Drug prescription patterns and their association with mortality and hospitalization duration in COVID-19 patients: insights from big data

• Main Authors: Reza Mehrizi (Author), Ali Golestani (Author), Mohammad-Reza Malekpour (Author), Hossein Karami (Author), Mohammad Mahdi Nasehi (Author), Mohammad Effatpanah (Author), Hossein Ranjbaran (Author), Zahra Shahali (Author), Ali Akbari Sari (Author), Rajabali Daroudi (Author)
• Format: Book
• Published: Frontiers Media S.A., 2023-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2023.1280434
• Keywords: COVID-19; drug prescriptions; electronic health records; claims data; mortality; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 11 (2023)

BackgroundDifferent medication prescription patterns have been associated with varying course of disease and outcomes in COVID-19. Health claims data is a rich source of information on disease treatment and outcomes. We aimed to investigate drug prescription patterns and their association with mortality and hospitalization via insurance data for a relatively long period of the pandemic in Iran.MethodsWe retrieved hospitalized patients' data from Iran Health Insurance Organization (IHIO) spanning 26 months (2020-2022) nationwide. Included were patients with ICD-10 codes U07.1/U07.2 for confirmed/suspected COVID-19. A case was defined as a single hospitalization event for an individual patient. Multiple hospitalizations of a patient within a 30-day interval were aggregated into a single case, while hospitalizations with intervals exceeding 30 days were treated as independent cases. The Anatomical Therapeutic Chemical (ATC) was used for medications classification. The two main study outcomes were general and intensive care unit (ICU) hospitalization periods and mortality. Besides, various demographic and clinical associate factors were analyzed to derive the associations with medication prescription patterns and study outcomes using accelerated failure time (AFT) and logistic regression models.ResultsDuring the 26 months of the study period, 1,113,678 admissions with COVID-19 diagnosis at hospitals working in company with IHIO were recorded. 917,198 cases were detected from the database, among which 51.91% were females and 48.09% were males. Among the main groups of medications, antithrombotics (55.84% [95% CI: 55.74-55.94]), corticosteroids (54.14% [54.04-54.24]), and antibiotics (42.22% [42.12-42.32]) were the top used medications among cases with COVID-19. Investigation of the duration of hospitalization based on main medication groups showed antithrombotics (adjusted median ratio = 0.94 [0.94-0.95]) were significantly associated with shorter periods of overall hospitalization. Also, antithrombotics (adjusted odds ratio = 0.74 [95%CI, 0.73-0.76]), corticosteroids (0.97 [0.95-0.99]), antivirals (0.82 [0.80-0.83]), and ACE inhibitor/ARB (0.79 [0.77-0.80]) were significantly associated with lower mortality.ConclusionOver 2 years of investigation, antithrombotics, corticosteroids, and antibiotics were the top medications for hospitalized patients with COVID-19. Trends in medication prescription varied based on various factors across the country. Medication prescriptions could potentially significantly impact the trends of mortality and hospitalization during epidemics, thereby affecting both health and economic burdens.