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A Narrative Review of Analytics in Pediatric Cardiac Anesthesia and Critical Care Medicine

Kelly L Grogan1, Michael P Goldsmith1, Aaron J Masino1

  • 1Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA; Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

Journal of Cardiothoracic and Vascular Anesthesia
|July 23, 2019
PubMed

Insights

Analytics in pediatric cardiac anesthesia improve care for children with congenital heart disease (CHD). Leveraging electronic health records and advanced monitoring enhances patient outcomes and reduces risks associated with general anesthesia.

Area of Science:

  • Pediatric Cardiac Anesthesia and Critical Care
  • Health Informatics
  • Biomedical Data Analytics

Background:

  • Congenital heart disease (CHD) is a common birth anomaly, with significant morbidity and mortality risks for affected children undergoing general anesthesia.
  • Despite decades of improved care, pediatric patients with CHD still face heightened risks during surgical procedures requiring general anesthesia.
  • Advancements in electronic health records (EHRs) and patient monitoring systems provide unprecedented opportunities for data collection and analysis in pediatric cardiac care.

Purpose of the Study:

  • To review recent advancements in leveraging data analytics within pediatric cardiac anesthesia and critical care.
  • To explore how novel analytical methods applied to EHR and monitoring data can enhance clinical decision-making and patient outcomes for children with CHD.
  • To highlight the potential of data-driven approaches in improving the safety and efficacy of care for pediatric CHD patients.

Main Methods:

  • This narrative review synthesizes recent literature on the application of analytics in pediatric cardiac anesthesia and critical care.
  • The review focuses on studies utilizing electronic health record data and sophisticated patient monitoring.
  • Emphasis is placed on the innovative analytical methods employed to interpret complex patient data.

Main Results:

  • Recent efforts demonstrate the potential of data analytics to identify at-risk pediatric patients with CHD.
  • Analytics can provide real-time insights to guide anesthetic management and critical care interventions.
  • The application of advanced analytics facilitates personalized treatment strategies for children with CHD.

Conclusions:

  • Leveraging data analytics in pediatric cardiac anesthesia and critical care is crucial for improving outcomes in children with CHD.
  • Effective analysis of EHR and monitoring data can mitigate risks associated with general anesthesia in this population.
  • Future research should focus on developing and implementing advanced analytical tools to further optimize care for pediatric CHD patients.

Keywords:
analyticscardiac anesthesiacardiac critical caremachine learningpediatrics

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