Development and implementation of clinical guidelines : an artificial intelligence perspective

Detalhes bibliográficos
Autor(a) principal: Oliveira, Tiago José Martins
Data de Publicação: 2014
Outros Autores: Novais, Paulo, Neves, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/32070
Resumo: Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.
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spelling Development and implementation of clinical guidelines : an artificial intelligence perspectiveComputer-interpretable guidelinesOntologiesDecision supportQuality of informationEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaScience & TechnologyClinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst-OE/EEI/UI0752/2011".SpringerUniversidade do MinhoOliveira, Tiago José MartinsNovais, PauloNeves, José20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/32070eng0269-282110.1007/s10462-013-9402-2http://link.springer.com/article/10.1007/s10462-013-9402-2info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:15:11Zoai:repositorium.sdum.uminho.pt:1822/32070Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:07:37.143099Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Development and implementation of clinical guidelines : an artificial intelligence perspective
title Development and implementation of clinical guidelines : an artificial intelligence perspective
spellingShingle Development and implementation of clinical guidelines : an artificial intelligence perspective
Oliveira, Tiago José Martins
Computer-interpretable guidelines
Ontologies
Decision support
Quality of information
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
title_short Development and implementation of clinical guidelines : an artificial intelligence perspective
title_full Development and implementation of clinical guidelines : an artificial intelligence perspective
title_fullStr Development and implementation of clinical guidelines : an artificial intelligence perspective
title_full_unstemmed Development and implementation of clinical guidelines : an artificial intelligence perspective
title_sort Development and implementation of clinical guidelines : an artificial intelligence perspective
author Oliveira, Tiago José Martins
author_facet Oliveira, Tiago José Martins
Novais, Paulo
Neves, José
author_role author
author2 Novais, Paulo
Neves, José
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Oliveira, Tiago José Martins
Novais, Paulo
Neves, José
dc.subject.por.fl_str_mv Computer-interpretable guidelines
Ontologies
Decision support
Quality of information
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
topic Computer-interpretable guidelines
Ontologies
Decision support
Quality of information
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Science & Technology
description Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/32070
url http://hdl.handle.net/1822/32070
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0269-2821
10.1007/s10462-013-9402-2
http://link.springer.com/article/10.1007/s10462-013-9402-2
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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