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DataLab Partners with UC Davis Medical Center to Predict COVID-19 Admissions

By Pamela Reynolds and Jessica Nusbaum

The Delta variant is driving a surge in hospital admissions and straining ICUs around the world. Under such conditions, accurately anticipating demand for hospital resources can mean the difference between timely treatment and, in some cases, between life and death. When and how are COVID-related admissions rates likely to change, and by how much? And how far in advance can we make such predictions accurately?

In response to this challenge, the UC Davis DataLab has partnered with UC Davis Health to develop improved machine learning and AI models for predicting COVID-19 admissions and overnight stays, and to put them into use by doctors and nurses working with COVID patients. The models have increased the UC Davis Medical Center’s ability to predict COVID-related admissions one day, two days, and even a full week in advance. And, these predictions are also more accurate, with an 8% decrease in the error rate. More accurate predictions of hospital admissions and bed occupancy have real, tangible consequences for hospital operations, such as ensuring adequate staffing levels and equipment availability, that help maintain standards of care during this health crisis. Increasing the prediction timeline also benefits hospital staff, providing workers longer windows for adjusting their work-life schedules.

Read the full article on Egghead. Learn more about the UC Davis DataLab here.

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