Antje Wulff1, Michael Marschollek1. 1. Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig and Hannover Medical School, Germany.
Abstract
BACKGROUND: The vast amount of data generated in healthcare can be reused to support decision-making by developing clinical decision-support systems. Since evidence is lacking in Pediatrics, it seems to be beneficial to design future systems towards the vision of generating evidence through cross-institutional data analysis and continuous learning cycles. OBJECTIVES: Presentation of an approach for cross-institutional and data-driven decision support in pediatric intensive care units (PICU), and the long-term vision of Learning Healthcare Systems in Pediatrics. METHODS: Using a four-step approach, including the design of interoperable decision-support systems and data-driven algorithms, for establishing a Learning Health Cycle. RESULTS: We developed and started to follow that approach on exemplary of systemic inflammatory response syndrome (SIRS) detection in PICU. CONCLUSIONS: Our approach has great potential to establish our vision of learning systems, which support decision-making in PICU by analyzing cross-institutional data and giving insights back to both, their own knowledge base and clinical care, to continuously learn about practices and evidence in Pediatrics.
BACKGROUND: The vast amount of data generated in healthcare can be reused to support decision-making by developing clinical decision-support systems. Since evidence is lacking in Pediatrics, it seems to be beneficial to design future systems towards the vision of generating evidence through cross-institutional data analysis and continuous learning cycles. OBJECTIVES: Presentation of an approach for cross-institutional and data-driven decision support in pediatric intensive care units (PICU), and the long-term vision of Learning Healthcare Systems in Pediatrics. METHODS: Using a four-step approach, including the design of interoperable decision-support systems and data-driven algorithms, for establishing a Learning Health Cycle. RESULTS: We developed and started to follow that approach on exemplary of systemic inflammatory response syndrome (SIRS) detection in PICU. CONCLUSIONS: Our approach has great potential to establish our vision of learning systems, which support decision-making in PICU by analyzing cross-institutional data and giving insights back to both, their own knowledge base and clinical care, to continuously learn about practices and evidence in Pediatrics.
Keywords:
Clinical Decision Support Systems; Critical Care; Health Information Interoperability; Learning Healthcare System; Pediatrics
Authors: Antje Wulff; Sara Montag; Bianca Steiner; Michael Marschollek; Philipp Beerbaum; André Karch; Thomas Jack Journal: BMJ Open Date: 2019-06-19 Impact factor: 2.692