GOALI/Collaborative Research: Improving Patient Flow in Hospitals

Columbia University, New York NY

Investigators

Abstract

This Grant Opportunity for Academic Liaison with Industry (GOALI) Program award will advance the national health by reducing congestion and improving patient flow within hospital units and between hospitals. By developing models that predict flow dynamics and address sources of congestion, this project will improve patient safety and satisfaction, and at the same time reduce staffing and equipment costs to the hospital. Reduced congestion will also improve occupancy prediction, thus reducing ambulance diversions within the hospital network. This research employs novel modeling techniques that are informed by a close collaboration between the PIs and the GOALI partner, Northwestern Memorial Hospital (NMH). Models will be developed that are easy to calibrate and sufficiently general, so that their analyses and insights are applicable in a broad range of clinical settings within the hospital. The award provides support for graduate students to engage in research that will be of direct benefit to healthcare operations. The PIs will incorporate the results of their research in courses on queueing and service engineering. The outcomes of the research will be disseminated to both the operations research and the healthcare practitioner communities. This award supports research on multi-server queueing models, tailored specifically to hospital operations, that address key features of patient-flow dynamics. These features include bursty departures due to periodic discharge windows and non-stationary arrival processes. Because of the complexity of the dynamics, the research develops appropriate approximations for queueing phenomena based on fluid approximations during peak loads and infinite server approximations during lightly loaded periods. These methods, in conjunction with high-fidelity simulations, will be used to characterize long-run behavior of the patient-flow process, such as the maximum throughput of hospital units, and their (periodic) time-dependent equilibria behavior under different operational policies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.