Selected article for: "hospital protective equipment and personal hospital protective equipment"

Author: Gonzatto, O. A.; do Nascimento, D. C.; Russo, C. M.; Henriques, M. J.; Tomazella, C. P.; Santos, M. O.; Neves, D.; Assad, D.; Guerra, R.; Bertazo, E. K.; Louzada, F.
Title: Safety Stock: Predicting demand on the supply chain in Brazilian hospitals during the COVID-19 pandemic
  • Cord-id: 2ct51ggq
  • Document date: 2020_5_28
  • ID: 2ct51ggq
    Snippet: Background: Many challenges lie ahead for COVID-19, not only related to the acceleration of the pandemic, but also to the prediction of the hospital's personal protective equipment to accommodate the explosive demand. Due to the situation of uncertainty, the hospital administration encourages the excess stock of these materials, causing excess products in some hospitals, but shortages in others. Although three main factors limit the number of patients seen at a hospital: the number of beds avail
    Document: Background: Many challenges lie ahead for COVID-19, not only related to the acceleration of the pandemic, but also to the prediction of the hospital's personal protective equipment to accommodate the explosive demand. Due to the situation of uncertainty, the hospital administration encourages the excess stock of these materials, causing excess products in some hospitals, but shortages in others. Although three main factors limit the number of patients seen at a hospital: the number of beds available, the number of equipment, and, above all, the number of health professionals available at the hospital, per shift. Objective: In this scenario, a challenge is to build an easy-to-use computational tool to predict the demand for personal protective equipment in hospitals during the COVID-19 pandemic, with updating in real-time. Methods: We propose naive statistical modeling, which combines historical data on the consumption of personal protective equipment by hospitals, current protocols for their uses and epidemiological data related to the disease, in order to build predictive models for the demand for personal protective equipment in Brazilian hospitals during the pandemic. We then embed our modeling in a tool that can provide the safety stock for a particular hospital. Results: Our tool presents forecasts of consumption/demand for personal protective equipment over time, indicating the moment when the hospital reaches maximum consumption, the estimate of how long it will work in this state, and when it will leave it. Conclusion: With our forecasting, a hospital may have estimated, based on its stock levels and possible new purchases, its needs related to a specific personal protective equipment, which allows for the adoption of strategies to control and keep the stock at safety levels to the demand. As a direct consequence, it enables interchange and cooperation between hospitals, aiming to maximize the care during the pandemic.

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