How to Allocate Scarce Health Resources Without Discriminating Against People With Disabilities

John, Tyler M.; Millum, Joseph; Wasserman, David

doi:10.1017/s0266267116000237

Cited by 19 publications

(11 citation statements)

References 39 publications

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“…The “double jeopardy” argument [ 47 ] states that those with “very poor quality of life” not only suffer from their condition but also receive lower priority for life-saving treatment compared to perfectly healthy individuals. Singer et al [ 48 ] objected to this argument in that if “the treatment can be given to only one patient, a rational egoist choosing from behind a veil of ignorance would choose to give the treatment to the patient who will gain more from it.” However, this reply was challenged by John et al [ 49 ], who pointed out the underlying “simple utilitarian social welfare function.” Instead, John et al [ 49 ] suggested considering not only the gain in QALYs but also wellbeing over a lifetime. Accounting for the latter would favor operative procedures given that the median age of operation in Germany is approximately 60 years ([ 25 ], p. 427), which is lower than the median age of death of a COVID-19 patient during the first wave (82 years) [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

COVID-19 and the forgone health benefits of elective operations

Gandjour

2022

BMC Health Serv Res

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Background and aim The first SARS-CoV-2 pandemic wave in Germany involved a tradeoff between saving the lives of COVID-19 patients by providing sufficient intensive care unit (ICU) capacity and foregoing the health benefits of elective procedures. This study aims to quantify this tradeoff. Methods The analysis is conducted at both the individual and population levels. The analysis calculates quality-adjusted life years (QALYs) to facilitate a comparison between the health gains from saving the lives of COVID-19 patients in the ICU and the health losses associated with postponing operative procedures. The QALYs gained from saving the lives of COVID-19 patients are calculated based on both the real-world ICU admissions and deaths averted from flattening the first wave. Scenario analysis was used to account for variation in input factors. Results At the individual level, the resource-adjusted QALY gain of saving one COVID-19 life is predicted to be 3 to 15 times larger than the QALY loss of deferring one operation (the average multiplier is 9). The real-world QALY gain at the population level is estimated to fall within the range of the QALY loss due to delayed procedures. The modeled QALY gain by flattening the first wave is 3 to 31 times larger than the QALY loss due to delayed procedures (the average multiplier is 17). Conclusion During the first wave of the pandemic, the resource-adjusted health gain from treating one COVID-19 patient in the ICU was found to be much larger than the health loss from deferring one operation. At the population level, flattening the first wave led to a much larger health gain than the health loss from delaying operative procedures.

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Section: Discussionmentioning

confidence: 99%

COVID-19 and the forgone health benefits of elective operations

Gandjour

2022

BMC Health Serv Res

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“…Owili [ 52 ] and Sun [ 53 ] analyzed the impact of professionals and health care system reform on the allocation of health resources in Kenya and China using a structural equation model. Pinho [ 54 ] and John [ 55 ] critically analyzed the cost-effectiveness analysis (CEA) approach and further proposed novel solutions that do not discriminate against people with disabilities.…”

Section: Literature Reviewmentioning

confidence: 99%

Geographical Pattern Evolution of Health Resources in China: Spatio-Temporal Dynamics and Spatial Mismatch

et al. 2022

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(1) Background: The rational allocation of limited medical resources is the premise of safeguarding the public health. Especially since the outbreak of COVID-19, the evolution dynamics and spatial mismatch of medical resources have been a focal and frontier issue in academic discussions. (2) Methods: Based on the competitive state model and spatial mismatch index, this paper uses GIS and Geodetector spatial analysis methods and three typical indicators of hospitals, doctors, and beds to conduct an empirical study on the evolutionary characteristics and degree of mismatch in the geographic pattern of health resources in China from 2010 to 2020 (the data are from official publications issued by the National Bureau of statistics in China), in two dimensions of resource supply (economic carrying capacity) and demand (potential demand or need of residents). (3) Results: The spatial pattern of health resources at the provincial level in China has been firmly established for a long time, and the children and elderly population, health care government investment, and service industry added value are the key factors influencing the geographical distribution of health resources. The interaction between the different influence factors is dominated by bifactor enhancement, and about 30–40% of the factor pairs are in a nonlinear enhancement relationship. Hospital, doctor, and bed evolution trends and the magnitude and speed of their changes vary widely in spatial differentiation, but all are characterized by a high level of geographic agglomeration, heterogeneity, and gradient. Dynamic matching is the mainstream of development, while the geographical distribution of negative and positive mismatch shows strong spatial agglomeration and weak spatial autocorrelation. The cold and hot spots with evolution trend and space mismatch are highly clustered, shaping a center-periphery or gradient-varying spatial structure. (4) Conclusions: Despite the variability in the results of the analyses by different dimensions and indicators, the mismatch of health resources in China should not be ignored. According to the mismatch types and change trend, and following the geographic differentiation and spatial agglomeration patterns, this paper constructs a policy design framework of “regionalized governance-classified management”, in line with the concept of spatial adaptation and spatial justice, in order to provide a decision making basis for the government to optimize the allocation of health resources and carry out health spatial planning.

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“…The United States National Council on Disability has called for a moratorium on the use of QALYs in decision-making for Medicare and Medicaid (public health insurance programs) on the grounds that QALYs devalue interventions that extend the lives of people with disabilities and that mitigate the impact of disability on health [8]. Compared to interventions provided to people without disabilities, those provided to people with disabilities generate fewer future QALYs, thus driving discriminatory policies that may deprioritize people with disabilities [9]. This discrimination is exacerbated by the general practice of having people without disabilities participate in the assignment of QALYs, as people without a particular disability rate their expected quality of life with the disability as lower than do people living with that disability [10].…”

Section: Personalization and The Patientmentioning

confidence: 99%

Moving to Personalized Medicine Requires Personalized Health Plans

Powell¹,

Dolan²

2022

J Particip Med

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When individuals, families, and employers select health plans in the United States, they are typically only shown the financial structure of the plans and their provider networks. This variation in financial structure can lead patients to have health plans aligned with their financial needs, but not with their underlying nonfinancial preferences. Compounding the challenge is the fact that managed care organizations have historically used a combination of population-level budget impact models, cost-effectiveness analyses, medical necessity criteria, and current medical consensus to make coverage decisions. This approach to creating and presenting health plan options does not consider heterogeneity in patient and family preferences and values, as it treats populations as uniform. Similarly, it does not consider that there are some situations in which patients are price-insensitive. We seek to highlight the challenges posed by presenting health plans to patients in strictly financial terms, and to call for more consideration of nonfinancial patient preferences in the health plan design and selection process.

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How to Allocate Scarce Health Resources Without Discriminating Against People With Disabilities

Cited by 19 publications

References 39 publications

COVID-19 and the forgone health benefits of elective operations

COVID-19 and the forgone health benefits of elective operations

Geographical Pattern Evolution of Health Resources in China: Spatio-Temporal Dynamics and Spatial Mismatch

Moving to Personalized Medicine Requires Personalized Health Plans

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