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To develop and evaluate a knowledge graph-augmented large language model (LLM) framework that synthesizes epidemiological evidence to infer life-course exposure-outcome pathways, using gestational diabetes mellitus (GDM) and dementia as a case study.

Documentation of gender identity (GI) and anatomy data in the electronic health record (EHR) is a proposed standard of care for transgender populations. However, there is limited research on implementation of proposed best practices, particularly anatomy data collection. This study aims to characterize factors that influence patient preferences and comfort around the collection and documentation of GI and anatomy in EHRs.

Real-world evidence (RWE) increasingly informs clinical decisions, yet manual adjustment for confounding limits scalability. Data-adaptive (DA) algorithms for high-dimensional proxy adjustment show promise but have not been systematically compared to investigator-specified (IS) approaches across diverse treatment scenarios. We evaluated whether DA strategies perform comparably to manually curated IS models using claims-based emulations of 15 randomized trials from the RCT-DUPLICATE initiative.

Atrial fibrillation (AF) is common among intensive care unit (ICU) patients. Effective management of AF in this setting remains a subject of debate, with current guidelines often derived from outpatient studies. This study aims to evaluate the effectiveness of different AF management strategies-both, rhythm, rate, or no control-in reducing mortality in ICU patients using a deep learning-based causal inference model.

We propose Heterogeneity-aware Collaborative One-shot Lossless Algorithm for Generalized Linear Model (COLA-GLM-H), a novel one-shot lossless distributed algorithm that enables the integration of heterogeneous multi-institutional data while relying solely on instituion-level summary information rather than patient-level data.

Ensuring data quality and maintaining remote accessibility remain key challenges in clinical trials conducted in low-resource settings. Although several software platforms and digital tools attempt to address these challenges, no single, comprehensive solution adequately meets the complex demands of decentralized and intermittently connected trial environments. Consequently, context-specific tools must be developed and adapted to ensure reliable performance under such constraints.

The current study examined the relationship between nursing informatics competency (NIC) and perceived clinical decision-making (CDM) skills among nurses in Saudi Arabia.

The amount of time ambulatory physicians spend in an electronic health record (EHR) outside scheduled hours has grown in recent years and been linked to burnout. Measures provided by EHR vendors can help health systems track EHR use outside scheduled hours, but different measures track different periods of EHR use and none currently tracks all EHR use outside patient scheduled hours. How much vendor-derived measures differ from one another or [...]