The COVID-19 pandemic has created unprecedented challenges for the U.S. healthcare system due to the mismatch between healthcare system capacity and patient demand. The healthcare industry has been a slow adopter of digital innovation due to the conventional belief that humans need to be at the center of every healthcare delivery task. In the setting of the COVID-19 pandemic, however, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and allow clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare implemented an automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.
ObjectivesTo compare the impact of respirator extended use and reuse strategies with regard to cost and sustainability during the COVID-19 pandemic.DesignCost analysis.SettingUSA.ParticipantsAll healthcare workers within the USA.InterventionsNot applicable.Main outcome measuresA model was developed to estimate usage, costs and waste incurred by several respirator usage strategies over the first 6 months of the pandemic in the USA. This model assumed universal masking of all healthcare workers. Estimates were taken from the literature, government databases and commercially available data from approved vendors.ResultsA new N95 respirator per patient encounter would require 7.41 billion respirators, cost $6.38 billion and generate 84.0 million kg of waste in the USA over 6 months. One respirator per day per healthcare worker would require 3.29 billion respirators, cost $2.83 billion and generate 37.22 million kg of waste. Decontamination by ultraviolet germicidal irradiation would require 1.64 billion respirators, cost $1.41 billion and accumulate 18.61 million kg of waste. H2O2 vapour decontamination would require 1.15 billion respirators, cost $1.65 billion and produce 13.03 million kg of waste. One reusable respirator with daily disposable filters would require 18 million respirators, cost $1.24 billion and generate 15.73 million kg of waste. Pairing a reusable respirator with H2O2 vapour-decontaminated filters would reduce cost to $831 million and generate 1.58 million kg of waste. The use of one surgical mask per healthcare worker per day would require 3.29 billion masks, cost $460 million and generate 27.92 million kg of waste.ConclusionsDecontamination and reusable respirator-based strategies decreased the number of respirators used, costs and waste generated compared with single-use or daily extended-use of disposable respirators. Future development of low-cost,simple technologies to enable respirator and/or filter decontamination is needed to further minimise the economic and environmental costs of masks.
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