Resource allocation in ICU

McGuire, Andrew; McConnell, Paul

doi:10.1097/aco.0000000000000688

Cited by 12 publications

(4 citation statements)

References 13 publications

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“…Consequently, health professionals must work together for an optimal transfer of patients between hospital departments. [92] also discuss fairness and ethics in the ICU allocation problem, suggesting that an alliance of ethical and moral principles must be applied to obtain a moral, ethical, and common-sense approach to deal with this complex problem. This review demonstrates that the ICU allocation problem is not a trivial decision problem, first, because the scarcity of resources for intensive care cannot be overcome quickly because the cost of doing so is very high and there are shortages of appropriately qualified and experienced personnel and, secondly, because the no allocation of a place in an ICU in some cases is likely to increase the probability that the patient will die.…”

Section: Resultsmentioning

confidence: 99%

Bed Allocation Optimization Based on Survival Analysis, Treatment Trajectory and Costs Estimations

Karboub

Tabaa

2023

IEEE Access

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The intensive care units are a key element of patient flow, but due to high demand and an alternating rate of arriving patients, these units are often challenged by insufficient capacity, very high expenses, and in some cases, an unfair distribution of resources. Proper allocation of resources to match demand is, therefore, a vital task for many wards in these units. The patient bed assignment problem consists of managing in the best possible way a set of beds with equipment to be assigned to a particular type of patient. However, in real-world scenarios, constraints like a possible treatment trajectory are violated in most cases. In this paper, we present a new approach for solving patient bed assignment problems constrained by targets on survival function estimation, cost estimation, and possible treatment trajectory estimation for patients with cardiovascular diseases. For survival function estimations, we used the nave estimator and Kaplan-Meier, and for treatment effect estimations, we used logistic regression and T-learning. Estimations of the three components are used as weights in a genetic algorithm. This technique allows for the consideration of various constraints, which, unlike other techniques, allows for the selection of dominant solutions as solutions that satisfy dominant constraints. In addition, we demonstrate the robustness of our approach by testing the algorithms with multiple classes of patients, testing multiple sets of parameters, and comparing our results with several similar research studies showing the added value of working on this management axis in hospitals using the new approach to bed allocation.

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Section: Resultsmentioning

confidence: 99%

Bed Allocation Optimization Based on Survival Analysis, Treatment Trajectory and Costs Estimations

Karboub

Tabaa

2023

IEEE Access

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“…35 The guidelines are based on well-established literature. 22,36,37 The planner helps inform choices in the preparation of hospitals for the pandemic. The current format has been chosen to make it as widely usable as possible, requiring minimal inputs, assumptions, and technical expertise from the user.…”

Section: Discussionmentioning

confidence: 99%

“…Policies need to be assessed carefully with respect to existing guidelines, such as those published by the World Health Organization,32,33 the African Federation for Emergency Medicine,34 the UK National Institute for Health and Care Excellence in preparation for the COVID-19 pandemic,21 or those of the Società Italiana di Anestesia Analgesia Rianimazione e Terapia Intensiva in Italy 35. The guidelines are based on well-established literature 22,36,37…”

Section: Discussionmentioning

confidence: 99%

The J-IDEA Pandemic Planner

Christen¹,

D'Aeth²,

Løchen³

et al. 2021

Medical Care

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Background: Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for COVID-19, while retaining capacity for other emergency conditions, is one of the most challenging tasks faced by health care providers and policymakers during the pandemic. Health systems must be well-prepared to cope with large and sudden changes in demand by implementing interventions to ensure adequate access to care. We developed the first planning tool for the COVID-19 pandemic to account for how hospital provision interventions (such as cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affect the capacity of hospitals to provide life-saving care. Methods: We conducted a review of interventions implemented or considered in 12 European countries in March to April 2020, an evaluation of their impact on capacity, and a review of key parameters in the care of COVID-19 patients. This information was used to develop a planner capable of estimating the impact of specific interventions on doctors, nurses, beds, and respiratory support equipment. We applied this to a scenario-based case study of 1 intervention, the setup of field hospitals in England, under varying levels of COVID-19 patients. Results: The Abdul Latif Jameel Institute for Disease and Emergency Analytics pandemic planner is a hospital planning tool that allows hospital administrators, policymakers, and other decision-makers to calculate the amount of capacity in terms of beds, staff, and crucial medical equipment obtained by implementing the interventions. Flexible assumptions on baseline capacity, the number of hospitalizations, staff-to-beds ratios, and staff absences due to COVID-19 make the planner adaptable to multiple settings. The results of the case study show that while field hospitals alleviate the burden on the number of beds available, this intervention is futile unless the deficit of critical care nurses is addressed first. Discussion: The tool supports decision-makers in delivering a fast and effective response to the pandemic. The unique contribution of the planner is that it allows users to compare the impact of interventions that change some or all inputs.

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“…In the study performed by Oerlemans et al (2015), a collective responsibility has been suggested to alleviate moral distress caused by ethical dilemmas faced in ICU allocation problem. On the other hand, McGuire & McConnell (2019) suggested that ethical and moral principles should be considered to obtain a common-sense to deal with this complex problem.…”

Section: Literature Review Concerning Screening and Triage Decision-m...mentioning

confidence: 99%

Methodology to Support the Triage of Suspected COVID-19 Patients in Resource-Limited Circumstances

Alberti

Frej

Roselli

et al. 2022

International Journal of Decision Support System Technology

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COVID-19 pandemic has put health systems worldwide under pressure. Thus, establish a triage protocol to support the allocation of resources is important to deal with this public health crisis. In this paper, a structured methodology to support the triage of suspected or confirmed COVID-19 patients has been proposed, based on the utilitarian principle. A decision model has been proposed for evaluating three treatment alternatives: intensive care, hospital stay and home isolation. The model is developed according to multi-attribute utility theory and considers two criteria: the life of the patient and the overall cost to the health system. A screening protocol is proposed to support the use of the decision model, and a method is presented for calculating the probability of which of three treatment is the best one. The proposed methodology was implemented in an information and decision system. The originality of this study is using of the multi-attribute utility theory to support the triage of suspected COVID-19 and implement the decision model in an information and decision system.

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Resource allocation in ICU

Cited by 12 publications

References 13 publications

Bed Allocation Optimization Based on Survival Analysis, Treatment Trajectory and Costs Estimations

Bed Allocation Optimization Based on Survival Analysis, Treatment Trajectory and Costs Estimations

The J-IDEA Pandemic Planner

Methodology to Support the Triage of Suspected COVID-19 Patients in Resource-Limited Circumstances

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