Skip to content

UCI School of Medicine: COVID-19 predictive analytics tool (18 December 2020)

Summary

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.

UCI School of Medicine: COVID-19 predictive analytics tool (18 December 2020) http://covidrisk.hs.uci.edu/

Edited by Patient Safety Learning

User Feedback

Recommended Comments

There are no comments to display.

Create an account or sign in to comment

Registered address: Patient Safety Learning, China Works SB203, 100 Black Prince Road Vauxhall, London, SE1 7SJ

Account

Navigation

Search

Search

Configure browser push notifications

Chrome (Android)
  1. Tap the lock icon next to the address bar.
  2. Tap Permissions → Notifications.
  3. Adjust your preference.
Chrome (Desktop)
  1. Click the padlock icon in the address bar.
  2. Select Site settings.
  3. Find Notifications and adjust your preference.