Inpatient Hospital Costs for COVID-19 Patients in the United States

美国新冠肺炎患者住院费用

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Abstract

INTRODUCTION: Reliable cost and resource use data for COVID-19 hospitalizations are crucial to better inform local healthcare resource decisions; however, available data are limited and vary significantly. METHODS: COVID-19 hospital admissions data from the Premier Healthcare Database were evaluated to estimate hospital costs, length of stay (LOS), and discharge status. Adult COVID-19 patients (ICD-10-CM: U07.1) hospitalized in the US from April 1 to December 31, 2020, were identified. Analyses were stratified by patient and hospital characteristics, levels of care during hospitalization, and discharge status. Factors associated with changes in costs, LOS, and discharge status were estimated using regression analyses. Monthly trends in costs, LOS, and discharge status were examined. RESULTS: Of the 247,590 hospitalized COVID-19 patients, 49% were women, 76% were aged ≥ 50, and 36% were admitted to intensive care units (ICU). Overall median hospital LOS, cost, and cost/day were 6 days, US$11,267, and $1772, respectively; overall median ICU LOS, cost, and cost/day were 5 days, $13,443, and $2902, respectively. Patients requiring mechanical ventilation had the highest hospital and ICU median costs ($47,454 and $41,510) and LOS (16 and 11 days), respectively. Overall, 14% of patients died in hospital and 52% were discharged home. Older age, Black and Caucasian race, hypertension and obesity, treatment with extracorporeal membrane oxygenation, and discharge to long-term care facilities were major drivers of costs, LOS, and risk of death. Admissions in December had significantly lower median hospital and ICU costs and LOS compared to April. CONCLUSION: The burden from COVID-19 in terms of hospital and ICU costs and LOS has been substantial, though significant decreases in cost and LOS and increases in the share of hospital discharges to home were observed from April to December 2020. These estimates will be useful for inputs to economic models, disease burden forecasts, and local healthcare resource planning.

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