bayesian spatial analysis
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Vaccine ◽  
2021 ◽  
Vol 39 (8) ◽  
pp. 1349-1357
Author(s):  
Sarah E. Wilson ◽  
Andrean Bunko ◽  
Steven Johnson ◽  
Jillian Murray ◽  
Yue Wang ◽  
...  

2020 ◽  
pp. 175114372091446
Author(s):  
Philip Emerson ◽  
David R Green ◽  
Steve Stott ◽  
Graeme Maclennan ◽  
Marion K Campbell ◽  
...  

Background There is increasing evidence that access to critical care services is not equitable. We aimed to investigate whether location of residence in Scotland impacts on the risk of admission to an Intensive Care Unit and on outcomes. Methods This was a population-based Bayesian spatial analysis of adult patients admitted to Intensive Care Units in Scotland between January 2011 and December 2015. We used a Besag–York–Mollié model that allows us to make direct probabilistic comparisons between areas regarding risk of admission to Intensive Care Units and on outcomes. Results A total of 17,596 patients were included. The five-year age- and sex-standardised admission rate was 352 per 100,000 residents. There was a cluster of Council Areas in the North-East of the country which had lower adjusted admission rates than the Scottish average. Midlothian, in South East Scotland had higher spatially adjusted admission rates than the Scottish average. There was no evidence of geographical variation in mortality. Conclusion Access to critical care services in Scotland varies with location of residence. Possible reasons include differential co-morbidity burden, service provision and access to critical care services. In contrast, the probability of surviving an Intensive Care Unit admission, if admitted, does not show geographical variation.


2019 ◽  
Vol 31 (4) ◽  
Author(s):  
Reihaneh Entezari ◽  
Patrick E. Brown ◽  
Jeffrey S. Rosenthal

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