RAPID: Variation in Resilience Under Shortages in the Medical Supply Chain
Division of Chemical, Bioengineering, Environmental, and Transport Systems
2027927
Grant
Bruce Hamilton
$200,000.00
Cassandra L Thiel
[email protected] (Principal Investigator)
Kimia Ghobadi (Co-Principal Investigator)
New York University Medical Center
550 1ST AVE
NEW YORK
NY
100166402
The research objectives of this proposal are to measure the effects of Covid-19 on the medical Personal Protective Equipment (PPE) supply chain, analyze emerging hospital resource conservation policies, and identify short-term and long-term solutions to increase resilience in the medical supply chain. The research team will focus specifically on the effects of Covid-19 as a stressor to healthcare end-users of PPE (i.e., hospitals and medical clinics). The team will focus on the uncertainty of supply and demand and seeks to identify the best policies to reduce the impact for these end-users while ensuring quality of care and protection of medical staff. The primary aim of this study is to collect data and use optimization and analytical methods to assist medical providers during the Covid-19 crisis while also considering the longer-term potential of mitigating environmental impact and increasing resilience in healthcare supply chains.
The approach of the study is two-fold: (1) data collection on PPE usage and supply chains, and (2) development of novel robust optimization models. A contribution of this study is to be collection of data on the physical PPE supply chain, hospitals' historic and current (emergency) use of PPE, and emerging PPE conservation policies and practices enacted by hospitals during the Covid-19 pandemic. To gather additional data, the research team has developed a novel crowd sourcing data collection platform that can later be adapted for other healthcare data collection as well. An additional feature parallel of this work lies in the development of mathematical scenario-based and robust optimization models for PPE supply chain and resource allocation. The research team will develop linear and robust optimization models to allocate the scarce resources given large uncertainty in demand and supply. These resource-allocation models will use the collected data. The team will also develop scenario-base models to test and validate the different hospital policies for the use of PPE during Covid-19 outbreak. The intended immediate impact of this research is to inform healthcare workers about effective policies for PPE conservation that lead to optimal health outcomes for patients and staff during the Covid-19 pandemic. The findings and the data collected as a result of this work will be made available to the medical community as soon as possible to help manage the need for PPE. Specifically, PPE conservation policies will be compiled, and a paper immediately released to the medical community to broadly help conserve resources during the Covid-19 pandemic. In the longer term, the strategies developed to effectively mitigate resource consumption and climate impacts of healthcare activities will be shared with the medical and the wider academic communities. The results of this study target increased resilience of medical supply chain and healthcare operations during times of crisis, including future pandemics and climate related disasters, as well as a general increase in emissions mitigation by continuing reasonable resource conservation practices beyond the pandemic.
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.