Every day, hospital staff do the best they can to navigate the daily chaos of bed management by making educated guesses as to what is going to happen over the course of the day. Relying on team huddles throughout the day, staff pore over Excel or paper spreadsheets to predict how many beds will open and when. They try to estimate demand for those beds by the time of day, unsure when to deploy “surge capacity.”
Matching the competing bed needs of multiple patients in the post-pandemic quaternary health care system that is always at capacity stresses traditional bed management models that rely on subjective individual preferences and bias. Who gets the next ICU bed? Do you take an ER Border or place the PACU border? How do you place direct admits or accept transfers with any time frame certainty?
It takes sophisticated algorithms and real-time predictive and prescriptive analytics to shape demand, successfully match bed supply, place the right patient in the right bed at the right time, and identify and address discharge barriers. This session will explore how to unlock the full potential of inpatient bed capacity with artificial intelligence and drive objective automated point of care bed management decision making.
Sanjay Pattani, MD, MHSA, FACEP, VP | Associate Chief Medical Officer, Mission Control, Central Florida Division, South Region
Attending, Emergency Medicine, AdventHealth Central Florida
Penny Porteous, MHA , BSN, RN Executive Director | Capacity Management & EMS Transport, AdventHealth