Prediction of personal protective equipment use in hospitals during COVID-19
Autor: | Fahad Razak, Amol A. Verma, Alex M. Cressman, Alexey Kuznetsov, Saeha Shin, Eugene Furman, Adam Diamant |
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Rok vydání: | 2021 |
Předmět: |
FOS: Computer and information sciences
Medical staff Coronavirus disease 2019 (COVID-19) 0211 other engineering and technologies Medicine (miscellaneous) Time horizon 02 engineering and technology Operations research Queueing Systems Statistics - Applications Health informatics Article Health administration 03 medical and health sciences Health care Medical Staff Hospital Cluster Analysis Humans Medicine Applications (stat.AP) Poisson Distribution Personal Protective Equipment Personal protective equipment 021103 operations research SARS-CoV-2 business.industry 030503 health policy & services COVID-19 Workload medicine.disease Health Care General Health Professions Medical emergency 0305 other medical science business Algorithms Forecasting |
Zdroj: | Health Care Management Science |
ISSN: | 1572-9389 1386-9620 |
Popis: | Demand for Personal Protective Equipment (PPE) such as surgical masks, gloves, and gowns has increased significantly since the onset of the COVID-19 pandemic. In hospital settings, both medical staff and patients are required to wear PPE. As these facilities resume regular operations, staff will be required to wear PPE at all times while additional PPE will be mandated during medical procedures. This will put increased pressure on hospitals which have had problems predicting PPE usage and sourcing its supply. To meet this challenge, we propose an approach to predict demand for PPE. Specifically, we model the admission of patients to a medical department using multiple independent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$M_{t}/G/\infty $\end{document}Mt/G/∞ queues. Each queue represents a class of patients with similar treatment plans and hospital length-of-stay. By estimating the total workload of each class, we derive closed-form estimates for the expected amount of PPE required over a specified time horizon using current PPE guidelines. We apply our approach to a data set of 22,039 patients admitted to the general internal medicine department at St. Michael’s hospital in Toronto, Canada from April 2010 to November 2019. We find that gloves and surgical masks represent approximately 90% of predicted PPE usage. We also find that while demand for gloves is driven entirely by patient-practitioner interactions, 86% of the predicted demand for surgical masks can be attributed to the requirement that medical practitioners will need to wear them when not interacting with patients. |
Databáze: | OpenAIRE |
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