Modeling and Simulation of the Emergency Department of an Italian Hospital

Author(s):  
Wanying Chen ◽  
Alain Guinet ◽  
Tao Wang
2017 ◽  
Vol 22 (33) ◽  
Author(s):  
Andrea Porretta ◽  
Filippo Quattrone ◽  
Francesco Aquino ◽  
Giulio Pieve ◽  
Beatrice Bruni ◽  
...  

We describe a nosocomial outbreak of measles that occurred in an Italian hospital during the first months of 2017, involving 35 persons and including healthcare workers, support personnel working in the hospital, visitors and community contacts. Late diagnosis of the first case, support personnel not being promptly recognised as hospital workers and diffusion of the infection in the emergency department had a major role in sustaining this outbreak.


2019 ◽  
Author(s):  
Andrea Fabbri ◽  
Giulio Marchesini ◽  
Barbara Benazzi ◽  
Alice Morelli ◽  
Danilo Montesi ◽  
...  

Abstract Background: The burden of sepsis represents a global health care problem. We aimed to assess the case fatality rate (CFR) and its predictors in subjects with sepsis admitted to a general Italian hospital from 2009 to 2016, stratified by risk score.Methods: We performed a retrospective analysis of all sepsis-related hospitalizations after Emergency Department (ED) visit in a public Italian hospital in an 8-year period. A risk score to predict CFR was computed by logistic regression analysis of selected variables in a training set (2009-2012), and then confirmed in the whole study population. A trend analysis of CFR during the study period was performed dividing patient as high-risk (upper tertile of risk score) or low-risk . Results: 2,492 subjects were included. Over time the incidental admission rate (no. of sepsis-related admissions per 100 total admissions) increased from 4.1% (2009-2010) to 5.4% (2015-2016); P<0.001, accompanied by a reduced CFR (from 38.0% to 18.4%; P<0.001). A group of 10 variables (admission in intensive care unit, cardio-vascular dysfunction, HIV infection, diabetes, age ≥80 years, respiratory diseases, number of organ dysfunction, digestive diseases, dementia and cancer) were selected by the logistic model to predict CFR with good accuracy: AUC 0.873 [0.009]. Along the years CFR decreased from 31.8% (2009-2010) to 25.0% (2015-2016); P = 0.007. The relative proportion of subjects ≥80 years (overall, 52.9% of cases) and classified as high-risk did not change along the years. CFR decreased only in low-risk subjects (from 13.3% to 5.2%; P<0.001), and particularly in those aged ≥80 (from 18.2% to 6.6%; P=0.003), but not in high-risk individuals (from 69.9% to 64.2%; P=0.713). Conclusion: Between 2009 and 2016 the incidence of sepsis-related hospitalization increased in a general Italian hospital, with a downward trend in CFR, only limited to low-risk patients and particularly to subjects ≥80 years.


2019 ◽  
Author(s):  
Andrea Fabbri ◽  
Giulio Marchesini ◽  
Barbara Benazzi ◽  
Alice Morelli ◽  
Danilo Montesi ◽  
...  

Abstract Background The burden of sepsis represents a global health care problem. We aimed to assess the case fatality rate (CFR) and its predictors in subjects with sepsis admitted to a general Italian hospital from 2009 to 2016, stratified by risk score. Methods We performed a retrospective analysis of all sepsis-related hospitalizations after Emergency Department (ED) visit in a public Italian hospital in an 8-year period. A risk score to predict CFR was computed by logistic regression analysis of selected variables in a training set (2009-2012), and then confirmed in the whole study population. A trend analysis of CFR during the study period was performed dividing patient as high-risk (upper tertile of risk score) or low-risk . Results 2,492 subjects were included. Over time the incidental admission rate (no. of sepsis-related admissions per 100 total admissions) increased from 4.1% (2009-2010) to 5.4% (2015-2016); P<0.001, accompanied by a reduced CFR (from 38.0% to 18.4%; P<0.001). A group of 10 variables (admission in intensive care unit, cardio-vascular dysfunction, HIV infection, diabetes, age ≥80 years, respiratory diseases, number of organ dysfunction, digestive diseases, dementia and cancer) were selected by the logistic model to predict CFR with good accuracy: AUC 0.873 [0.009]. Along the years CFR decreased from 31.8% (2009-2010) to 25.0% (2015-2016); P = 0.007. The relative proportion of subjects ≥80 years (overall, 52.9% of cases) and classified as high-risk did not change along the years. CFR decreased only in low-risk subjects (from 13.3% to 5.2%; P<0.001), and particularly in those aged ≥80 (from 18.2% to 6.6%; P=0.003), but not in high-risk individuals (from 69.9% to 64.2%; P=0.713). Conclusion Between 2009 and 2016 the incidence of sepsis-related hospitalization increased in a general Italian hospital, with a downward trend in CFR, only limited to low-risk patients and particularly to subjects ≥80 years.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Andrea Fabbri ◽  
Giulio Marchesini ◽  
Barbara Benazzi ◽  
Alice Morelli ◽  
Danilo Montesi ◽  
...  

Abstract Background The burden of sepsis represents a global health care problem. We aimed to assess the case fatality rate (CFR) and its predictors in subjects with sepsis admitted to a general Italian hospital from 2009 to 2016, stratified by risk score. Methods We performed a retrospective analysis of all sepsis-related hospitalizations after Emergency Department (ED) visit in a public Italian hospital in an 8-year period. A risk score to predict CFR was computed by logistic regression analysis of selected variables in a training set (2009–2012), and then confirmed in the whole study population. A trend analysis of CFR during the study period was performed dividing patient as high-risk (upper tertile of risk score) or low-risk. Results Two thousand four hundred ninety-two subjects were included. Over time the incidental admission rate (no. of sepsis-related admissions per 100 total admissions) increased from 4.1% (2009–2010) to 5.4% (2015–2016); P < 0.001, accompanied by a reduced CFR (from 38.0 to 18.4%; P < 0.001). A group of 10 variables (admission to intensive care unit, cardio-vascular dysfunction, HIV infection, diabetes, age ≥ 80 years, respiratory diseases, number of organ dysfunction, digestive diseases, dementia and cancer) were selected by the logistic model to predict CFR with good accuracy: AUC 0.873 [0.009]. Along the years CFR decreased from 31.8% (2009–2010) to 25.0% (2015–2016); P = 0.007. The relative proportion of subjects ≥80 years (overall, 52.9% of cases) and classified as high-risk did not change along the years. CFR decreased only in low-risk subjects (from 13.3 to 5.2%; P < 0.001), and particularly in those aged ≥80 (from 18.2 to 6.6%; P = 0.003), but not in high-risk individuals (from 69.9 to 64.2%; P = 0.713). Conclusion Between 2009 and 2016 the incidence of sepsis-related hospitalization increased in a general Italian hospital, with a downward trend in CFR, only limited to low-risk patients and particularly to subjects ≥80 years.


Author(s):  
Manel Saad Saoud ◽  
Abdelhak Boubetra ◽  
Safa Attia

In the last decades, multi-agent based modeling and simulation systems have become more increasingly used to model the dynamic and the complex healthcare systems which contain many variabilities and uncertainties such as the hospital emergency departments (ED). Modeling and creating virtual societies almost identical and similar to the reality are considered as the strongest advantages of these agents systems. However, during the dynamic development of the artificial societies, a massive volume of data, which generally contains non-express and shrouded information and even knowledge, is involved. Therefore, dealing with this data, to study and to analyze the unclear relationships and the emerging phenomena, is a well-known weakness and bottleneck that the multi-agent systems is suffering from. In conjunction, data mining techniques are the most powerful tools that can help simulation experts to tackle this issue. This paper presents an ongoing research that combines the multi-agent based modeling and simulation systems and data mining techniques to develop a decision support system to improve the operation of the emergency department.


2008 ◽  
Vol 52 (4) ◽  
pp. S120
Author(s):  
V. Gai ◽  
S. Battista ◽  
C. Moiraghi ◽  
G. Genta ◽  
G. Barbato ◽  
...  

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