Hospital Systems Occupancy Prediction and Control to Increase Access, Smooth Provider Workload, and Reduce Cost

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

This research project creates an innovative methodology based upon enterprise-wide patient flow modeling to guide operational admission and scheduling practices to smooth hospital census/occupancy. Our research will provide theoretical foundations as well as a practical decision support methodology incorporating (1) the stochasticity of unscheduled/emergent patient arrivals, (2) scheduled elective surgical and medical inpatients, (3) the stochastic system dynamics of bed block and occupancy by bed unit/ward and (4) the patient's treatment trajectory through the bed units and (5) other critical hospital resources (i.e. physicians, nurses, equipment, specialized beds, operating time etc.). Analytical models will be developed to approximate the hospital beds as a dynamically controlled queueing network. A theoretical patient flow modeling methodology will be used to capture the stochastic evolution of the patient's bed resource needs and thereby census. New optimization/control models will provide methods for (1) elective admission planning and (2) census recourse/control. Hospitals frequently lack rigorous, accurate enterprise level planning and daily census management tools developed from a systems perspective. This research will provide the theoretical foundations, practical methodologies, and proof of concept for a novel online decision support approach to achieve increased access by reducing turnaways and delays to access, better matching of the care workload to the scheduled staff for improved quality of patient care, and reduced hospital operating costs. This research engages partner hospitals that are recognized as leaders in innovation. Outcomes will be disseminated to engineering and public health communities through publications targeting highly visible journals in engineering, and medicine/healthcare. Graduate and undergraduate students in engineering, business, and public health will benefit through classroom instruction (including teaching tools) and involvement in the research. The highly relevant application will equip students to be change agents in improving hospital operations.