Back in 2003, I was honored to be asked by Dr. Abey Kuruvilla, from the Department of Industrial Engineering at the University of Louisville, KY, to participate in a study he was doing for his PhD dissertation in Systems Engineering on Ambulance Diversion. His hypothesis was that using historical ambulance call volume patterns coupled with historical hospital diversion data, that a predictive mathematical model could be created to provide an early warning system for both EMS Agencies and Hospitals alike, thus providing time to try and avert the impending situation.
Hospital diversion effects everyone in the pre-hospital continuum. Hospitals lose revenue, EMS systems prolong transport and task times thus impacting response capabilities and public safety, patients don’t get served as desired and insurance companies pay for larger out of network bills and longer ambulance mileage reimbursement claims. Given these issues, any tool to help hospitals and EMS systems cope with the problem before it starts is useful. While I truly believe that hospital diversion is a direct function of poor systems and process engineering within our healthcare systems, until such concepts are realized and systems engineering is adopted by hospitals to help solve their internal design flaws, diversions will continue and more then likely will get worse as our boomer population ages.
In a collaborative project between Dr. Kuruvilla, his colleagues, MAST Ambulance, the regional Kansas City hospitals and FirstWatch (of which I am proudly a co-founder and partner) embarked on finding a solution. Dr, Kuruvilla was successful in finding such a solution and while only tested in the Kansas City region, I believe has the potential to help EMS systems with this ever growing problem.
Click on the links below to download Dr. Kuruvilla’s presentation and paper on the subject. I believe that Dr. Kuruvilla is still looking for trial cities and if you find his work interesting, please let me know and I will put you in contact with him.
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