Switching from algorithm-based to universal admission screening for COVID-19 in hospital settings
Abstract
Detection of COVID-19 positive cases on admission to hospitals is crucial to protect patients and staff at the same time. While universal admission screening can prevent more undetected introductions than the algorithm-based screening, which preselects patient based on their symptoms and exposure, it is a more costly strategy as it involves testing a large number of patients.
We construct a simple tool to help determine when the benefit of additionally found cases outweighs the cost of the additionally tested patients, based on the numbers of patients to be screened in an acceptable time span to find an additional case when screening all admitted patients.
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