98%
921
2 minutes
20
: To describe the process, benefits, and challenges of linking Arizona's prehospital registry to hospital discharge data. Data were queried from the Arizona Prehospital Information and Emergency Medical Services Registry System (AZ-PIERS) and the Arizona Hospital Discharge Database (HDD) for the calendar year 2015. To maximize the number of matched records, the databases were deterministically linked in 17 steps using different combinations/variations of patient personal identifiers. Random samples of at least 1% of matched pairs from each of 16 linkage steps (excluding Step 1) were manually reviewed to assess the rate of false positive matches. A total of 626,413 records were reported to AZ-PIERS in 2015. Of those, 503,715 qualified for linkage. These records were matched against 3,125,689 discharge records reported to the HDD in 2015. The first step, which involved exact matching on first name, last name, date of birth, gender, and date of incident/date of admission, yielded a linkage of 64.6% ( = 325,156). The 16 successive steps yielded a further linkage of 26.6% ( = 134,006) for a total linkage of 91.2% ( = 459,162). The manual review indicated an overall false positive match rate for the 16 reviewed steps of 6.96% ( = 99). The 2 steps with the highest false positive match rates were Step 16 (43.02%, = 77) and Step 17 (31.43%, = 11). It is feasible to link prehospital and hospital data using stepwise deterministic linkage; this method returns a high linkage rate with a low false positive error rate. Data linkage is vital to identifying and bridging gaps in the continuum of care and is a useful tool in statewide and agency-specific research and quality improvement.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/10903127.2019.1604925 | DOI Listing |
Brain Behav
September 2025
School of Pharmacy and Medical Technology, Putian University, Putian, China.
Background: Recent research has started to uncover an important connection between immune system activity and cognitive abilities. Although correlative associations have been documented, the causal mechanisms connecting specific immune cell subpopulations to cognitive capabilities remain insufficiently characterized. Our research aimed to determine directional relationships between distinct immune cell subtypes and cognitive function, potentially identifying targets for immunomodulatory interventions.
View Article and Find Full Text PDFOral Radiol
September 2025
Department of Oral and Maxillofacial Radiology, Eskisehir Osmangazi University, Meşelik Campus, Büyükdere Neighborhood, Prof. Dr. Nabi Avcı Boulevard No:4, Odunpazarı, Eskişehir, 26040, Turkey.
Objectives: The primary objective of this study is to evaluate the effectiveness of artificial intelligence-assisted segmentation methods in detecting carotid artery calcification (CAC) in panoramic radiographs and to compare the performance of different YOLO models: YOLOv5x-seg, YOLOv8x-seg, and YOLOv11x-seg. Additionally, the study aims to investigate the association between patient gender and the presence of CAC, as part of a broader epidemiological analysis.
Methods: In this study, 30,883 panoramic radiographs were scanned.
Vox Sang
September 2025
Blood Group Genetics Laboratory, Irish Blood Transfusion Service, Dublin, Ireland.
Background And Objectives: The discovery of circulating fetal DNA in maternal plasma enabled non-invasive prenatal testing (NIPT) for targeted anti-D prophylaxis. In 2019, Ireland implemented an in-house test to guide this care. Here, we report 6 years of service.
View Article and Find Full Text PDFSci Justice
September 2025
Department of Multidisciplinary Radiological Science, The Graduate School of Dongseo University, 47 Jurye-ro, Sasang-gu, Busan 47011, Republic of Korea. Electronic address:
The identification of deceased individuals is essential in forensic investigations, particularly when primary identification methods such as odontology, fingerprint, or DNA analysis are unavailable. In such cases, implanted medical devices may serve as supplementary identifiers for positive identification. This study proposes deep learning-based methods for the automatic detection of metallic implants in scout images acquired from computed tomography (CT).
View Article and Find Full Text PDFBMJ Open
September 2025
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada
Objective: This study validates the previously tested Screening for Poverty And Related social determinants to improve Knowledge of and access to resources ('SPARK Tool') against comparison questions from well-established national surveys (Post Survey Questionnaire (PSQ)) to inform the development of a standardised tool to collect patients' demographic and social needs data in healthcare.
Design: Cross-sectional study.
Setting: Pan-Canadian study of participants from four Canadian provinces (SK, MB, ON and NL).