IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v40y2022i5d10.1007_s40273-022-01131-z.html
   My bibliography  Save this article

Assessments of the Value of New Interventions Should Include Health Equity Impact

Author

Listed:
  • Jeroen P. Jansen

    (University of California, San Francisco
    Philip R. Lee Institute for Health Policy Studies, University of California)

  • Thomas A. Trikalinos

    (Brown University School of Public Health)

  • Kathryn A. Phillips

    (University of California, San Francisco
    Philip R. Lee Institute for Health Policy Studies, University of California)

Abstract

A formal evaluation of the health equity impact of a new intervention is hardly ever performed as part of a health technology assessment to understand its value. This should change, in our view. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, programme designs, and quality initiatives focused on optimizing both total health and health equity given the treatment options available. We outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly US FDA-approved drug for Alzheimer’s disease (aducanumab) as an example. We argue that gaps in the evidence base for the new intervention, for example, due to limited clinical research participation among racial and ethnic minority groups, do not preclude such an evaluation. Understanding these uncertainties has implications for fair pricing, decision making, and future research. If we are serious about population-level decision making that not only is focused on improving total health but also aims to improve health equity, we should consider routinely assessing the health equity impact of new interventions.

Suggested Citation

  • Jeroen P. Jansen & Thomas A. Trikalinos & Kathryn A. Phillips, 2022. "Assessments of the Value of New Interventions Should Include Health Equity Impact," PharmacoEconomics, Springer, vol. 40(5), pages 489-495, May.
  • Handle: RePEc:spr:pharme:v:40:y:2022:i:5:d:10.1007_s40273-022-01131-z
    DOI: 10.1007/s40273-022-01131-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-022-01131-z
    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/s40273-022-01131-z?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. John Paul Gosling, 2018. "SHELF: The Sheffield Elicitation Framework," International Series in Operations Research & Management Science, in: Luis C. Dias & Alec Morton & John Quigley (ed.), Elicitation, chapter 0, pages 61-93, Springer.
    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. Claire Copeland & Britta Turner & Gareth Powells & Kevin Wilson, 2022. "In Search of Complementarity: Insights from an Exercise in Quantifying Qualitative Energy Futures," Energies, MDPI, vol. 15(15), pages 1-21, July.
    2. Cameron J. Williams & Kevin J. Wilson & Nina Wilson, 2021. "A comparison of prior elicitation aggregation using the classical method and SHELF," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 920-940, July.
    3. Christoph Werner & Tim Bedford & John Quigley, 2018. "Sequential Refined Partitioning for Probabilistic Dependence Assessment," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2683-2702, December.
    4. Christopher J. Cadham & Marie Knoll & Luz María Sánchez-Romero & K. Michael Cummings & Clifford E. Douglas & Alex Liber & David Mendez & Rafael Meza & Ritesh Mistry & Aylin Sertkaya & Nargiz Travis , 2022. "The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review," Medical Decision Making, , vol. 42(5), pages 684-703, July.
    5. Perepolkin, Dmytro & Lindsröm, Erik & Sahlin, Ullrika, 2023. "Quantile-parameterized distributions for expert knowledge elicitation," OSF Preprints tq3an, Center for Open Science.
    6. Raices Cruz, Ivette & Lindström, Johan & Troffaes, Matthias C.M. & Sahlin, Ullrika, 2022. "Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    7. Danila Azzolina & Paola Berchialla & Silvia Bressan & Liviana Da Dalt & Dario Gregori & Ileana Baldi, 2022. "A Bayesian Sample Size Estimation Procedure Based on a B-Splines Semiparametric Elicitation Method," IJERPH, MDPI, vol. 19(21), pages 1-15, October.
    8. Alice Morgan & Sally Hartmanis & Emmanuel Tsochatzis & Philip N. Newsome & Stephen D. Ryder & Rachel Elliott & Lefteris Floros & Richard Hall & Victoria Higgins & George Stanley & Sandrine Cure & Shar, 2021. "Disease burden and economic impact of diagnosed non-alcoholic steatohepatitis (NASH) in the United Kingdom (UK) in 2018," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(4), pages 505-518, June.
    9. Fadlalla G. Elfadaly & Paul H. Garthwaite, 2020. "On quantifying expert opinion about multinomial models that contain covariates," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 959-981, June.

    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:5:d:10.1007_s40273-022-01131-z. 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.