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Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population

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  • Rowen, Donna
  • Powell, Philip A.
  • Hole, Arne Risa
  • Aragon, Maria-Jose
  • Castelli, Adriana
  • Jacobs, Rowena

Abstract

High and sustained healthcare quality is important worldwide, though health policy may prioritise the achievement of certain aspects of quality over others. This study determines the relative importance of different aspects of mental healthcare quality to different stakeholders by eliciting preferences in a UK sample using a discrete choice experiment (DCE). DCE attributes were generated using triangulation between policy documents and mental healthcare service user and mental healthcare professional views, whilst ensuring attributes were measurable using available data. Ten attributes were selected: waiting times; ease of access; person-centred care; co-ordinated approach; continuity; communication, capacity and resources; treated with dignity and respect; recovery focus; inappropriate discharge; quality of life (QoL). The DCE was conducted online (December 2018 to February 2019) with mental healthcare service users (n = 331), mental healthcare professionals (n = 510), and members of the general population (n = 1018). Respondents’ choices were analysed using conditional logistic regression. Relative preferences for each attribute were generated using the marginal rate of substitution (MRS) with QoL as numeraire. Across all stakeholders, being treated with dignity and respect was of high importance. A coordinated approach was important across all stakeholders, whereas communication had higher relative importance for healthcare professionals and service users and ease of access had higher relative importance for the general population. This implies that policy could be affected by the choice of whose preferences (service users, healthcare professionals or general population) to use, since this impacts on the relative value and implied ranking of different aspects of mental healthcare quality.

Suggested Citation

  • Rowen, Donna & Powell, Philip A. & Hole, Arne Risa & Aragon, Maria-Jose & Castelli, Adriana & Jacobs, Rowena, 2022. "Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population," Social Science & Medicine, Elsevier, vol. 301(C).
    • Handle: RePEc:eee:socmed:v:301:y:2022:i:c:s0277953622001915
    DOI: 10.1016/j.socscimed.2022.114885
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    References listed on IDEAS

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    1. Caroline M. Vass & Stuart Wright & Michael Burton & Katherine Payne, 2018. "Scale Heterogeneity in Healthcare Discrete Choice Experiments: A Primer," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(2), pages 167-173, April.
    2. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    3. Esther Bekker-Grob & Bas Donkers & Marcel Jonker & Elly Stolk, 2015. "Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 8(5), pages 373-384, October.
    4. Vikas Soekhai & Esther W. Bekker-Grob & Alan R. Ellis & Caroline M. Vass, 2019. "Discrete Choice Experiments in Health Economics: Past, Present and Future," PharmacoEconomics, Springer, vol. 37(2), pages 201-226, February.
    5. Alison Pearce & Mark Harrison & Verity Watson & Deborah J. Street & Kirsten Howard & Nick Bansback & Stirling Bryan, 2021. "Respondent Understanding in Discrete Choice Experiments: A Scoping Review," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(1), pages 17-53, January.
    6. Fredrik Carlsson & Peter Martinsson, 2003. "Design techniques for stated preference methods in health economics," Health Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 281-294, April.
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    1. Nicolet, Anna & Perraudin, Clémence & Krucien, Nicolas & Wagner, Joël & Peytremann-Bridevaux, Isabelle & Marti, Joachim, 2023. "Preferences of older adults for healthcare models designed to improve care coordination: Evidence from Western Switzerland," Health Policy, Elsevier, vol. 132(C).

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