Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement

Robert W. Grundmeier; Aaron J. Masino; T. Charles Casper; Jonathan M. Dean; Jamie Bell; Rene Enriquez; Sara Deakyne; James M. Chamberlain; Elizabeth R. Alpern; The Pediatric Emergency Care Applied Research Network

doi:10.4338/ACI-2016-08-RA-0129

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2016; 07(04): 1051-1068
DOI: 10.4338/ACI-2016-08-RA-0129

Research Article

Schattauer GmbH

Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement

Robert W. Grundmeier

¹Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States

²Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States

,

Aaron J. Masino

¹Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States

,

T. Charles Casper

³Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, United States

,

Jonathan M. Dean

³Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, United States

,

Jamie Bell

³Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, United States

,

Rene Enriquez

³Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, United States

,

Sara Deakyne

⁴Children’s Hospital Colorado, Denver, Colorado, United States

,

James M. Chamberlain

⁵Division of Emergency Medicine, Children’s National Health System, Washington, District of Columbia, United States

,

Elizabeth R. Alpern

⁶Department of Pediatrics, Ann and Robert H. Lurie Children’s Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States

,

The Pediatric Emergency Care Applied Research Network

› Author Affiliations

Abstract

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Keywords

Natural language processing - machine learning - quality improvement - pediatrics - emergency medicine

References

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