This paper proposes an innovative approach for measuring real-time operational load within Emergency Departments. Currently, there is no agreement regarding standard matrices for measuring operational load within ED. As a result, it is difficult to develop methods and approaches for reducing operational load. We propose a flexible framework based on neural networks that calculate user-tuned load value based on a set of well-defined operational and clinical indicators. The operational load value is calculated by learning the weights of the raw operational indicators within a particular emergency department.
By: Edward Vitkin, Boaz Carmeli, Ohad Greenshpan, Dorit Baras, Yariv Marmor
Published in: H-0270 in 2009
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