Strategic and Tactical Hospital Bed Management in Belgium and in France

Gossart, Daisy; Meskens, Nadine; Guinet, Alain

doi:10.1007/978-3-642-15961-9_29

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…However, moderate to severe dengue cases (such as those which are the focus of this study) need more intensive care and support, in which case temporary facilities might not be a good solution. Therefore, the management of resources in a regional hospital network becomes more and more critical for hospitals [5], such as the Regional Emergency Operation Center (EOC) in Tainan, which contains nine regional hospitals [33]. To detect the uniform distribution of spatial accessibility, the PSO is used to find the optimal hospital resources from each solution of hospital resources in the network.…”

Section: Discussionmentioning

confidence: 99%

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Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak

Chu

Lin

et al. 2016

IJERPH

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Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model’s demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations.

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Section: Discussionmentioning

confidence: 99%

“…The demand for resources during the dengue outbreak in Tainan exceeded the capacity of individual health facilities. Thus, the management of hospital resources, including beds, equipment, and clinical manpower, and so on [4], in the existing hospital networks has become a significant issue [5]. …”

Section: Introductionmentioning

confidence: 99%

Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak

Chu

Lin

et al. 2016

IJERPH

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“…Gossart et al. () focused their research on the strategic and tactical level, determining the number of rooms and bed capacity with regard to the evolution of hospital settings. From the tactical point of view, they focused on the planning of activity (elective patient admissions), forecasting demand, and measuring the impact of ED patients inside the system.…”

Section: Literature Reviewmentioning

confidence: 99%

Multiobjective bed management considering emergency and elective patient flows

Landa

Sonnessa

Tànfani

et al. 2016

Int Trans Operational Res

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In recent years, hospitals have increasingly been faced with a growing proportion of their inpatient work coming from the fluctuating and unpredictable demand of emergency admissions. The opportunity to move emergency patients who have been selected for admission out of the emergency department (ED) is linked to the ability of the hospital network to actually admit them. The latter is, in turn, correlated to the availability of inpatient beds in the hospital wards, which are shared resources between elective and emergency patients. Due to the overcrowding of EDs and the growing concern regarding reducing the number of inpatient ward beds, it is thus becoming crucial to improve the bed capacity planning and the management of emergency and elective patient admissions. In this direction, greater coordination and communication among the different healthcare providers involved in the pathway flows is required, and the so-called "bed management" function plays a key role. This study starts with collaboration with the local health government (LHG) of the Liguria region aimed at studying the hospital bed management function. A large quantity of data records have been collected during one year of activity to obtain information related to the flow of emergency and elective patient pathways. A medium-sized hospital located in the city of Genova has been chosen as a case study, and a discrete event simulation model has been developed to reproduce the multiple patient flows involved in the system. Multiobjective optimization analysis has been performed to choose the best bed allocations considering both operational and tactical decisions characterized by various trade-offs among alternative conflicting objectives. The model can be used to help decision makers find a representative set of Paretooptimal solutions and quantify trade-offs when satisfying different objectives.

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