PIs: Gilles Clermont, MD, Andrew Schaefer, PhD, MCAM, Guodong Pang, PhD
Funding: National Science Foundation (September 1, 2016 to August 31, 2019)
This collaborative research project targets the heavy resource burden that ICUs place on a hospital system, carrying operating costs that may at times make up 20 percent of a hospital’s budget. The research team aims to model patient flow through a hospital system by employing methods that are often used in other cases to improve the efficiency of supply chains, flight schedules, or vehicular traffic while at the same time maintaining an optimized level of resource use. In the case of hospital systems, ensuring that patients are assigned to the proper level of care, such as an ICU, is vital for achieving an optimal trade-off between outcomes and resource use.
The research team will leverage the large repository of EHR data at UPMC, along with transfer request data and actual transfer times, in order to systematically quantitate the existing discrepancies between patient state and level of care. That information can then be used to design improved transfer request policies based on patient state, expected readmission rates, and outcomes.