DescriptionThe population is aging; the patients’ expectation for the quality of care is increasing, and, as a consequence, hospitals face a growing patient workload. Beds are an essential resource, which follows the patients, and must be adequately managed. Stock-outs could lead to severe consequences: delays, redirectionsor procedure cancellations. Therefore, reliable and robust bed management is fundamental for well-performing hospitals.
Beds have their own internal flow. The whole bed cycle has two parts: in use with the patient and after usage, without, including cleaning, transport, and storage. Beds navigate with the patients through all the departments of the hospital and their specific and independent processes. The patients constitute a highly uncertain demand, as their number and characteristics (length of stay or pathology) make forecasting, planning, and execution more difficult.
Bed management involves several disciplines and methods from Management Science. We conducted a literature review that highlights the cross-departmental aspects of bed management and the potential for holistic approaches. With the digital technologies, the quantity of hospital data has skyrocketed, giving the opportunity to devise new data-driven decision-support tools. In that optic, we work jointly with Rigshospitalet, a public hospital in Denmark, using their data in a bed
management case study to build a simulation model that can help better understand, optimize, beds and patients flows. This model takes into account the entire bed flow of the hospital, which allows operating on the entire bed cycle and bed fleet and evaluate new policies and processes. The objectives are to smooth the demand, minimize the workload, and reduce the need for storage and resources
|Period||30 Jul 2020|
|Event title||46th Annual Meeting of the EURO Working Group on Operational Research in Health Care|
- Bed Management