Early predictions underestimated how long patients with COVID-19 would need to stay in hospitals and how many would require intensive care, according to a study looking at California and Washington state.
A principal goal of physical distancing and lockdown measures during the COVID-19 pandemic is to prevent healthcare services from becoming overwhelmed.
In the United States, policymakers had to rely almost entirely on data from China, where the pandemic started, to inform their early estimates of how it would impact hospitals.
A study by researchers at the University of California (UC) Berkeley and Kaiser Permanente now suggests that this led to significant underestimates of the average time patients would stay in hospitals, how many would need treatment in an intensive care unit (ICU), and the case fatality risk.
“The hospital resources needed to meet the needs of severely ill patients are substantial,” says Joseph Lewnard, an assistant professor of epidemiology at UC Berkeley and lead author of the paper. “We found that observations from China may not provide a sufficient basis for anticipating the U.S. health care demand.”
The researchers tracked 1,328 confirmed cases of COVID-19 in hospitals run by Kaiser Permanente in Washington state and California up to April 9, 2020.
They monitored their length of stay, admission to ICU, and mortality rate.
Modeling estimates using data from hospitals in China usually assume that about 30% of hospitalized patients will require ICU care.
Of the patients in the U.S. hospitals, however, the probability of ICU admissions was 40.7%, and the probability of death was 18.9% for those with COVID-19 who doctors had admitted by April 9, 2020.
Similarly, in China, the average length of hospital stay among those who died was 7.5 days, whereas, in the U.S., the average stay was 11 days for survivors and 15 days for nonsurvivors.
A widely used modeling study from Imperial College London in the United Kingdom assumes an average hospital stay of 8 days. But the new study foun