Advanced access scheduling is a system designed to allow patients to be seen same day or next day or in the future according to their preference. The scheduling system has been associated with patients being seen earlier in the course of illness and patients being hospitalized less often. The advanced access system focuses on timely access to primary healthcare, ideally within 48 hours. A group of Ontario primary healthcare nurse practitioners recently implemented the system at a newly established nurse practitioner-led clinic. The team's experiences with the implementation of the advanced access scheduling system are reviewed. The team's experiences are then compared and contrasted with what has been published on the scheduling system to date. The article approaches the subject matter from the perspectives of primary healthcare providers, clerical staff and administrators. Advanced access has become a timely subject in primary care, given the chronic shortages of service and funding constraints and the need for enhanced effectiveness.
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http://dx.doi.org/10.12927/hcq.2015.24241 | DOI Listing |
Diabetol Metab Syndr
January 2025
First Central Clinical Medical Institute, Tianjin Medical University, Tianjin, China.
Background: To identify the relationship between BMI or lipid metabolism and diabetic neuropathy using a Mendelian randomization (MR) study.
Methods: Body constitution-related phenotypes, namely BMI (kg/m), total cholesterol (TC), and triglyceride (TG), were investigated in this study. Despite the disparate origins of these data, all were accessible through the IEU OPEN GWAS database ( https://gwas.
J Transl Med
January 2025
Allen Institute for Immunology, Seattle, WA, USA.
Background: The field of single cell technologies has rapidly advanced our comprehension of the human immune system, offering unprecedented insights into cellular heterogeneity and immune function. While cryopreserved peripheral blood mononuclear cell (PBMC) samples enable deep characterization of immune cells, challenges in clinical isolation and preservation limit their application in underserved communities with limited access to research facilities. We present CryoSCAPE (Cryopreservation for Scalable Cellular And Proteomic Exploration), a scalable method for immune studies of human PBMC with multi-omic single cell assays using direct cryopreservation of whole blood.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Islamic Republic of Iran.
Introduction: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced them.
View Article and Find Full Text PDFNat Ecol Evol
January 2025
Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK.
Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption.
View Article and Find Full Text PDFPurpose Of Review: This review aims to evaluate the impact of artificial intelligence (AI) on cancer health equity, specifically investigating whether AI is addressing or widening disparities in cancer outcomes.
Recent Findings: Recent studies demonstrate significant advancements in AI, such as deep learning for cancer diagnosis and predictive analytics for personalized treatment, showing potential for improved precision in care. However, concerns persist about the performance of AI tools across diverse populations due to biased training data.
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