The goal of this Grant Opportunity for Academic Liaison with Industry (GOALI) collaborative research award is to offer insights into improving patient flow through inpatient units and efficiently managing staff workload. This research will allow hospital managers to increase patient satisfaction and service throughput, policy makers to develop improved benchmarks for hospital workflows, and front-line providers to make intelligent data-driven decisions. Hospitals locally and nationally will be able to better align care processes, improve patient flow, all while lowering costs. Patients will have improved access to and quality of care. One of the concrete outputs of the project is a decision-support system that is expected to have have high potential for commercialization, and hence yield broad impact of the research, in the healthcare analytics market.
The research goals will be met via the development of a set of innovative models and solution approaches for analyzing and optimizing inpatient discharge decisions pertaining to patient flow alignment and care professional workload management. This work will help reduce inpatient discharge lateness and overnight stays, alleviate delays in transfers from upstream units, as well as balance discharge and non-discharge related workload for hospital staff. These improvements will be accomplished by optimally aligning bed-requests from upstream units with bed-releases from the inpatient unit. A novel decision-dependent stochastic combinatorial optimization framework will be developed that integrates inpatient discharge prioritization and workload scheduling decisions, which will be solved using an innovative scenario decomposition method. Rigorous theoretical derivation and comprehensive computational studies will be conducted for the proposed solution approach using real-data from our hospital partner.
