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Critical carE Database for Advanced Research (CEDAR): An automated method to support intensive care units with electronic health record data.
Schenck, Edward J; Hoffman, Katherine L; Cusick, Marika; Kabariti, Joseph; Sholle, Evan T; Campion, Thomas R.
  • Schenck EJ; Weill Department of Medicine, Weill Cornell Medicine, New York, NY, United States.
  • Hoffman KL; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
  • Cusick M; Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, United States.
  • Kabariti J; Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, United States.
  • Sholle ET; Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, United States.
  • Campion TR; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States; Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, United States; Department of Pediatrics, Weill Cornell Medicine, New York, NY, United States; Clinical & Transl
J Biomed Inform ; 118: 103789, 2021 06.
Article in English | MEDLINE | ID: covidwho-1188720
ABSTRACT
Patients treated in an intensive care unit (ICU) are critically ill and require life-sustaining organ failure support. Existing critical care data resources are limited to a select number of institutions, contain only ICU data, and do not enable the study of local changes in care patterns. To address these limitations, we developed the Critical carE Database for Advanced Research (CEDAR), a method for automating extraction and transformation of data from an electronic health record (EHR) system. Compared to an existing gold standard of manually collected data at our institution, CEDAR was statistically similar in most measures, including patient demographics and sepsis-related organ failure assessment (SOFA) scores. Additionally, CEDAR automated data extraction obviated the need for manual collection of 550 variables. Critically, during the spring 2020 COVID-19 surge in New York City, a modified version of CEDAR supported pandemic response efforts, including clinical operations and research. Other academic medical centers may find value in using the CEDAR method to automate data extraction from EHR systems to support ICU activities.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Databases, Factual / Electronic Health Records / COVID-19 / Intensive Care Units Type of study: Prognostic study / Reviews Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: J Biomed Inform Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: J.jbi.2021.103789

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Databases, Factual / Electronic Health Records / COVID-19 / Intensive Care Units Type of study: Prognostic study / Reviews Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: J Biomed Inform Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: J.jbi.2021.103789