Hospital influenza pandemic stockpiling needs: A computer simulation

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Abstract

Background:

A severe influenza pandemic could overwhelm hospitals but planning guidance that accounts for the dynamic interrelationships between planning elements is lacking. We developed a methodology to calculate pandemic supply needs based on operational considerations in hospitals and then tested the methodology at Mayo Clinic in Rochester, MN.

Methods:

We upgraded a previously designed computer modeling tool and input carefully researched resource data from the hospital to run 10,000 Monte Carlo simulations using various combinations of variables to determine resource needs across a spectrum of scenarios.

Results:

Of 10,000 iterations, 1,315 fell within the parameters defined by our simulation design and logical constraints. From these valid iterations, we projected supply requirements by percentile for key supplies, pharmaceuticals, and personal protective equipment requirements needed in a severe pandemic.

Discussion:

We projected supplies needs for a range of scenarios that use up to 100% of Mayo Clinic–Rochester's surge capacity of beds and ventilators. The results indicate that there are diminishing patient care benefits for stockpiling on the high side of the range, but that having some stockpile of critical resources, even if it is relatively modest, is most important.

Conclusions:

We were able to display the probabilities of needing various supply levels across a spectrum of scenarios. The tool could be used to model many other hospital preparedness issues, but validation in other settings is needed.

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