IDEAS home Printed from https://ideas.repec.org/a/spr/hecrev/v11y2021i1d10.1186_s13561-021-00312-4.html
   My bibliography  Save this article

Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

Author

Listed:
  • Sameera Senanayake

    (Queensland University of Technology (QUT))

  • Nicholas Graves

    (Duke-NUS Medical School)

  • Helen Healy

    (Royal Brisbane Hospital for Women
    School of Medicine, University of Queensland)

  • Keshwar Baboolal

    (Royal Brisbane Hospital for Women
    School of Medicine, University of Queensland)

  • Adrian Barnett

    (Queensland University of Technology (QUT))

  • Sanjeewa Kularatna

    (Queensland University of Technology (QUT))

Abstract

Background Economic-evaluations using decision analytic models such as Markov-models (MM), and discrete-event-simulations (DES) are high value adds in allocating resources. The choice of modelling method is critical because an inappropriate model yields results that could lead to flawed decision making. The aim of this study was to compare cost-effectiveness when MM and DES were used to model results of transplanting a lower-quality kidney versus remaining waitlisted for a kidney. Methods Cost-effectiveness was assessed using MM and DES. We used parametric survival models to estimate the time-dependent transition probabilities of MM and distribution of time-to-event in DES. MMs were simulated in 12 and 6 monthly cycles, out to five and 20-year time horizon. Results DES model output had a close fit to the actual data. Irrespective of the modelling method, the cycle length of MM or the time horizon, transplanting a low-quality kidney as compared to remaining waitlisted was the dominant strategy. However, there were discrepancies in costs, effectiveness and net monetary benefit (NMB) among different modelling methods. The incremental NMB of the MM in the 6-months cycle lengths was a closer fit to the incremental NMB of the DES. The gap in the fit of the two cycle lengths to DES output reduced as the time horizon increased. Conclusion Different modelling methods were unlikely to influence the decision to accept a lower quality kidney transplant or remain waitlisted on dialysis. Both models produced similar results when time-dependant transition probabilities are used, most notable with shorter cycle lengths and longer time-horizons.

Suggested Citation

  • Sameera Senanayake & Nicholas Graves & Helen Healy & Keshwar Baboolal & Adrian Barnett & Sanjeewa Kularatna, 2021. "Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney," Health Economics Review, Springer, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:spr:hecrev:v:11:y:2021:i:1:d:10.1186_s13561-021-00312-4
    DOI: 10.1186/s13561-021-00312-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13561-021-00312-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s13561-021-00312-4?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. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    2. Jonathan Karnon, 2003. "Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation," Health Economics, John Wiley & Sons, Ltd., vol. 12(10), pages 837-848, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sameera Senanayake & Helen Healy & Steven M. McPhail & Keshwar Baboolal & Sanjeewa Kularatna, 2022. "Cost-Effectiveness and Budget Impact Analysis of Implementing a 'Soft Opt-Out' System for Kidney Donation in Australia," Applied Health Economics and Health Policy, Springer, vol. 20(5), pages 769-779, September.

    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. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    2. Marta O Soares & L Canto e Castro, 2010. "Simulation or cohort models? Continuous time simulation and discretized Markov models to estimate cost-effectiveness," Working Papers 056cherp, Centre for Health Economics, University of York.
    3. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    4. Francisco J. Díez & Mar Yebra & Iñigo Bermejo & Miguel A. Palacios-Alonso & Manuel Arias Calleja & Manuel Luque & Jorge Pérez-Martín, 2017. "Markov Influence Diagrams," Medical Decision Making, , vol. 37(2), pages 183-195, February.
    5. Mattias Ekman & Peter Lindgren & Carolin Miltenburger & Genevieve Meier & Julie Locklear & Mary Chatterton, 2012. "Cost Effectiveness of Quetiapine in Patients with Acute Bipolar Depression and in Maintenance Treatment after an Acute Depressive Episode," PharmacoEconomics, Springer, vol. 30(6), pages 513-530, June.
    6. An Tran-Duy & Annelies Boonen & Wietske Kievit & Piet Riel & Mart Laar & Johan Severens, 2014. "Modelling Outcomes of Complex Treatment Strategies Following a Clinical Guideline for Treatment Decisions in Patients with Rheumatoid Arthritis," PharmacoEconomics, Springer, vol. 32(10), pages 1015-1028, October.
    7. John Graves & Shawn Garbett & Zilu Zhou & Jonathan S. Schildcrout & Josh Peterson, 2021. "Comparison of Decision Modeling Approaches for Health Technology and Policy Evaluation," Medical Decision Making, , vol. 41(4), pages 453-464, May.
    8. Chiranjeev Sanyal & Don Husereau, 2020. "Systematic Review of Economic Evaluations of Services Provided by Community Pharmacists," Applied Health Economics and Health Policy, Springer, vol. 18(3), pages 375-392, June.
    9. Mark Oppe & Daniela Ortín-Sulbarán & Carlos Vila Silván & Anabel Estévez-Carrillo & Juan M. Ramos-Goñi, 2021. "Cost-effectiveness of adding Sativex® spray to spasticity care in Belgium: using bootstrapping instead of Monte Carlo simulation for probabilistic sensitivity analyses," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 711-721, July.
    10. Kaitlyn Hastings & Clara Marquina & Jedidiah Morton & Dina Abushanab & Danielle Berkovic & Stella Talic & Ella Zomer & Danny Liew & Zanfina Ademi, 2022. "Projected New-Onset Cardiovascular Disease by Socioeconomic Group in Australia," PharmacoEconomics, Springer, vol. 40(4), pages 449-460, April.
    11. Andrea Marcellusi & Raffaella Viti & Loreta A. Kondili & Stefano Rosato & Stefano Vella & Francesco Saverio Mennini, 2019. "Economic Consequences of Investing in Anti-HCV Antiviral Treatment from the Italian NHS Perspective: A Real-World-Based Analysis of PITER Data," PharmacoEconomics, Springer, vol. 37(2), pages 255-266, February.
    12. Risha Gidwani & Louise B. Russell, 2020. "Estimating Transition Probabilities from Published Evidence: A Tutorial for Decision Modelers," PharmacoEconomics, Springer, vol. 38(11), pages 1153-1164, November.
    13. Joseph F. Levy & Marjorie A. Rosenberg, 2019. "A Latent Class Approach to Modeling Trajectories of Health Care Cost in Pediatric Cystic Fibrosis," Medical Decision Making, , vol. 39(5), pages 593-604, July.
    14. Qi Cao & Erik Buskens & Hans L. Hillege & Tiny Jaarsma & Maarten Postma & Douwe Postmus, 2019. "Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 475-482, April.
    15. Jorge Luis García & James J. Heckman, 2021. "Early childhood education and life‐cycle health," Health Economics, John Wiley & Sons, Ltd., vol. 30(S1), pages 119-141, November.
    16. Tushar Srivastava & Nicholas R. Latimer & Paul Tappenden, 2021. "Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals," PharmacoEconomics, Springer, vol. 39(8), pages 869-878, August.
    17. Eleanor Heather & Katherine Payne & Mark Harrison & Deborah Symmons, 2014. "Including Adverse Drug Events in Economic Evaluations of Anti-Tumour Necrosis Factor-α Drugs for Adult Rheumatoid Arthritis: A Systematic Review of Economic Decision Analytic Models," PharmacoEconomics, Springer, vol. 32(2), pages 109-134, February.
    18. Manuel Gomes & Robert Aldridge & Peter Wylie & James Bell & Owen Epstein, 2013. "Cost-Effectiveness Analysis of 3-D Computerized Tomography Colonography Versus Optical Colonoscopy for Imaging Symptomatic Gastroenterology Patients," Applied Health Economics and Health Policy, Springer, vol. 11(2), pages 107-117, April.
    19. Isaac Corro Ramos & Maureen P. M. H. Rutten-van Mölken & Maiwenn J. Al, 2013. "The Role of Value-of-Information Analysis in a Health Care Research Priority Setting," Medical Decision Making, , vol. 33(4), pages 472-489, May.
    20. Wei Fang & Zhenru Wang & Michael B. Giles & Chris H. Jackson & Nicky J. Welton & Christophe Andrieu & Howard Thom, 2022. "Multilevel and Quasi Monte Carlo Methods for the Calculation of the Expected Value of Partial Perfect Information," Medical Decision Making, , vol. 42(2), pages 168-181, February.

    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:hecrev:v:11:y:2021:i:1:d:10.1186_s13561-021-00312-4. 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/economics/journal/13561 .

    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.