IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v42y2022i1p8-16.html
   My bibliography  Save this article

Partial Personalization of Medical Treatment Decisions: Adverse Effects and Possible Solutions

Author

Listed:
  • Christopher Weyant

    (Department of Management Science and Engineering, Stanford University, Stanford, CA, USA)

  • Margaret L. Brandeau

    (Department of Management Science and Engineering, Stanford University, Stanford, CA, USA)

Abstract

Background Personalizing medical treatment decisions based on patient-specific risks and/or preferences can improve health outcomes. Decision makers frequently select treatments based on partial personalization (e.g., personalization based on risks but not preferences or vice versa) due to a lack of data about patient-specific risks and preferences. However, partially personalizing treatment decisions based on a subset of patient risks and/or preferences can result in worse population-level health outcomes than no personalization and can increase the variance of population-level health outcomes. Methods We develop a new method for partially personalizing treatment decisions that avoids these problems. Using a case study of antipsychotic treatment for schizophrenia, as well as 4 additional illustrative examples, we demonstrate the adverse effects and our method for avoiding them. Results For the schizophrenia treatment case study, using a previously proposed modeling approach for personalizing treatment decisions and using only a subset of patient preferences regarding treatment efficacy and side effects, mean population-level health outcomes decreased by 0.04 quality-adjusted life-years (QALYs; 95% credible interval [crI]: 0.02–0.06) per patient compared with no personalization. Using our new method and considering the same subset of patient preferences, mean population-level health outcomes increased by 0.01 QALYs (95% crI: 0.00–0.03) per patient as compared with no personalization, and the variance decreased. Limitations We assumed a linear and additive utility function. Conclusions Selecting personalized treatments for patients should be done in a way that does not decrease expected population-level health outcomes and does not increase their variance, thereby resulting in worse risk-adjusted, population-level health outcomes compared with treatment selection with no personalization. Our method can be used to ensure this, thereby helping patients realize the benefits of treatment personalization without the potential harms.

Suggested Citation

  • Christopher Weyant & Margaret L. Brandeau, 2022. "Partial Personalization of Medical Treatment Decisions: Adverse Effects and Possible Solutions," Medical Decision Making, , vol. 42(1), pages 8-16, January.
    • Handle: RePEc:sae:medema:v:42:y:2022:i:1:p:8-16
    DOI: 10.1177/0272989X211013773
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X211013773
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X211013773?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
    ---><---

    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:sae:medema:v:42:y:2022:i:1:p:8-16. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: SAGE Publications (email available below). General contact details of provider: .

    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.