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Explanatory models in neonatal intensive care: a tutorial
BACKGROUND: Acute care providers intervening on fragile patients face many knowledge and information related challenges. Explanation based on causal chains of events has limitations when applied to complex physiological systems, and model-driven educational software may overwhelm the learner with in...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302436/ https://www.ncbi.nlm.nih.gov/pubmed/30598843 http://dx.doi.org/10.1186/s41077-018-0085-2 |
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author | van Meurs, Willem W.L. Antonius, Timothy A.J. |
author_facet | van Meurs, Willem W.L. Antonius, Timothy A.J. |
author_sort | van Meurs, Willem W.L. |
collection | PubMed |
description | BACKGROUND: Acute care providers intervening on fragile patients face many knowledge and information related challenges. Explanation based on causal chains of events has limitations when applied to complex physiological systems, and model-driven educational software may overwhelm the learner with information. We introduce a new concept and educational technology to facilitate understanding, reasoning, and communication in the clinical environment. The aim is to grasp complex physiology in a more intuitive way. EXPLANATORY MODELS (EM): An EM is a representation of relevant physiologic processes that provides insight into the relationships between therapeutic interventions and monitored variables, and their dependency on incidents and pathologies. We systematically analyze types of information incorporated into models and displayed in simulations and consider their explanatory relevance. TRANSPOSITION OF THE GREAT ARTERIES (TGA): A conceptual model (diagram) of the normal neonatal cardiorespiratory system is adapted to reflect TGA and implemented in animated, interactive software. ILLUSTRATION OF EDUCATIONAL USE: The use of this model is illustrated via the explanation to pediatric residents of the relationships between blood pressures, blood flow rates, ventilation, oxygen saturation, and oxygen distribution in a neonate with TGA. Learners explore clinical scenarios and effects of therapeutic interventions. DISCUSSION: Explanatory models hold promise as mental models for clinical practice and could possibly play a role in clinical decision making in neonatal intensive care and beyond. COMPANION SOFTWARE: The software is freely available via the web addendum: https://www.dropbox.com/sh/ciufq5rqxgs9bkt/AAC7oKsvkEr73eYUJkx0pZ1Ya?dl=0 |
format | Online Article Text |
id | pubmed-6302436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63024362018-12-31 Explanatory models in neonatal intensive care: a tutorial van Meurs, Willem W.L. Antonius, Timothy A.J. Adv Simul (Lond) Innovation BACKGROUND: Acute care providers intervening on fragile patients face many knowledge and information related challenges. Explanation based on causal chains of events has limitations when applied to complex physiological systems, and model-driven educational software may overwhelm the learner with information. We introduce a new concept and educational technology to facilitate understanding, reasoning, and communication in the clinical environment. The aim is to grasp complex physiology in a more intuitive way. EXPLANATORY MODELS (EM): An EM is a representation of relevant physiologic processes that provides insight into the relationships between therapeutic interventions and monitored variables, and their dependency on incidents and pathologies. We systematically analyze types of information incorporated into models and displayed in simulations and consider their explanatory relevance. TRANSPOSITION OF THE GREAT ARTERIES (TGA): A conceptual model (diagram) of the normal neonatal cardiorespiratory system is adapted to reflect TGA and implemented in animated, interactive software. ILLUSTRATION OF EDUCATIONAL USE: The use of this model is illustrated via the explanation to pediatric residents of the relationships between blood pressures, blood flow rates, ventilation, oxygen saturation, and oxygen distribution in a neonate with TGA. Learners explore clinical scenarios and effects of therapeutic interventions. DISCUSSION: Explanatory models hold promise as mental models for clinical practice and could possibly play a role in clinical decision making in neonatal intensive care and beyond. COMPANION SOFTWARE: The software is freely available via the web addendum: https://www.dropbox.com/sh/ciufq5rqxgs9bkt/AAC7oKsvkEr73eYUJkx0pZ1Ya?dl=0 BioMed Central 2018-12-20 /pmc/articles/PMC6302436/ /pubmed/30598843 http://dx.doi.org/10.1186/s41077-018-0085-2 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Innovation van Meurs, Willem W.L. Antonius, Timothy A.J. Explanatory models in neonatal intensive care: a tutorial |
title | Explanatory models in neonatal intensive care: a tutorial |
title_full | Explanatory models in neonatal intensive care: a tutorial |
title_fullStr | Explanatory models in neonatal intensive care: a tutorial |
title_full_unstemmed | Explanatory models in neonatal intensive care: a tutorial |
title_short | Explanatory models in neonatal intensive care: a tutorial |
title_sort | explanatory models in neonatal intensive care: a tutorial |
topic | Innovation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302436/ https://www.ncbi.nlm.nih.gov/pubmed/30598843 http://dx.doi.org/10.1186/s41077-018-0085-2 |
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