Studies in health technology and informatics
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Stud Health Technol Inform · Jun 2020
An Analysis of the Growth in Uptake of OpenWHO's Online Learning Resources for COVID-19.
From 26 January - 21 April 2020, 9 online courses for COVID-19 were published on OpenWHO.org. The courses are available in 18 different languages, totalling 53 learning resources and more than 1.5 million course enrolments. ⋯ The number of enrolments increased significantly between 26 January and 21 April, with distinct spikes in growth preceded by important global milestones in the timeline of the outbreak. The surge in users demonstrates that the platform is serving as a source of digitized learning for COVID-19, helping meet the broad demand for outbreak-related information.
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Stud Health Technol Inform · Jun 2020
Application of Topic Modeling to Tweets as the Foundation for Health Disparity Research for COVID-19.
We randomly extracted publicly available Tweets mentioning COVID-19 related terms (n=2,558,474 Tweets) from Tweet corpora collected daily using an API from Jan 21st to May 3rd, 2020. We applied a clustering algorithm to publicly available Tweets authored by African Americans (n=1,763) to detect topics and sentiment applying natural language processing (NLP). ⋯ Compared to the COVID-19 related Tweets authored by others, positive sentiments, cohesively encouraging online discussions (e.g., Black strong 27.1%, growing up Blacks 22.8%, support Black business 17.0%, how to build resilience 7.8%), and COVID-19 prevention behaviors (e.g., masks 4.7%, encouraging social distancing 9.4%) were uniquely observed in African American Twitter communities. Application of topic modeling techniques to streaming social media Twitter provides the foundation for research team insights regarding information and future virtual based intervention and social media based health disparity research for COVID-19.
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Stud Health Technol Inform · Jun 2020
Global Access to OpenWHO's Online Learning Resources for COVID-19.
This poster presents the COVID-19 online learning response by the World Health Organization's (WHO) OpenWHO learning platform for health emergencies. Platform use shifted during the pandemic from being the highest in the WHO African and Eastern Mediterranean regions to the American and European regions. The largest traffic channels were search engines, social media and WHO websites.
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Clinical decision support systems (CDSSs) provides vital information for managing patients by advising clinicians through an alert or reminders about adverse events and medication errors. Clinicians receive a high number of alerts, resulting in alert override and workflow disruptions. ⋯ The review findings identified several influencing factors of CDSS alert appropriateness including: technology (usability, alert presentation, workload and data entry), human (training, knowledge and skills, attitude and behavior), organization (rules and regulation, privacy and security) and process (waste, delay, tuning and optimization). The findings can be used to guide the design of CDSS alert and minimise potential safety hazards associated with CDSS use.
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This paper reports a case study on the spontaneous personalization discussions emerged from interviews with healthcare professionals when asked about their work practices and the role of information technology (IT) during consultations. We thematically analyzed the personalization elements using an existing personalization framework to provide insights on the service personalization. Our results contribute to the better design of IT solutions that can support health services' personalization.