Low-income U.S. patients with co-occurring behavioral and physical health conditions often struggle to obtain high-quality health care. The health and sociocultural resources of such "complex" patients are misaligned with expectations in most medical settings, which ask patients to mobilize forms of these assets common among healthier and wealthier populations. Thus, complex patients encounter barriers to engagement with their health behaviors and health care providers, resulting in poor outcomes. But this outcome is not inevitable. This study uses in-depth interviews with two interprofessional primary care teams and surveys of all six teams in a complex patient program to examine strategies for improving patient engagement. Five primary care team strategies are identified. While team member burnout was a common byproduct, professional support offered by the team structure reduced this effect. Team perspectives offer insight into mechanisms of improvement and the professional burdens and benefits of efforts to counter health care marginalization among complex patients.
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http://dx.doi.org/10.1177/1049732320909100 | DOI Listing |
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Department of Orthopedics, First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Background: Teaching severe pelvic trauma poses a significant challenge in orthopedic surgery education due to the necessity of both clinical reasoning and procedural operational skills for mastery. Traditional methods of instruction, including theoretical teaching and mannequin practice, face limitations due to the complexity, the unpredictability of treatment scenarios, the scarcity of typical cases, and the abstract nature of traditional teaching, all of which impede students' knowledge acquisition.
Objective: This study aims to introduce a novel experimental teaching methodology for severe pelvic trauma, integrating virtual reality (VR) technology as a potent adjunct to existing teaching practices.
J Neurosurg Pediatr
January 2025
2Norton Children's Hospital and Norton Children's Neuroscience Institute, Norton Healthcare, Louisville; and.
Objective: CSF leaks are a significant source of patient morbidity following intradural spine surgeries. Watertight dural closure is crucial during these procedures to minimize the risk of a CSF leak. This study reports postoperative outcomes and changes in patient management after switching to penetrating titanium clips for dural closure in a large cohort of pediatric patients receiving a tethered cord release (TCR) or a selective dorsal rhizotomy (SDR).
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore, Singapore.
Background: Metastatic spine tumor surgery (MSTS) is often complex and extensive leading to significant blood loss. Allogeneic blood transfusion (ABT) is the mainstay of blood replenishment but with immune-mediated postoperative complications. Alternative blood management techniques (salvaged blood transfusion [SBT]) allow us to overcome such complications.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!