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To identify demographic, social, and clinical factors associated with HIV self-management and evaluate whether the CHAMPS intervention is associated with changes in an individual's HIV self-management.

Timely access to data is needed to improve care for substance-exposed birthing persons and their infants, a significant public health problem in the United States. We examined the current state of birthing person and infant/child (dyad) data-sharing capabilities supported by health information exchange (HIE) standards and HIE network capabilities for data exchange to inform point-of-care needs assessment for the substance-exposed dyad.

To develop an advanced multi-task large language model (LLM) framework for extracting diverse types of information about dietary supplements (DSs) from clinical records.

Propose a framework to empirically evaluate and report validity of findings from observational studies using pre-specified objective diagnostics, increasing trust in real-world evidence (RWE).

Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare applications such as synthesizing BHCs from clinical notes have not been shown. We introduce a novel preprocessed dataset, the MIMIC-IV-BHC, encapsulating clinical note and BHC pairs to adapt LLMs for BHC synthesis. Furthermore, we introduce a benchmark of the summarization [...]

We sought to assess whether race, ethnicity, and preferred language were associated with digital health literacy in pediatric caregivers.

This article describes the implementation of preemptive clinical pharmacogenomics (PGx) testing linked to an automated clinical decision support (CDS) system delivering actionable PGx information to clinicians at the point of care at UCSF Health, a large Academic Medical Center.

 Healthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care. Ambient artificial intelligence (AI) offers a novel approach to mitigating burnout by reducing the documentation burden through advanced speech recognition and natural language processing technologies that summarize the patient encounter into a clinical note to be [...]

The use of electronic health records (EHRs) in research demands robust and interoperable systems. By linking biorepositories to EHR algorithms, researchers can efficiently identify cases and controls for large observational studies (e.g., genome-wide association studies). This is critical for ensuring efficient and cost-effective research. However, the lack of standardized metadata and algorithms across different EHRs complicates their sharing and application. Our study presents an example of a successful implementation and [...]