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Development of Attention-based Prediction Models for All-cause Mortality, Home Care Need, and Nursing Home Admission in Ageing Adults in Spain Using Longitudinal Electronic Health Record Data.
J Med Syst
January 2025
Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), C/ Mare de Déu de Guadalupe, 2, Mataró, 08303, Barcelona, Spain.
Predicting health-related outcomes can help with proactive healthcare planning and resource management. This is especially important on the older population, an age group growing in the coming decades. Considering longitudinal rather than cross-sectional information from primary care electronic health records (EHRs) can contribute to more informed predictions.
View Article and Find Full Text PDFLower electronic health record adoption and interoperability in rural versus urban physician participants: a cross-sectional analysis from the CMS quality payment program.
BMC Health Serv Res
January 2025
Department of Internal Medicine, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA.
Background: The Health Information Technology for Economic and Clinical Health Act of 2009 introduced the Meaningful Use program to incentivize the adoption of electronic health records (EHRs) in the U.S. This study investigates the disparities in EHR adoption and interoperability between rural and urban physicians in the context of federal programs like the Medicare Access and CHIP Reauthorization Act of 2015 and the 21st Century Cures Act.
View Article and Find Full Text PDFIncidence and risk factors for insulinoma diagnosed in dogs under primary veterinary care in the UK.
Sci Rep
January 2025
Department of Clinical Science and Services, Royal Veterinary College, Hatfield, AL9 7TA, UK.
Insulinoma is the most common pancreatic tumor diagnosed in dogs. This study aimed to report incidence risk, breed predispositions and other demographic risk factors for insulinoma diagnosed in dogs under primary veterinary care in the UK. The VetCompass Program supports research on anonymized electronic health records (EHRs) from dogs under UK veterinary care.
View Article and Find Full Text PDFBuilding a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study.
J Med Internet Res
January 2025
Vibrent Health, Inc, Fairfax, VA, United States.
Background: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used.
Objective: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU).
Development and validation of a risk prediction model for acute kidney injury in coronary artery disease.
BMC Cardiovasc Disord
January 2025
Center for Coronary Artery Disease, Division of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, China.
Background: Acute Kidney Injury (AKI) is a sudden and often reversible condition characterized by rapid kidney function reduction, posing significant risks to coronary artery disease (CAD) patients. This study focuses on developing accurate predictive models to improve the early detection and prognosis of AKI in CAD patients.
Methods: We used Electronic Health Records (EHRs) from a nationwide CAD registry including 54 429 patients.
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