Cargando…
Development and Validation of Algorithms to Identify COVID-19 Patients Using a US Electronic Health Records Database: A Retrospective Cohort Study
INTRODUCTION: In order to identify and evaluate candidate algorithms to detect COVID-19 cases in an electronic health record (EHR) database, this study examined and compared the utilization of acute respiratory disease codes from February to August 2020 versus the corresponding time period in the 3...
Autores principales: | Brown, Carolyn A, Londhe, Ajit A, He, Fang, Cheng, Alvan, Ma, Junjie, Zhang, Jie, Brooks, Corinne G, Sprafka, J Michael, Roehl, Kimberly A, Carlson, Katherine B, Page, John H |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139367/ https://www.ncbi.nlm.nih.gov/pubmed/35633659 http://dx.doi.org/10.2147/CLEP.S355086 |
Ejemplares similares
-
Pediatric BMI changes during COVID-19 pandemic: An electronic health record-based retrospective cohort study
por: Brooks, Corinne G., et al.
Publicado: (2021) -
Trends in characteristics and outcomes among US adults hospitalised with COVID-19 throughout 2020: an observational cohort study
por: Page, John H, et al.
Publicado: (2022) -
An Algorithm for Building an Electronic Database
por: Cohen, Wess A., et al.
Publicado: (2016) -
Cerner real-world data (CRWD) - A de-identified multicenter electronic health records database
por: Ehwerhemuepha, Louis, et al.
Publicado: (2022) -
Risk of retinal detachment and exposure to fluoroquinolones, common antibiotics, and febrile illness using a self-controlled case series study design: Retrospective analyses of three large healthcare databases in the US
por: Londhe, Ajit A., et al.
Publicado: (2022)