IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v40y2022i9d10.1007_s40273-022-01167-1.html
   My bibliography  Save this article

Best–Worst Scaling and the Prioritization of Objects in Health: A Systematic Review

Author

Listed:
  • Ilene L. Hollin

    (Temple University College of Public Health)

  • Jonathan Paskett

    (The Ohio State University College of Medicine)

  • Anne L. R. Schuster

    (The Ohio State University College of Medicine)

  • Norah L. Crossnohere

    (The Ohio State University College of Medicine)

  • John F. P. Bridges

    (The Ohio State University College of Medicine)

Abstract

Background and Objective Best–worst scaling is a theory-driven method that can be used to prioritize objects in health. We sought to characterize all studies of best–worst scaling to prioritize objects in health, to assess trends of using best–worst scaling in prioritization over time, and to assess the relationship between a legacy measure of quality (PREFS) and a novel assessment of subjective quality and policy relevance. Methods A systematic review identified studies published through to the end of 2021 that applied best–worst scaling to study priorities in health (PROSPERO CRD42020209745), updating a prior review published in 2016. The PubMed, EBSCOhost, Embase, Scopus, APA PsychInfo, Web of Science, and Google Scholar databases were used and were supplemented by a hand search. Data describing the application, development, design, administration/analysis, quality, and policy relevance were summarized and we tested for trends by comparing articles before and after 1 January, 2017. Multivariate statistics were then used to assess the relationships between PREFS, subjective quality, policy relevance, and other possible indicators. Results From a total of 2826 unique papers identified, 165 best–worst scaling studies were included in this review. Applications of best–worst scaling to study priorities in health have continued to grow (p

Suggested Citation

  • Ilene L. Hollin & Jonathan Paskett & Anne L. R. Schuster & Norah L. Crossnohere & John F. P. Bridges, 2022. "Best–Worst Scaling and the Prioritization of Objects in Health: A Systematic Review," PharmacoEconomics, Springer, vol. 40(9), pages 883-899, September.
    • Handle: RePEc:spr:pharme:v:40:y:2022:i:9:d:10.1007_s40273-022-01167-1
    DOI: 10.1007/s40273-022-01167-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-022-01167-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40273-022-01167-1?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. Louviere, Jordan J. & Lancsar, Emily, 2009. "Choice experiments in health: the good, the bad, the ugly and toward a brighter future," Health Economics, Policy and Law, Cambridge University Press, vol. 4(4), pages 527-546, October.
    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. Anna Nicolet & Antoinette D I van Asselt & Karin M Vermeulen & Paul F M Krabbe, 2020. "Value judgment of new medical treatments: Societal and patient perspectives to inform priority setting in The Netherlands," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
    2. Thomas G. Poder & Nathalie Carrier & Mathieu Roy & Chantal Camden, 2020. "A Discrete Choice Experiment on Women’s Preferences for Water Immersion During Labor and Birth: Identification, Refinement and Selection of Attributes and Levels," IJERPH, MDPI, vol. 17(6), pages 1-11, March.
    3. Vujicic, Marko & Shengelia, Bakhuti & Alfano, Marco & Thu, Ha Bui, 2011. "Physician shortages in rural Vietnam: Using a labor market approach to inform policy," Social Science & Medicine, Elsevier, vol. 73(7), pages 970-977.
    4. Buckley, Neil J. & Cuff, Katherine & Hurley, Jeremiah & McLeod, Logan & Mestelman, Stuart & Cameron, David, 2012. "An experimental investigation of mixed systems of public and private health care finance," Journal of Economic Behavior & Organization, Elsevier, vol. 84(3), pages 713-729.
    5. Paul F M Krabbe, 2013. "A Generalized Measurement Model to Quantify Health: The Multi-Attribute Preference Response Model," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-12, November.
    6. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    7. Christian Pfarr & Andreas Schmid & Morten Raun Mørkbak, 2018. "Modelling Heterogeneous Preferences for Income Redistribution–An Application of Continuous and Discrete Distributions," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 270-294, June.
    8. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    9. De Ayala Bilbao, Amaya & Hoyos Ramos, David & Mariel Chladkova, Petr, 2012. "Landscape valuation through discrete choice experiments: Current practice and future research reflections," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    10. Anthony Scott & Peter Sivey, 2022. "Motivation and competition in health care," Health Economics, John Wiley & Sons, Ltd., vol. 31(8), pages 1695-1712, August.
    11. Kim, Ga-Eun & Kim, Ju-Hee & Yoo, Seung-Hoon, 2019. "South Korean consumers’ preferences for eco-friendly gasoline sedans: Results from a choice experiment survey," Transport Policy, Elsevier, vol. 77(C), pages 1-7.
    12. Pedersen, Line Bjørnskov & Hess, Stephane & Kjær, Trine, 2016. "Asymmetric information and user orientation in general practice: Exploring the agency relationship in a best–worst scaling study," Journal of Health Economics, Elsevier, vol. 50(C), pages 115-130.
    13. Caroline M. Vass & Niall J. Davison & Geert Stichele & Katherine Payne, 2020. "A Picture is Worth a Thousand Words: The Role of Survey Training Materials in Stated-Preference Studies," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 13(2), pages 163-173, April.
    14. Peyron, Christine & Pélissier, Aurore & Béjean, Sophie, 2018. "Preference heterogeneity with respect to whole genome sequencing. A discrete choice experiment among parents of children with rare genetic diseases," Social Science & Medicine, Elsevier, vol. 214(C), pages 125-132.
    15. Liu, Yun & Kong, Qingxia & de Bekker-Grob, Esther W., 2019. "Public preferences for health care facilities in rural China: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 237(C), pages 1-1.
    16. Pfarr, Christian & Schmid, Andreas & Mørkbak, Morten Raun, 2015. "Latent characteristics and preferences for income redistribution," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113001, Verein für Socialpolitik / German Economic Association.
    17. Chiara Seghieri & Alessandro Mengoni & Sabina Nuti, 2014. "Applying discrete choice modelling in a priority setting: an investigation of public preferences for primary care models," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 773-785, September.
    18. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    19. Mark Harrison & Dan Rigby & Caroline Vass & Terry Flynn & Jordan Louviere & Katherine Payne, 2014. "Risk as an Attribute in Discrete Choice Experiments: A Systematic Review of the Literature," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(2), pages 151-170, June.
    20. Mandeville, Kate L. & Ulaya, Godwin & Lagarde, Mylène & Muula, Adamson S. & Dzowela, Titha & Hanson, Kara, 2016. "The use of specialty training to retain doctors in Malawi: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 169(C), pages 109-118.

    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:spr:pharme:v:40:y:2022:i:9:d:10.1007_s40273-022-01167-1. 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.springer.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.