Brown researchers among group using new AI tool to benchmark cesarean deliveries

AN OBSTETRICIAN and gynecologist from Women & Infants Hospital, along with researchers from the Warren Alpert Medical School of Brown University, was part of a team that used a new artificial intelligence algorithm to benchmark individual physician groups’ rates of cesarean deliveries and the health of their patients. / COURTESY WOMEN & INFANTS HOSPITAL

PROVIDENCE – A research team from the Warren Alpert Medical School of Brown University is among a group that used a new artificial intelligence algorithm to assess how often physician groups are performing cesarean deliveries and how their patients are faring.

Brown researchers partnered with a team from the Northwestern University Feinberg School of Medicine on the project.

Dr. Alexis C. Gimovsky, an obstetrician and gynecologist at Women & Infants Hospital, is the lead author of an article on the project that was recently published by “Health Services Research.”

Cesarean birth rates for low-risk births in the United States not only exceed the World Health Organization’s goal rate, but they are also associated with increased health problems and death for mothers, according to Gimovsky.

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“Groups have tried in the past to compare performance metrics of physician groups to hospital standards in order to understand who is performing too many cesarean deliveries and why,” Gimovsky said. “However, prior research has been limited by patient-related factors, the use of a single summary measure of hospital performance and outdated analytical methods. Additionally, comparison of cesarean delivery rates between hospitals or practice groups may not be appropriate given the wide variety in patients across groups.”

The algorithm, an optimal classification tree, keeps track of cesarean delivery rates of various physician groups in a large hospital system. The tool can then compare those rates with hospital standards to see how groups’ cesarean rates balance out against the health of their patients.

“This is important because it can serve as a valuable tool for hospital self-assessment and quality improvement in decreasing the number of cesarean deliveries, which is crucial to the goal of reducing maternal morbidity and mortality,” Gimovsky said.

Elizabeth Graham is a PBN contributing writer.

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