Bioengineering alum Wei Yu

UCLA Launches New COVID-19 Hospital Resources-Projection Model

Aug 31, 2020

By UCLA Samueli Newsroom
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Researchers at UCLA have developed a web-app to help hospitals better predict needed resources for patients infected with the coronavirus. As the pandemic continues to task the health care system, reliable estimates of inpatient and ICU beds, as well as ventilators, are critical to timely patient care.

Available to the public and implemented since mid-April, STOP COVID Hospital Projections uses multiple simulations to generate short-term predictions that allow hospitals to better maximize capacity for COVID patients. The system also helps prevent underutilization of available resources, avoiding prolonged delays and cancellations for elective procedures, which are medically necessary even if they are not urgent. Such long delays may have adverse effects on patient health as the system becomes backlogged and further treatment remains unavailable.

“Accurate modeling of exactly what resources are necessary for COVID-19 patients is critical for reserving just the right amount for these patients so that we could plan what capacity can be used for other patients,” says Eleazar Eskin, chair of the department of computational medicine, which is affiliated with both the UCLA Samueli School of Engineering and the David Geffen School of Medicine.

As cities and states around the country reopened and public testing became more accessible, health care providers need to expand resources to meet the potential surge in demand for COVID-19 patients while allowing more timely care for other patients. The system focuses on resource projections up to a few weeks and is highly accurate in helping UCLA Health during the first coronavirus-caused patient surge in Los Angeles.

“Our approach models the rate of change in the number of COVID-19 patients in the community, as well as the resources used by these patients as a function of their demographic characteristics, for example, their age,” says Eran Halperin, professor in the department of computational medicine. “This results in accurate predictions of resource usage that can be adapted by hospitals in different parts of the country and we developed a publicly available tool for them to use.”

For further information, please read the UCLA Health announcement here.

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