Predictors of COVID-19 Patients' Hospitalization Costs: A Cross-Sectional Study from Iran
DOI:
https://doi.org/10.22100/ijhs.v11i3.1196Keywords:
COVID-19, Hospitalization Costs, Quantile RegressionAbstract
Background: One of the important issues in managing COVID-19 is the correct, principled and timely provision of health services. To achieve this goal, full attention to its economic dimensions is important. The aim of the present study was to estimate direct medical costs of COVID-19 cases and its predictors at a referral hospital in Shahroud, Northeast of Iran.
Methods: This descriptive-analytical cross-sectional study was performed on all confirmed cases with COVID-19 infection who were hospitalized in the referral hospital in Shahroud, Northeast of Iran, between February 20, 2020, and May 23, 2020. A total of 744 confirmed cases were hospitalized during this period. Analyses were conducted on data from 697 patients who survived at admission and had complete records, with final status recorded as discharged or deceased. The bottom-up costing approach was applied to calculate direct medical costs. Univariate analyses were performed using Mann-Whitney U test, Friedman test, and Spearman correlation test. Also, quantile regression was applied in the multivariate analysis. A significance level of 0.05 was used for all statistical tests.
Results: A total of 697 patients were included in the analysis. The mean (SD) of the costs was US$ 965.8 (1477.2) with the median (IQR) of US$ 493.7 (366.5, 880). Of the studied patients, 120 (17.2%) were admitted to the ICU, with the mean (SD) and median (IQR) costs of US$ 2894.6 (2644.6) and US$ 2129.9 (1212.6, 3895.7), respectively. The highest mean costs were observed for bed and hoteling (42.5% of total costs) and for medications and supplies (34.5%). Age, diabetes, cardiovascular disease, other comorbidities, and patients' intubation had a significant association with the length of stay and the costs of hospitalization in the univariate analysis. The quantile regression results identified that male gender, cardiovascular disease, patients' intubation, and length of stay all were predictors of the patients' hospitalization costs.
Conclusions: The results of the present study showed that clinical management of COVID-19 inpatients incurs a significant financial burden to the healthcare system. Diseases severity was the only modifiable factor which increased the hospitalization costs at its different levels. Mitigating the incidence and severity of the disease through adherence to the health protocols, increasing vaccination coverage, and early diagnosis and timely treatment of patients can play an important role in reducing costs and effective use of health care resources in the management of COVID-19.
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