IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v62y2014i6p1265-1282.html
   My bibliography  Save this article

Design and Optimization Methods for Elective Hospital Admissions

Author

Listed:
  • Jonathan E. Helm

    (Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Mark P. Van Oyen

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

Hospitals typically lack effective enterprise level strategic planning of bed and care resources, contributing to bed census levels that are statistically “out of control.” This system dysfunction manifests itself in bed block, surgical cancelation, ambulance diversions, and operational chaos. This is the classic hospital admission scheduling and control (HASC) problem, which has been addressed in its entirety only through inexact simulation-based search heuristics. This paper develops new analytical models of controlled hospital census that can, for the first time, be incorporated into a mixed-integer programming model to optimally solve the strategic planning/scheduling portion of the HASC. Our new solution method coordinates elective admissions with other hospital subsystems to reduce system congestion. We formulate a new Poisson-arrival-location model (PALM) based on an innovative stochastic location process that we developed and call the patient temporal resource needs model. We further extend the PALM approach to the class of deterministic controlled-arrival-location models (d-CALM) and develop linearizing approximations to stochastic blocking metrics. This work provides the theoretical foundations for an efficient scheduled admissions planning system as well as a practical decision support methodology to stabilize hospital census.

Suggested Citation

  • Jonathan E. Helm & Mark P. Van Oyen, 2014. "Design and Optimization Methods for Elective Hospital Admissions," Operations Research, INFORMS, vol. 62(6), pages 1265-1282, December.
    • Handle: RePEc:inm:oropre:v:62:y:2014:i:6:p:1265-1282
    DOI: 10.1287/opre.2014.1317
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.2014.1317
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2014.1317?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. Ivo Adan & Jos Bekkers & Nico Dellaert & Jan Vissers & Xiaoting Yu, 2009. "Patient mix optimisation and stochastic resource requirements: A case study in cardiothoracic surgery planning," Health Care Management Science, Springer, vol. 12(2), pages 129-141, June.
    2. René Bekker & Paulien Koeleman, 2011. "Scheduling admissions and reducing variability in bed demand," Health Care Management Science, Springer, vol. 14(3), pages 237-249, September.
    3. Yunan Liu & Ward Whitt, 2011. "A Network of Time-Varying Many-Server Fluid Queues with Customer Abandonment," Operations Research, INFORMS, vol. 59(4), pages 835-846, August.
    4. J B Jun & S H Jacobson & J R Swisher, 1999. "Application of discrete-event simulation in health care clinics: A survey," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(2), pages 109-123, February.
    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. Jim G. Dai & Pengyi Shi, 2021. "Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1838-1862, June.
    2. Jillian A. Berry Jaeker & Anita L. Tucker, 2017. "Past the Point of Speeding Up: The Negative Effects of Workload Saturation on Efficiency and Patient Severity," Management Science, INFORMS, vol. 63(4), pages 1042-1062, April.
    3. Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017. "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, vol. 262(1), pages 60-74.
    4. Neyshabouri, Saba & Berg, Bjorn P., 2017. "Two-stage robust optimization approach to elective surgery and downstream capacity planning," European Journal of Operational Research, Elsevier, vol. 260(1), pages 21-40.
    5. Karsten Schwarz & Michael Römer & Taïeb Mellouli, 2019. "A data-driven hierarchical MILP approach for scheduling clinical pathways: a real-world case study from a German university hospital," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 597-636, December.
    6. Na Geng & Xiaolan Xie, 2022. "Managing Advance Admission Requests for Obstetric Care," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1224-1239, March.
    7. 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.
    8. J. G. Dai & Pengyi Shi, 2019. "Inpatient Overflow: An Approximate Dynamic Programming Approach," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 894-911, October.
    9. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    10. Alex F. Mills & Jonathan E. Helm & Yu Wang, 2021. "Surge Capacity Deployment in Hospitals: Effectiveness of Response and Mitigation Strategies," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 367-387, March.
    11. Soroush Saghafian & Nikolaos Trichakis & Ruihao Zhu & Helen A. Shih, 2023. "Joint patient selection and scheduling under no‐shows: Theory and application in proton therapy," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 547-563, February.
    12. 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.
    13. 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.
    14. Amirhossein Meisami & Jivan Deglise-Hawkinson & Mark E. Cowen & Mark P. Oyen, 2019. "Data-driven optimization methodology for admission control in critical care units," Health Care Management Science, Springer, vol. 22(2), pages 318-335, June.
    15. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    16. David Oakley & Bhakti Stephan Onggo & Dave Worthington, 2020. "Symbiotic simulation for the operational management of inpatient beds: model development and validation using Δ-method," Health Care Management Science, Springer, vol. 23(1), pages 153-169, March.
    17. Hessam Bavafa & Charles M. Leys & Lerzan Örmeci & Sergei Savin, 2019. "Managing Portfolio of Elective Surgical Procedures: A Multidimensional Inverse Newsvendor Problem," Operations Research, INFORMS, vol. 67(6), pages 1543-1563, November.
    18. Minglong Zhou & Melvyn Sim & Shao‐Wei Lam, 2022. "Advance admission scheduling via resource satisficing," Production and Operations Management, Production and Operations Management Society, vol. 31(11), pages 4002-4020, November.

    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. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
    2. Thomas Schneider, A.J. & Theresia van Essen, J. & Carlier, Mijke & Hans, Erwin W., 2020. "Scheduling surgery groups considering multiple downstream resources," European Journal of Operational Research, Elsevier, vol. 282(2), pages 741-752.
    3. 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.
    4. Hessam Bavafa & Charles M. Leys & Lerzan Örmeci & Sergei Savin, 2019. "Managing Portfolio of Elective Surgical Procedures: A Multidimensional Inverse Newsvendor Problem," Operations Research, INFORMS, vol. 67(6), pages 1543-1563, November.
    5. Ana Batista & Jorge Vera & David Pozo, 2020. "Multi-objective admission planning problem: a two-stage stochastic approach," Health Care Management Science, Springer, vol. 23(1), pages 51-65, March.
    6. Kozlowski, Dawid & Worthington, Dave, 2015. "Use of queue modelling in the analysis of elective patient treatment governed by a maximum waiting time policy," European Journal of Operational Research, Elsevier, vol. 244(1), pages 331-338.
    7. Avishai Mandelbaum & Petar Momčilović, 2017. "Personalized queues: the customer view, via a fluid model of serving least-patient first," Queueing Systems: Theory and Applications, Springer, vol. 87(1), pages 23-53, October.
    8. repec:ipg:wpaper:2013-014 is not listed on IDEAS
    9. repec:ipg:wpaper:14 is not listed on IDEAS
    10. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).
    11. Bohui Liang & Ayten Turkcan & Mehmet Erkan Ceyhan & Keith Stuart, 2015. "Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7177-7190, December.
    12. Lixiang Jiang & Ronald Giachetti, 2008. "A queueing network model to analyze the impact of parallelization of care on patient cycle time," Health Care Management Science, Springer, vol. 11(3), pages 248-261, September.
    13. 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.
    14. Ahmet Bahadır Şimşek & Seher Merdane & Aydanur Belindir & Ayşenur Akbaş, 2021. "Pharmacy Duty Scheduling Problem: Gumushane Case," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 9(1), pages 85-98, June.
    15. Mielczarek, Bożena, 2014. "Simulation modelling for contracting hospital emergency services at the regional level," European Journal of Operational Research, Elsevier, vol. 235(1), pages 287-299.
    16. Eren Demir & Christos Vasilakis & Reda Lebcir & David Southern, 2015. "A simulation-based decision support tool for informing the management of patients with Parkinson’s disease," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7238-7251, December.
    17. K Katsaliaki & N Mustafee, 2011. "Applications of simulation within the healthcare context," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1431-1451, August.
    18. Kaya, Onur & Teymourifar, Aydin & Ozturk, Gurkan, 2020. "Analysis of different public policies through simulation to increase total social utility in a healthcare system," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    19. Roshanaei, Vahid & Booth, Kyle E.C. & Aleman, Dionne M. & Urbach, David R. & Beck, J. Christopher, 2020. "Branch-and-check methods for multi-level operating room planning and scheduling," International Journal of Production Economics, Elsevier, vol. 220(C).
    20. Cappanera, Paola & Visintin, Filippo & Banditori, Carlo, 2014. "Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach," International Journal of Production Economics, Elsevier, vol. 158(C), pages 179-196.
    21. Mohammadi Bidhandi, Hadi & Patrick, Jonathan & Noghani, Pedram & Varshoei, Peyman, 2019. "Capacity planning for a network of community health services," European Journal of Operational Research, Elsevier, vol. 275(1), pages 266-279.
    22. Navonil Mustafee & Korina Katsaliaki & Paul Fishwick, 2014. "Exploring the modelling and simulation knowledge base through journal co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2145-2159, March.

    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:oropre:v:62:y:2014:i:6:p:1265-1282. 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.