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Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals

BACKGROUND: As more health care organizations transition to using electronic health record (EHR) systems, it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have sys...

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Autores principales: Noor, Kawsar, Roguski, Lukasz, Bai, Xi, Handy, Alex, Klapaukh, Roman, Folarin, Amos, Romao, Luis, Matteson, Joshua, Lea, Nathan, Zhu, Leilei, Asselbergs, Folkert W, Wong, Wai Keong, Shah, Anoop, Dobson, Richard JB
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453582/
https://www.ncbi.nlm.nih.gov/pubmed/36001371
http://dx.doi.org/10.2196/38122
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author Noor, Kawsar
Roguski, Lukasz
Bai, Xi
Handy, Alex
Klapaukh, Roman
Folarin, Amos
Romao, Luis
Matteson, Joshua
Lea, Nathan
Zhu, Leilei
Asselbergs, Folkert W
Wong, Wai Keong
Shah, Anoop
Dobson, Richard JB
author_facet Noor, Kawsar
Roguski, Lukasz
Bai, Xi
Handy, Alex
Klapaukh, Roman
Folarin, Amos
Romao, Luis
Matteson, Joshua
Lea, Nathan
Zhu, Leilei
Asselbergs, Folkert W
Wong, Wai Keong
Shah, Anoop
Dobson, Richard JB
author_sort Noor, Kawsar
collection PubMed
description BACKGROUND: As more health care organizations transition to using electronic health record (EHR) systems, it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have systems capable of harnessing the unstructured data fields in the record (clinical notes, letters, etc) and more practically have such systems interact with all of the hospital data systems (legacy and current). OBJECTIVE: We describe the deployment of the EHR interfacing information extraction and retrieval platform CogStack at University College London Hospitals (UCLH). METHODS: At UCLH, we have deployed the CogStack platform, an information retrieval platform with natural language processing capabilities. The platform addresses the problem of data ingestion and harmonization from multiple data sources using the Apache NiFi module for managing complex data flows. The platform also facilitates the extraction of structured data from free-text records through use of the MedCAT natural language processing library. Finally, data science tools are made available to support data scientists and the development of downstream applications dependent upon data ingested and analyzed by CogStack. RESULTS: The platform has been deployed at the hospital, and in particular, it has facilitated a number of research and service evaluation projects. To date, we have processed over 30 million records, and the insights produced from CogStack have informed a number of clinical research use cases at the hospital. CONCLUSIONS: The CogStack platform can be configured to handle the data ingestion and harmonization challenges faced by a hospital. More importantly, the platform enables the hospital to unlock important clinical information from the unstructured portion of the record using natural language processing technology.
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spelling pubmed-94535822022-09-09 Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals Noor, Kawsar Roguski, Lukasz Bai, Xi Handy, Alex Klapaukh, Roman Folarin, Amos Romao, Luis Matteson, Joshua Lea, Nathan Zhu, Leilei Asselbergs, Folkert W Wong, Wai Keong Shah, Anoop Dobson, Richard JB JMIR Med Inform Original Paper BACKGROUND: As more health care organizations transition to using electronic health record (EHR) systems, it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have systems capable of harnessing the unstructured data fields in the record (clinical notes, letters, etc) and more practically have such systems interact with all of the hospital data systems (legacy and current). OBJECTIVE: We describe the deployment of the EHR interfacing information extraction and retrieval platform CogStack at University College London Hospitals (UCLH). METHODS: At UCLH, we have deployed the CogStack platform, an information retrieval platform with natural language processing capabilities. The platform addresses the problem of data ingestion and harmonization from multiple data sources using the Apache NiFi module for managing complex data flows. The platform also facilitates the extraction of structured data from free-text records through use of the MedCAT natural language processing library. Finally, data science tools are made available to support data scientists and the development of downstream applications dependent upon data ingested and analyzed by CogStack. RESULTS: The platform has been deployed at the hospital, and in particular, it has facilitated a number of research and service evaluation projects. To date, we have processed over 30 million records, and the insights produced from CogStack have informed a number of clinical research use cases at the hospital. CONCLUSIONS: The CogStack platform can be configured to handle the data ingestion and harmonization challenges faced by a hospital. More importantly, the platform enables the hospital to unlock important clinical information from the unstructured portion of the record using natural language processing technology. JMIR Publications 2022-08-24 /pmc/articles/PMC9453582/ /pubmed/36001371 http://dx.doi.org/10.2196/38122 Text en ©Kawsar Noor, Lukasz Roguski, Xi Bai, Alex Handy, Roman Klapaukh, Amos Folarin, Luis Romao, Joshua Matteson, Nathan Lea, Leilei Zhu, Folkert W Asselbergs, Wai Keong Wong, Anoop Shah, Richard JB Dobson. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 24.08.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Noor, Kawsar
Roguski, Lukasz
Bai, Xi
Handy, Alex
Klapaukh, Roman
Folarin, Amos
Romao, Luis
Matteson, Joshua
Lea, Nathan
Zhu, Leilei
Asselbergs, Folkert W
Wong, Wai Keong
Shah, Anoop
Dobson, Richard JB
Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title_full Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title_fullStr Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title_full_unstemmed Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title_short Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals
title_sort deployment of a free-text analytics platform at a uk national health service research hospital: cogstack at university college london hospitals
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453582/
https://www.ncbi.nlm.nih.gov/pubmed/36001371
http://dx.doi.org/10.2196/38122
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