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Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration

INTRODUCTION: We report a pathfinder study of AI/knowledge engineering methods to rapidly formalise COVID‐19 guidelines into an executable model of decision making and care pathways. The knowledge source for the study was material published by BMJ Best Practice in March 2020. METHODS: The PROforma g...

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Autores principales: Fox, John, Khan, Omar, Curtis, Hywel, Wright, Andrew, Pal, Carla, Cockburn, Neil, Cooper, Jennifer, Chandan, Joht S., Nirantharakumar, Krishnarajah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323421/
https://www.ncbi.nlm.nih.gov/pubmed/32838035
http://dx.doi.org/10.1002/lrh2.10236
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author Fox, John
Khan, Omar
Curtis, Hywel
Wright, Andrew
Pal, Carla
Cockburn, Neil
Cooper, Jennifer
Chandan, Joht S.
Nirantharakumar, Krishnarajah
author_facet Fox, John
Khan, Omar
Curtis, Hywel
Wright, Andrew
Pal, Carla
Cockburn, Neil
Cooper, Jennifer
Chandan, Joht S.
Nirantharakumar, Krishnarajah
author_sort Fox, John
collection PubMed
description INTRODUCTION: We report a pathfinder study of AI/knowledge engineering methods to rapidly formalise COVID‐19 guidelines into an executable model of decision making and care pathways. The knowledge source for the study was material published by BMJ Best Practice in March 2020. METHODS: The PROforma guideline modelling language and OpenClinical.net authoring and publishing platform were used to create a data model for care of COVID‐19 patients together with executable models of rules, decisions and plans that interpret patient data and give personalised care advice. RESULTS: PROforma and OpenClinical.net proved to be an effective combination for rapidly creating the COVID‐19 model; the Pathfinder 1 demonstrator is available for assessment at https://www.openclinical.net/index.php?id=746. CONCLUSIONS: This is believed to be the first use of AI/knowledge engineering methods for disseminating best‐practice in COVID‐19 care. It demonstrates a novel and promising approach to the rapid translation of clinical guidelines into point of care services, and a foundation for rapid learning systems in many areas of healthcare.
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spelling pubmed-73234212020-06-29 Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration Fox, John Khan, Omar Curtis, Hywel Wright, Andrew Pal, Carla Cockburn, Neil Cooper, Jennifer Chandan, Joht S. Nirantharakumar, Krishnarajah Learn Health Syst Brief Reports INTRODUCTION: We report a pathfinder study of AI/knowledge engineering methods to rapidly formalise COVID‐19 guidelines into an executable model of decision making and care pathways. The knowledge source for the study was material published by BMJ Best Practice in March 2020. METHODS: The PROforma guideline modelling language and OpenClinical.net authoring and publishing platform were used to create a data model for care of COVID‐19 patients together with executable models of rules, decisions and plans that interpret patient data and give personalised care advice. RESULTS: PROforma and OpenClinical.net proved to be an effective combination for rapidly creating the COVID‐19 model; the Pathfinder 1 demonstrator is available for assessment at https://www.openclinical.net/index.php?id=746. CONCLUSIONS: This is believed to be the first use of AI/knowledge engineering methods for disseminating best‐practice in COVID‐19 care. It demonstrates a novel and promising approach to the rapid translation of clinical guidelines into point of care services, and a foundation for rapid learning systems in many areas of healthcare. John Wiley and Sons Inc. 2020-07-14 /pmc/articles/PMC7323421/ /pubmed/32838035 http://dx.doi.org/10.1002/lrh2.10236 Text en © 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Brief Reports
Fox, John
Khan, Omar
Curtis, Hywel
Wright, Andrew
Pal, Carla
Cockburn, Neil
Cooper, Jennifer
Chandan, Joht S.
Nirantharakumar, Krishnarajah
Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title_full Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title_fullStr Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title_full_unstemmed Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title_short Rapid translation of clinical guidelines into executable knowledge: A case study of COVID‐19 and online demonstration
title_sort rapid translation of clinical guidelines into executable knowledge: a case study of covid‐19 and online demonstration
topic Brief Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323421/
https://www.ncbi.nlm.nih.gov/pubmed/32838035
http://dx.doi.org/10.1002/lrh2.10236
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