Ambulance Diversion and Lost Hospital Revenues

2006 ◽  
Vol 48 (6) ◽  
pp. 702-710 ◽  
Author(s):  
K. John McConnell ◽  
Christopher F. Richards ◽  
Mohamud Daya ◽  
Cody C. Weathers ◽  
Robert A. Lowe
BMJ ◽  
1900 ◽  
Vol 2 (2064) ◽  
pp. 199-199
Author(s):  
T. Holmes
Keyword(s):  

2011 ◽  
Vol 19 (3) ◽  
pp. 573-580 ◽  
Author(s):  
Raquel Silva Bicalho Zunta ◽  
Valéria Castilho

This study aimed to: estimate the billing of nursing procedures at an intensive care unit and calculate how much of total ICU revenues are generated by nursing. An exploratory-descriptive, documentary research with a quantitative approach was carried out. The study was performed at a general ICU of a private hospital in the city of Sao Paulo. The sample consisted of 159 patients. It was concluded that the nursing procedures were responsible for 15.1% of total ICU revenues, which breaks down to an average 11.3% of revenues coming from nursing prescriptions and 3.8% from medical prescriptions. Demonstrating how much nursing contributes to hospital revenues is essential information for nursing managers, as it is an important argument to obtain resources and guarantee safe care.


Author(s):  
Abey Kuruvilla ◽  
Suraj M. Alexander ◽  
Xiaolin Li

This research effort is undertaken to determine the impact that one hospital’s diversion status has on other hospitals in a region and the strength of these interactions. The conditional probability of one hospital going on diversion given that another is already on diversion is evaluated. Based on this analysis, the strength of interactions among the hospitals is established. Through statistical analyses of historical data, the strength of the mutual effects of diversion among a collection of hospitals is determined. These effects are mutual if one hospital’s diversion status affected another’s, then the reverse was also true. The intensity of these interactions between hospitals is varied, some being stronger than others. The model illustrates an approach to studying the cascading effects of diversion among hospitals in a region. This is important, because the status of any hospital in a region can signal the likelihood of impending diversion in every other hospital in the region. This allows actions that might prevent the occurrence of diversion or mitigate the cascading effects of Emergency Medical Systems diversion.


Author(s):  
Abey Kuruvilla ◽  
Suraj M. Alexander ◽  
Xiaolin Li

This research effort is undertaken to determine the impact that one hospital’s diversion status has on other hospitals in a region and the strength of these interactions. The conditional probability of one hospital going on diversion given that another is already on diversion is evaluated. Based on this analysis, the strength of interactions among the hospitals is established. Through statistical analyses of historical data, the strength of the mutual effects of diversion among a collection of hospitals is determined. These effects are mutual if one hospital’s diversion status affected another’s, then the reverse was also true. The intensity of these interactions between hospitals is varied, some being stronger than others. The model illustrates an approach to studying the cascading effects of diversion among hospitals in a region. This is important, because the status of any hospital in a region can signal the likelihood of impending diversion in every other hospital in the region. This allows actions that might prevent the occurrence of diversion or mitigate the cascading effects of Emergency Medical Systems diversion.


BMJ ◽  
2013 ◽  
Vol 346 (apr11 2) ◽  
pp. f2311-f2311
Author(s):  
M. McCarthy
Keyword(s):  

2011 ◽  
Vol 57 (7) ◽  
pp. 1300-1319 ◽  
Author(s):  
Sarang Deo ◽  
Itai Gurvich
Keyword(s):  

2005 ◽  
Vol 46 (3) ◽  
pp. 40-41 ◽  
Author(s):  
A. Al Darrab ◽  
C.M. Fernandes ◽  
A. Worster ◽  
K. Woolfrey ◽  
S. Moneta
Keyword(s):  

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