IDEAS home Printed from https://ideas.repec.org/a/spr/pharmo/v7y2023i4d10.1007_s41669-023-00414-1.html
   My bibliography  Save this article

A Simple Cost-Effectiveness Model of Screening: An Open-Source Teaching and Research Tool Coded in R

Author

Listed:
  • Yi-Shu Lin

    (Trinity College Dublin)

  • James F O’Mahony

    (Trinity College Dublin)

  • Joost Rosmalen

    (Erasmus Medical Centre
    Erasmus Medical Centre)

Abstract

Applied cost-effectiveness analysis models are an important tool for assessing health and economic effects of healthcare interventions but are not best suited for illustrating methods. Our objective is to provide a simple, open-source model for the simulation of disease-screening cost-effectiveness for teaching and research purposes. We introduce our model and provide an initial application to examine changes to the efficiency frontier as input parameters vary and to demonstrate face validity. We described a vectorised, discrete-event simulation of screening in R with an Excel interface to define parameters and inspect principal results. An R Shiny app permits dynamic interpretation of simulation outputs. An example with 8161 screening strategies illustrates the cost and effectiveness of varying the disease sojourn time, treatment effectiveness, and test performance characteristics and costs on screening policies. Many of our findings are intuitive and straightforward, such as a reduction in screening costs leading to decreased overall costs and improved cost-effectiveness. Others are less obvious and depend on whether we consider gross outcomes or those net to no screening. For instance, enhanced treatment of symptomatic disease increases gross effectiveness, but reduces the net effectiveness and cost-effectiveness of screening. A lengthening of the preclinical sojourn time has ambiguous effects relative to no screening, as cost-effectiveness improves for some strategies but deteriorates for others. Our simple model offers an accessible platform for methods research and teaching. We hope it will serve as a public good and promote an intuitive understanding of the cost-effectiveness of screening.

Suggested Citation

  • Yi-Shu Lin & James F O’Mahony & Joost Rosmalen, 2023. "A Simple Cost-Effectiveness Model of Screening: An Open-Source Teaching and Research Tool Coded in R," PharmacoEconomics - Open, Springer, vol. 7(4), pages 507-523, July.
    • Handle: RePEc:spr:pharmo:v:7:y:2023:i:4:d:10.1007_s41669-023-00414-1
    DOI: 10.1007/s41669-023-00414-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41669-023-00414-1
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1007/s41669-023-00414-1?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
    ---><---

    References listed on IDEAS

    as
    1. David M. Eddy, 1983. "A Mathematical Model for Timing Repeated Medical Tests," Medical Decision Making, , vol. 3(1), pages 45-62, February.
    2. Eline M. Krijkamp & Fernando Alarid-Escudero & Eva A. Enns & Hawre J. Jalal & M. G. Myriam Hunink & Petros Pechlivanoglou, 2018. "Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial," Medical Decision Making, , vol. 38(3), pages 400-422, April.
    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. Fernando Alarid-Escudero & Eline Krijkamp & Eva A. Enns & Alan Yang & M. G. Myriam Hunink & Petros Pechlivanoglou & Hawre Jalal, 2023. "A Tutorial on Time-Dependent Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example," Medical Decision Making, , vol. 43(1), pages 21-41, January.
    2. Mei-Chin Su & Yi-Jen Wang & Tzeng-Ji Chen & Shiao-Hui Chiu & Hsiao-Ting Chang & Mei-Shu Huang & Li-Hui Hu & Chu-Chuan Li & Su-Ju Yang & Jau-Ching Wu & Yu-Chun Chen, 2020. "Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated H," IJERPH, MDPI, vol. 17(3), pages 1-17, February.
    3. Anna Heath & Petros Pechlivanoglou, 2022. "Prioritizing Research in an Era of Personalized Medicine: The Potential Value of Unexplained Heterogeneity," Medical Decision Making, , vol. 42(5), pages 649-660, July.
    4. John C. Hershey & Randall D. Cebul & Sankey V. Williams, 1986. "Clinical Guidelines for Using Two Dichotomous Tests," Medical Decision Making, , vol. 6(2), pages 68-78, June.
    5. Isaac Corro Ramos & Talitha Feenstra & Salah Ghabri & Maiwenn Al, 2024. "Evaluating the Validation Process: Embracing Complexity and Transparency in Health Economic Modelling," PharmacoEconomics, Springer, vol. 42(7), pages 715-719, July.
    6. Peter Shewmaker & Stavroula A. Chrysanthopoulou & Rowan Iskandar & Derek Lake & Earic Jutkowitz, 2022. "Microsimulation Model Calibration with Approximate Bayesian Computation in R: A Tutorial," Medical Decision Making, , vol. 42(5), pages 557-570, July.
    7. Stavroula A. Chrysanthopoulou & Carolyn M. Rutter & Constantine A. Gatsonis, 2021. "Bayesian versus Empirical Calibration of Microsimulation Models: A Comparative Analysis," Medical Decision Making, , vol. 41(6), pages 714-726, August.
    8. Giovanni Parmigiani & Steven Skates & Marvin Zelen, 2002. "Modeling and Optimization in Early Detection Programs with a Single Exam," Biometrics, The International Biometric Society, vol. 58(1), pages 30-36, March.
    9. William, Jananie & Loong, Bronwyn & Hanna, Dana & Parkinson, Bonny & Loxton, Deborah, 2022. "Lifetime health costs of intimate partner violence: A prospective longitudinal cohort study with linked data for out-of-hospital and pharmaceutical costs," Economic Modelling, Elsevier, vol. 116(C).
    10. Elizabeth A. Handorf & J. Robert Beck & Andres Correa & Chethan Ramamurthy & Daniel M. Geynisman, 2023. "Cost-Effectiveness Analysis for Therapy Sequence in Advanced Cancer: A Microsimulation Approach with Application to Metastatic Prostate Cancer," Medical Decision Making, , vol. 43(7-8), pages 949-960, October.
    11. Fernando Alarid-Escudero & Eline Krijkamp & Eva A. Enns & Alan Yang & M. G. Myriam Hunink & Petros Pechlivanoglou & Hawre Jalal, 2023. "An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example," Medical Decision Making, , vol. 43(1), pages 3-20, January.
    12. Paolo Candio & Koen B. Pouwels & David Meads & Andrew J. Hill & Laura Bojke & Claire Williams, 2022. "Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1151-1157, September.

    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:pharmo:v:7:y:2023:i:4:d:10.1007_s41669-023-00414-1. 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.