Cost of Illness in Patients With COVID-19 Admitted in three Brazilian Public Hospitals

Objectives: The severity and transmissibility of COVID-19 justifies the need to identify the factors associated with its cost of illness (CoI). This study aimed to identify CoI, cost predictors, and cost drivers in the management of patients with COVID-19 from hospital and Brazil's Public Healt...

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Detalles Bibliográficos
Autores: Oliveira, Layssa Andrade, Lucchetta, Rosa Camila [UNESP], Mendes, Antônio Matoso, Bonetti, Aline de Fátima, Xavier, Cecilia Silva [UNESP], Sanches, Andréia Cristina Conegero, Borba, Helena Hiemisch Lobo, Oliota, Ana Flávia Redolfi, Rossignoli, Paula, Mastroianni, Patrícia de Carvalho [UNESP], Venson, Rafael, Virtuoso, Suzane, de Nadai, Tales Rubens [UNESP], Wiens, Astrid
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Brasil
Institución:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/249810
Acceso en línea:http://dx.doi.org/10.1016/j.vhri.2023.02.004
http://hdl.handle.net/11449/249810
Access Level:acceso abierto
Palabra clave:cost analysis
cost of illness
COVID-19
hospital care
hospital costs
Descripción
Sumario:Objectives: The severity and transmissibility of COVID-19 justifies the need to identify the factors associated with its cost of illness (CoI). This study aimed to identify CoI, cost predictors, and cost drivers in the management of patients with COVID-19 from hospital and Brazil's Public Health System (SUS) perspectives. Methods: This is a multicenter study that evaluated the CoI in patients diagnosed of COVID-19 who reached hospital discharge or died before being discharged between March and September 2020. Sociodemographic, clinical, and hospitalization data were collected to characterize and identify predictors of costs per patients and cost drivers per admission. Results: A total of 1084 patients were included in the study. For hospital perspective, being overweight or obese, being between 65 and 74 years old, or being male showed an increased cost of 58.4%, 42.9%, and 42.5%, respectively. From SUS perspective, the same predictors of cost per patient increase were identified. The median cost per admission was estimated at US$359.78 and US$1385.80 for the SUS and hospital perspectives, respectively. In addition, patients who stayed between 1 and 4 days in the intensive care unit (ICU) had 60.9% higher costs than non-ICU patients; these costs significantly increased with the length of stay (LoS). The main cost driver was the ICU-LoS and COVID-19 ICU daily for hospital and SUS perspectives, respectively. Conclusions: The predictors of increased cost per patient at admission identified were overweight or obesity, advanced age, and male sex, and the main cost driver identified was the ICU-LoS. Time-driven activity-based costing studies, considering outpatient, inpatient, and long COVID-19, are needed to optimize our understanding about cost of COVID-19.