Author: Lum, K.; Johndrow, J.; Cardone, A.; Fuchs, B.; Cotner, C.; Jew, O.; Parikh, R.; Draugelis, M.; Luong, T.; Hanish, A.; Weissman, G. E.; Terwiesch, C.; Volpp, K.
Title: Forecasting PPE Consumption during a Pandemic: The Case of Covid-19 Cord-id: zkdnik6d Document date: 2020_8_23
ID: zkdnik6d
Snippet: Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patien
Document: Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patients, it is agnostic as to which model--of which many are available--provides these projections. The tool combines COVID-19 patient census projections with information like staffing ratios and frequency of patient contact to provide projections of the number of items of key types of PPE needed under three built-in conservation scenarios: standard, contingency, and crisis. Users are also able to customize the tool to the specifics of their hospital and design custom conservation policies.
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