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A clinical informatics approach to bronchopulmonary dysplasia: current barriers and future possibilities.
Moreira, Alvaro G; Husain, Ameena; Knake, Lindsey A; Aziz, Khyzer; Simek, Kelsey; Valadie, Charles T; Pandillapalli, Nisha Reddy; Trivino, Vanessa; Barry, James S.
Afiliación
  • Moreira AG; Department of Pediatrics, University of Texas Health San Antonio, San Antonio, TX, United States.
  • Husain A; Department of Pediatrics, University of Utah, Salt Lake City, UT, United States.
  • Knake LA; Department of Pediatrics, University of Iowa, Iowa City, IA, United States.
  • Aziz K; Department of Pediatrics, Johns Hopkins University, Baltimore, MD, United States.
  • Simek K; Department of Pediatrics, University of Utah, Salt Lake City, UT, United States.
  • Valadie CT; Department of Pediatrics, University of Texas Health San Antonio, San Antonio, TX, United States.
  • Pandillapalli NR; Department of Pediatrics, University of Texas Health San Antonio, San Antonio, TX, United States.
  • Trivino V; Department of Pediatrics, University of Texas Health San Antonio, San Antonio, TX, United States.
  • Barry JS; Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, United States.
Front Pediatr ; 12: 1221863, 2024.
Article en En | MEDLINE | ID: mdl-38410770
ABSTRACT
Bronchopulmonary dysplasia (BPD) is a complex, multifactorial lung disease affecting preterm neonates that can result in long-term pulmonary and non-pulmonary complications. Current therapies mainly focus on symptom management after the development of BPD, indicating a need for innovative approaches to predict and identify neonates who would benefit most from targeted or earlier interventions. Clinical informatics, a subfield of biomedical informatics, is transforming healthcare by integrating computational methods with patient data to improve patient outcomes. The application of clinical informatics to develop and enhance clinical therapies for BPD presents opportunities by leveraging electronic health record data, applying machine learning algorithms, and implementing clinical decision support systems. This review highlights the current barriers and the future potential of clinical informatics in identifying clinically relevant BPD phenotypes and developing clinical decision support tools to improve the management of extremely preterm neonates developing or with established BPD. However, the full potential of clinical informatics in advancing our understanding of BPD with the goal of improving patient outcomes cannot be achieved unless we address current challenges such as data collection, storage, privacy, and inherent data bias.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Pediatr Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Pediatr Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza