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Lessons learned in the use of clinical registry data in a multi-centre prospective study: the Pediatric Heart Network Residual Lesion Score Study

Published online by Cambridge University Press:  17 June 2019

Carol J. Prospero
Nemours Cardiac Center, Alfred I. duPont Hospital for Children, Wilmington, DE, USA
Felicia L. Trachtenberg
New England Research Institutes, Watertown, MA, USA
Victoria L. Pemberton
National Heart, Lung, and Blood Institute, NIH, Bethesda, MD, USA
Sara K. Pasquali
Division of Pediatric Cardiology, Department of Pediatrics, University of Michigan C.S. Mott Children’s Hospital, Ann Arbor, MI, USA
Brett R. Anderson
Division of Pediatric Cardiology, New York Presbyterian/Morgan Stanley Children’s Hospital, New York, NY, USA
Kathleen E. Ash
Division of Pediatric Cardiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Jessica Bainton
Division of Pediatric Cardiology, The Hospital for Sick Children, Toronto, ON, Canada
Carolyn Dunbar-Masterson
Department of Cardiology, Boston Children’s Hospital, Boston, MA, USA
Eric M. Graham
Division of Pediatric Cardiology, Medical University of South Carolina, Charleston, SC, USA
Michelle S. Hamstra
Division of Pediatric Cardiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Danielle Hollenbeck-Pringle
New England Research Institutes, Watertown, MA, USA
Jeffrey P. Jacobs
Department of Surgery, Johns Hopkins All Children’s Hospital, Saint Petersburg, FL, USA
Marshall L. Jacobs
Division of Cardiac Surgery, Johns Hopkins Heart and Vascular Institute, Baltimore, MD, USA
Rija John
Division of Congenital Heart Surgery, Texas Children’s Hospital, Houston, TX, USA
Linda M. Lambert
Division of Pediatric Cardiothoracic Surgery, University of Utah, Salt Lake City, UT, USA
Matthew E. Oster
Division of Pediatric Cardiology, Emory University School of Medicine, Children’s Healthcare of Atlanta, Atlanta, GA, USA
Elizabeth Swan
Division of Pediatric Cardiology, Riley Hospital for Children, Indianapolis, IN, USA
Abigail Waldron
Division of Cardiology, Children’s Hospital Philadelphia, Philadelphia, PA, USA
Meena Nathan*
Department of Cardiac Surgery, Boston Children’s Hospital, Boston, MA, USA
Author for correspondence: Meena Nathan MD, MPH, Department of Cardiac Surgery, Bader 273, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, USA. Tel: +1 617 355 7932; Fax: +1 617 730 0214; E-mail:



Using existing data from clinical registries to support clinical trials and other prospective studies has the potential to improve research efficiency. However, little has been reported about staff experiences and lessons learned from implementation of this method in pediatric cardiology.


We describe the process of using existing registry data in the Pediatric Heart Network Residual Lesion Score Study, report stakeholders’ perspectives, and provide recommendations to guide future studies using this methodology.


The Residual Lesion Score Study, a 17-site prospective, observational study, piloted the use of existing local surgical registry data (collected for submission to the Society of Thoracic Surgeons-Congenital Heart Surgery Database) to supplement manual data collection. A survey regarding processes and perceptions was administered to study site and data coordinating center staff.


Survey response rate was 98% (54/55). Overall, 57% perceived that using registry data saved research staff time in the current study, and 74% perceived that it would save time in future studies; 55% noted significant upfront time in developing a methodology for extracting registry data. Survey recommendations included simplifying data extraction processes and tailoring to the needs of the study, understanding registry characteristics to maximise data quality and security, and involving all stakeholders in design and implementation processes.


Use of existing registry data was perceived to save time and promote efficiency. Consideration must be given to the upfront investment of time and resources needed. Ongoing efforts focussed on automating and centralising data management may aid in further optimising this methodology for future studies.

Original Article
© Cambridge University Press 2019 

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