Emergency Preparedness Planning Before and During a Crisis

Logo
Presented by

Henry Yennie, Program Manager, Louisiana Department of Health

About this talk

The current COVID-19 pandemic has kick-started a world of forecasting and “modeling” designed to anticipate the need for scarce medical resources. Across the country, modelers are producing estimates for leadership that have been orders of magnitude wrong, like in the case of the depletion of hospital beds. In Emergency Preparedness, many risk managers are locked into a deterministic model, but at their core, they are based on single-point estimates of various “uncertain” variables. These assumptive single-point estimates are used throughout the spectrum of problems and response scenarios healthcare professionals face, from estimating available hospital beds, mortality expectation, general population evacuation, medical special needs sheltering, etc. In almost every case, there are considerable front-end debates and meetings to generate “planning factors” and “rate-limiting factors”. In other words, everyone is looking for “the number”. In this webinar, we will review the history of these planning efforts over the last 15 years and glance at some stochastic models we’ve employed based on distributions of data with @RISK. Utilizing Monte Carlo simulation in statistical methods has been validated by real-world results in providing the small efforts in formulating a better approach.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (185)
Subscribers (50796)
Palisade Company is the world’s leading provider of risk and decision analysis software solutions for science and industry. Our array of software products and custom services enhance the management experience by combining the latest in cutting-edge technology with over 35 years of analytics experience. Palisade’s unified software platform helps clients increase margins, improve performance, expand market share, and maximize operational efficiencies. We have a very simple mission: to minimize risk while maximizing potential.