Choosing who shall not be treated in the NHS

Charny, Mark; Lewis, Peter; Farrow, Scott

doi:10.1016/0277-9536(89)90352-3

Cited by 97 publications

(51 citation statements)

References 11 publications

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“…The evidence base reviewed demonstrated that health gain, and the level of health gain, is an important consideration for respondents when eliciting preferences for the allocation of health-care resources (e.g. Charny et al, 1989;Bowling, 1996;Cookson and Dolan, 1999;Edwards et al, 2003). While this attribute is linked with the attribute of 'value for money', it is clear from the empirical literature reviewed, and from the literature around the cost-effectiveness of health technologies, that it is possible to have different levels of health improvement, at any of the levels used for value for money.…”

Section: Improvement In Healthmentioning

confidence: 99%

Exploring the social value of health‐care interventions: a stated preference discrete choice experiment

2008

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SUMMARYMuch of the literature on distributive preferences covers specific considerations in isolation, and recent reviews have suggested that research is required to inform on the relative importance of various key considerations. Responding to this research recommendation, we explore the distributive preferences of the general public using a set of generic social value judgments. We report on a discrete choice experiment (DCE) survey, using face-to-face interviews, in a sample of the general population (n 5 259). The context for the survey was resource allocation decisions in the UK National Health Service, using the process of health technology appraisal as an example. The attributes used covered health improvement, value for money, severity of health, and availability of other treatments, and it is the first such survey to use cost-effectiveness in scenarios described to the general public. Results support the feasibility and acceptability of the DCE approach for the elicitation of public preferences. Choice data are used to consider the relative importance of changes across attribute levels, and to model utility scores and relative probabilities for the full set of combinations of attributes and levels in the experimental design used (n 5 64). Results allow the relative social value of health technology scenarios to be explored. Findings add to a sparse literature on 'social' preferences, and show that DCE data can be used to consider the strength of preference over alternative scenarios in a prioritysetting context.

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Section: Improvement In Healthmentioning

confidence: 99%

Exploring the social value of health‐care interventions: a stated preference discrete choice experiment

2008

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“…However, most studies suggest that health gains to the old are weighted less. Respondents to a number of studies want to give lower priority to older people [30][31][32][33][34][35][36]. Browning and Thomas found that the age of a potential recipient of a donor organ was as important a consideration as their prognosis [37].…”

Section: Qaly Maximisationmentioning

confidence: 99%

“…For example, a person who has family or friends who are dependent upon them might be given priority over someone else that does not. There is evidence that people wish to discriminate in favour of those with dependents, particularly young children [32,36,37,51,56,58]. Edwards and colleagues present an exception to this general consensus, and found that respondents did not want to prioritise those with dependents [57].…”

Section: Qaly Maximisationmentioning

confidence: 99%

QALY maximisation and people's preferences: a methodological review of the literature

et al. 2004

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SummaryIn cost-utility analysis, the numbers of quality-adjusted life years (QALYs) gained are aggregated according to the sum-ranking (or QALY maximisation) rule. This requires that the social value from health improvements is a simple product of gains in quality of life, length of life and the number of persons treated. The results from a systematic review of the literature suggest that QALY maximisation is descriptively flawed. Rather than being linear in quality and length of life, it would seem that social value diminishes in marginal increments of both. And rather than being neutral to the characteristics of people other than their propensity to generate QALYs, the social value of a health improvement seems to be higher if the person has worse lifetime health prospects and higher if that person has dependents. In addition, there is a desire to reduce inequalities in health. However, there are some uncertainties surrounding the results, particularly in relation to what might be affecting the responses, and there is the need for more studies of the general public that attempt to highlight the relative importance of various key factors. Copyright

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“…There have been other studies across a range of different contexts which have demonstrated a broadly similar set of public preferences; that is, to discriminate in favour of the young and those with dependants, and to discriminate against those who are considered to be in some way responsible for their ill health [7,8]. However, we are not aware of any studies that have looked specifically at kidney transplantation.…”

Section: Introductionmentioning

confidence: 96%

A note on a discussion group study of public preferences regarding priorities in the allocation of donor kidneys

Dolan

Shaw

2004

Health Policy

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Objective: To explore whether and how people wish to give differential priority based on certain characteristics of the potential recipient of a donor kidney. Design: A random sample of people resident in York was invited to attend two focus group meetings each, a fortnight apart. Setting: The City of York. Participants: Twenty-three randomly chosen people meeting in four groups of five or six. Main outcome measures: Those factors that people think should be taken into account when allocating donor kidneys, in addition to the expected benefits from transplantation. Results: People are willing and able to distinguish between potential recipients of a kidney transplantation according to a range of characteristics beyond the expected benefits from treatment. There is a clear consensus across the four groups that one of the most important considerations is what will happen to the patient without treatment, and so priority is given to those with a poor prognosis. There is also a strong view that priority should be given to younger patients and to those with dependants. The time spent waiting for a transplant is also important, but less so. Conclusions: A sample of the general public, after discussion and debate, wish to take account of a number of patient characteristics when allocating donor kidneys. There is some degree of consensus about what these factors should be and this suggests that it might be possible to develop a set of guidelines for the allocation of donor kidneys.

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Choosing who shall not be treated in the NHS

Cited by 97 publications

References 11 publications

Exploring the social value of health‐care interventions: a stated preference discrete choice experiment

Exploring the social value of health‐care interventions: a stated preference discrete choice experiment

QALY maximisation and people's preferences: a methodological review of the literature

A note on a discussion group study of public preferences regarding priorities in the allocation of donor kidneys

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