Characteristics of the Pediatric Patients Treated by the Pediatric Emergency Care Applied Research Network's Affiliated EMS Agencies

2013 ◽  
Vol 18 (1) ◽  
pp. 52-59 ◽  
Author(s):  
E. Brooke Lerner ◽  
Peter S. Dayan ◽  
Kathleen Brown ◽  
Susan Fuchs ◽  
Julie Leonard ◽  
...  
2018 ◽  
Vol 19 (3) ◽  
pp. 295-303 ◽  
Author(s):  
Rachel M. Stanley ◽  
Mona Jabbour ◽  
Jessica M. Saunders ◽  
Sally Jo Zuspan

2017 ◽  
Vol 47 ◽  
pp. 1770-1777 ◽  
Author(s):  
Fatma Dilek GÖKHARMAN ◽  
Sonay AYDIN ◽  
Erdem FATİHOĞLU ◽  
Pınar Nercis KOŞAR

2018 ◽  
Vol 09 (02) ◽  
pp. 366-376 ◽  
Author(s):  
Sara Deakyne Davies ◽  
Robert Grundmeier ◽  
Diego Campos ◽  
Katie Hayes ◽  
Jamie Bell ◽  
...  

Background Electronic health record (EHR)-based registries allow for robust data to be derived directly from the patient clinical record and can provide important information about processes of care delivery and patient health outcomes. Methods A data dictionary, and subsequent data model, were developed describing EHR data sources to include all processes of care within the emergency department (ED). ED visit data were deidentified and XML files were created and submitted to a central data coordinating center for inclusion in the registry. Automated data quality control occurred prior to submission through an application created for this project. Data quality reports were created for manual data quality review. Results The Pediatric Emergency Care Applied Research Network (PECARN) Registry, representing four hospital systems and seven EDs, demonstrates that ED data from disparate health systems and EHR vendors can be harmonized for use in a single registry with a common data model. The current PECARN Registry represents data from 2,019,461 pediatric ED visits, 894,503 distinct patients, more than 12.5 million narrative reports, and 12,469,754 laboratory tests and continues to accrue data monthly. Conclusion The Registry is a robust harmonized clinical registry that includes data from diverse patients, sites, and EHR vendors derived via data extraction, deidentification, and secure submission to a central data coordinating center. The data provided may be used for benchmarking, clinical quality improvement, and comparative effectiveness research.


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