Using inpatient electronic medical records to study influenza for pandemic preparedness
| Autor: | Robert Orr, Kenneth Sands, Russell E. Poland, Sarah K. Dutcher, Austin Cosgrove, Alfred Sorbello, Henry Francis, Noelle M. Cocoros, Karla M Miller, Greg Measer, Edward Rosen, Candace C. Fuller |
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| Rok vydání: | 2021 |
| Předmět: |
Pulmonary and Respiratory Medicine
medicine.medical_specialty Epidemiology medicine.medical_treatment Antiviral Agents law.invention Influenza A Virus H1N1 Subtype Public health surveillance law Influenza Human medicine Electronic Health Records Humans In patient Pandemics Mechanical ventilation Inpatients business.industry Medical record Pandemic preparedness Public Health Environmental and Occupational Health Electronic medical record Intensive care unit Hospitalization Intensive Care Units Infectious Diseases Emergency medicine Respiratory virus business |
| Zdroj: | Influenza and Other Respiratory Viruses. 16:265-275 |
| ISSN: | 1750-2659 1750-2640 |
| DOI: | 10.1111/irv.12921 |
| Popis: | Background We assessed the ability to identify key data relevant to influenza and other respiratory virus surveillance in a large-scale US-based hospital electronic medical record (EMR) dataset using seasonal influenza as a use case. We describe characteristics and outcomes of hospitalized influenza cases across three seasons. Methods We identified patients with an influenza diagnosis between March 2017 and March 2020 in 140 US hospitals as part of the US FDA's Sentinel System. We calculated descriptive statistics on the presence of high-risk conditions, influenza antiviral administrations, and severity endpoints. Results Among 5.1 million hospitalizations, we identified 29,520 hospitalizations with an influenza diagnosis; 64% were treated with an influenza antiviral within 2 days of admission, and 25% were treated >2 days after admission. Patients treated >2 days after admission had more comorbidities than patients treated within 2 days of admission. Patients never treated during hospitalization had more documentation of cardiovascular and other diseases than treated patients. We observed more severe endpoints in patients never treated (death = 3%, mechanical ventilation [MV] = 9%, intensive care unit [ICU] = 26%) or patients treated >2 days after admission (death = 2%, MV = 14%, ICU = 32%) than in patients treated earlier (treated on admission: death = 1%, MV = 5%, ICU = 23%, treated within 2 days of admission: death = 1%, MV = 7%, ICU = 27%). Conclusions We identified important trends in influenza severity related to treatment timing in a large inpatient dataset, laying the groundwork for the use of this and other inpatient EMR data for influenza and other respiratory virus surveillance. |
| Databáze: | OpenAIRE |
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