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Public Preferences for Allocating Ventilators in an Intensive Care Unit: A Discrete Choice Experiment

Author

Listed:
  • Richard Norman

    (Curtin University)

  • Suzanne Robinson

    (Curtin University)

  • Helen Dickinson

    (University of Birmingham)

  • Iestyn Williams

    (University of New South Wales)

  • Elena Meshcheriakova

    (University of Technology Sydney)

  • Kathleen Manipis

    (University of Technology Sydney)

  • Matthew Anstey

    (Curtin University
    University of Western Australia)

Abstract

Background and Objective During the COVID-19 pandemic, resources in intensive care units (ICUs) have the potential to be inadequate to treat all those who might benefit. Therefore, it is paramount to identify the views of the community regarding how to allocate such resources. This study aims to quantify Australian community preferences for ventilation allocation. Methods A discrete choice experiment was designed and administrated to an adult Australian online panel. Each survey respondent answered 12 choice sets from a total design of 120. Each choice set placed the respondent in the role of hypothetical decision maker, prioritising care between two patients. Conditional logit, mixed logit regression and latent class analysis were used to analyse the data. Additionally, we asked a series of attitudinal questions about different methods of making such decisions in practice, focusing on who should be responsible. Results A total of 1050 community members completed the survey and responded to each choice. Dimensions considered most important were age, likely effectiveness, smoking status, whether the person has dependents, whether they are a healthcare worker, and whether they have a disability or not. Estimating marginal rates of substitution between patient characteristics and chance of survival if ventilated yielded values of up to 30 percentage points if the patient was 70 years old relative to being 30. However, respondents typically said they would prefer such decisions to be made by medical professionals. Conclusion This study demonstrated the preferences of the community to allocation of ventilators during the COVID-19 pandemic. The use of such information should be treated with some caution as the underlying reason for such preferences are unclear, and respondents themselves preferred the decision to be made by others.

Suggested Citation

  • Richard Norman & Suzanne Robinson & Helen Dickinson & Iestyn Williams & Elena Meshcheriakova & Kathleen Manipis & Matthew Anstey, 2021. "Public Preferences for Allocating Ventilators in an Intensive Care Unit: A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(3), pages 319-330, May.
    • Handle: RePEc:spr:patien:v:14:y:2021:i:3:d:10.1007_s40271-021-00498-z
    DOI: 10.1007/s40271-021-00498-z
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    References listed on IDEAS

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    1. Shah, Koonal K., 2009. "Severity of illness and priority setting in healthcare: A review of the literature," Health Policy, Elsevier, vol. 93(2-3), pages 77-84, December.
    2. Yoo, Hong Il, 2019. "lclogit2: An enhanced module to estimate latent class conditional logit models," MPRA Paper 97014, University Library of Munich, Germany.
    3. Lancsar, Emily & Louviere, Jordan & Flynn, Terry, 2007. "Several methods to investigate relative attribute impact in stated preference experiments," Social Science & Medicine, Elsevier, vol. 64(8), pages 1738-1753, April.
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    Cited by:

    1. Rachael L. DiSantostefano & Fern Terris-Prestholt, 2021. "Using Societal Values to Inform Public Health Policy During the COVID-19 Pandemic: The Role of Health Preference Research," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(3), pages 303-307, May.
    2. Sprengholz, Philipp & Felgendreff, Lisa & Buyx, Alena & Betsch, Cornelia, 2023. "Toward future triage regulations: Investigating preferred allocation principles of the German public," Health Policy, Elsevier, vol. 134(C).

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