Literature DB >> 29494360

A Hospital Bed Allocation Hybrid Model Based on Situation Awareness.

Murillo da Silveira Grübler1, Cristiano André da Costa, Rodrigo da Rosa Righi, Sandro José Rigo, Leonardo Dagnino Chiwiacowsky.   

Abstract

Bed management is an important area of planning and control for hospitals, as it has the important role of maintaining the balance between patients from the emergency department, patients who have elective surgery or scheduled treatment, and patients who are discharged from the hospital, while maintaining high bed occupancy rates. Effective management of these resources has always been a challenge for managers. In the 1980s and 1990s, thousands of patients had operations canceled due to nonmedical reasons. Due to the constant uncertainty experienced by hospitals today, use of the cognitive model known as situation awareness has been increasing in healthcare. Situation awareness seeks to understand environmental context to design the future, using artificial intelligence techniques. In this context, this article contributes the use of situation awareness in bed management using a hybrid system that combines known techniques of artificial neural networks and multiattribute value theory for decision-making by automating the process of bed allocation. The system was evaluated in a hospital in Porto Alegre, Brazil, yielding a result of 93.5% similarity between the beds determined by the proposed model and those chosen by the hospital manager.

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Year:  2018        PMID: 29494360     DOI: 10.1097/CIN.0000000000000421

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  2 in total

1.  Recursive neural networks in hospital bed occupancy forecasting.

Authors:  Ekaterina Kutafina; Istvan Bechtold; Klaus Kabino; Stephan M Jonas
Journal:  BMC Med Inform Decis Mak       Date:  2019-03-07       Impact factor: 2.796

2.  Optimization of Markov Queuing Model in Hospital Bed Resource Allocation.

Authors:  Jingna Wu; Bo Chen; Danping Wu; Jianqiang Wang; Xiaodong Peng; Xia Xu
Journal:  J Healthc Eng       Date:  2020-12-08       Impact factor: 2.682

  2 in total

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