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Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example
BACKGROUND: Great strides have been made exploring and exploiting new and different sources of disease surveillance data and developing robust statistical methods for analyzing the collected data. However, there has been less research in the area of dissemination. Proper dissemination of surveillanc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Gunther Eysenbach
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3222192/ https://www.ncbi.nlm.nih.gov/pubmed/22001082 http://dx.doi.org/10.2196/jmir.1658 |
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author | Cheng, Calvin KY Ip, Dennis KM Cowling, Benjamin J Ho, Lai Ming Leung, Gabriel M Lau, Eric HY |
author_facet | Cheng, Calvin KY Ip, Dennis KM Cowling, Benjamin J Ho, Lai Ming Leung, Gabriel M Lau, Eric HY |
author_sort | Cheng, Calvin KY |
collection | PubMed |
description | BACKGROUND: Great strides have been made exploring and exploiting new and different sources of disease surveillance data and developing robust statistical methods for analyzing the collected data. However, there has been less research in the area of dissemination. Proper dissemination of surveillance data can facilitate the end user's taking of appropriate actions, thus maximizing the utility of effort taken from upstream of the surveillance-to-action loop. OBJECTIVE: The aims of the study were to develop a generic framework for a digital dashboard incorporating features of efficient dashboard design and to demonstrate this framework by specific application to influenza surveillance in Hong Kong. METHODS: Based on the merits of the national websites and principles of efficient dashboard design, we designed an automated influenza surveillance digital dashboard as a demonstration of efficient dissemination of surveillance data. We developed the system to synthesize and display multiple sources of influenza surveillance data streams in the dashboard. Different algorithms can be implemented in the dashboard for incorporating all surveillance data streams to describe the overall influenza activity. RESULTS: We designed and implemented an influenza surveillance dashboard that utilized self-explanatory figures to display multiple surveillance data streams in panels. Indicators for individual data streams as well as for overall influenza activity were summarized in the main page, which can be read at a glance. Data retrieval function was also incorporated to allow data sharing in standard format. CONCLUSIONS: The influenza surveillance dashboard serves as a template to illustrate the efficient synthesization and dissemination of multiple-source surveillance data, which may also be applied to other diseases. Surveillance data from multiple sources can be disseminated efficiently using a dashboard design that facilitates the translation of surveillance information to public health actions. |
format | Online Article Text |
id | pubmed-3222192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Gunther Eysenbach |
record_format | MEDLINE/PubMed |
spelling | pubmed-32221922011-11-22 Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example Cheng, Calvin KY Ip, Dennis KM Cowling, Benjamin J Ho, Lai Ming Leung, Gabriel M Lau, Eric HY J Med Internet Res Original Paper BACKGROUND: Great strides have been made exploring and exploiting new and different sources of disease surveillance data and developing robust statistical methods for analyzing the collected data. However, there has been less research in the area of dissemination. Proper dissemination of surveillance data can facilitate the end user's taking of appropriate actions, thus maximizing the utility of effort taken from upstream of the surveillance-to-action loop. OBJECTIVE: The aims of the study were to develop a generic framework for a digital dashboard incorporating features of efficient dashboard design and to demonstrate this framework by specific application to influenza surveillance in Hong Kong. METHODS: Based on the merits of the national websites and principles of efficient dashboard design, we designed an automated influenza surveillance digital dashboard as a demonstration of efficient dissemination of surveillance data. We developed the system to synthesize and display multiple sources of influenza surveillance data streams in the dashboard. Different algorithms can be implemented in the dashboard for incorporating all surveillance data streams to describe the overall influenza activity. RESULTS: We designed and implemented an influenza surveillance dashboard that utilized self-explanatory figures to display multiple surveillance data streams in panels. Indicators for individual data streams as well as for overall influenza activity were summarized in the main page, which can be read at a glance. Data retrieval function was also incorporated to allow data sharing in standard format. CONCLUSIONS: The influenza surveillance dashboard serves as a template to illustrate the efficient synthesization and dissemination of multiple-source surveillance data, which may also be applied to other diseases. Surveillance data from multiple sources can be disseminated efficiently using a dashboard design that facilitates the translation of surveillance information to public health actions. Gunther Eysenbach 2011-10-14 /pmc/articles/PMC3222192/ /pubmed/22001082 http://dx.doi.org/10.2196/jmir.1658 Text en ©Calvin KY Cheng, Dennis KM Ip, Benjamin J Cowling, Lai Ming Ho, Gabriel M Leung, Eric HY Lau. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.10.2011. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), 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 | Original Paper Cheng, Calvin KY Ip, Dennis KM Cowling, Benjamin J Ho, Lai Ming Leung, Gabriel M Lau, Eric HY Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title | Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title_full | Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title_fullStr | Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title_full_unstemmed | Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title_short | Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example |
title_sort | digital dashboard design using multiple data streams for disease surveillance with influenza surveillance as an example |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3222192/ https://www.ncbi.nlm.nih.gov/pubmed/22001082 http://dx.doi.org/10.2196/jmir.1658 |
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