Diagnostic and Therapeutic Costs of Patients With a Diagnosis of or Suspected Coronavirus Disease in Iran.

ABSTRACT

OBJECTIVES: To understand the social and individual effects of the disease and make decisions on the allocation of health resources, it is necessary to understand the economic burden of coronavirus disease (COVID-19); however, there are limited data in this field. This study aimed to estimate diagnostic and therapeutic costs of patients with a diagnosis of or suspected of COVID-19 disease admitted to hospitals in northeast Iran. METHODS: This descriptive and analytical research was conducted as a retrospective study using the data collected from 2980 patients admitted to 30 hospitals from February to April 2020 in Iran. For data collection, an appropriate data capture tool was designed to record detailed resource use. A multivariate regression analysis was performed to examine the association between the treatment costs and sociodemographic, disease severity, and underlying diseases. Data were analyzed using Excel 2017 (Microsoft, Redmond, WA) and SPSS version 21 software (SPSS Inc., Chicago, IL). RESULTS: The inpatient costs per patient were Int$416, of which 74% were paid by social health insurance systems, 19% by the government, and 7% by the patients. The largest cost components were hoteling (37%) and medicine (36%). The 4 subscales of age, sex, underlying disease, and severity predicted 48.6% of the cost variance. CONCLUSION: Understanding the economic consequences of diseases can help policymakers to make plans to reduce out-of-pocket payments and make plans for funding. Since COVID-19 is a newly emerging disease and there is no definitive cure for the disease, the discovery of an effective medicine may alter medical costs and reduce the hospital length of stay, therefore significantly reducing treatment costs.