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Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform
The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patient...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257473/ https://www.ncbi.nlm.nih.gov/pubmed/32442130 http://dx.doi.org/10.2196/18707 |
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author | Schulz, Wade L Durant, Thomas J S Torre Jr, Charles J Hsiao, Allen L Krumholz, Harlan M |
author_facet | Schulz, Wade L Durant, Thomas J S Torre Jr, Charles J Hsiao, Allen L Krumholz, Harlan M |
author_sort | Schulz, Wade L |
collection | PubMed |
description | The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patients presenting with suspected respiratory tract infection and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2. This tool was built upon our computational health platform, which provides access to near real-time data from disparate HIT sources across our health system. This combination of technology allowed us to rapidly prototype, iterate, and deploy a platform to support a cohesive organizational response to a rapidly evolving outbreak. Platforms that allow for agile analytics are needed to keep pace with evolving needs within the health care system. |
format | Online Article Text |
id | pubmed-7257473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-72574732020-08-06 Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform Schulz, Wade L Durant, Thomas J S Torre Jr, Charles J Hsiao, Allen L Krumholz, Harlan M J Med Internet Res Viewpoint The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patients presenting with suspected respiratory tract infection and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2. This tool was built upon our computational health platform, which provides access to near real-time data from disparate HIT sources across our health system. This combination of technology allowed us to rapidly prototype, iterate, and deploy a platform to support a cohesive organizational response to a rapidly evolving outbreak. Platforms that allow for agile analytics are needed to keep pace with evolving needs within the health care system. JMIR Publications 2020-05-28 /pmc/articles/PMC7257473/ /pubmed/32442130 http://dx.doi.org/10.2196/18707 Text en ©Wade L Schulz, Thomas J S Durant, Charles J Torre Jr, Allen L Hsiao, Harlan M Krumholz. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.05.2020. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Schulz, Wade L Durant, Thomas J S Torre Jr, Charles J Hsiao, Allen L Krumholz, Harlan M Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title | Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title_full | Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title_fullStr | Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title_full_unstemmed | Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title_short | Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform |
title_sort | agile health care analytics: enabling real-time disease surveillance with a computational health platform |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257473/ https://www.ncbi.nlm.nih.gov/pubmed/32442130 http://dx.doi.org/10.2196/18707 |
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