Prediction of personal protective equipment use in hospitals during COVID-19

Area of Science:

• Healthcare Operations Research
• Infectious Disease Control
• Supply Chain Management

Background:

• The COVID-19 pandemic has drastically increased demand for personal protective equipment (PPE).
• Hospitals face significant challenges in predicting PPE usage and managing supply chains.
• Resuming regular operations requires continuous and often increased PPE utilization by staff and patients.

Purpose of the Study:

• To develop a predictive model for hospital personal protective equipment (PPE) demand.
• To estimate the required quantities of PPE over a specified time horizon.
• To inform better inventory management and resource allocation for healthcare facilities.

Main Methods:

• Modeling patient admissions using multiple independent queues, each representing a patient class.
• Estimating the total workload for each patient class based on treatment plans and length-of-stay.
• Deriving closed-form estimates for PPE requirements using current guidelines.

Main Results:

• Gloves and surgical masks constitute approximately 90% of the predicted PPE usage.
• Glove demand is solely driven by patient-practitioner interactions.
• 86% of surgical mask demand is attributed to continuous use by medical practitioners, independent of patient interaction.

Conclusions:

• The proposed queueing model provides a reliable method for predicting hospital PPE demand.
• Understanding the drivers of PPE demand (patient interaction vs. continuous use) is crucial for effective inventory management.
• Surgical masks and gloves are the primary focus for optimizing PPE supply chains in hospital settings.