Alastair Canaway1, Hareth Al-Janabi2, Philip Kinghorn2, Cara Bailey2, Joanna Coast3. 1. Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK. a.canaway@warwick.ac.uk. 2. Health Economics Unit, University of Birmingham, Birmingham, UK. 3. School of Social and Community Medicine, University of Bristol, Bristol, UK.
Abstract
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: 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.
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