Improving Emergency Department Patient Flow Through Near Real-Time Analytics

摘要: IMPROVING EMERGENCY DEPARTMENT PATIENT FLOW THROUGH NEAR REAL-TIME ANALYTICS by SHANSHAN QIU August 2014 Advisor: Dr. Ratna Babu Chinnam Co-Advisor: Alper Murat Major: Industrial Engineering Degree: Doctor of Philosophy This dissertation research investigates opportunities for developing effective decision support models that exploit near real-time (NRT) information to enhance the “operational intelligence” within hospital Emergency Departments (ED). Approaching from a systems engineering perspective, study proposes novel framework streamlining ED patient flow employs machine learning, statistical and operations methods facilitate its operationalization. crowding has become subject significant public academic attention, it is known cause number adverse outcomes patients, staff as well revenues. Despite many efforts investigate causes, consequences interventions overcrowding in past two decades, scientific knowledge remains limited regards strategies pragmatic approaches actually improve EDs. Motivated gaps research, we develop triage system reduce boarding flow. The proposed variant newsvendor modeling integrates admission probability