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Background: Cancer care is described as insufficiently patient-centered, requiring improved accessibility and coordination. Breast oncology nurse navigators may help provide timely patient care by improving care coordination.
Objectives: This study evaluated a breast cancer navigation (BCN) program in a large ambulatory healthcare system. It examined measures related to quality and value, including timely service delivery, appropriate use of resources, and care coordination.
Methods: Using Lean methods, a BCN program focused on women receiving a breast biopsy was developed at a pilot site and later implemented throughout the healthcare system. Study data evaluated timely disclosure of biopsy results, prompt scheduling of initial consultations, outpatient use of cancer specialists, and coordination between primary care and oncology practices.
Findings: After implementing the BCN program, more timely biopsy results were delivered to patients. Patients were more likely to complete an initial consultation within two weeks of biopsy and made fewer outpatient visits. Referrals to cancer specialists within a month of biopsy increased, and primary care encounters with patients decreased.
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http://dx.doi.org/10.1188/22.CJON.503-509 | DOI Listing |
Neurocase
August 2025
Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Postoperative aphasia is a significant complication following brain tumor resection, affecting both quality of life and prognosis. Currently, speech language therapy (SLT) is the primary approach for treating aphasia, with no alternative rehabilitation options available. However, rTMS has shown promise intreating stroke-related language impairments.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
August 2025
Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Amsterdam 1066 CX, The Netherlands.
While Estrogen receptor alpha (ERα)+ breast cancer treatment is considered effective, resistance to endocrine therapy is common. Since ERα is still the main driver in most therapy-resistant tumors, alternative therapeutic strategies are needed to disrupt ERα transcriptional activity. In this work, we position TRIM24 as a therapeutic target in endocrine resistance, given its role as a key component of the ERα transcriptional complex.
View Article and Find Full Text PDFACS Sens
August 2025
Department of Chemistry, University of Tennessee Knoxville, Knoxville, Tennessee 37996, United States.
Nucleic acid-based sensors (NBEs) are used for biomolecular detection and can enable continuous, real-time molecular monitoring . NBEs are typically constructed via thiol self-assembled monolayers (SAMs) on gold electrodes, consisting of redox-reporter-modified oligonucleotides diluted within an alkylthiol monolayer. However, the limited stability of thiol SAMs when chronically exposed to biological fluids restricts the long-term lifespan of NBEs.
View Article and Find Full Text PDFAm J Clin Nutr
August 2025
BCNatal (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Barcelona, Spain; Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain; Primary care interventions to prevent maternal and child chronic diseases of perinatal and developmental origin RD21/0012/0003, Insti
Background: Despite the importance of gestation period for human health, studies addressing the impact of maternal microbiota on its progression and its modulation by maternal lifestyle are scarce. Although most of the evidence in the field comes from observational studies, we recently described how some lifestyle interventions during pregnancy reduced the small-for-gestational-age (SGA) incidence. We hypothesized the pregnant individual's microbiome modulation as potential mechanism by which lifestyle interventions could impact gestation progression.
View Article and Find Full Text PDFFoods
July 2025
College of Engineering, Nanjing Agricultural University, Nanjing 210000, China.
Deep learning approaches for pork freshness grading typically require large datasets, which limits their practical application due to the high costs associated with data collection. To address this challenge, we propose BBSNet, a lightweight few-shot learning model designed for accurate freshness classification with a limited number of images. BBSNet incorporates a batch channel normalization (BCN) layer to enhance feature distinguishability and employs BiFormer for optimized fine-grained feature extraction.
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