A quality improvement study on how a simulation model can help decision making on organization of ICU wards

• Published in: BMC health services research 2024-06, Vol.24 (1), p.708-9
• Main Authors: Sent, Danielle, van der Meulen, Delanie M, Alban, Andres, Chick, Stephen E, Wissink, Ilse J A, Vlaar, Alexander P J, Dongelmans, Dave A
• Format: Article
• Language: English
• Subjects: Computer Simulation; Computer-generated environments; Critical care; Decision Making; Decision Making, Organizational; Emergency medical care; Expenditures; Hospital Bed Capacity; Hospitals; Hospitals, University; Humans; Intensive care; Intensive care units; Intensive Care Units - organization & administration; Length of stay; Length of Stay - statistics & numerical data; Management; Medical care; Methods; Organizational decision making; Patients; Quality Improvement; Quality management; Quality of Healthcare; Simulation
• ISSN: 1472-6963; 1472-6963
• DOI: 10.1186/s12913-024-11161-2

Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.