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Mitigating the COVID-19 Pandemic through Data-Driven Resource Sharing.

Esmaeil Keyvanshokooh1, Mohammad Fattahi2, Kenneth A Freedberg3,4

  • 1Department of Information & Operations Management, Mays Business School, Texas A&M University, College Station, TX 77845, USA.

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Summary
This summary is machine-generated.

Sharing mechanical ventilators across regions can significantly reduce the number of machines needed during COVID-19 outbreaks. This strategy also lowers healthcare costs and preserves capacity for elective procedures.

Keywords:
COVID-19Data-driven optimizationPolicy-guided modelResource sharingSimulation

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Area of Science:

  • Healthcare resource management
  • Operations research
  • Epidemiology

Background:

  • COVID-19 outbreaks caused mechanical ventilator shortages, leading hospitals to purchase excess equipment and cancel elective procedures.
  • These measures created financial strain and negatively impacted non-COVID-19 patient care.
  • Regional variations in COVID-19 transmission offer opportunities for resource sharing.

Purpose of the Study:

  • To develop a data-driven adaptive robust simulation-based optimization (DARSO) methodology for optimal allocation and relocation of mechanical ventilators.
  • To enable real-time resource-sharing decisions by addressing limitations of current robust and stochastic models.

Main Methods:

  • Developed a novel data-driven adaptive robust simulation-based optimization (DARSO) methodology.
  • Implemented a policy-guided approach and an efficient algorithmic framework.
  • Conducted a case study on sharing ventilators among regions in Ohio and Michigan in collaboration with medical experts.

Main Results:

  • The optimal policy satisfied ventilator demand during the first pandemic peak in Ohio and Michigan.
  • Ventilator demand was met with 14% (limited sharing) to 63% (full sharing) fewer ventilators compared to a no-sharing strategy.
  • Sharing ventilators reduced expenditure by 5% (limited sharing) to 44% (full sharing) compared to purchasing new machines.

Conclusions:

  • The DARSO methodology provides an effective strategy for optimizing mechanical ventilator allocation and relocation during public health crises.
  • Resource sharing can significantly reduce the total number of ventilators required and associated costs.
  • Implementing sharing strategies allows hospitals to maintain capacity for elective procedures, improving overall patient care.