Distributionally robust optimization of a Canadian healthcare supply chain to enhance resilience during the COVID-19 pandemic

Ash, Cecil; Diallo, Claver; Venkatadri, Uday; Vanberkel, Peter T.

doi:10.1016/j.cie.2022.108051

Cited by 41 publications

(20 citation statements)

References 51 publications

(65 reference statements)

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“…This infers that, e-logistics operations predict performance of health care supply chain management in the context of Uganda's public referral hospitals. These results are supported by preceding researchers whose findings depicted that, there is a positive significant relationship between e-logistics practices and performance of health care supply chain management (Alzoubi et al, 2022;Ash et al, 2022)…”

Section: Discussion and Interpretation Of The Research Findingssupporting

confidence: 83%

“…to examine e-logistics operations and health care supply chain management in the context of Uganda's public referral hospitals. Although literature there is an extensive literature on health care supply chain management (Fathollahi-Fard et al, 2022;Ash et al, 2022;Kim & Kim, 2019;Mackintosh et al, 2018), there is still limited studies on e-logistics operations and health care supply chain management, particularly in the developing countries like Uganda.…”

Section: Introductionmentioning

confidence: 99%

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E-logistic Practices and Health Care Supply Chain Management for Public Referral Hospitals in Uganda

Kagoya

Mkwizu

2022

udslj

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This paper examined e-logistic practices and health care supply chain management in the context of Ugandan public referral hospitals. The prime objective was to examine the relationship between e-logistics operations and performance of health care supply chain management. A quantitative research approach was utilized to gather data from public referral hospitals respondents using structured survey questionnaires. For data analysis, descriptive statistics and Partial Least Squares-Structural Equation Modelling were utilised, aided by SmartPLS 3. Findings showed a positive significant relationship between e-logistics operations and performance of health care supply chain management in the context of Ugandan public referral hospitals. This study implies that the key e-logistics operations in relation to the performance of health care supply chain management, are central management of drugs, the correct order picking of drugs given to the right patients for quality control, and presence of an electronic system to update stock daily. Additionally, the findings designated that, e-logistics operations are related to the performance of health care supply chain management in terms of ICTs tracking systems and data transparency. The practical implication to the health sector- stakeholders, is to consider ICT-tracking systems and data transparency for e-logistics operations and performance of health care supply chain management.

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Section: Discussion and Interpretation Of The Research Findingssupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

E-logistic Practices and Health Care Supply Chain Management for Public Referral Hospitals in Uganda

Kagoya

Mkwizu

2022

udslj

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“… Long, Nohdurft, & Spinler (2018) present a dynamic distribution planning problem to optimize both location and timing of Ebola treatment units across different geographical regions where the transmission rate depends on the number of beds allocated in each region. Ash, Diallo, Venkatadri, & VanBerkel (2022) propose a distributionally robust approach to enhance the resilience of the healthcare supply chain against demand uncertainty during the COVID-19 pandemic by minimizing the maximum proportion of unmet demand, while Baloch, Gzara, & Elhedhli (2022) suggest a robust dynamic distribution planning problem to enhance the government’s PPE supply capabilities by utilizing the idle capacity of independent service providers that arose due to the pandemic raking into account supply uncertainty. Zaric & Brandeau (2001) model an allocation problem to select a subset of interventions under the objective to minimize the number of infected cases using a simple susceptible-infected (SI) compartmental model for which a closed-form expression exists.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk-based allocation of COVID-19 personal protective equipment under supply shortages

Baloch

Gzara

Elhedhli

2023

European Journal of Operational Research

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“…Also, medical employees and field and backup hospitals upgraded the system's resilience. Ash et al ( 2022 ) developed a robust multi-objective multi-period framework for distribution optimization to boost the supply chains' resiliency of personal protective equipment (PPE) against disturbances induced by pandemic diseases, inspired by challenges facing a healthcare supplier in a province of Canada over the COVID-19 epidemic disease. Specifying demand, cost, and supply as undetermined parameters, they produced effective solutions along a trade-off between maximizing service rank and minimizing cost by the -constraint strategy.…”

Section: Related Literaturementioning

confidence: 99%

Resilient and social health service network design to reduce the effect of COVID-19 outbreak

2023

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With the severe outbreak of the novel coronavirus (COVID-19), researchers are motivated to develop efficient methods to face related issues. The present study aims to design a resilient health system to offer medical services to COVID-19 patients and prevent further disease outbreaks by social distancing, resiliency, cost, and commuting distance as decisive factors. It incorporated three novel resiliency measures (i.e., health facility criticality, patient dissatisfaction level, and dispersion of suspicious people) to promote the designed health network against potential infectious disease threats. Also, it introduced a novel hybrid uncertainty programming to resolve a mixed degree of the inherent uncertainty in the multi-objective problem, and it adopted an interactive fuzzy approach to address it. The actual data obtained from a case study in Tehran province in Iran proved the strong performance of the presented model. The findings show that the optimum use of medical centers’ potential and the corresponding decisions result in a more resilient health system and cost reduction. A further outbreak of the COVID-19 pandemic is also prevented by shortening the commuting distance for patients and avoiding the increasing congestion in the medical centers. Also, the managerial insights show that establishing and evenly distributing camps and quarantine stations within the community and designing an efficient network for patients with different symptoms result in the optimum use of the potential capacity of medical centers and a decrease in the rate of bed shortage in the hospitals. Another insight drawn is that an efficient allocation of the suspect and definite cases to the nearest screening and care centers makes it possible to prevent the disease carriers from commuting within the community and increase the coronavirus transmission rate.

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Distributionally robust optimization of a Canadian healthcare supply chain to enhance resilience during the COVID-19 pandemic

Cited by 41 publications

References 51 publications

E-logistic Practices and Health Care Supply Chain Management for Public Referral Hospitals in Uganda

E-logistic Practices and Health Care Supply Chain Management for Public Referral Hospitals in Uganda

Risk-based allocation of COVID-19 personal protective equipment under supply shortages

Resilient and social health service network design to reduce the effect of COVID-19 outbreak

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