IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i7p3510-d525632.html
   My bibliography  Save this article

Flexibility and Bed Margins of the Community of Madrid’s Hospitals during the First Wave of the SARS-CoV-2 Pandemic

Author

Listed:
  • Eugenio F. Sánchez-Úbeda

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain)

  • Pedro Sánchez-Martín

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain)

  • Macarena Torrego-Ellacuría

    (Unidad de Innovación, Hospital Clínico San Carlos, IdISSC, 28040 Madrid, Spain)

  • Ángel Del Rey-Mejías

    (Unidad de Innovación, Hospital Clínico San Carlos, IdISSC, 28040 Madrid, Spain
    Departamento de Psicobiología y Metodología en Ciencias del Comportamiento, Facultad de Psicología, Universidad Complutense, 28223 Madrid, Spain)

  • Manuel F. Morales-Contreras

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain
    Faculty of Business Management and Economics, ICADE, Comillas Pontifical University, 28015 Madrid, Spain)

  • José-Luis Puerta

    (Consejería de Sanidad y Dirección General de Estadística, Comunidad de Madrid, 28013 Madrid, Spain)

Abstract

Background: The COVID-19 pandemic has had global effects; cases have been counted in the tens of millions, and there have been over two million deaths throughout the world. Health systems have been stressed in trying to provide a response to the increasing demand for hospital beds during the different waves. This paper analyzes the dynamic response of the hospitals of the Community of Madrid (CoM) during the first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in the period between 18 March and 31 May 2020. The aim was to model the response of the CoM’s health system in terms of the number of available beds. Methods: A research design based on a case study of the CoM was developed. To model this response, we use two concepts: “bed margin” (available beds minus occupied beds, expressed as a percentage) and “flexibility” (which describes the ability to adapt to the growing demand for beds). The Linear Hinges Model allowed a robust estimation of the key performance indicators for capturing the flexibility of the available beds in hospitals. Three new flexibility indicators were defined: the Average Ramp Rate Until the Peak (ARRUP), the Ramp Duration Until the Peak (RDUP), and the Ramp Growth Until the Peak (RGUP). Results: The public and private hospitals of the CoM were able to increase the number of available beds from 18,692 on 18 March 2020 to 23,623 on 2 April 2020. At the peak of the wave, the number of available beds increased by 160 in 48 h, with an occupancy of 90.3%. Within that fifteen-day period, the number of COVID-19 inpatients increased by 200% in non-intensive care unit (non-ICU) wards and by 155% in intensive care unit (ICU) wards. The estimated ARRUP for non-ICU beds in the CoM hospital network during the first pandemic wave was 305.56 beds/day, the RDUP was 15 days, and the RGUP was 4598 beds. For the ICU beds, the ARRUP was 36.73 beds/day, the RDUP was 20 days, and the RGUP was 735 beds. This paper includes a further analysis of the response estimated for each hospital. Conclusions: This research provides insights not only for academia, but also for hospital management and practitioners. The results show that not all of the hospitals dealt with the sudden increase in bed demand in the same way, nor did they provide the same flexibility in order to increase their bed capabilities. The bed margin and the proposed indicators of flexibility summarize the dynamic response and can be included as part of a hospital’s management dashboard for monitoring its behavior during pandemic waves or other health crises as a complement to other, more steady-state indicators.

Suggested Citation

  • Eugenio F. Sánchez-Úbeda & Pedro Sánchez-Martín & Macarena Torrego-Ellacuría & Ángel Del Rey-Mejías & Manuel F. Morales-Contreras & José-Luis Puerta, 2021. "Flexibility and Bed Margins of the Community of Madrid’s Hospitals during the First Wave of the SARS-CoV-2 Pandemic," IJERPH, MDPI, vol. 18(7), pages 1-22, March.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3510-:d:525632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/7/3510/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/7/3510/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ludwig Kuntz & Stefan Scholtes & Antonio Vera, 2007. "Incorporating efficiency in hospital-capacity planning in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 8(3), pages 213-223, September.
    2. Miguel Casares & Hashmat Khan, 2020. "The Timing and Intensity of Social Distancing to Flatten the COVID-19 Curve: The Case of Spain," IJERPH, MDPI, vol. 17(19), pages 1-14, October.
    3. Edward H. Kaplan, 2020. "Containing 2019-nCoV (Wuhan) coronavirus," Health Care Management Science, Springer, vol. 23(3), pages 311-314, September.
    4. Richard M Wood & Christopher J McWilliams & Matthew J Thomas & Christopher P Bourdeaux & Christos Vasilakis, 2020. "COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care," Health Care Management Science, Springer, vol. 23(3), pages 315-324, September.
    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. Matthias Klumpp & Dominic Loske & Silvio Bicciato, 2022. "COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1263-1285, November.
    2. G.J. Melman & A.K. Parlikad & E.A.B. Cameron, 2021. "Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation," Health Care Management Science, Springer, vol. 24(2), pages 356-374, June.
    3. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    4. Linying Yang & Teng Zhang & Peter Glynn & David Scheinker, 2021. "The development and deployment of a model for hospital-level COVID-19 associated patient demand intervals from consistent estimators (DICE)," Health Care Management Science, Springer, vol. 24(2), pages 375-401, June.
    5. 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).
    6. Gillis, Melissa & Urban, Ryley & Saif, Ahmed & Kamal, Noreen & Murphy, Matthew, 2021. "A simulation–optimization framework for optimizing response strategies to epidemics," Operations Research Perspectives, Elsevier, vol. 8(C).
    7. Richard M. Wood & Adrian C. Pratt & Charlie Kenward & Christopher J. McWilliams & Ross D. Booton & Matthew J. Thomas & Christopher P. Bourdeaux & Christos Vasilakis, 2021. "The Value of Triage during Periods of Intense COVID-19 Demand: Simulation Modeling Study," Medical Decision Making, , vol. 41(4), pages 393-407, May.
    8. Anna Nagurney & Pritha Dutta, 2021. "A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model," SN Operations Research Forum, Springer, vol. 2(3), pages 1-30, September.
    9. Costase Ndayishimiye & Christoph Sowada & Patrycja Dyjach & Agnieszka Stasiak & John Middleton & Henrique Lopes & Katarzyna Dubas-Jakóbczyk, 2022. "Associations between the COVID-19 Pandemic and Hospital Infrastructure Adaptation and Planning—A Scoping Review," IJERPH, MDPI, vol. 19(13), pages 1-22, July.
    10. Joseph T. Chang & Forrest W. Crawford & Edward H. Kaplan, 2021. "Repeat SARS-CoV-2 testing models for residential college populations," Health Care Management Science, Springer, vol. 24(2), pages 305-318, June.
    11. Atul Pokharel & Robert Soulé & Avi Silberschatz, 2021. "A case for location based contact tracing," Health Care Management Science, Springer, vol. 24(2), pages 420-438, June.
    12. Akira Watanabe & Hiroyuki Matsuda, 2023. "Effectiveness of feedback control and the trade-off between death by COVID-19 and costs of countermeasures," Health Care Management Science, Springer, vol. 26(1), pages 46-61, March.
    13. Samantha L. Zimmerman & Alexander R. Rutherford & Alexa Waall & Monica Norena & Peter Dodek, 2023. "A queuing model for ventilator capacity management during the COVID-19 pandemic," Health Care Management Science, Springer, vol. 26(2), pages 200-216, June.
    14. Kostas Kounetas & Fotis Papathanassopoulos, 2013. "How efficient are Greek hospitals? A case study using a double bootstrap DEA approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(6), pages 979-994, December.
    15. Dana Jašková, 2021. "Efficiency of management processes in a private hospital," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(1), pages 436-446, September.
    16. Katarzyna Dubas-Jakóbczyk & Ewa Kocot & Anna Kozieł, 2020. "Financial Performance of Public Hospitals: A Cross-Sectional Study among Polish Providers," IJERPH, MDPI, vol. 17(7), pages 1-14, March.
    17. Berta, P. & Bratti, M. & Fiorio, C.V. & Pisoni, E. & Verzillo, S., 2021. "Administrative border effects in Covid-19 related mortality," Health, Econometrics and Data Group (HEDG) Working Papers 21/21, HEDG, c/o Department of Economics, University of York.
    18. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    19. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2024. "Testing, Voluntary Social Distancing, and the Spread of an Infection," Operations Research, INFORMS, vol. 72(2), pages 533-548, March.
    20. Michaela-Maria Schaffhauser-Linzatti & Achim Zeileis & Marion Rauner, 2009. "Effects of the Austrian performance-oriented inpatient reimbursement system on treatment patterns: illustrated on cases with knee-joint problems," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 17(3), pages 293-314, September.

    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:gam:jijerp:v:18:y:2021:i:7:p:3510-:d:525632. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.