The resurgence of interest in the promise of interprofessional education and collaborative practice (IPECP) to positively impact health outcomes, requires the collection of appropriate data that can be analyzed and from which information and knowledge linking IPECP interventions to improved health outcomes might be produced and reported to stakeholders such as health systems, policy makers and regulators, payers, and accreditation agencies. To generate such knowledge the National Center for Interprofessional Practice and Education at the University of Minnesota has developed three strategies, the first two of which are: (1) creating an IPECP research agenda, and (2) a national Nexus Innovation Network (NIN) of intervention projects that are generating data that are being input and housed in a National Center Data Repository (NCDR). In this paper, the informatics platform supporting the work of these first two strategies is presented as the third interconnected strategy for knowledge generation. The proof of concept for the informatics strategy is developed in this paper by describing: data input from the NIN into the NCDR, the linking and merging of those data to produce analyzable data files that incorporate institutional and individual level data, and the production of meaningful analyses to create and provide relevant information and knowledge. This paper is organized around the concepts of data, information and knowledge-the three conceptual foundations of informatics.
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http://dx.doi.org/10.3390/healthcare3041158 | DOI Listing |
NPJ Digit Med
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Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
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January 2025
Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Moorenstr. 5, 40225, Dusseldorf, Germany.
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January 2025
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Machine learning algorithms have proven to be effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of a chiral edge state and a topological surface state.
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January 2025
School of Nursing and Midwifery, La Trobe University, Bundoora, VIC 3086, Australia; Judith Lumley Centre, La Trobe University, Bundoora, VIC 3086, Australia.
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Compound-specific stable isotope analysis (CSIA) using liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is a powerful tool for determining the isotopic composition of carbon in analytes from complex mixtures. However, LC-IRMS methods are constrained to fully aqueous eluents. Previous efforts to overcome this limitation were unsuccessful, as the use of organic eluents in LC-IRMS was deemed impossible.
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