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The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment
BACKGROUND: Digital health is a dynamic field that has been generating a large number of tools; many of these tools do not have the level of maturity required to function in a sustainable model. It is in this context that the concept of global goods maturity is gaining importance. Digital Square dev...
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/PMC7221633/ https://www.ncbi.nlm.nih.gov/pubmed/32347809 http://dx.doi.org/10.2196/15860 |
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author | Tom-Aba, Daniel Silenou, Bernard Chawo Doerrbecker, Juliane Fourie, Carl Leitner, Carl Wahnschaffe, Martin Strysewske, Maté Arinze, Chinedu Chukwujekwu Krause, Gerard |
author_facet | Tom-Aba, Daniel Silenou, Bernard Chawo Doerrbecker, Juliane Fourie, Carl Leitner, Carl Wahnschaffe, Martin Strysewske, Maté Arinze, Chinedu Chukwujekwu Krause, Gerard |
author_sort | Tom-Aba, Daniel |
collection | PubMed |
description | BACKGROUND: Digital health is a dynamic field that has been generating a large number of tools; many of these tools do not have the level of maturity required to function in a sustainable model. It is in this context that the concept of global goods maturity is gaining importance. Digital Square developed a global good maturity model (GGMM) for digital health tools, which engages the digital health community to identify areas of investment for global goods. The Surveillance Outbreak Response Management and Analysis System (SORMAS) is an open-source mobile and web application software that we developed to enable health workers to notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreak response. OBJECTIVE: The objective of this study was to evaluate the maturity of SORMAS using Digital Square’s GGMM and to describe the applicability of the GGMM on the use case of SORMAS and identify opportunities for system improvements. METHODS: We evaluated SORMAS using the GGMM version 1.0 indicators to measure its development. SORMAS was scored based on all the GGMM indicator scores. We described how we used the GGMM to guide the development of SORMAS during the study period. GGMM contains 15 subindicators grouped into the following core indicators: (1) global utility, (2) community support, and (3) software maturity. RESULTS: The assessment of SORMAS through the GGMM from November 2017 to October 2019 resulted in full completion of all subscores (10/30, (33%) in 2017; 21/30, (70%) in 2018; and 30/30, (100%) in 2019). SORMAS reached the full score of the GGMM for digital health software tools by accomplishing all 10 points for each of the 3 indicators on global utility, community support, and software maturity. CONCLUSIONS: To our knowledge, SORMAS is the first electronic health tool for disease surveillance, and also the first outbreak response management tool, that has achieved a 100% score. Although some conceptual changes would allow for further improvements to the system, the GGMM already has a robust supportive effect on developing software toward global goods maturity. |
format | Online Article Text |
id | pubmed-7221633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-72216332020-05-18 The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment Tom-Aba, Daniel Silenou, Bernard Chawo Doerrbecker, Juliane Fourie, Carl Leitner, Carl Wahnschaffe, Martin Strysewske, Maté Arinze, Chinedu Chukwujekwu Krause, Gerard JMIR Public Health Surveill Original Paper BACKGROUND: Digital health is a dynamic field that has been generating a large number of tools; many of these tools do not have the level of maturity required to function in a sustainable model. It is in this context that the concept of global goods maturity is gaining importance. Digital Square developed a global good maturity model (GGMM) for digital health tools, which engages the digital health community to identify areas of investment for global goods. The Surveillance Outbreak Response Management and Analysis System (SORMAS) is an open-source mobile and web application software that we developed to enable health workers to notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreak response. OBJECTIVE: The objective of this study was to evaluate the maturity of SORMAS using Digital Square’s GGMM and to describe the applicability of the GGMM on the use case of SORMAS and identify opportunities for system improvements. METHODS: We evaluated SORMAS using the GGMM version 1.0 indicators to measure its development. SORMAS was scored based on all the GGMM indicator scores. We described how we used the GGMM to guide the development of SORMAS during the study period. GGMM contains 15 subindicators grouped into the following core indicators: (1) global utility, (2) community support, and (3) software maturity. RESULTS: The assessment of SORMAS through the GGMM from November 2017 to October 2019 resulted in full completion of all subscores (10/30, (33%) in 2017; 21/30, (70%) in 2018; and 30/30, (100%) in 2019). SORMAS reached the full score of the GGMM for digital health software tools by accomplishing all 10 points for each of the 3 indicators on global utility, community support, and software maturity. CONCLUSIONS: To our knowledge, SORMAS is the first electronic health tool for disease surveillance, and also the first outbreak response management tool, that has achieved a 100% score. Although some conceptual changes would allow for further improvements to the system, the GGMM already has a robust supportive effect on developing software toward global goods maturity. JMIR Publications 2020-04-29 /pmc/articles/PMC7221633/ /pubmed/32347809 http://dx.doi.org/10.2196/15860 Text en ©Daniel Tom-Aba, Bernard Chawo Silenou, Juliane Doerrbecker, Carl Fourie, Carl Leitner, Martin Wahnschaffe, Maté Strysewske, Chinedu Chukwujekwu Arinze, Gerard Krause. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 29.04.2020. 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 JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Tom-Aba, Daniel Silenou, Bernard Chawo Doerrbecker, Juliane Fourie, Carl Leitner, Carl Wahnschaffe, Martin Strysewske, Maté Arinze, Chinedu Chukwujekwu Krause, Gerard The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title | The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title_full | The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title_fullStr | The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title_full_unstemmed | The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title_short | The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment |
title_sort | surveillance outbreak response management and analysis system (sormas): digital health global goods maturity assessment |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7221633/ https://www.ncbi.nlm.nih.gov/pubmed/32347809 http://dx.doi.org/10.2196/15860 |
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