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COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences
BACKGROUND: As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex pub...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415382/ https://www.ncbi.nlm.nih.gov/pubmed/34298500 http://dx.doi.org/10.2196/29310 |
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author | Patterson, Jenny Rees Shaw, Donna Thomas, Sharita R Hayes, Julie A Daley, Christopher R Knight, Stefania Aikat, Jay Mieczkowska, Joanna O Ahalt, Stanley C Krishnamurthy, Ashok K |
author_facet | Patterson, Jenny Rees Shaw, Donna Thomas, Sharita R Hayes, Julie A Daley, Christopher R Knight, Stefania Aikat, Jay Mieczkowska, Joanna O Ahalt, Stanley C Krishnamurthy, Ashok K |
author_sort | Patterson, Jenny Rees |
collection | PubMed |
description | BACKGROUND: As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex public health problem, North Carolinians relied on data from state, federal, and global health organizations to increase their understanding of the pandemic and guide decision-making. OBJECTIVE: We aimed to describe the role that stakeholders involved in COVID-19–related data played in managing the pandemic in North Carolina. The study investigated the processes used by organizations throughout the state in using, collecting, and reporting COVID-19 data. METHODS: We used an exploratory qualitative study design to investigate North Carolina’s COVID-19 data collection efforts. To better understand these processes, key informant interviews were conducted with employees from organizations that collected COVID-19 data across the state. We developed an interview guide, and open-ended semistructured interviews were conducted during the period from June through November 2020. Interviews lasted between 30 and 45 minutes and were conducted by data scientists by videoconference. Data were subsequently analyzed using qualitative data analysis software. RESULTS: Results indicated that electronic health records were primary sources of COVID-19 data. Often, data were also used to create dashboards to inform the public or other health professionals, to aid in decision-making, or for reporting purposes. Cross-sector collaboration was cited as a major success. Consistency among metrics and data definitions, data collection processes, and contact tracing were cited as challenges. CONCLUSIONS: Findings suggest that, during future outbreaks, organizations across regions could benefit from data centralization and data governance. Data should be publicly accessible and in a user-friendly format. Additionally, established cross-sector collaboration networks are demonstrably beneficial for public health professionals across the state as these established relationships facilitate a rapid response to evolving public health challenges. |
format | Online Article Text |
id | pubmed-8415382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84153822021-09-24 COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences Patterson, Jenny Rees Shaw, Donna Thomas, Sharita R Hayes, Julie A Daley, Christopher R Knight, Stefania Aikat, Jay Mieczkowska, Joanna O Ahalt, Stanley C Krishnamurthy, Ashok K JMIR Public Health Surveill Original Paper BACKGROUND: As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex public health problem, North Carolinians relied on data from state, federal, and global health organizations to increase their understanding of the pandemic and guide decision-making. OBJECTIVE: We aimed to describe the role that stakeholders involved in COVID-19–related data played in managing the pandemic in North Carolina. The study investigated the processes used by organizations throughout the state in using, collecting, and reporting COVID-19 data. METHODS: We used an exploratory qualitative study design to investigate North Carolina’s COVID-19 data collection efforts. To better understand these processes, key informant interviews were conducted with employees from organizations that collected COVID-19 data across the state. We developed an interview guide, and open-ended semistructured interviews were conducted during the period from June through November 2020. Interviews lasted between 30 and 45 minutes and were conducted by data scientists by videoconference. Data were subsequently analyzed using qualitative data analysis software. RESULTS: Results indicated that electronic health records were primary sources of COVID-19 data. Often, data were also used to create dashboards to inform the public or other health professionals, to aid in decision-making, or for reporting purposes. Cross-sector collaboration was cited as a major success. Consistency among metrics and data definitions, data collection processes, and contact tracing were cited as challenges. CONCLUSIONS: Findings suggest that, during future outbreaks, organizations across regions could benefit from data centralization and data governance. Data should be publicly accessible and in a user-friendly format. Additionally, established cross-sector collaboration networks are demonstrably beneficial for public health professionals across the state as these established relationships facilitate a rapid response to evolving public health challenges. JMIR Publications 2021-09-02 /pmc/articles/PMC8415382/ /pubmed/34298500 http://dx.doi.org/10.2196/29310 Text en ©Jenny Rees Patterson, Donna Shaw, Sharita R Thomas, Julie A Hayes, Christopher R Daley, Stefania Knight, Jay Aikat, Joanna O Mieczkowska, Stanley C Ahalt, Ashok K Krishnamurthy. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 02.09.2021. 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 https://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Patterson, Jenny Rees Shaw, Donna Thomas, Sharita R Hayes, Julie A Daley, Christopher R Knight, Stefania Aikat, Jay Mieczkowska, Joanna O Ahalt, Stanley C Krishnamurthy, Ashok K COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title | COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title_full | COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title_fullStr | COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title_full_unstemmed | COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title_short | COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences |
title_sort | covid-19 data utilization in north carolina: qualitative analysis of stakeholder experiences |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415382/ https://www.ncbi.nlm.nih.gov/pubmed/34298500 http://dx.doi.org/10.2196/29310 |
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