The University of California, Irvine, health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organisation to use.
"The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset," said Daniel S. Chow, an assistant professor in residence in radiological sciences and first author of the study, published in PLOS ONE. The tool predicts whether a patient's condition will worsen within 72 hours.
Coupled with decision-making specific to the healthcare setting in which the tool is used, the model uses a patient's medical history to determine who can be sent home and who will need critical care. The study found that at UCI Health, the tool's predictions were accurate about 95% of the time.