ArticleHealth care management science2011
Scheduling admissions and reducing variability in bed demand.
Article in Health care management science, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Designing Governance Boundaries for Hospital Bed Management: Balancing Centralized Pooling and Local Protection.Healthcare (Basel, Switzerland) · 2026Article
- Review
- Team Size and Composition in Home Healthcare: Quantitative Insights and Six Model-Based Principles.Healthcare (Basel, Switzerland) · 2023Article
- Physician-Customized Strategies for Reducing Outpatient Waiting Time in South Korea Using Queueing Theory and Probabilistic Metamodels.International journal of environmental research and public health · 2022Article
- Multi-objective admission planning problem: a two-stage stochastic approach.Health care management science · 2020Article
- The Boarding Patient: Effects of ICU and Hospital Occupancy Surges on Patient Flow.Production and operations management · 2018Article
- A Capacity Allocation Planning Model for Integrated Care and Access Management.Production and operations management · 2018Article
- The probability of readmission within 30 days of hospital discharge is positively associated with inpatient bed occupancy at discharge--a retrospective cohort study.BMC emergency medicine · 2015Article
- Optimal control of ICU patient discharge: from theory to implementation.Health care management science · 2015Article
- Associations between in-hospital bed occupancy and unplanned 72-h revisits to the emergency department: a register study.International journal of emergency medicine · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Variability in admissions and lengths of stay inherently leads to variability in bed occupancy. The aim of this paper is to analyse the impact of these sources of variability on the required amount of capacity and to determine admission quota for scheduled admissions to regulate the occupancy pattern. For the impact of variability on the required number of beds, we use a heavy-traffic limit theorem for the G/G/∞ queue yielding an intuitively appealing approximation in case the arrival process is not Poisson. Also, given a structural weekly admission pattern, we apply a time-dependent analysis to determine the mean offered load per day. This time-dependent analysis is combined with a Quadratic Programming model to determine the optimal number of elective admissions per day, such that an average desired daily occupancy is achieved. From the mathematical results, practical scenarios and guidelines are derived that can be used by hospital managers and support the method of quota scheduling. In practice, the results can be implemented by providing admission quota prescribing the target number of admissions for each patient group.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.