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Delivering Health Intelligence For Healthcare Services

Bibliographic Details
Main Author: Murray, Michael
Publication Date: 2019
Other Authors: Macedo, Mário, Glynn, Carole
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10884/1467
Summary: The systems barrier for clinical information interoperability and standards has now evolved from a technology barrier to a semantic barrier. The processes to gather clinical data and to build clinical information and knowledge cannot be fully implemented, owing to semantic dissonances and limited data normalization. According to [1], “Just over a half of entered codes were appropriate for a given scenario and about a quarter were omitted.” This is a significant data and financial gap for healthcare provision. Huge amount of addition to the financial cost, lack of data integration and loss of information affects the ability to maintain standards in clinical care delivery and patient outcomes. This paper proposes that the solution to these issues is an augmented network of clinical note taking, where coding is automatically generated by an AI system as clinicians write their clinical notes. The system (AI-KEN) offers enhanced web support that is integrated to local clinical systems, whereby clinical notes are prompted by suggested predictive text options in real time. The anticipated benefits include reducing financial loss for acute services, support for clinical standard maintenance and enhanced advancements for clinical practice and research in real time.
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spelling Delivering Health Intelligence For Healthcare ServicesArtificial intelligenceHealthcareClinical decision support systemsThe systems barrier for clinical information interoperability and standards has now evolved from a technology barrier to a semantic barrier. The processes to gather clinical data and to build clinical information and knowledge cannot be fully implemented, owing to semantic dissonances and limited data normalization. According to [1], “Just over a half of entered codes were appropriate for a given scenario and about a quarter were omitted.” This is a significant data and financial gap for healthcare provision. Huge amount of addition to the financial cost, lack of data integration and loss of information affects the ability to maintain standards in clinical care delivery and patient outcomes. This paper proposes that the solution to these issues is an augmented network of clinical note taking, where coding is automatically generated by an AI system as clinicians write their clinical notes. The system (AI-KEN) offers enhanced web support that is integrated to local clinical systems, whereby clinical notes are prompted by suggested predictive text options in real time. The anticipated benefits include reducing financial loss for acute services, support for clinical standard maintenance and enhanced advancements for clinical practice and research in real time.2020-01-22T16:46:41Z2020-01-222019-11-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10884/1467http://hdl.handle.net/10884/1467engMurray, M.; Macedo, M. & Glynn, C.(2019). Delivering Health Intelligence For Healthcare Services. 2019 First International Conference on Digital Data Processing (DDP)Murray, MichaelMacedo, MárioGlynn, Caroleinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-05-15T17:44:49Zoai:repositorio-cientifico.uatlantica.pt:10884/1467Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T07:28:03.044284Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Delivering Health Intelligence For Healthcare Services
title Delivering Health Intelligence For Healthcare Services
spellingShingle Delivering Health Intelligence For Healthcare Services
Murray, Michael
Artificial intelligence
Healthcare
Clinical decision support systems
title_short Delivering Health Intelligence For Healthcare Services
title_full Delivering Health Intelligence For Healthcare Services
title_fullStr Delivering Health Intelligence For Healthcare Services
title_full_unstemmed Delivering Health Intelligence For Healthcare Services
title_sort Delivering Health Intelligence For Healthcare Services
author Murray, Michael
author_facet Murray, Michael
Macedo, Mário
Glynn, Carole
author_role author
author2 Macedo, Mário
Glynn, Carole
author2_role author
author
dc.contributor.author.fl_str_mv Murray, Michael
Macedo, Mário
Glynn, Carole
dc.subject.por.fl_str_mv Artificial intelligence
Healthcare
Clinical decision support systems
topic Artificial intelligence
Healthcare
Clinical decision support systems
description The systems barrier for clinical information interoperability and standards has now evolved from a technology barrier to a semantic barrier. The processes to gather clinical data and to build clinical information and knowledge cannot be fully implemented, owing to semantic dissonances and limited data normalization. According to [1], “Just over a half of entered codes were appropriate for a given scenario and about a quarter were omitted.” This is a significant data and financial gap for healthcare provision. Huge amount of addition to the financial cost, lack of data integration and loss of information affects the ability to maintain standards in clinical care delivery and patient outcomes. This paper proposes that the solution to these issues is an augmented network of clinical note taking, where coding is automatically generated by an AI system as clinicians write their clinical notes. The system (AI-KEN) offers enhanced web support that is integrated to local clinical systems, whereby clinical notes are prompted by suggested predictive text options in real time. The anticipated benefits include reducing financial loss for acute services, support for clinical standard maintenance and enhanced advancements for clinical practice and research in real time.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-01T00:00:00Z
2020-01-22T16:46:41Z
2020-01-22
dc.type.driver.fl_str_mv conference object
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10884/1467
http://hdl.handle.net/10884/1467
url http://hdl.handle.net/10884/1467
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Murray, M.; Macedo, M. & Glynn, C.(2019). Delivering Health Intelligence For Healthcare Services. 2019 First International Conference on Digital Data Processing (DDP)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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