IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v6y2022i2d10.1038_s41562-021-01280-9.html
   My bibliography  Save this article

Patient traits shape health-care stakeholders’ choices on how to best allocate life-saving care

Author

Listed:
  • Charles Crabtree

    (Dartmouth College)

  • John B. Holbein

    (University of Virginia)

  • J. Quin Monson

    (Brigham Young University)

Abstract

During global pandemics, health-care decision makers often face critical shortages of life-saving medical equipment. How do medical stakeholders prioritize which patients are most deserving of scarce treatment? We report the results of three conjoint experiments conducted in the United States in 2020, testing for biases in US physicians’, citizens’ and elected politicians’ preferences for scarce ventilator distribution. We found that all stakeholders prioritized younger patients and patients who had a higher probability of surviving with ventilator access. When patients’ survivability was tied, physicians prioritized patients from racial/ethnic minorities (that is, Asian, Black and Hispanic patients) over all-else-equal white patients, religious minorities (that is, Muslim patients) over religious majority group members (that is, Catholic patients) and patients of lower socio-economic status over wealthier patients. The public also prioritized Black and Hispanic patients over white patients but were biased against religious minorities (that is, Atheist and Muslim patients) relative to religious majority group members. Elected politicians were also biased against Atheist patients. Our effects varied by political party—with Republican physicians, politicians and members of the public showing bias against religious minority patients and Democratic physicians showing preferential treatment of racial and religious minorities. Our results suggest that health-care stakeholders’ personal biases impact decisions on who deserves life-saving medical equipment.

Suggested Citation

  • Charles Crabtree & John B. Holbein & J. Quin Monson, 2022. "Patient traits shape health-care stakeholders’ choices on how to best allocate life-saving care," Nature Human Behaviour, Nature, vol. 6(2), pages 244-257, February.
  • Handle: RePEc:nat:nathum:v:6:y:2022:i:2:d:10.1038_s41562-021-01280-9
    DOI: 10.1038/s41562-021-01280-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-021-01280-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41562-021-01280-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 313-350.
    2. Knox, Dean & Lowe, Will & Mummolo, Jonathan, 2020. "Administrative Records Mask Racially Biased Policing—CORRIGENDUM," American Political Science Review, Cambridge University Press, vol. 114(4), pages 1394-1394, November.
    3. Auerbach, Adam Michael & Thachil, Tariq, 2018. "How Clients Select Brokers: Competition and Choice in India's Slums," American Political Science Review, Cambridge University Press, vol. 112(4), pages 775-791, November.
    4. Morgan, Kimberly J. & Campbell, Andrea Louise, 2011. "The Delegated Welfare State: Medicare, Markets, and the Governance of Social Policy," OUP Catalogue, Oxford University Press, number 9780199730353.
    5. Bansak, Kirk & Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2021. "Beyond the breaking point? Survey satisficing in conjoint experiments," Political Science Research and Methods, Cambridge University Press, vol. 9(1), pages 53-71, January.
    6. Devon E McMahon & Gregory A Peters & Louise C Ivers & Esther E Freeman, 2020. "Global resource shortages during COVID-19: Bad news for low-income countries," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(7), pages 1-3, July.
    7. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
    8. Street Jr., Richard L. & Gordon, Howard & Haidet, Paul, 2007. "Physicians' communication and perceptions of patients: Is it how they look, how they talk, or is it just the doctor?," Social Science & Medicine, Elsevier, vol. 65(3), pages 586-598, August.
    9. Hagiwara, Nao & Penner, Louis A. & Gonzalez, Richard & Eggly, Susan & Dovidio, John F. & Gaertner, Samuel L. & West, Tessa & Albrecht, Terrance L., 2013. "Racial attitudes, physician–patient talk time ratio, and adherence in racially discordant medical interactions," Social Science & Medicine, Elsevier, vol. 87(C), pages 123-131.
    10. Schwab, Stewart, 1986. "Is Statistical Discrimination Efficient?," American Economic Review, American Economic Association, vol. 76(1), pages 228-234, March.
    11. Daniel M. Butler & David E. Broockman, 2011. "Do Politicians Racially Discriminate Against Constituents? A Field Experiment on State Legislators," American Journal of Political Science, John Wiley & Sons, vol. 55(3), pages 463-477, July.
    12. Jonathan Guryan & Kerwin Kofi Charles, 2013. "Taste‐based or Statistical Discrimination: The Economics of Discrimination Returns to its Roots," Economic Journal, Royal Economic Society, vol. 123(11), pages 417-432, November.
    13. Nicholas Carnes & John Holbein, 2019. "Do public officials exhibit social class biases when they handle casework? Evidence from multiple correspondence experiments," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-9, March.
    14. Van Ryn, M. & Burgess, D. & Malat, J. & Griffin, J., 2006. "Physicians' perceptions of patients' social and behavioral characteristics and race disparities in treatment recommendations for men with coronary artery disease," American Journal of Public Health, American Public Health Association, vol. 96(2), pages 351-357.
    15. Liyin Jin & Yunhui Huang & Yongheng Liang & Qiang Zhang, 2021. "Who Gets the Ventilator? Moral Decision Making Regarding Medical Resource Allocation in a Pandemic," Journal of the Association for Consumer Research, University of Chicago Press, vol. 6(1), pages 159-167.
    16. Currie, Janet & Lin, Wanchuan & Meng, Juanjuan, 2014. "Addressing antibiotic abuse in China: An experimental audit study," Journal of Development Economics, Elsevier, vol. 110(C), pages 39-51.
    17. Bansak, Kirk & Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2018. "The Number of Choice Tasks and Survey Satisficing in Conjoint Experiments," Political Analysis, Cambridge University Press, vol. 26(1), pages 112-119, January.
    18. Mummolo, Jonathan & Peterson, Erik, 2019. "Demand Effects in Survey Experiments: An Empirical Assessment," American Political Science Review, Cambridge University Press, vol. 113(2), pages 517-529, May.
    19. Knox, Dean & Lowe, Will & Mummolo, Jonathan, 2020. "Administrative Records Mask Racially Biased Policing," American Political Science Review, Cambridge University Press, vol. 114(3), pages 619-637, August.
    20. Daniel M. Butler & Craig Volden & Adam M. Dynes & Boris Shor, 2017. "Ideology, Learning, and Policy Diffusion: Experimental Evidence," American Journal of Political Science, John Wiley & Sons, vol. 61(1), pages 37-49, January.
    21. Erin Hartman & F. Daniel Hidalgo, 2018. "An Equivalence Approach to Balance and Placebo Tests," American Journal of Political Science, John Wiley & Sons, vol. 62(4), pages 1000-1013, October.
    22. Carsten Jensen & Michael Bang Petersen, 2017. "The Deservingness Heuristic and the Politics of Health Care," American Journal of Political Science, John Wiley & Sons, vol. 61(1), pages 68-83, January.
    23. Costa, Mia, 2017. "How Responsive are Political Elites? A Meta-Analysis of Experiments on Public Officials," Journal of Experimental Political Science, Cambridge University Press, vol. 4(3), pages 241-254, December.
    24. Jacob M. Montgomery & Brendan Nyhan & Michelle Torres, 2018. "How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do about It," American Journal of Political Science, John Wiley & Sons, vol. 62(3), pages 760-775, July.
    25. Jenke, Libby & Bansak, Kirk & Hainmueller, Jens & Hangartner, Dominik, 2021. "Using Eye-Tracking to Understand Decision-Making in Conjoint Experiments," Political Analysis, Cambridge University Press, vol. 29(1), pages 75-101, January.
    26. Clinton, Joshua D. & Sances, Michael W., 2018. "The Politics of Policy: The Initial Mass Political Effects of Medicaid Expansion in the States," American Political Science Review, Cambridge University Press, vol. 112(1), pages 167-185, February.
    27. Jens Hainmueller & Daniel J. Hopkins, 2015. "The Hidden American Immigration Consensus: A Conjoint Analysis of Attitudes toward Immigrants," American Journal of Political Science, John Wiley & Sons, vol. 59(3), pages 529-548, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Janne Tukiainen & Sebastian Blesse & Albrecht Bohne & Leonardo M. Giuffrida & Jan Jäässkeläinen & Ari Luukinen & Antti Sieppi, 2021. "What Are the Priorities of Bureaucrats? Evidence from Conjoint Experiments with Procurement Officials," EconPol Working Paper 63, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Briggs, Ryan C & Solodoch, Omer, 2021. "Changes in perceptions of border security influence desired levels of immigration," OSF Preprints wt74y, Center for Open Science.
    3. Hoffmann, Robert & Coate, Bronwyn, 2022. "Fame, What’s your name? quasi and statistical gender discrimination in an art valuation experimentc," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 184-197.
    4. Barceló, Joan & Sheen, Greg Chih-Hsin & Tung, Hans H. & Wu, Wen-Chin, 2022. "Vaccine nationalism among the public: A cross-country experimental evidence of own-country bias towards COVID-19 vaccination," Social Science & Medicine, Elsevier, vol. 310(C).
    5. Pfaff, Steven & Crabtree, Charles & Kern, Holger L. & Holbein, John B., 2018. "Does religious bias shape access to public services? A large-scale audit experiment among street-level bureaucrats," SocArXiv 9khds, Center for Open Science.
    6. Andrea F.M. Martinangeli & Lisa Windsteiger, 2019. "Immigration vs. Poverty: Causal Impact on Demand for Redistribution in a Survey Experiment," Working Papers tax-mpg-rps-2019-13, Max Planck Institute for Tax Law and Public Finance.
    7. Gian Maria Campedelli, 2022. "Explainable Machine Learning for Predicting Homicide Clearance in the United States," Papers 2203.04768, arXiv.org.
    8. Song Han, 2011. "Creditor Learning and Discrimination in Lending," Journal of Financial Services Research, Springer;Western Finance Association, vol. 40(1), pages 1-27, October.
    9. Anuli Njoku & Marcelin Joseph & Rochelle Felix, 2021. "Changing the Narrative: Structural Barriers and Racial and Ethnic Inequities in COVID-19 Vaccination," IJERPH, MDPI, vol. 18(18), pages 1-14, September.
    10. Mikula, Stepan & Montag, Josef, 2023. "Roma and Bureaucrats: A Field Experiment on Ethnic and Socioeconomic Discrimination," IZA Discussion Papers 16218, Institute of Labor Economics (IZA).
    11. Fenton, Anny T. & Elliott, Marc N. & Schwebel, David C. & Berkowitz, Zahava & Liddon, Nicole C. & Tortolero, Susan R. & Cuccaro, Paula M. & Davies, Suzy L. & Schuster, Mark A., 2018. "Unequal interactions: Examining the role of patient-centered care in reducing inequitable diffusion of a medical innovation, the human papillomavirus (HPV) vaccine," Social Science & Medicine, Elsevier, vol. 200(C), pages 238-248.
    12. Anne-Marie Jeannet & Tobias Heidland & Martin Ruhs, 2021. "What asylum and refugee policies do Europeans want? Evidence from a cross-national conjoint experiment," European Union Politics, , vol. 22(3), pages 353-376, September.
    13. Boeri, Tito & Gamalerio, Matteo & Morelli, Massimo & Negri, Margherita, 2023. "Pay-As-They-Get-In: Attitudes Towards Migrants and Pension Systems," IZA Discussion Papers 15989, Institute of Labor Economics (IZA).
    14. Wu, Bao & Liu, Zijia & Gu, Qiuyang & Tsai, Fu-Sheng, 2023. "Underdog mentality, identity discrimination and access to peer-to-peer lending market: Exploring effects of digital authentication," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    15. Gaddis, S. Michael, 2018. "An Introduction to Audit Studies in the Social Sciences," SocArXiv e5hfc, Center for Open Science.
    16. List, John A. & Rasul, Imran, 2011. "Field Experiments in Labor Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 2, pages 103-228, Elsevier.
    17. Atsuko Tanaka, "undated". "Estimation of the Effects of Statistical Discrimination on the Gender Wage Gap," Working Papers 2015-22, Department of Economics, University of Calgary, revised 21 Dec 2015.
    18. Grossman, Shelby & Honig, Dan, 2017. "Evidence from Lagos on Discrimination across Ethnic and Class Identities in Informal Trade," World Development, Elsevier, vol. 96(C), pages 520-528.
    19. Giulietti, Corrado & Tonin, Mirco & Vlassopoulos, Michael, 2015. "Racial Discrimination in Local Public Services: A Field Experiment in the US," IZA Discussion Papers 9290, Institute of Labor Economics (IZA).
    20. Martinangeli, Andrea F.M. & Windsteiger, Lisa, 2023. "Immigration vs. poverty: Causal impact on demand for redistribution in a survey experiment," European Journal of Political Economy, Elsevier, vol. 78(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nathum:v:6:y:2022:i:2:d:10.1038_s41562-021-01280-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.