Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research
Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of cont...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/10356/146361 |
| _version_ | 1826128225681539072 |
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| author | Lee, Edmund Wei Jian Viswanath, Kasisomayajula |
| author2 | Wee Kim Wee School of Communication and Information |
| author_facet | Wee Kim Wee School of Communication and Information Lee, Edmund Wei Jian Viswanath, Kasisomayajula |
| author_sort | Lee, Edmund Wei Jian |
| collection | NTU |
| description | Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities. |
| first_indexed | 2024-10-01T07:21:28Z |
| format | Journal Article |
| id | ntu-10356/146361 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:21:28Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1463612023-03-05T15:58:47Z Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research Lee, Edmund Wei Jian Viswanath, Kasisomayajula Wee Kim Wee School of Communication and Information Science::Medicine Big Data Artificial Intelligence Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities. Published version 2021-02-11T01:29:31Z 2021-02-11T01:29:31Z 2020 Journal Article Lee, E. W. J., & Viswanath, K. (2020). Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research. Journal of Medical Internet Research, 22(1), e16377-. doi:10.2196/16377 1438-8871 https://hdl.handle.net/10356/146361 10.2196/16377 31909724 2-s2.0-85077570365 1 22 en Journal of medical Internet research © Edmund W J Lee, Kasisomayajula Viswanath. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.01.2020. 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. application/pdf |
| spellingShingle | Science::Medicine Big Data Artificial Intelligence Lee, Edmund Wei Jian Viswanath, Kasisomayajula Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title | Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title_full | Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title_fullStr | Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title_full_unstemmed | Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title_short | Big data in context : addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| title_sort | big data in context addressing the twin perils of data absenteeism and chauvinism in the context of health disparities research |
| topic | Science::Medicine Big Data Artificial Intelligence |
| url | https://hdl.handle.net/10356/146361 |
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