Length of Hospital Stay and Quality of Care

被引:2
|
作者
Neves, Jose [1 ]
Abelha, Vasco [2 ]
Vicente, Henrique [3 ]
Neves, Joao [4 ]
Machado, Jose [1 ]
机构
[1] Univ Minho, Ctr Algoritmi, Dept Informat, Braga, Portugal
[2] Univ Minho, Dept Informat, Braga, Portugal
[3] Univ Evora, Dept Quim, Ctr Quim Evora, Escola Ciencias & Tecnol, Evora, Portugal
[4] DRS NICOLAS & ASP, Dubai, U Arab Emirates
来源
KNOWLEDGE, INFORMATION AND CREATIVITY SUPPORT SYSTEMS | 2016年 / 416卷
关键词
Length of hospital stay; Logic programming; Knowledge representation and reasoning; Artificial neural networks; ARTIFICIAL NEURAL-NETWORKS;
D O I
10.1007/978-3-319-27478-2_19
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The relationship between Length Of hospital Stay (LOS) and Quality-of-Care (QofC) is demanding and difficult to assess. Indeed, a multifaceted intertwining network of countless services and LOS factors is available, which may range from organizational culture to hospital physicians availability, without discarding the possibility of lifting the foot on intermediate care services, to the customs and cultures of the people. On health policy terms, LOS remains a measurable index of efficiency, and most of the studies that have been undertaken show that QoC or health outcomes do not appear to be compromised by reductions in LOS times. Therefore, and in order to assess this statement, a Logic Programming based methodology to Knowledge Representation and Reasoning, allowing the modeling of the universe of discourse in terms of defective data, information and knowledge is used, being complemented with an Artificial Neural Networks based approach to computing, allowing one to predict for how long a patient should remain in a hospital or at home, during his/her illness experience.
引用
收藏
页码:273 / 287
页数:15
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