loss, wound contamination, etc. The University built predictive models using Dell Statistica predictive analytics software to achieve these impressive results. Running this analysis allows the hospital to determine a patient's risk level for post-surgical infection, providing the medical team with clear insight into the medications and treatment plans to employ going forward to minimize the risk of infection.

Along with providing better patient outcomes the University of Iowa also has likely reduced medical costs. This is an exciting example of the potential of predictive analysis. Learn more about the university's results here.