TY - CHAP
T1 - Applications of Hospital Bed Optimization
AU - Schneider, A J (Thomas)
AU - van de Vrugt, Maartje
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/3/30
Y1 - 2021/3/30
N2 - In this chapter we show typical bed capacity management decisions and how these can be supported using operations research (OR) models. During hospitalization, patients spend most of their time in a bed, situated at a ward. These wards, which include staff, beds, and equipment, are one of the most expensive resources of hospitals. Often patients who stay at a ward receive one or multiple treatments, which usually take place at different departments. Many wards still struggle to accommodate all incoming patients. Without aligned schedules, the flow of patients will fluctuate significantly, and therefore beds at wards will congest. As a result of this “disorganization,” staff will experience an unbalanced workload, and wards require more (buffer) capacity to accommodate all patients. With operations research techniques, planning and scheduling of both patient admissions and staff presence at wards can be optimized aiming to reduce variation in the bed occupancy. We also show three case studies using OR in bed management decision-making and discuss success and pitfalls.
AB - In this chapter we show typical bed capacity management decisions and how these can be supported using operations research (OR) models. During hospitalization, patients spend most of their time in a bed, situated at a ward. These wards, which include staff, beds, and equipment, are one of the most expensive resources of hospitals. Often patients who stay at a ward receive one or multiple treatments, which usually take place at different departments. Many wards still struggle to accommodate all incoming patients. Without aligned schedules, the flow of patients will fluctuate significantly, and therefore beds at wards will congest. As a result of this “disorganization,” staff will experience an unbalanced workload, and wards require more (buffer) capacity to accommodate all patients. With operations research techniques, planning and scheduling of both patient admissions and staff presence at wards can be optimized aiming to reduce variation in the bed occupancy. We also show three case studies using OR in bed management decision-making and discuss success and pitfalls.
U2 - 10.1007/978-3-030-60212-3_5
DO - 10.1007/978-3-030-60212-3_5
M3 - Chapter
SN - 978-3-030-60211-6
T3 - International Series in Operations Research & Management Science
SP - 57
EP - 94
BT - Handbook of Healthcare Logistics
A2 - Zonderland, Maartje E.
A2 - Boucherie, Richard J.
A2 - Hans, Erwin W.
A2 - Kortbeek, Nikky
PB - Springer
CY - Cham
ER -