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Valuing attributes of home palliative care with service users: a pilot discrete choice experiment

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Barbara Gomes, Maja de Brito, Vera P Sarmento, Deokhee Yi, Duarte Soares, Jacinta Fernandes, Bruno Fonseca, Edna Gonçalves, Pedro L Ferreira, Irene J Higginson

Original languageEnglish
JournalJournal of pain and symptom management
Early online date8 Aug 2017
Accepted/In press25 May 2017
E-pub ahead of print8 Aug 2017


King's Authors


CONTEXT: Discrete choice experiment (DCE) is a quantitative method that helps determine which service attributes are most valued by people and consequently improve their well-being.

OBJECTIVES: To test a new DCE on home palliative care (HPC).

METHODS: Cross-sectional survey using the DCE method with adult patients and their family caregivers, users of three HPC services in Portugal. Service attributes were based on a Cochrane review, a meta-ethnography, and the few existing DCEs on HPC: 1) team's availability, 2) support for family caregivers, 3) homecare support, 4) information and planning, and 5) waiting time. The experimental design consisted in three blocks of eight choice sets where participants chose between two service alternatives that combined different levels of each attribute. We piloted the DCE using cognitive interviewing. Interviews were analysed for difficulties using Tourangeau's model of information processing.

RESULTS: The DCE was conducted with 21 participants out of 37 eligible (10 patients with median Palliative Performance Scale =45, 11 caregivers). Most participants found the DCE easy (median 2 from 1-5), though 2 patients did not finish the exercise. Key difficulties related to comprehension (e.g. waiting time sometimes understood as response time for visit instead of time from referral to care start) and judgement (e.g. indecision due to similar service alternatives).

CONCLUSION: The DCE method is feasible and acceptable, but not all patients are able to participate. In the main study phase we will give more attention to the explanation of the waiting time attribute.

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