Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources
This paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is...
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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2021/8853787 |
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doaj-3a7b195b56134681ab8276fcc8f68c522021-02-15T12:52:57ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182021-01-01202110.1155/2021/88537878853787Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce ResourcesEduarda Asfora Frej0Lucia Reis Peixoto Roselli1Rodrigo José Pires Ferreira2Alexandre Ramalho Alberti3Adiel Teixeira de Almeida4Universidade Federal de Pernambuco, Av. Acadêmico Hélio Ramos, s/n-Cidade Universitária, Recife, PE CEP 50740-530, BrazilUniversidade Federal de Pernambuco, Av. Acadêmico Hélio Ramos, s/n-Cidade Universitária, Recife, PE CEP 50740-530, BrazilUniversidade Federal de Pernambuco, Av. Acadêmico Hélio Ramos, s/n-Cidade Universitária, Recife, PE CEP 50740-530, BrazilUniversidade Federal de Pernambuco, Av. Acadêmico Hélio Ramos, s/n-Cidade Universitária, Recife, PE CEP 50740-530, BrazilUniversidade Federal de Pernambuco, Av. Acadêmico Hélio Ramos, s/n-Cidade Universitária, Recife, PE CEP 50740-530, BrazilThis paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is developed in order to find the best allocation for ICU beds, considering candidate patients with suspected/confirmed COVID-19. Experts’ subjective knowledge and prior probabilities are considered to estimate the input data for the proposed model, considering the particular aspects of the decision problem. Since the chances of survival of patients in several scenarios may not be precisely defined due to the inherent subjectivity of such kinds of information, the proposed model works based on imprecise information provided by users. A Monte-Carlo simulation is performed to build a recommendation, and a robustness index is computed for each alternative according to its performance as evidenced by the results of the simulation.http://dx.doi.org/10.1155/2021/8853787 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eduarda Asfora Frej Lucia Reis Peixoto Roselli Rodrigo José Pires Ferreira Alexandre Ramalho Alberti Adiel Teixeira de Almeida |
spellingShingle |
Eduarda Asfora Frej Lucia Reis Peixoto Roselli Rodrigo José Pires Ferreira Alexandre Ramalho Alberti Adiel Teixeira de Almeida Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources Computational and Mathematical Methods in Medicine |
author_facet |
Eduarda Asfora Frej Lucia Reis Peixoto Roselli Rodrigo José Pires Ferreira Alexandre Ramalho Alberti Adiel Teixeira de Almeida |
author_sort |
Eduarda Asfora Frej |
title |
Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources |
title_short |
Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources |
title_full |
Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources |
title_fullStr |
Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources |
title_full_unstemmed |
Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources |
title_sort |
decision model for allocation of intensive care unit beds for suspected covid-19 patients under scarce resources |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2021-01-01 |
description |
This paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is developed in order to find the best allocation for ICU beds, considering candidate patients with suspected/confirmed COVID-19. Experts’ subjective knowledge and prior probabilities are considered to estimate the input data for the proposed model, considering the particular aspects of the decision problem. Since the chances of survival of patients in several scenarios may not be precisely defined due to the inherent subjectivity of such kinds of information, the proposed model works based on imprecise information provided by users. A Monte-Carlo simulation is performed to build a recommendation, and a robustness index is computed for each alternative according to its performance as evidenced by the results of the simulation. |
url |
http://dx.doi.org/10.1155/2021/8853787 |
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