Because extensive data from medical records are gathered by organ procurement teams, the process of data transfer between sites created a data security risk. This includes the use of fax machines, courier services, and employees' vehicles. Even health records transmitted over public Wi-Fi become at risk for a data breach. The Plan-Do-Study-Act method for performance improvement was used to address this time-consuming and labor-intensive process. A secured virtual private network from within the donor hospital site setting was developed to improve the transfer of images and data. The goal was to improve the process and increase data security. Once the new network was in place, the process steps decreased and eliminated data vulnerability. Average process time decreased by approximately 1 hour. Organs procured increased from pre (expected 3, observed 2) to post (expected 3, observed 5) implementation of the new process.
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http://dx.doi.org/10.1177/1526924819855077 | DOI Listing |
J Public Health Policy
January 2025
Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, 110029, India.
Collaborative initiatives of the drone industry and healthcare sector are becoming a pivotal step in restructuring healthcare service delivery in India. This paper documents knowledge and perceptions of healthcare workers from various districts of Manipur and Nagaland towards the use of drones for medical supply in the region. The study utilized 27 in-depth interviews with healthcare workers to collect qualitative data, which was then analyzed using NVivo 14 for thematic and content analysis.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Artificial Intelligence and Data Science, College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia.
In the present digital scenario, the explosion of Internet of Things (IoT) devices makes massive volumes of high-dimensional data, presenting significant data and privacy security challenges. As IoT networks enlarge, certifying sensitive data privacy while still employing data analytics authority is vital. In the period of big data, statistical learning has seen fast progressions in methodological practical and innovation applications.
View Article and Find Full Text PDFIn cybersecurity, anomaly detection in tabular data is essential for ensuring information security. While traditional machine learning and deep learning methods have shown some success, they continue to face significant challenges in terms of generalization. To address these limitations, this paper presents an innovative method for tabular data anomaly detection based on large language models, called "Tabular Anomaly Detection via Guided Prompts" (TAD-GP).
View Article and Find Full Text PDFNat Commun
January 2025
Department of Traffic Management School, People's Public Security University of China, Beijing, 100038, China.
The takeover issue, especially the setting of the takeover time budget, is a critical factor restricting the implementation and development of conditionally automated vehicles. The general fixed takeover time budget has certain limitations, as it does not take into account the driver's non-driving behaviors. Here, we propose an intelligent takeover assistance system consisting of all-round sensing gloves, a non-driving behavior identification module, and a takeover time budget determination module.
View Article and Find Full Text PDFClin Microbiol Infect
January 2025
Infectious Diseases and Microbiology Division, Hospital Universitario Virgen Macarena; Department of Medicine, University of Seville; Instituto de Biomedicina de Sevilla (IBiS)/Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain; CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain.
Background: Data sharing accelerates scientific progress and improves evidence quality. Even though journals and funding institutions require investigators to share data, only a small part of studies made their data publicly available upon publication. The procedures necessary to share retrospective data for re-use in secondary data analysis projects can be cumbersome.
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