Background: The novel coronavirus disease 2019 (COVID-19) pandemic has presented the healthcare system with a plethora of challenges, including implementation of an efficient vaccination strategy. Mass vaccinations have been used during previous pandemics; however, the associated data have largely been limited to theoretical simulations and post hoc analysis.
Methods: An innovative data collection tool was created to deliver real-time data analysis during a drive-through mass vaccination. Patients were assigned unique identification numbers at the clinic entrance. Using these identification numbers, and the web-based spreadsheet, patients were tracked throughout the vaccination process. Static timestamps corresponding to the entry and exit at each checkpoint were recorded in real time.
Results: Data were collected on a total of 3,744 vehicles over five clinic days. Total time was collected, from entry to exit, on 2,860 vehicles. Registration and vaccination times were collected on 3,111 vehicles. Of the vehicles sampled, 1,588 (42%) had data points associated with all checkpoints.
Conclusions: This open-source, innovative data collection tool was successfully implemented in our mass vaccination clinic for tracking patients in real time providing actionable data on overall throughput efficiency. This cost-effective tool can be used on a variety of healthcare-related projects to provide data-driven evaluation on the efficiency of care.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245533 | PMC |
http://dx.doi.org/10.1097/JHQ.0000000000000343 | DOI Listing |
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Brain Imaging Behav
January 2025
Macquarie Medical School, Macquarie University, Sydney, NSW, Australia.
Magnetic resonance imaging (MRI) is frequently used to monitor disease progression in multiple sclerosis (MS). This study aims to systematically evaluate the correlation between MRI measures and histopathological changes, including demyelination, axonal loss, and gliosis, in the central nervous system of MS patients. We systematically reviewed post-mortem histological studies evaluating myelin density, axonal loss, and gliosis using quantitative imaging in MS.
View Article and Find Full Text PDFCardiovasc Eng Technol
January 2025
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, MA, Cambridge, USA.
Purpose: Atrial fibrillation (AF) is the most common chronic cardiac arrhythmia that increases the risk of stroke, primarily due to thrombus formation in the left atrial appendage (LAA). Left atrial appendage occlusion (LAAO) devices offer an alternative to oral anticoagulation for stroke prevention. However, the complex and variable anatomy of the LAA presents significant challenges to device design and deployment.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Artificial Intelligence and Data Science, College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia.
In the present digital scenario, the explosion of Internet of Things (IoT) devices makes massive volumes of high-dimensional data, presenting significant data and privacy security challenges. As IoT networks enlarge, certifying sensitive data privacy while still employing data analytics authority is vital. In the period of big data, statistical learning has seen fast progressions in methodological practical and innovation applications.
View Article and Find Full Text PDFInflamm Res
January 2025
Department of Orthopedics and Traumatology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, Sichuan Province, China.
Background: One of the etiologic components of degenerative spinal illnesses is intervertebral disc degeneration (IVDD), and the accompanying lower back pain is progressively turning into a significant public health problem. Important pathologic characteristics of IVDD include inflammation and acidic microenvironment, albeit it is unclear how these factors contribute to the disease.
Purpose: To clarify the functions of inflammation and the acidic environment in IVDD, identify the critical connections facilitating glycolytic crosstalk and nucleus pulposus cells (NPCs) pyroptosis, and offer novel approaches to IVDD prevention and therapy.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!