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Short research paper: Personal protective equipment for the care of suspected and confirmed COVID-19 patients – Modelling requirements and burn rate

BACKGROUND: The COVID-19 pandemic has caused unprecedented global demand for personal protective equipment (PPE). A paucity of data on PPE burn rate (PPE consumption over time) in pandemic situations exacerbated these issues as there was little historic research to indicate volumes of PPE required t...

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Detalles Bibliográficos
Autores principales: Kam, Andrew W., King, Nicole, Sharma, Ashima, Phillips, Nicole, Nayyar, Vineet, Shaban, Ramon Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Australasian College for Infection Prevention and Control. Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064831/
https://www.ncbi.nlm.nih.gov/pubmed/33972186
http://dx.doi.org/10.1016/j.idh.2021.04.001
Descripción
Sumario:BACKGROUND: The COVID-19 pandemic has caused unprecedented global demand for personal protective equipment (PPE). A paucity of data on PPE burn rate (PPE consumption over time) in pandemic situations exacerbated these issues as there was little historic research to indicate volumes of PPE required to care for surges in infective patients and thus plan procurement requirements. METHODS: To better understand PPE requirements for care of suspected or confirmed COVID-19 patients in our Australian quaternary referral hospital, the number of staff-to-patient interactions in a 24-h period for three patient groups (ward-based COVID suspect, ward-based COVID confirmed, intensive care COVID confirmed) was audited prospectively from 1st to 30th April 2020. RESULTS: The average number of staff-to-patient interactions in a 24-h period was: 13.1 ± 5.0 (mean ± SD) for stable ward-managed COVID-19 suspect patients; 11.9 ± 3.8 for stable ward-managed confirmed COVID-19 patients; and 30.0 ± 5.3 for stable, mechanically ventilated, ICU-managed COVID-19 patients. This data can be used in PPE demand simulation modelling for COVID-19 and potentially other respiratory illnesses. CONCLUSION: Data on the average number of staff-to-patient interactions needed for the care of COVID-19 patients is presented. This data can be used for PPE demand simulation modelling.