RAPID: A Portal to Support Models for Assessing Strategies for Hospitals in the COVID-19 and other Pandemics - MASH-Pandemics

  • Funded by National Science Foundation (NSF)
  • Total publications:1 publications

Grant number: 2027624

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $200,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Elise Miller-Hooks
  • Research Location

    United States of America
  • Lead Research Institution

    George Mason University
  • Research Priority Alignment

    N/A
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Supportive care, processes of care and management

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Engineering - This Rapid Response Research (RAPID) grant will develop the Models for Assessing Strategies for Hospitals (MASH) in Pandemics (MASH-Pandemics) Portal with requisite modeling capabilities urgently needed by hospitals and regions in responding to the COVID-19 pandemic. Important perishable, time-sensitive data and information to support this effort will be collected. MASH-Pandemics will build on previously developed sophisticated, detailed discrete-event simulation-based hospital capacity and capability analysis models of typical U.S. urban hospitals. This RAPID project will support the re-specification of these models, data collection, model runs, and results analysis, outcomes from which will aid hospital administrators and regions in making optimal operational changes and collaboration plans enabled through state and national emergency declarations in response to the COVID-19 outbreak. An online portal will be constructed on which details of the modeling capabilities, practical findings and recommendations, along with potential policy implications, for responding to the COVID-19 pandemic will be posted. Additionally, run requests from hospitals, hospital collaborations and geographical regions will be taken through the portal. This work will generate crucial synthetic data needed to develop quick recommendations and analyses in a period where time is of the essence. Key outputs will include, for example: potential for various modified operational strategies to benefit hospital performance and patient survival, hospital collaboration strategies to aid regional response, anticipating critical supply needs to mobilize and prioritize support from supply chains (or Federal response capabilities), and recommendations for effective implementation of capacity enhancement strategies (alternative standards of care, modified operations, demand management). The project will provide input to educational activities in the future, once the project is complete and the pandemic subsides. The focus of this work during the period of performance will be on providing, as quickly as possible, crucially needed recommendations to hospitals and regions based on results from runs of high-quality models.

This RAPID award will advance mathematical modeling techniques for capturing critical hospital services during crises. It employs concepts of open queuing networks, discrete event simulation, stochastic modeling, transient system analysis, and statistical methods. The work will collect critical, perishable data, and will generate crucial synthetic data for rapid analysis and prediction urgently needed in this period of a global COVID-19 pandemic. With its quantitative approach, the project will enhance hospital readiness, capacity and capability, by identifying means for efficiently using severely limited, critical personnel and physical resources, the allocation of which will affect the survival of potentially thousands of lives and the safety of health care workers along with support staff. Findings from this effort will directly support hospitals at the front line, or regions in COVID-19 ?hot spots,? by providing the opportunity to request runs and receive analyses of the effectiveness of COVID-19 response strategies and collaboration mechanisms. It is anticipated that the run requests will come in a variety of forms, requiring data collection, modeling work, investigation to capture stochastic processes with input distributions and parameters, and results analyses. The models can be quickly enhanced and mobilized, and initial findings and recommendations made public in only weeks.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Assessing resilience of hospitals to cyberattack.