Model for estimating the impact of healthcare costs in non-hospitalized Covid-19 patients treated with remdesivir
DOI:
https://doi.org/10.33393/ao.2022.2473Keywords:
COVID-19, Hospitalization, Intensive care, remdesivir, SARS-CoV-2Abstract
Objectives: In March 2020, the COVID-19 pandemic outbreak caused significant negative changes worldwide. Important investments were suddenly needed in the economic, social, and healthcare fields. This analysis sets out to show the economic impact of the administration of remdesivir in ambulatory patients, who are affected by Covid-19, at high risk for severe progression, and eligible for the antiviral treatment.
Methods: The budget impact analysis is based on the assumptions already presented in a study published in 2020 by the same Authors. The analysis was updated with a new simulation of the pandemic curve which included the vaccination plan. Data were collected from official Italian sources and from the academic literature. The Italian National Health Service (NHS) perspective was used in the analysis. Remdesivir treatment was compared in terms of economic costs with the Standard of Care over a period of 20 weeks. Such timeframe was chosen because of the uncertainty of the pandemic evolution and considering that this is the time of a complete pandemic curve. A comparison with other therapeutic solutions was not performed in this analysis as the relative costs were not available at the time of the study.
Results: The model estimates that, in 20 weeks, 8,002,015 subjects are infected by Covid-19, with a 0.8% hospitalization rate. Among hospitalized patients, 19.6% could be eligible for remdesivir treatment, for a total number of 3,619 patients, with a 12% market share.
Conclusion: The analysis shows that remdesivir therapy is dominant and its use could determine a reduction in hospitalizations and transfers to intensive care units compared to the Standard of Care, with a potential saving of € 50.8 million and a decrease of the number of Covid-19-related deaths between 600 and 1,100.
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Copyright (c) 2022 Matteo Ruggeri, Alessandro Signorini, Silvia Caravaggio, Marco Falcone, Giovanni Di Perri
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Accepted 2022-11-07
Published 2022-12-27
