In today’s highly cost sensitive environment many hospitals are running at greater than 90% capacity. Delays within a hospital are a significant cause of reduced throughput and compromised patient safety. For example, delay in triaging and boarding in the Emergency Department can result in patient left without been seen or increased time to care. This has consequences on in-hospital mortality rates, as well risking lives of patients who leave the hospital. Much research has been conducted in studying and redesigning the emergency department processes to optimize its throughput rates. However, little attention has been paid in the literature (other than the patient discharge process) on how upstream processes result in emergency department inefficiencies. Two such upstream processes are patient transport and dirty bed turnover. This proposal intends to fill this major gap towards developing techniques to improve patient flow in a hospital system. A patient waiting in the emergency room for transport or for cleaning of a dirty bed is blocking an emergency room bed that could be used to admit a new patient. The proposed project has two major goals: (1) Develop and study models for hospital level staffing of support staff to ensure cost effectiveness to the system while ensuring patient safety; (2) Develop real-time patient prioritization and dispatch timing policies to reduce the wasted time in the system. To achieve these goals we intend to combine stochastic optimization and policy decision modeling in a novel way by incorporating elements from skill-mixing and simulation to facilitate management decision making. Our preliminary analysis suggests that an improved process may result in about 5% improvement in the system throughput. However, much work is needed to systematically study this problem in the context of a real system. Elements of this real system include message generation to notify a downstream unit for a future admission whose final admission trigger awaits further physician work. The models will be tested using the patient data available to us from the Electronic Patient/Physician Record System at Northwestern Memorial Hospital (NMH). The project will be executed in close collaboration with members of NMH operations team including emergency department manager of finance and strategy, and NMH performance manager for patient throughput. By combing the optimization modeling and queuing system modeling expertise, together with access to the NMH operational staff makes the research team uniquely qualified to achieve the stated goals, and translate the research outcome into practice.
|Effective start/end date||10/1/13 → 9/30/18|
- National Science Foundation (CMMI-1335585)
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