Background: The use of quality-adjusted life years rests on the assertion that the objective of the health care system is to improve health.
Aim: To elicit the views of expert stakeholders on the purpose and evaluation of supportive end of life care, and explore how different purposes of end of life care imply the need for different evaluative frameworks.
Design:Semi-structured qualitative interviews, analysed through an economic lens using a constant comparative approach.
Participants: Twenty professionals working in or visiting the United Kingdom or Republic of Ireland, with clinical experience and/or working as academics in health-related disciplines.
Results: Four purposes of end of life care were identified from and are critiqued with the aid of the qualitative data: to improve health, to enable patients to die in their preferred place, to enable the patient to experience a good death, and to enable the patient to experience a good death, and those who are close to the patient to have an experience which is as free as possible from fear, stress and distress.
Conclusion: Managing symptoms and reducing anxiety were considered to be core objectives of end of life care and fit with the wider health service objective of improving/maximising health. A single objective across the entire health system ensures consistency in the way that resource allocation is informed across that entire system. However, the purpose of care at the end of life is more complex, encompassing diverse and patient-centred objectives which we have interpreted as enabling the patient to experience a good death.
BACKGROUND: Guidelines for economic evaluations often request that costs and outcomes beyond the patient are captured; this can include carers and also other affected parties. End-of-life care is one context where impacts of care spill over onto those other than patients, but there is little evidence about who should be included within economic evaluations.
OBJECTIVE: The purpose of this article was to examine (1) how many people are close to those at the end of life (2); their characteristics; and (3) what influences the network size at the end of life.
METHODS: In-depth interviews were conducted with 23 participants who were either recently bereaved or had somebody close to them currently receiving end-of-life care. Interviews were used in conjunction with hierarchical mapping to explore the network size and composition and influences upon these networks. Interviews were transcribed verbatim. Descriptive statistics were used to analyse the hierarchical maps and this information was combined with a constant comparative analysis of the qualitative data.
RESULTS: On average, close-person networks at the end of life contained eight individuals, three of whom were rated as being 'closest'. These were typically family members, although in a small number of cases non-family members were included amongst the closest individuals. There was variation in terms of network composition. Qualitative analyses revealed two key influences on network size: death trajectory (those with cognitive problems/diseases towards the end of life had smaller networks) and family size (larger families had larger networks).
CONCLUSIONS: The findings of this article have important implications for researchers wishing to include those affected by end-of-life care in an economic evaluation. Focussing on the three closest individuals would be a key starting point for economists seeking to capture spill-overs, whilst a truly societal perspective would require looking beyond proximal family members. This article further discusses the implications of including close persons in economic evaluations for decision makers.
BACKGROUND: Values used in economic evaluation are typically obtained from the general public, which is problematic when measures are to be used with people experiencing a life-course stage such as the end of life.
OBJECTIVE: To assess the feasibility of obtaining values for the ICECAP-Supportive Care Measure (SCM) from patients receiving advanced supportive care through a hospice.
METHODS: Participants completed eight best-worst scaling questions in a think-aloud interview to explain choices in different hypothetical end-of-life scenarios. Three independent raters identified errors in completion of the best-worst scaling task, and thematic analysis of associated qualitative data was undertaken to explore task difficulty and choices.
RESULTS: Twelve hospice patients were recruited. Most were able to complete the task and prioritise aspects of supportive care with either no difficulty (n=50%) or difficulty in just one of the eight scenarios (n=25%). Two patients (n=17%) were unable to comprehend the hypothetical nature of the task. The qualitative data confirmed there was good engagement with the task and identified the importance the respondents attached to maintaining dignity.
CONCLUSION: The findings suggest that people at the end of life will be able to complete a short, interviewer-administered, best-worst scaling task. To maximise engagement, it is recommended that the task is short and initiated with an example. Scenarios are best presented on show-cards in large print. A full evaluation of the ICECAP-SCM with those at the end of life is feasible.
BACKGROUND: The goal of Palliative Day Services is to provide holistic care that contributes to the quality of life of people with life-threatening illness and their families. Quality indicators provide a means by which to describe, monitor and evaluate the quality of Palliative Day Services provision and act as a starting point for quality improvement. However, currently, there are no published quality indicators for Palliative Day Services.
AIM: To develop and provide the first set of quality indicators that describe and evaluate the quality of Palliative Day Services.
DESIGN AND SETTING: A modified Delphi technique was used to combine best available research evidence derived from a systematic scoping review with multidisciplinary expert appraisal of the appropriateness and feasibility of candidate indicators. The resulting indicators were compiled into 'toolkit' and tested in five UK Palliative Day Service settings.
RESULTS: A panel of experts independently reviewed evidence summaries for 182 candidate indicators and provided ratings on appropriateness, followed by a panel discussion and further independent ratings of appropriateness, feasibility and necessity. This exercise resulted in the identification of 30 indicators which were used in practice testing. The final indicator set comprised 7 structural indicators, 21 process indicators and 2 outcome indicators.
CONCLUSION: The indicators fulfil a previously unmet need among Palliative Day Service providers by delivering an appropriate and feasible means to assess, review, and communicate the quality of care, and to identify areas for quality improvement.
BACKGROUND AND OBJECTIVES: Adaptive preferences occur when people subconsciously alter their views to account for the possibilities available to them. Adaptive preferences may be problematic where these views are used in resource allocation decisions because they may lead to underestimation of the true benefits of providing services. This research explored the nature and extent of both adaptation (changing to better suit the context) and adaptive preferences (altering preferences in response to restricted options) in individuals approaching the end of life (EoL).
METHODS: Qualitative data from 'thinkaloud' interviews with 33 hospice patients, 22 close persons and 17 health professionals were used alongside their responses to three health/well-being measures for use in resource allocation decisions: EQ-5D-5L (health status); ICECAP-A (adult capability); and ICECAP-SCM (Supportive Care Measure; EoL capability). Constant comparative analysis combined a focus on both verbalised perceptions across the three groups and responses to the measures.
RESULTS: Data collection took place between October 2012 and February 2014. Informants spoke clearly about how patients had adapted their lives in response to symptoms associated with their terminal condition. It was often seen as a positive choice to accept their state and adapt in this way but, at the same time, most patients were fully aware of the health and capability losses that they had faced. Self-assessments of health and capability generally appeared to reflect the pre-adaptation state, although there were exceptions.
CONCLUSION: Despite adapting to their conditions, the reference group for individuals approaching EoL largely remained a healthy, capable population, and most did not show evidence of adaptive preferences.
BACKGROUND: Sen's capability approach is underspecified; one decision left to those operationalising the approach is how to identify sets of relevant and important capabilities. Sen has suggested that lists be developed for specific policy or research objectives through a process of public reasoning and discussion. Robeyns offers further guidance in support of Sen's position, suggesting that lists should be explicit, discussed and defended; methods be openly scrutinised; lists be considered both in terms of what is ideal and what is practical ('generality'); and that lists be exhaustive. Here, the principles suggested by Robeyns are operationalised to facilitate external scrutiny of a list of capabilities identified for use in the evaluation of supportive end of life care.
METHODS: This work started with an existing list of seven capabilities (the ICECAP-SCM), identified as being necessary for a person to experience a good death. Semi-structured qualitative interviews were conducted with 20 experts in economics, psychology, ethics and palliative care, to facilitate external scrutiny of the developed list. Interviews were recorded, transcribed and analysed using constant comparison.
RESULTS: The seven capabilities were found to encompass concepts identified as important by expert stakeholders (to be exhaustive) and the measure was considered feasible for use with patients receiving care at the end of life.
CONCLUSION: The rigorous development of lists of capabilities using both initial participatory approaches with affected population groups, and subsequent assessment by experts, strengthens their democratic basis and may encourage their use in policy contexts.
End of life care may have elements of value that go beyond health. A generic measure of the benefits of end of life care could be helpful to decision makers. Such a measure, based on the capability approach, has recently been developed: the ICECAP Supportive Care Measure. This paper reports the first valuation exercise for that measure, with data from 6020 individuals collected from an on-line general population panel during June 2013. Individuals were asked to complete a stated choice experiment that combined best-worst scaling and a standard discrete choice experiment. Analysis of the best-worst data used limited dependent variable models within the random utility framework including the multinomial logit models and latent class choice model analysis. Exploratory steps were taken to determine the similarity of the best-worst and DCE data before formal testing and pooling of the two data sources. Combined data were analysed in a heteroscedastic conditional logit model adjusting for continuous scale. Two sets of tariffs were generated, one from the best-worst data capturing only main effects, and a second from the pooled data allowing for two-way interactions. Either tariff could be used in economic evaluation of interventions at the end of life, although there are advantages and disadvantages with each. This extensive valuation exercise for the ICECAP Supportive Care Measure, with a large number of members of the general public, could be complemented in the future with best-worst scaling studies amongst those experiencing the end of life.