Introduction to Personal Protective Equipment (PPE)
Why is forecasting PPE important?
Personal protective equipment (PPE) such as masks, gloves, gowns, or other gear that protect clinicians from infection when delivering their care is an essential input into any clinical operation. During normal hospital operations, PPE procurement is a routine exercise of obtaining supplies at the lowest possible price from reliable suppliers. Not much forecasting is needed – hospital administrators simply place replenishment orders for the materials they have consumed in the recent past. This creates a “pull system” in which the consumption of materials triggers orders for new ones.
Though such pull systems enable hospitals, many of which are operating under significant cost pressure, to be “lean” and to operate with low inventory levels, they are not adequately preparing them for exceptional situations such as a pandemic. COVID-19 caused a surge in patient volume in some clinics, while the CMS mandated shut-downs have triggered a reduced volume in other clinics. Moreover, the mix of patients has changed dramatically, most notably to include patient conditions that are highly contagious and thus require a much higher use of PPE. This has led to a PPE shortage throughout the country, making procurement of new PPE increasingly difficult. Knowing how much PPE will be needed in the near future is central for effective procurement decision making. It is also important to anticipate future shortages and mitigate them by adjusting consumption behavior.
An introduction to our PPE Forecast Calculator
Our tool uses forecasted patient admission and census information as its inputs and creates the predicted consumption of a set of PPE critical for the care of COVID-19 patients as its output. The underlying calculations are based on PPE consumption data that we collected at the University of Pennsylvania. Our tool also allows users to input their own custom scenarios, tailored to the specific situations relevant to their hospital or health system. The overall architecture of our tool is summarized in the following figure.
Moreover, our tool allows hospitals and health systems to make projections using three pre-populated scenarios. These scenarios—standard, contingency, and crisis-- correspond to projections for PPE use under increasingly strict PPE conservation policies. These scenarios were developed in consultation with providers across several different departments to ensure they capture realistic assumptions about how PPE materials are used in standard care within a hospital and what would constitute reasonable PPE conservation strategies in case of PPE shortages.
In partnership with the Penn Medicine Predictive Healthcare team, this tool was developed by experts across a wide variety of domains at the University of Pennsylvania (Department of Computer and Information Science; Wharton School; Perelman School of Medicine; Center for Health Incentives and Behavioral Economics) and Penn Medicine (Hospital of the University of Pennsylvania).
Collaborators include: Kristian Lum, James Johndrow, April Cardone, Barry Fuchs, Cody E. Cotner, Olivia Jew, Richard Eden, Ravi B. Parikh, Gary E. Weissman, Christian Terwiesch, and Kevin G. Volpp