Clinical networks (CNs) can promote innovation and collaboration across providers and stakeholders. However, little is known about the structure and operations of CNs, particularly in emergency care. As Canada advances learning health systems (LHSs), foundational research is essential to enable future comparisons across CNs to identify those that contribute to positive system change. Drawing from the results of our international survey, we provide a description of 32 emergency care CNs worldwide, including their structure, operations and sustainability. Future research should consider the context of such networks, how they may contribute to an LHS and how they impact patient outcomes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751757 | PMC |
http://dx.doi.org/10.12927/hcpol.2023.27235 | DOI Listing |
J Neurosurg Case Lessons
January 2025
Neurosurgery Department, Palmetto General Hospital, Hialeah, Florida.
Background: Astroblastoma is an extremely rare tumor of the central nervous system, and its origin and validity as a different entity are still being debated. Because of its rarity and similarities to other glial neoplasms, it is often misdiagnosed, impacting treatment and outcomes.
Observations: Astroblastoma is very rare and mainly affects children and young adults.
Europace
December 2024
Research Group Cardiovascular Diseases, University of Antwerp, Prinsstraat 13, Antwerp 2000, Belgium.
Aims: Trials on integrated care for atrial fibrillation (AF) showed mixed results in different AF populations using various approaches. The multicentre, randomized AF-EduCare trial evaluated the effect of targeted patient education on unplanned cardiovascular outcomes.
Methods And Results: Patients willing to participate were randomly assigned to in-person education, online education, or standard care (SC) and followed for minimum 18 months.
Oncologist
January 2025
Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Background: Peritoneal metastasis (PM) after the rupture of hepatocellular carcinoma (HCC) is a critical issue that negatively affects patient prognosis. Machine learning models have shown great potential in predicting clinical outcomes; however, the optimal model for this specific problem remains unclear.
Methods: Clinical data were collected and analyzed from 522 patients with ruptured HCC who underwent surgery at 7 different medical centers.
CJEM
January 2025
Centre for Urgent and Emergency Care Research (CURE) Group, Sheffield Centre for Health and Related Research (SCHARR), University of Sheffield, Sheffield, United Kingdom.
Ir J Med Sci
January 2025
Department of Emergency Medicine, University of Health Sciences, Taksim Training and Research Hospital, Istanbul, Türkiye.
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