A review of big data and medical research.
Big data
COVID-19
epidemiology/public health
medical research
real-world evidence
research paradigm
Journal
SAGE open medicine
ISSN: 2050-3121
Titre abrégé: SAGE Open Med
Pays: England
ID NLM: 101624744
Informations de publication
Date de publication:
2020
2020
Historique:
received:
26
12
2019
accepted:
21
05
2020
entrez:
9
7
2020
pubmed:
9
7
2020
medline:
9
7
2020
Statut:
epublish
Résumé
Universally, the volume of data has increased, with the collection rate doubling every 40 months, since the 1980s. "Big data" is a term that was introduced in the 1990s to include data sets too large to be used with common software. Medicine is a major field predicted to increase the use of big data in 2025. Big data in medicine may be used by commercial, academic, government, and public sectors. It includes biologic, biometric, and electronic health data. Examples of biologic data include biobanks; biometric data may have individual wellness data from devices; electronic health data include the medical record; and other data demographics and images. Big data has also contributed to the changes in the research methodology. Changes in the clinical research paradigm has been fueled by large-scale biological data harvesting (biobanks), which is developed, analyzed, and managed by cheaper computing technology (big data), supported by greater flexibility in study design (real-world data) and the relationships between industry, government regulators, and academics. Cultural changes along with easy access to information via the Internet facilitate ease of participation by more people. Current needs demand quick answers which may be supplied by big data, biobanks, and changes in flexibility in study design. Big data can reveal health patterns, and promises to provide solutions that have previously been out of society's grasp; however, the murkiness of international laws, questions of data ownership, public ignorance, and privacy and security concerns are slowing down the progress that could otherwise be achieved by the use of big data. The goal of this descriptive review is to create awareness of the ramifications for big data and to encourage readers that this trend is positive and will likely lead to better clinical solutions, but, caution must be exercised to reduce harm.
Identifiants
pubmed: 32637104
doi: 10.1177/2050312120934839
pii: 10.1177_2050312120934839
pmc: PMC7323266
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
2050312120934839Informations de copyright
© The Author(s) 2020.
Déclaration de conflit d'intérêts
Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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