IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v22y2019i1d10.1007_s10729-017-9426-2.html
   My bibliography  Save this article

Reducing COPD readmissions through predictive modeling and incentive-based interventions

Author

Listed:
  • Xiang Zhong

    (University of Florida)

  • Sujee Lee

    (University of Wisconsin)

  • Cong Zhao

    (University of Wisconsin)

  • Hyo Kyung Lee

    (University of Wisconsin)

  • Philip A. Bain

    (Dean Health System)

  • Tammy Kundinger

    (St. Mary’s Hospital)

  • Craig Sommers

    (St. Mary’s Hospital)

  • Christine Baker

    (St. Mary’s Hospital)

  • Jingshan Li

    (University of Wisconsin)

Abstract

This paper introduces a case study at a community hospital to develop a predictive model to quantify readmission risks for patients with chronic obstructive pulmonary disease (COPD), and use it to support decision making for appropriate incentive-based interventions. Data collected from the community hospital’s database are analyzed to identify risk factors and a logistic regression model is developed to predict the readmission risk within 30 days post-discharge of an individual COPD patient. By targeting on the high-risk patients, we investigate the implementability of the incentive policy which encourages patients to take interventions and helps them to overcome the compliance barrier. Specifically, the conditions and scenarios are identified for either achieving the desired readmission rate while minimizing the total cost, or reaching the lowest readmission rate under incentive budget constraint. Currently, such models are under consideration for a pilot study at the community hospital.

Suggested Citation

  • Xiang Zhong & Sujee Lee & Cong Zhao & Hyo Kyung Lee & Philip A. Bain & Tammy Kundinger & Craig Sommers & Christine Baker & Jingshan Li, 2019. "Reducing COPD readmissions through predictive modeling and incentive-based interventions," Health Care Management Science, Springer, vol. 22(1), pages 121-139, March.
    • Handle: RePEc:kap:hcarem:v:22:y:2019:i:1:d:10.1007_s10729-017-9426-2
    DOI: 10.1007/s10729-017-9426-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-017-9426-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10729-017-9426-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sheldon H. Jacobson & Shane N. Hall & James R. Swisher, 2006. "Discrete-Event Simulation of Health Care Systems," International Series in Operations Research & Management Science, in: Randolph W. Hall (ed.), Patient Flow: Reducing Delay in Healthcare Delivery, chapter 0, pages 211-252, Springer.
    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. Xiang Zhong & Jie Song & Jingshan Li & Susan M. Ertl & Lauren Fiedler, 2016. "Design and analysis of gastroenterology (GI) clinic in Digestive Health Center of University of Wisconsin Health," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 90-119, June.
    2. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.
    3. Kenneth Martínez & David Claudio, 2023. "Expanding Fundamental Boundaries between Resilience and Survivability in Systems Engineering: A Literature Review," Sustainability, MDPI, vol. 15(6), pages 1-27, March.
    4. Zexian Zeng & Zhenghao Fan & Xiaolei Xie & Colleen H. Swartz & Paul DePriest & Jingshan Li, 2020. "A two-level iteration approach for modeling and analysis of rapid response process with multiple deteriorating patients," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 35-71, March.
    5. Ran Liu & Xiaolan Xie, 2018. "Physician Staffing for Emergency Departments with Time-Varying Demand," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 588-607, August.
    6. Syed Salleh & Praveen Thokala & Alan Brennan & Ruby Hughes & Andrew Booth, 2017. "Simulation Modelling in Healthcare: An Umbrella Review of Systematic Literature Reviews," PharmacoEconomics, Springer, vol. 35(9), pages 937-949, September.
    7. Pablo Santibáñez & Vincent Chow & John French & Martin Puterman & Scott Tyldesley, 2009. "Reducing patient wait times and improving resource utilization at British Columbia Cancer Agency’s ambulatory care unit through simulation," Health Care Management Science, Springer, vol. 12(4), pages 392-407, December.
    8. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    9. Song-Hee Kim & Ward Whitt & Won Chul Cha, 2018. "A Data-Driven Model of an Appointment-Generated Arrival Process at an Outpatient Clinic," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 181-199, February.
    10. Melo, Teresa, 2012. "A note on challenges and opportunities for Operations Research in hospital logistics," Technical Reports on Logistics of the Saarland Business School 2, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    11. J. Jaime Caro & Andrew H. Briggs & Uwe Siebert & Karen M. Kuntz, 2012. "Modeling Good Research Practices—Overview," Medical Decision Making, , vol. 32(5), pages 667-677, September.
    12. 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.
    13. Inas S. Khayal & Amro M. Farid, 2018. "Architecting a System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes," Complexity, Hindawi, vol. 2018, pages 1-24, March.
    14. Lalit Garg & Sally McClean & Brian Meenan & Peter Millard, 2010. "A non-homogeneous discrete time Markov model for admission scheduling and resource planning in a cost or capacity constrained healthcare system," Health Care Management Science, Springer, vol. 13(2), pages 155-169, June.
    15. Vahab Vahdat & Jacqueline Griffin & James E. Stahl, 2018. "Decreasing patient length of stay via new flexible exam room allocation policies in ambulatory care clinics," Health Care Management Science, Springer, vol. 21(4), pages 492-516, December.
    16. Martin Comis & Catherine Cleophas & Christina Büsing, 2021. "Patients, primary care, and policy: Agent-based simulation modeling for health care decision support," Health Care Management Science, Springer, vol. 24(4), pages 799-826, December.
    17. Xiang Zhong & Hyo Kyung Lee & Molly Williams & Sally Kraft & Jeffery Sleeth & Richard Welnick & Lori Hauschild & Jingshan Li, 2018. "Workload balancing: staffing ratio analysis for primary care redesign," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 6-29, June.
    18. Hui Zhang & Thomas J. Best & Anton Chivu & David O. Meltzer, 2020. "Simulation-based optimization to improve hospital patient assignment to physicians and clinical units," Health Care Management Science, Springer, vol. 23(1), pages 117-141, March.
    19. Thomas Hanne & Teresa Melo & Stefan Nickel, 2009. "Bringing Robustness to Patient Flow Management Through Optimized Patient Transports in Hospitals," Interfaces, INFORMS, vol. 39(3), pages 241-255, June.
    20. Pengyi Shi & Mabel C. Chou & J. G. Dai & Ding Ding & Joe Sim, 2016. "Models and Insights for Hospital Inpatient Operations: Time-Dependent ED Boarding Time," Management Science, INFORMS, vol. 62(1), pages 1-28, January.

    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:kap:hcarem:v:22:y:2019:i:1:d:10.1007_s10729-017-9426-2. 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.