IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v37y2017i2p253-263.html
   My bibliography  Save this article

Understanding the Effects of Competition for Constrained Colonoscopy Services with the Introduction of Population-level Colorectal Cancer Screening

Author

Listed:
  • Leslie Anne Campbell
  • John T. Blake
  • George Kephart
  • Eva Grunfeld
  • Donald MacIntosh

Abstract

Background : Median wait times for gastroenterology services in Canada exceed consensus-recommended targets and have worsened substantially over the past decade. Meanwhile, efforts to control colorectal cancer have shifted their focus to screening asymptomatic, average-risk individuals. Along with increasing prevalence of colorectal cancer due to an aging population, screening programs are expected to add substantially to the existing burden on colonoscopy services, and create competition for limited services among individuals of varying risk. Failure to understand the effects of operational programmatic screening decisions may cause unintended harm to both screening participants and higher-risk patients, make inefficient use of limited health care resources, and ultimately hinder a program’s success. Methods : We present a new simulation model (Simulation of Cancer Outcomes for Planning Exercises, or SCOPE) for colorectal cancer screening which, unlike many other colorectal cancer screening models, reflects the effects of competition for limited colonoscopy services between patient groups and can be used to guide planning to ensure adequate resource allocation. We include verification and validation results for the SCOPE model. Results : A discrete event simulation model was developed based on an epidemiological representation of colorectal cancer in a sample population. Colonoscopy service and screening modules were added to allow observation of screening scenarios and resource considerations. The model reproduces population-based data on prevalence of colorectal cancer by stage, and mortality by cause of death, age, and sex, and attendant demand and wait times for colonoscopy services. Conclusions : The study model differs from existing screening models in that it explicitly considers the colonoscopy resource implications of screening activities and the impact of constrained resources on screening effectiveness.

Suggested Citation

  • Leslie Anne Campbell & John T. Blake & George Kephart & Eva Grunfeld & Donald MacIntosh, 2017. "Understanding the Effects of Competition for Constrained Colonoscopy Services with the Introduction of Population-level Colorectal Cancer Screening," Medical Decision Making, , vol. 37(2), pages 253-263, February.
  • Handle: RePEc:sae:medema:v:37:y:2017:i:2:p:253-263
    DOI: 10.1177/0272989X16670638
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X16670638
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X16670638?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. 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)

    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. Topuz, Kazim & Urban, Timothy L. & Yildirim, Mehmet B., 2024. "A Markovian score model for evaluating provider performance for continuity of care—An explainable analytics approach," European Journal of Operational Research, Elsevier, vol. 317(2), pages 341-351.
    2. Hossein Haji Ali Afzali & Jonathan Karnon & Jodi Gray, 2012. "A proposed model for economic evaluations of major depressive disorder," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(4), pages 501-510, August.
    3. Schulenburg J.-Matthias Graf von der & Vauth Christoph, 2007. "Nach welchen ökonomischen Methoden sollten Gesundheitsleistungen in Deutschland evaluiert werden? / According to Which Economic Methods Should Health Care Services Become Evaluated in Germany?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(5-6), pages 787-806, October.
    4. Matthew J. Glover & Edmund Jones & Katya L. Masconi & Michael J. Sweeting & Simon G. Thompson, 2018. "Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening," Medical Decision Making, , vol. 38(4), pages 439-451, May.
    5. K Cooper & S C Brailsford & R Davies, 2007. "Choice of modelling technique for evaluating health care interventions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 168-176, February.
    6. L. B. Standfield & T. A. Comans & P. A. Scuffham, 2017. "An empirical comparison of Markov cohort modeling and discrete event simulation in a capacity-constrained health care setting," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(1), pages 33-47, January.
    7. Hareth Al-Janabi & Jenny Coles & John Copping & Nishit Dhanji & Carol McLoughlin & Jacky Murphy & Jean Nicholls, 2021. "Patient and Public Involvement (PPI) in Health Economics Methodology Research: Reflections and Recommendations," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(4), pages 421-427, July.
    8. James O’Mahony & Anthony Newall & Joost Rosmalen, 2015. "Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice," PharmacoEconomics, Springer, vol. 33(12), pages 1255-1268, December.
    9. Jesús Isaac Vázquez-Serrano & Rodrigo E. Peimbert-García & Leopoldo Eduardo Cárdenas-Barrón, 2021. "Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    10. 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.
    11. Robin de Vries & Mirjam Kretzschmar & Joop F P Schellekens & Florens G A Versteegh & Tjalke A Westra & John J Roord & Maarten J Postma, 2010. "Cost-Effectiveness of Adolescent Pertussis Vaccination for The Netherlands: Using an Individual-Based Dynamic Model," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-11, October.
    12. Syed Mohiuddin, 2014. "A Systematic and Critical Review of Model-Based Economic Evaluations of Pharmacotherapeutics in Patients with Bipolar Disorder," Applied Health Economics and Health Policy, Springer, vol. 12(4), pages 359-372, August.
    13. 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.
    14. 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.
    15. 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.
    16. Lih-Wen Mau & Jaime M. Preussler & Linda J. Burns & Susan Leppke & Navneet S. Majhail & Christa L. Meyer & Tatenda Mupfudze & Wael Saber & Patricia Steinert & David J. Vanness, 2020. "Healthcare Costs of Treating Privately Insured Patients with Acute Myeloid Leukemia in the United States from 2004 to 2014: A Generalized Additive Modeling Approach," PharmacoEconomics, Springer, vol. 38(5), pages 515-526, May.
    17. Annemieke Leunis & W. Redekop & Kees van Montfort & Bob Löwenberg & Carin Uyl-de Groot, 2013. "The Development and Validation of a Decision-Analytic Model Representing the Full Disease Course of Acute Myeloid Leukemia," PharmacoEconomics, Springer, vol. 31(7), pages 605-621, July.
    18. 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.
    19. Olivier Ethgen & Baudouin Standaert, 2012. "Population–versus Cohort–Based Modelling Approaches," PharmacoEconomics, Springer, vol. 30(3), pages 171-181, March.
    20. James A. Hall & Kika Konstantinou & Martyn Lewis & Raymond Oppong & Reuben Ogollah & Sue Jowett, 2019. "Systematic Review of Decision Analytic Modelling in Economic Evaluations of Low Back Pain and Sciatica," Applied Health Economics and Health Policy, Springer, vol. 17(4), pages 467-491, August.

    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:37:y:2017:i:2:p:253-263. 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: 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.