The dataset is expected to help the research community develop new algorithms and predictive tools to improve the care of surgical patients globally
A team of researchers from UCLA and UC Irvine have created a unique repository of electronic health record data and high-fidelity physiological waveform data from tens of thousands of surgeries that will integrate artificial intelligence to improve patient outcomes.
The project led is by Dr. Maxime Cannesson, professor and chair of anesthesiology and perioperative medicine at the David Geffen School of Medicine at UCLA; and Dr. Pierre Baldi, Distinguished Professor of information and computer sciences and Dr. Joe Rinehart, clinical professor of anesthesiology, both at UC Irvine. It is freely available to legitimate researchers who sign a data use agreement (DUA).
The team has published a paper describing the database and its uses in JAMIA Open.
“We expect it to help the research community to develop new algorithms, new predictive tools, to improve the care of surgical patients basically globally,” Cannesson said. “It’s the first time a surgical database like this has been released. It’s a very wide spectrum of surgeries.”
The repository, which had been in the works since 2012, fills a gap in publicly accessible databases that researchers can use to train and test AI algorithms. It is intended to advance a wide variety of healthcare research and serve as a resource to evaluate new clinical decision support and monitoring algorithms for patients undergoing surgery and anesthesia.