In the News: Closing the Stable Door After the Horse has Bolted

Thanks to Google Alerts, I recently came across an article published by the folks at MedPage Today reporting on an algorithm developed by Dr. Cromwell at The University of Iowa  Hospital and Clinics touted to cut surgical site infections (SSI) by 58%. Results of that magnitude certainly pique my interest, so I did some internet sleuthing to learn more, and eventually came across a more thorough review on the WSJ CIO Blog and an unpublished manuscript describing their approach.

Although predictive analytics for surgical site infection isn’t in itself novel (NSQIP developed a patient risk assessment tool, for example), the novelty of Cromwell’s approach seems to be rooted in the strength of their data analytics and committment to incorporate detailed intraoperative factors into the assessment.

From the WSJ post:

“During surgery, as the surgeon closes up the patient’s abdomen, the circulating nurse logs onto a Web portal for the software and enters real-time data such as patient blood loss during the operation, the wound classification and whether it was contaminated, said Dr. Cromwell.”

The theory is that if caregivers are armed with this information before patients leave the operating room, doctors can create a plan to reduce the subsequent risk of infection by “altering medication or using different techniques in treating the wound.” The reader is left to wonder what those medications or techniques might be, especially when the physiology of wound healing dictates that infection prevention strategies are severely impaired after the incision is closed due to fibrosis and encapsulation of infectious material (Surgical Infections, March 2013).

Regardless, I think Cromwell is on to something here, because the events of operation itself represent the best opportunity to reduce risk. But assessing these predictive variables at closure is a bit like closing the stable door after the horse has bolted. A better approach would be to make sure the stable door is closed to begin with.

As an illustrative example, consider the Cromwell’s results: factors associated with increased risk of infection include certain patient zip codes, ostomy creation, higher wound class (i.e. wound contamination), higher ASA score, higher total # of procedures (per patient), surgical apgar score, and open procedural approach. We highlighted the importance of wound contamination in an earlier post, and would further maintain that of these factors, wound class (i.e. wound contamination) is the only one under direct control of the surgeon. So why aren’t we doing more to prevent wound contamination? We could start by directing powerful analytical tools like those developed by Cromwell towards the operative field.