Drug prescription patterns and their association with mortality and hospitalization duration in Covid-19 patients

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Bibliographic Data

ID22069853
AuthorsReza Mehrizi, Ali Golestani (0000-0002-5192-0435, Tehran University of Medical Sciences), Mohammad‐Reza Malekpour (0000-0002-8648-5402, Tehran University of Medical Sciences), Mohammad-Reza Malekpour, Hossein Karami (0000-0001-8969-3621), Mohammad Mahdi Nasehi, Mohammad Nasehi (0000-0002-3464-9129, Shahid Beheshti University of Medical Sciences), Mohammad Effatpanah (0000-0001-5344-7699, Imam Khomeini Hospital), Hossein Ranjbaran (0000-0002-4402-5002, Mazandaran University of Medical Sciences), Zahra Shahali (0000-0002-5457-5999), Ali Akbari Sari (0000-0002-6933-4071, Tehran University of Medical Sciences), Rajabali Daroudi (0000-0002-0487-4114, Tehran University of Medical Sciences, corresponding author)
Year2023
Volume11
Pages1280434-1280434
Publication date2023-12-18
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1280434
PMID38164450
OpenAlexW4389925575
LanguageEN
Citations received1
References cited48

Background: Different 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. Methods: We 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. Results: During 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. Conclusion: Over 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

2019-20 coronavirus outbreak · Disease · Medical prescription · Outbreak · COVID-19 Clinical Research Studies · Medicine · Pharmaceutical Practices and Patient Outcomes · Pharmacological Receptor Mechanisms and Effects · Psychology · Internal Medicine · Pharmacology · Virology

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