OBJECTIVE All electronic health (e-health) interventions require validation as health information technologies, ideally in randomized controlled trial settings. However, as with other types of complex interventions involving various active components and multiple targets, health informatics trials often experience problems of design, methodology, or analysis that can influence the results and acceptance of the research. Our objective was to review selected key methodologic issues in conducting and reporting randomized controlled trials in health informatics, provide examples from a recent study, and present practical recommendations. DESIGN For illustration, we use the COMPETE III study, a large randomized controlled clinical trial investigating the impact of a shared decision-support system on the quality of vascular disease management in Ontario, Canada. RESULTS We describe a set of methodologic, logistic, and statistical issues that should be considered when planning and implementing trials of complex e-health interventions, and provide practical recommendations for health informatics trialists. CONCLUSIONS Our recommendations emphasize validity and pragmatic considerations and would be useful for health informaticians conducting or evaluating e-health studies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2528041 | PMC |
http://dx.doi.org/10.1197/jamia.M2518 | DOI Listing |
JCO Precis Oncol
January 2025
Translational Research Support Office, National Cancer Center Hospital East, Chiba, Japan.
Purpose: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mCRC). Identifying optimal biomarkers for treatment decisions remains challenging. This study explores the potential of artificial intelligence (AI) in predicting treatment responses to trastuzumab plus pertuzumab (TP) in patients with -amplified mCRC from the phase II TRIUMPH trial.
View Article and Find Full Text PDFPLOS Glob Public Health
January 2025
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, Massachusetts, United States of America.
J Am Med Inform Assoc
January 2025
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37203, United States.
Objective: To develop a framework that models the impact of electronic health record (EHR) systems on healthcare professionals' well-being and their relationships with patients, using interdisciplinary insights to guide machine learning in identifying value patterns important to healthcare professionals in EHR systems.
Materials And Methods: A theoretical framework of EHR systems' implementation was developed using interdisciplinary literature from healthcare, information systems, and management science focusing on the systems approach, clinical decision-making, and interface terminologies.
Observations: Healthcare professionals balance personal norms of narrative and data-driven communication in knowledge creation for EHRs by integrating detailed patient stories with structured data.
J Am Med Inform Assoc
January 2025
Department of Biomedical Informatics, Columbia University, New York, NY 10032, United States.
Objective: Extracting PICO elements-Participants, Intervention, Comparison, and Outcomes-from clinical trial literature is essential for clinical evidence retrieval, appraisal, and synthesis. Existing approaches do not distinguish the attributes of PICO entities. This study aims to develop a named entity recognition (NER) model to extract PICO entities with fine granularities.
View Article and Find Full Text PDFJ Neurochem
January 2025
Department of Pathology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Enhancing protein O-GlcNAcylation by pharmacological inhibition of the enzyme O-GlcNAcase (OGA) has been considered as a strategy to decrease tau and amyloid-beta phosphorylation, aggregation, and pathology in Alzheimer's disease (AD). There is still more to be learned about the impact of enhancing global protein O-GlcNAcylation, which is important for understanding the potential of using OGA inhibition to treat neurodegenerative diseases. In this study, we investigated the acute effect of pharmacologically increasing O-GlcNAc levels, using the OGA inhibitor Thiamet G (TG), in normal mouse brains.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!