The Pediatric Emergency Care Applied Research Network and Knowledge Translation

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.


2020 ◽  
pp. 102490792097537
Author(s):  
Jon Soo Kim ◽  
Jin Cheol Kim ◽  
Won Young Sung

Background: Minor head trauma is frequently presented to the pediatric emergency department. Despite the burden this injury poses on public health, evidence-based clinical guidelines on the assessment and management of pediatric minor head trauma remain unestablished, particularly in children below 2 years. We aimed to assess the diagnostic accuracy of a clinical decision rule (Pediatric Emergency Care Applied Research Network rule) and physician discretion in the recognition of practically important traumatic brain injury in children below 2 years of age presenting with minor head trauma to the emergency department. Methods: The medical records of children younger than 2 years presenting with head trauma to the emergency department were reviewed with Glasgow Coma Scale scores of 14–15. Practically important traumatic brain injury is a clinically essential traumatic brain injury including all cranial abnormalities (e.g. skull fracture) detected by computed tomography. All predictor variables of the Pediatric Emergency Care Applied Research Network rule and practically important traumatic brain injury outcomes were validated. Results: We enrolled and analyzed 433 children below 2 years. The most frequently observed mechanisms of injury in decreasing order were as follows: falls > 90 cm, head struck by high-impact objects, slip down, and automobile traffic accident. Of 224 children, positive findings were observed in 35 and 144 had one or more predictors of Pediatric Emergency Care Applied Research Network rule. The sensitivity, specificity, and negative likelihood ratio of the Pediatric Emergency Care Applied Research Network rule for practically important traumatic brain injury were 94.3%, 41.3%, and 0.14, respectively. Conclusion: The Pediatric Emergency Care Applied Research Network rule would assist in clinical decision-making to appropriately detect potential head injuries in children below 2 years, thereby reducing unnecessary performance of computed tomography scan.


2006 ◽  
Vol 7 (2) ◽  
pp. 128-135 ◽  
Author(s):  
Peter Dayan ◽  
James Chamberlain ◽  
J. Michael Dean ◽  
Ronald F. Maio ◽  
Nathan Kuppermann

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