ArticleHealth care management science2005
Choice of models for the analysis and forecasting of hospital beds.
Article in Health care management science, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
16 citing papers in PubMed.
- Data-driven identification of outpatient-suitable procedures: a machine learning approach.Health care management science · 2026Article
- Bayesian model averaging based deep learning forecasts of inpatient bed occupancy in mental health facilities.Scientific reports · 2025Article
- Time series forecasting of bed occupancy in mental health facilities in India using machine learning.Scientific reports · 2025Article
- Feasibility of forecasting future critical care bed availability using bed management data.BMJ health & care informatics · 2024Article
- Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions.Health care management science · 2023Article
- Machine learning based forecast for the prediction of inpatient bed demand.BMC medical informatics and decision making · 2022Article
- Forecasting the Requirement for Nonelective Hospital Beds in the National Health Service of the United Kingdom: Model Development Study.JMIR medical informatics · 2021Article
- How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Health Care Needs of the State: Quantitative Analysis.JMIR public health and surveillance · 2021Article
- Recursive neural networks in hospital bed occupancy forecasting.BMC medical informatics and decision making · 2019Article
- Identifying seasonal and temporal trends in the pressures experienced by hospitals related to unscheduled care.BMC health services research · 2016Article
- Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data.JMIR medical informatics · 2016Article
- Surge capacity: analysis of census fluctuations to estimate the number of intensive care unit beds needed.Health services research · 2015Article
- Modelling Farm Animal Welfare.Animals : an open access journal from MDPI · 2013Review
- An open source software project for obstetrical procedure scheduling and occupancy analysis.Health care management science · 2011Article
- A non-homogeneous discrete time Markov model for admission scheduling and resource planning in a cost or capacity constrained healthcare system.Health care management science · 2010Article
- Short term hospital occupancy prediction.Health care management science · 2007Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is growing concern that current health care services are not sustainable. The compartmental flow model provides the opportunity for improved decision-making about bed occupancy decisions, particularly those of a strategic nature. This modelling can be applied to complement infrastructure and workforce-planning methods. Discussion about appropriateness of the level of model complexity, the degree of fit and the ability to use compartmental flow models for generalization and forecasting has been lacking. The authors investigated model selection and assessment in relation to hospital bed compartment flow models. A compartment model for a range of scenarios was created. The training and test data related to the 1998 and 1999 calendar years, respectively. The majority of scenarios tested were based upon commonly used periods that describe periods of time. The goodness-of-fit achieved by optimisation was measured against the training and test data. Model fit improved with increasing complexity as expected. The analysis of model fit against the test data showed that increasing model complexity did result in over-fitting, and better prediction was achieved with a relatively simple model. In terms of generalisation, the seasonal models performed best. Single day census type models, which have been used by Millard and his colleagues, were also generated. The performance of these models was similar, but inferior to that of the models generated from a full year of training data. The additional data make the models better able to capture the variation across the year in activity.
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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.