IDEAS home Printed from https://ideas.repec.org/a/inm/orserv/v11y2019i2p113-137.html
   My bibliography  Save this article

Regional Planning Model for Cancer Screening with Imperfect Patient Adherence

Author

Listed:
  • Aaron Ratcliffe

    (Department of Computer Information Systems and Supply Chain Management, Appalachian State University, Boone, North Carolina 28608-2049;)

  • Ann Marucheck

    (Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599-3490)

  • Sean Xin Xu

    (Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599-3490)

Abstract

The effectiveness of cancer screening and adherence to cancer screening guidelines can be inhibited by long wait times for screening appointments. We develop a queueing network model of screening for a disease within a population of patients with imperfect adherence to screening guidelines to characterize the relationship between the screening request frequency rate and the wait time for screens. We first use our model to derive the capacity needed by a given system or the population size a given system can serve to guarantee a certain service level. We analyze routine screening for average-risk patients as well as the additional capacity required for diagnostic screening and surveillance of high-risk patients. We perform a numerical study using national public health data for colorectal cancer (CRC) screening in the United States and provide insights for public health officials, providers, and policy makers by showing how queueing models can be applied to regional planning decisions for determining CRC screening capacity requirements.

Suggested Citation

  • Aaron Ratcliffe & Ann Marucheck & Sean Xin Xu, 2019. "Regional Planning Model for Cancer Screening with Imperfect Patient Adherence," Service Science, INFORMS, vol. 11(2), pages 113-137, June.
    • Handle: RePEc:inm:orserv:v:11:y:2019:i:2:p:113-137
    DOI: 10.1287/serv.2018.0232
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/serv.2018.0232
    Download Restriction: no
    File URL: https://libkey.io/10.1287/serv.2018.0232?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. Suleyman Özekici & Stanley R. Pliska, 1991. "Optimal Scheduling of Inspections: A Delayed Markov Model with False Positives and Negatives," Operations Research, INFORMS, vol. 39(2), pages 261-273, April.
    2. Bjorn P. Berg & Michael Murr & David Chermak & Jonathan Woodall & Michael Pignone & Robert S. Sandler & Brian T. Denton, 2013. "Estimating the Cost of No-Shows and Evaluating the Effects of Mitigation Strategies," Medical Decision Making, , vol. 33(8), pages 976-985, November.
    3. Sarang Deo & Seyed Iravani & Tingting Jiang & Karen Smilowitz & Stephen Samuelson, 2013. "Improving Health Outcomes Through Better Capacity Allocation in a Community-Based Chronic Care Model," Operations Research, INFORMS, vol. 61(6), pages 1277-1294, December.
    4. Evrim Didem Güneş & Egemen Lerzan Örmeci & Derya Kunduzcu, 2015. "Preventing and Diagnosing Colorectal Cancer with a Limited Colonoscopy Resource," Production and Operations Management, Production and Operations Management Society, vol. 24(1), pages 1-20, January.
    5. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    6. Chaitra Gopalappa & Selen Aydogan-Cremaschi & Tapas Das & Seza Orcun, 2011. "Probability model for estimating colorectal polyp progression rates," Health Care Management Science, Springer, vol. 14(1), pages 1-21, March.
    7. Fatih Safa Erenay & Oguzhan Alagoz & Adnan Said, 2014. "Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 381-400, July.
    8. Linda V. Green & Sergei Savin, 2008. "Reducing Delays for Medical Appointments: A Queueing Approach," Operations Research, INFORMS, vol. 56(6), pages 1526-1538, December.
    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. Kılıç, Hakan & Güneş, Evrim Didem, 2024. "Patient adherence in healthcare operations: A narrative review," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).

    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. Hessam Bavafa & Sergei Savin & Christian Terwiesch, 2021. "Customizing Primary Care Delivery Using E‐Visits," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4306-4327, November.
    2. E. Lerzan Örmeci & Evrim Didem Güneş & Derya Kunduzcu, 2016. "A Modeling Framework for Control of Preventive Services," Manufacturing & Service Operations Management, INFORMS, vol. 18(2), pages 227-244, May.
    3. Wang, Fan & Zhang, Shengfan & Henderson, Louise M., 2018. "Adaptive decision-making of breast cancer mammography screening: A heuristic-based regression model," Omega, Elsevier, vol. 76(C), pages 70-84.
    4. Elliot Lee & Mariel S. Lavieri & Michael Volk, 2019. "Optimal Screening for Hepatocellular Carcinoma: A Restless Bandit Model," Service Science, INFORMS, vol. 21(1), pages 198-212, January.
    5. Kılıç, Hakan & Güneş, Evrim Didem, 2024. "Patient adherence in healthcare operations: A narrative review," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    6. Elliot Lee & Mariel Lavieri & Michael Volk & Yongcai Xu, 2015. "Applying reinforcement learning techniques to detect hepatocellular carcinoma under limited screening capacity," Health Care Management Science, Springer, vol. 18(3), pages 363-375, September.
    7. Robert Kraig Helmeczi & Can Kavaklioglu & Mucahit Cevik & Davood Pirayesh Neghab, 2023. "A multi-objective constrained partially observable Markov decision process model for breast cancer screening," Operational Research, Springer, vol. 23(2), pages 1-42, June.
    8. Hessam Bavafa & Lorin M. Hitt & Christian Terwiesch, 2018. "The Impact of E-Visits on Visit Frequencies and Patient Health: Evidence from Primary Care," Management Science, INFORMS, vol. 64(12), pages 5461-5480, December.
    9. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout & Elizabeth S. Burnside, 2016. "Heterogeneity in Women’s Adherence and Its Role in Optimal Breast Cancer Screening Policies," Management Science, INFORMS, vol. 62(5), pages 1339-1362, May.
    10. Kazim Topuz & Timothy L. Urban & Robert A. Russell & Mehmet B. Yildirim, 2024. "Decision support system for appointment scheduling and overbooking under patient no-show behavior," Annals of Operations Research, Springer, vol. 342(1), pages 845-873, November.
    11. Xiao Yu & Armagan Bayram, 2021. "Managing capacity for virtual and office appointments in chronic care," Health Care Management Science, Springer, vol. 24(4), pages 742-767, December.
    12. Turgay Ayer, 2015. "Inverse optimization for assessing emerging technologies in breast cancer screening," Annals of Operations Research, Springer, vol. 230(1), pages 57-85, July.
    13. Wesley J. Marrero & Mariel S. Lavieri & Jeremy B. Sussman, 2021. "Optimal cholesterol treatment plans and genetic testing strategies for cardiovascular diseases," Health Care Management Science, Springer, vol. 24(1), pages 1-25, March.
    14. Zlatana Nenova & Jennifer Shang, 2022. "Personalized Chronic Disease Follow‐Up Appointments: Risk‐Stratified Care Through Big Data," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 583-606, February.
    15. Boloori, Alireza & Saghafian, Soroush & Chakkera, Harini A. A. & Cook, Curtiss B., 2017. "Data-Driven Management of Post-transplant Medications: An APOMDP Approach," Working Paper Series rwp17-036, Harvard University, John F. Kennedy School of Government.
    16. Tinglong Dai & Sridhar Tayur, 2020. "OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 869-887, September.
    17. Ting-Yu Ho & Shan Liu & Zelda B. Zabinsky, 2019. "A Multi-Fidelity Rollout Algorithm for Dynamic Resource Allocation in Population Disease Management," Health Care Management Science, Springer, vol. 22(4), pages 727-755, December.
    18. Jonathan E. Helm & Mariel S. Lavieri & Mark P. Van Oyen & Joshua D. Stein & David C. Musch, 2015. "Dynamic Forecasting and Control Algorithms of Glaucoma Progression for Clinician Decision Support," Operations Research, INFORMS, vol. 63(5), pages 979-999, October.
    19. Ali Hajjar & Oguzhan Alagoz, 2023. "Personalized Disease Screening Decisions Considering a Chronic Condition," Management Science, INFORMS, vol. 69(1), pages 260-282, January.
    20. Jingui Xie & Weifen Zhuang & Marcus Ang & Mabel C. Chou & Li Luo & David D. Yao, 2021. "Analytics for Hospital Resource Planning—Two Case Studies," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1863-1885, June.

    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:inm:orserv:v:11:y:2019:i:2:p:113-137. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.