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

{ 'indexed': { 'date-parts': [[2023, 12, 19]], 'date-time': '2023-12-19T00:33:41Z', 'timestamp': 1702946021750}, 'reference-count': 55, 'publisher': 'Frontiers Media SA', 'license': [ { 'start': { 'date-parts': [[2023, 12, 18]], 'date-time': '2023-12-18T00:00:00Z', 'timestamp': 1702857600000}, 'content-version': 'vor', 'delay-in-days': 0, 'URL': 'https://creativecommons.org/licenses/by/4.0/'}], 'content-domain': {'domain': ['frontiersin.org'], 'crossmark-restriction': True}, 'abstract': '<jats:sec><jats:title>Background</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We retrieved ' 'hospitalized patients’ data from Iran Health Insurance Organization (IHIO) spanning 26\u2009' '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\u2009days ' '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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>During the ' '26\u2009months 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\u2009=\u20090.94 [0.94–0.95]) were significantly ' 'associated with shorter periods of overall hospitalization. Also, antithrombotics (adjusted ' 'odds ratio\u2009=\u20090.74 [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.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Over ' '2\u2009years 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.</jats:p></jats:sec>', 'DOI': '10.3389/fpubh.2023.1280434', 'type': 'journal-article', 'created': { 'date-parts': [[2023, 12, 18]], 'date-time': '2023-12-18T09:42:21Z', 'timestamp': 1702892541000}, 'update-policy': 'http://dx.doi.org/10.3389/crossmark-policy', 'source': 'Crossref', 'is-referenced-by-count': 0, 'title': 'Drug prescription patterns and their association with mortality and hospitalization duration in ' 'COVID-19 patients: insights from big data', 'prefix': '10.3389', 'volume': '11', 'author': [ {'given': 'Reza', 'family': 'Mehrizi', 'sequence': 'first', 'affiliation': []}, {'given': 'Ali', 'family': 'Golestani', 'sequence': 'additional', 'affiliation': []}, {'given': 'Mohammad-Reza', 'family': 'Malekpour', 'sequence': 'additional', 'affiliation': []}, {'given': 'Hossein', 'family': 'Karami', 'sequence': 'additional', 'affiliation': []}, {'given': 'Mohammad Mahdi', 'family': 'Nasehi', 'sequence': 'additional', 'affiliation': []}, {'given': 'Mohammad', 'family': 'Effatpanah', 'sequence': 'additional', 'affiliation': []}, {'given': 'Hossein', 'family': 'Ranjbaran', 'sequence': 'additional', 'affiliation': []}, {'given': 'Zahra', 'family': 'Shahali', 'sequence': 'additional', 'affiliation': []}, {'given': 'Ali Akbari', 'family': 'Sari', 'sequence': 'additional', 'affiliation': []}, {'given': 'Rajabali', 'family': 'Daroudi', 'sequence': 'additional', 'affiliation': []}], 'member': '1965', 'published-online': {'date-parts': [[2023, 12, 18]]}, 'reference': [ { 'key': 'ref1', 'volume-title': 'Covid-19: WHO declares end of global health emergency', 'author': 'Wise', 'year': '2023'}, { 'key': 'ref2', 'doi-asserted-by': 'publisher', 'first-page': '164', 'DOI': '10.1016/j.vacun.2023.05.002', 'article-title': 'The end of COVID-19 public health emergency of international concern ' 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