Key info
Date:
10 December 2020
Authors:
Josh C. D’Aeth, Shubhechyya Ghosal, Fiona Grimm, David Haw, Esma Koca, Krystal Lau, Stefano Moret, Dheeya Rizmie, Sarah Deeny, Pablo N. Perez-Guzman, Neil Ferguson, Katharina Hauck, Peter C Smith, Wolfram Wiesemann, Giovanni Forchini, Marisa Miraldo
1Correspondence:
m.miraldo@imperial.ac.uk
WHO Collaborating Centre for Infectious Disease Modelling, MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), in collaboration with the Imperial College Business School, The Health Foundation and Umeå University.
Now published in Nature Computational Science; 13-08-2021. doi: https://doi.org/10.1038/s43588-021-00111-1
Summary
Countries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care.
We developed a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750-5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries &poisoning.
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- Italiano - Italian
- Arabic - العربية
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