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CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital
BACKGROUND: Traditional health information systems are generally devised to support clinical data collection at the point of care. However, as the significance of the modern information economy expands in scope and permeates the healthcare domain, there is an increasing urgency for healthcare organi...
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/PMC6020175/ https://www.ncbi.nlm.nih.gov/pubmed/29941004 http://dx.doi.org/10.1186/s12911-018-0623-9 |
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author | Jackson, Richard Kartoglu, Ismail Stringer, Clive Gorrell, Genevieve Roberts, Angus Song, Xingyi Wu, Honghan Agrawal, Asha Lui, Kenneth Groza, Tudor Lewsley, Damian Northwood, Doug Folarin, Amos Stewart, Robert Dobson, Richard |
author_facet | Jackson, Richard Kartoglu, Ismail Stringer, Clive Gorrell, Genevieve Roberts, Angus Song, Xingyi Wu, Honghan Agrawal, Asha Lui, Kenneth Groza, Tudor Lewsley, Damian Northwood, Doug Folarin, Amos Stewart, Robert Dobson, Richard |
author_sort | Jackson, Richard |
collection | PubMed |
description | BACKGROUND: Traditional health information systems are generally devised to support clinical data collection at the point of care. However, as the significance of the modern information economy expands in scope and permeates the healthcare domain, there is an increasing urgency for healthcare organisations to offer information systems that address the expectations of clinicians, researchers and the business intelligence community alike. Amongst other emergent requirements, the principal unmet need might be defined as the 3R principle (right data, right place, right time) to address deficiencies in organisational data flow while retaining the strict information governance policies that apply within the UK National Health Service (NHS). Here, we describe our work on creating and deploying a low cost structured and unstructured information retrieval and extraction architecture within King’s College Hospital, the management of governance concerns and the associated use cases and cost saving opportunities that such components present. RESULTS: To date, our CogStack architecture has processed over 300 million lines of clinical data, making it available for internal service improvement projects at King’s College London. On generated data designed to simulate real world clinical text, our de-identification algorithm achieved up to 94% precision and up to 96% recall. CONCLUSION: We describe a toolkit which we feel is of huge value to the UK (and beyond) healthcare community. It is the only open source, easily deployable solution designed for the UK healthcare environment, in a landscape populated by expensive proprietary systems. Solutions such as these provide a crucial foundation for the genomic revolution in medicine. |
format | Online Article Text |
id | pubmed-6020175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60201752018-07-06 CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital Jackson, Richard Kartoglu, Ismail Stringer, Clive Gorrell, Genevieve Roberts, Angus Song, Xingyi Wu, Honghan Agrawal, Asha Lui, Kenneth Groza, Tudor Lewsley, Damian Northwood, Doug Folarin, Amos Stewart, Robert Dobson, Richard BMC Med Inform Decis Mak Software BACKGROUND: Traditional health information systems are generally devised to support clinical data collection at the point of care. However, as the significance of the modern information economy expands in scope and permeates the healthcare domain, there is an increasing urgency for healthcare organisations to offer information systems that address the expectations of clinicians, researchers and the business intelligence community alike. Amongst other emergent requirements, the principal unmet need might be defined as the 3R principle (right data, right place, right time) to address deficiencies in organisational data flow while retaining the strict information governance policies that apply within the UK National Health Service (NHS). Here, we describe our work on creating and deploying a low cost structured and unstructured information retrieval and extraction architecture within King’s College Hospital, the management of governance concerns and the associated use cases and cost saving opportunities that such components present. RESULTS: To date, our CogStack architecture has processed over 300 million lines of clinical data, making it available for internal service improvement projects at King’s College London. On generated data designed to simulate real world clinical text, our de-identification algorithm achieved up to 94% precision and up to 96% recall. CONCLUSION: We describe a toolkit which we feel is of huge value to the UK (and beyond) healthcare community. It is the only open source, easily deployable solution designed for the UK healthcare environment, in a landscape populated by expensive proprietary systems. Solutions such as these provide a crucial foundation for the genomic revolution in medicine. BioMed Central 2018-06-25 /pmc/articles/PMC6020175/ /pubmed/29941004 http://dx.doi.org/10.1186/s12911-018-0623-9 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 | Software Jackson, Richard Kartoglu, Ismail Stringer, Clive Gorrell, Genevieve Roberts, Angus Song, Xingyi Wu, Honghan Agrawal, Asha Lui, Kenneth Groza, Tudor Lewsley, Damian Northwood, Doug Folarin, Amos Stewart, Robert Dobson, Richard CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title | CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title_full | CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title_fullStr | CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title_full_unstemmed | CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title_short | CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital |
title_sort | cogstack - experiences of deploying integrated information retrieval and extraction services in a large national health service foundation trust hospital |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020175/ https://www.ncbi.nlm.nih.gov/pubmed/29941004 http://dx.doi.org/10.1186/s12911-018-0623-9 |
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