In addition to predicting infections, physicians at UIHC have been able to design medication and wound treatment plans to reduce the infection risk. Using predictive analytics, the infection rate for colon surgery patients at UIHC decreased by 58 percent over a two year period, ending in late 2014.
Physicians have analyzed numerous sources of data, including the patient’s EMR and the specifics of their surgery, to predict the patient’s risk of infection. Previously, post-operative care had not adequately accounted for factors such as diabetes, hypertension and vital sign variability during surgery, according to the report.
According to Associate CMO and Director of Surgical Quality and Safety John Cromwell, MD, UIHC hopes to use predictive analytics to make post-surgical decisions with the same precisions as the surgery itself and reduce the risk of infections.
More articles on infections:
Surgical site infections top reason for unplanned readmissions
Postsurgical hospital readmission rates are a questionable measure of quality, study suggests
No matter the surgical setting – Inpatient or Outpatient – Compliant preoperative skin cleansing is vital
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.