The health system developed a model which integrating hospital procedures in surgery, post operation outcomes of previous surgeries and the risk of surgical site infections. Researchers then uploaded the model into predictive analytics software from Dell called Statistica, which pulls data from a number of sources, including patient medical records, biometric vitals and data from national registries, according to the report.
As the surgery comes to an end, a nurse will log onto a Web portal and enter real-time data from the surgery, like the amount of blood loss and wound classification, according to the report. This data are combined with data from the EMR, and pass through the model, returning to clinicians the risk of the patient getting an infection. Knowing the risk of infection allows clinicians to determine which therapies may be most effective for recovery, according to the report.
“Our goal has been to get that risk [of developing infection] before the patient leaves the operating room, mainly because there are some therapies out there that don’t make sense to apply to every patient,” said John Cromwell, MD, associate CMO and director of surgical quality and safety at University of Iowa Hospitals and Clinics, in the report.
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