General Public Preferences for Allocating Scarce Medical Resources During COVID-19

Huseynov, Samir; Palma, Marco A.; Nayga, Rodolfo M.

doi:10.3389/fpubh.2020.587423

Cited by 13 publications

(21 citation statements)

References 19 publications

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“…Participants did not consider age <80 to be a deciding factor in resource allocation. However, a study on the general public in the US reported that participants favored allocating more ventilators to patients of younger age groups ( 10 ). This conforms with the current proposed guidelines that prioritize younger patients to receive scarce medical resources ( 9 , 12 , 13 ).…”

Section: Discussionmentioning

confidence: 99%

“…The proposed principles for resource allocation could become controversial in the eyes of the public. Even the seemingly most holistic approaches for resource allocation proposed by healthcare systems could result in inequalities among patients ( 10 ). This could raise serious concerns about their fairness and result in loss of public trust in health care systems.…”

Section: Introductionmentioning

confidence: 99%

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Public Opinion on Priorities Toward Fair Allocation of Ventilators During COVID-19 Pandemic: A Nationwide Survey

Abbasi‐Kangevari

Arshi

Hassanian‐Moghaddam

et al. 2021

Front. Public Health

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Background: The rapidly growing imbalance between supply and demand for ventilators during the COVID-19 pandemic has highlighted the principles for fair allocation of scarce resources. Failing to address public views and concerns on the subject could fuel distrust. The objective of this study was to determine the priorities of the Iranian public toward the fair allocation of ventilators during the COVID-19 pandemic.Methods: This anonymous community-based national study was conducted from May 28 to Aug 20, 2020, in Iran. Data were collected via the Google Forms platform, using an online self-administrative questionnaire. The questionnaire assessed participants' assigned prioritization scores for ventilators based on medical and non-medical criteria. To quantify participants' responses on prioritizing ventilator allocation among sub-groups of patients with COVID-19 who need mechanical ventilation scores ranging from −2, very low priority, to +2, very high priority were assigned to each response.Results: Responses of 2,043 participants, 1,189 women, and 1,012 men, were analyzed. The mean (SD) age was 31.1 (9.5), being 32.1 (9.3) among women, and 29.9 (9.6) among men. Among all participants, 274 (13.4%) were healthcare workers. The median of assigned priority score was zero (equal) for gender, age 41–80, nationality, religion, socioeconomic, high-profile governmental position, high-profile occupation, being celebrities, employment status, smoking status, drug abuse, end-stage status, and obesity. The median assigned priority score was +2 (very high priority) for pregnancy, and having <2 years old children. The median assigned priority score was +1 (high priority) for physicians and nurses of patients with COVID-19, patients with nobel research position, those aged <40 years, those with underlying disease, immunocompromise status, and malignancy. Age>80 was the only factor participants assigned −1 (low priority) to.Conclusions: Participants stated that socioeconomic factors, except for age>80, should not be involved in prioritizing mechanical ventilators at the time of resources scarcity. Front-line physicians and nurses of COVID-19 patients, pregnant mothers, mothers who had children under 2 years old were given high priority.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Public Opinion on Priorities Toward Fair Allocation of Ventilators During COVID-19 Pandemic: A Nationwide Survey

Abbasi‐Kangevari

Arshi

Hassanian‐Moghaddam

et al. 2021

Front. Public Health

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“…The societal distribution of limited goods, such as medical resources and especially vaccines, is a social challenge that warrants research attention (Grover, McClelland, and Furnham 2020;Huseynov, Palma, and Nayga 2020;Ratcliffe 2000). The prioritization of vaccination is a hotly debated public issue as the world faces the threat of a global pandemic in early 2021.…”

Section: Adm Systems In Prioritization Of the Coronavirus Vaccine Dis...mentioning

confidence: 99%

Using automated decision-making (ADM) to allocate Covid-19 vaccinations? Exploring the roles of trust and social group preference on the legitimacy of ADM vs. human decision-making

Lünich,

Kieslich

2021

Preprint

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In combating the ongoing global health threat of the Covid-19 pandemic, decision-makers have to take actions based on a multitude of relevant health data with severe potential consequences for the affected patients. Because of their presumed advantages in handling and analyzing vast amounts of data, computer systems of automated decision-making (ADM) are implemented and substitute humans in decision-making processes. In this study, we focus on a specific application of ADM in contrast to human decision-making (HDM), namely the allocation of Covid-19 vaccines to the public. In particular, we elaborate on the role of trust and social group preference on the legitimacy of vaccine allocation. We conducted a survey with a 2x2 randomized factorial design among n=1602 German respondents, in which we utilized distinct decision-making agents (HDM vs. ADM) and prioritization of a specific social group (teachers vs. prisoners) as design factors. Our findings show that general trust in ADM systems and preference for vaccination of a specific social group influence the legitimacy of vaccine allocation. However, contrary to our expectations, trust in the agent making the decision did not moderate the link between social group preference and legitimacy. Moreover, the effect was also not moderated by the type of decision-maker (human vs. algorithm). We conclude that trustworthy ADM systems must not necessarily lead to the legitimacy of ADM systems.K eywords automated decision-making • trust • social group preference • Covid-19 • legitimacy • public opinion

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“…Favoring young patients (youngest first) was the outcome of an online survey completed by 586 US participants. The aim was to elicit the general public preferences to allocate ventilators for COVID-19 patients ( 25 ). This result is consistent with the proposed guiding ethical principles by Emanuel et al ( 19 ), summarized in treating patients equally, prioritizing the worst-off, and maximizing social and individual benefits.…”

Section: Introductionmentioning

confidence: 99%

Whom Should Be Saved? A Proposed Ethical Framework for Allocating Scarce Medical Resources to COVID-19 Patients Using Fuzzy Logic

Saadeh

Almobaideen

2021

Front. Med.

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COVID-19 is a global pandemic that affected the everyday life activities of billions around the world. It is an unprecedented crisis that the modern world had never experienced before. It mainly affected the economic state and the health care system. The rapid and increasing number of infected patients overwhelmed the healthcare infrastructure, which causes high demand and, thus, shortage in the required staff members and medical resources. This shortage necessitates practical and ethical suggestions to guide clinicians and medical centers when allocating and reallocating scarce resources for and between COVID-19 patients. Many studies proposed a set of ethical principles that should be applied and implemented to address this problem. In this study, five different ethical principles based on the most commonly recommended principles and aligned with WHO guidelines and state-of-the-art practices proposed in the literature were identified, and recommendations for their applications were discussed. Furthermore, a recent study highlighted physicians' propensity to apply a combination of more than one ethical principle while prioritizing the medical resource allocation. Based on that, an ethical framework that is based on Fuzzy inference systems was proposed. The proposed framework's input is the identified ethical principles, and the output is a weighted value (per patient). This value can be used as a rank or a priority factor given to the patients based on their condition and other relevant information, like the severity of their disease status. The main idea of implementing fuzzy logic in the framework is to combine more than one principle when calculating the weighted value, hence mimicking what some physicians apply in practice. Moreover, the framework's rules are aligned with the identified ethical principles. This framework can help clinicians and guide them while making critical decisions to allocate/reallocate the limited medical resources during the current COVID-19 crisis and future similar pandemics.

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General Public Preferences for Allocating Scarce Medical Resources During COVID-19

Cited by 13 publications

References 19 publications

Public Opinion on Priorities Toward Fair Allocation of Ventilators During COVID-19 Pandemic: A Nationwide Survey

Public Opinion on Priorities Toward Fair Allocation of Ventilators During COVID-19 Pandemic: A Nationwide Survey

Using automated decision-making (ADM) to allocate Covid-19 vaccinations? Exploring the roles of trust and social group preference on the legitimacy of ADM vs. human decision-making

Whom Should Be Saved? A Proposed Ethical Framework for Allocating Scarce Medical Resources to COVID-19 Patients Using Fuzzy Logic

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