PurposeThe benefits of health and social care are not confined to patient health alone and therefore broader measures of wellbeing may be useful for economic evaluation. This paper reports the development of a simple measure of capability wellbeing for adults (ICECAP-A).MethodsIn-depth, informant-led, interviews to identify the attributes of capability wellbeing were conducted with 36 adults in the UK. Eighteen semi-structured, repeat interviews were carried out to develop a capability-based descriptive system for the measure. Informants were purposively selected to ensure variation in socio-economic status, age, sex, ethnicity and health. Data analysis was carried out inductively and iteratively alongside interviews, and findings were used to shape the questions in later interviews.ResultsFive over-arching attributes of capability wellbeing were identified for the measure: “stability”, “attachment”, “achievement”, “autonomy” and “enjoyment”. One item, with four response categories, was developed for each attribute for the ICECAP-A descriptive system.ConclusionsThe ICECAP-A capability measure represents a departure from traditional health economics outcome measures, by treating health status as an influence over broader attributes of capability wellbeing. Further work is required to value and validate the attributes and test the sensitivity of the ICECAP-A to healthcare interventions.
This paper reports the first application of the capabilities approach to the development and valuation of an instrument for use in the economic evaluation of health and social care interventions. The ICECAP index of capability for older people focuses on quality of life rather than health or other influences on quality of life, and is intended to be used in decision making across health and social care in the UK. The measure draws on previous qualitative work in which five conceptual attributes were developed: attachment, security, role, enjoyment and control. This paper details the innovative use within health economics of further iterative qualitative work in the UK among 19 informants to refine lay terminology for each of the attributes and levels of attributes used in the eventual index. For the first time within quality of life measurement for economic evaluation, a best-worst scaling exercise has been used to estimate general population values (albeit for the population of those aged 65+ years) for the levels of attributes, with values anchored at one for full capability and zero for no capability. Death was assumed to be a state in which there is no capability. The values obtained indicate that attachment is the attribute with greatest impact but all attributes contribute to the total estimation of capability. Values that were estimated are feasible for use in practical applications of the index to measure the impact of health and social care interventions.
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Attribute generation for discrete choice experiments (DCEs) is often poorly reported, and it is unclear whether this element of research is conducted rigorously. This paper explores issues associated with developing attributes for DCEs and contrasts different qualitative approaches. The paper draws on eight studies, four developed attributes for measures, and four developed attributes for more ad hoc policy questions. Issues that have become apparent through these studies include the following: the theoretical framework for random utility theory and the need for attributes that are neither too close to the latent construct nor too intrinsic to people's personality; the need to think about attribute development as a two-stage process involving conceptual development followed by refinement of language to convey the intended meaning; and the difficulty in resolving tensions inherent in the reductiveness of condensing complex and nuanced qualitative findings into precise terms. The comparison of alternative qualitative approaches suggests that the nature of data collection will depend both on the characteristics of the question (its sensitivity, for example) and the availability of existing qualitative information. An iterative, constant comparative approach to analysis is recommended. Finally, the paper provides a series of recommendations for improving the reporting of this element of DCE studies.
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