Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Fairchild FrontPubHealth2018 6.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig5 Jalali JofMedIntRes2019 21-2.png|240px]]</div>
'''"[[Journal:Epidemiological data challenges: Planning for a more robust future through data standards|Epidemiological data challenges: Planning for a more robust future through data standards]]"'''
'''"[[Journal:Health care and cybersecurity: Bibliometric analysis of the literature|Health care and cybersecurity: Bibliometric analysis of the literature]]"'''


Accessible [[Epidemiology|epidemiological]] data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status quo, however, renders acquiring and using such data difficult in practice. In many cases, a primary way of obtaining epidemiological data is through the internet, but the methods by which the data are presented to the public often differ drastically among institutions. As a result, there is a strong need for better data sharing practices. This paper identifies, in detail and with examples, the three key challenges one encounters when attempting to acquire and use epidemiological data: (1) interfaces, (2) data formatting, and (3) reporting. ('''[[Journal:Epidemiological data challenges: Planning for a more robust future through data standards|Full article...]]''')<br />
Over the past decade, clinical care has become globally dependent on information technology. The [[cybersecurity]] of [[health informatics|health care information systems]] is now an essential component of safe, reliable, and effective health care delivery. The objective of this study was to provide an overview of the literature at the intersection of cybersecurity and health care delivery. A comprehensive search was conducted using PubMed and Web of Science for English-language peer-reviewed articles. We carried out chronological analysis, domain clustering analysis, and text analysis of the included articles to generate a high-level concept map composed of specific words and the connections between them. Our final sample included 472 English-language journal articles. Our review results revealed that a majority of the articles were focused on technology. Technology–focused articles made up more than half of all the clusters, whereas managerial articles accounted for only 32 percent of all clusters. ('''[[Journal:Health care and cybersecurity: Bibliometric analysis of the literature|Full article...]]''')<br />
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''Recently featured'':
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Revision as of 16:33, 21 June 2021

Fig5 Jalali JofMedIntRes2019 21-2.png

"Health care and cybersecurity: Bibliometric analysis of the literature"

Over the past decade, clinical care has become globally dependent on information technology. The cybersecurity of health care information systems is now an essential component of safe, reliable, and effective health care delivery. The objective of this study was to provide an overview of the literature at the intersection of cybersecurity and health care delivery. A comprehensive search was conducted using PubMed and Web of Science for English-language peer-reviewed articles. We carried out chronological analysis, domain clustering analysis, and text analysis of the included articles to generate a high-level concept map composed of specific words and the connections between them. Our final sample included 472 English-language journal articles. Our review results revealed that a majority of the articles were focused on technology. Technology–focused articles made up more than half of all the clusters, whereas managerial articles accounted for only 32 percent of all clusters. (Full article...)

Recently featured:

▪ Epidemiological data challenges: Planning for a more robust future through data standards
▪ Wrangling environmental exposure data: Guidance for getting the best information from your laboratory measurements
▪ One tool to find them all: A case of data integration and querying in a distributed LIMS platform
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