id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-285381-6e9umbpi	Fort, Daniel	Locally Informed Modeling to Predict Hospital and Intensive Care Unit Capacity During the COVID-19 Epidemic	2020		.txt	text/plain	2896	138	47	Methods: We developed a susceptible-infected-recovered (SIR) model that was adopted from the University of Pennsylvania COVID-19 Hospital Impact Model for Epidemics and employed at 8 hospitals within Ochsner Health, the largest integrated delivery system in Louisiana, between March 16 and April 15, 2020. During the uncertainty of the early phase of the 2019 novel coronavirus (COVID-19) pandemic, hospitals and health system leaders faced the urgent task of translating the unknown into forecasting models of acute care, critical care, and ventilator capacity. This report describes the development of a simplified COVID-19 forecasting tool that was derived from the CHIME concepts, demonstrates the validity of our early modeling using real-world hospital census data, and shows how the tool was used to make operational decisions for a large health system in one of the COVID-19 epicenters. Figure 2 displays the follow-up forecast and subsequent observed ICU/ventilator census and expanded bed capacity after real-time hospital data were acquired.	./cache/cord-285381-6e9umbpi.txt	./txt/cord-285381-6e9umbpi.txt