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To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum.

National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard [...]

The Observational Health Data Sciences and Informatics (OHDSI) is the largest distributed data network in the world encompassing more than 331 data sources with 2.1 billion patient records across 34 countries. It enables large-scale observational research through standardizing the data into a common data model (CDM) (Observational Medical Outcomes Partnership [OMOP] CDM) and requires a comprehensive, efficient, and reliable ontology system to support data harmonization.

This study aimed to identify barriers and facilitators to the implementation of family cancer history (FCH) collection tools in clinical practices and community settings by assessing clinicians' perceptions of implementing a chatbot interface to collect FCH information and provide personalized results to patients and providers.

Availability of easy-to-understand patient-reported outcome (PRO) trial data may help individuals make more informed healthcare decisions. Easily interpretable, patient-centric PRO data summaries and visualizations are therefore needed. This three-stage study explored graphical format preferences, understanding, and interpretability of clinical trial PRO data presented to people with prostate cancer (PC).

The increased availability of public data and accessible visualization technologies enhanced the popularity of public health data dashboards and broadened their audience from professionals to the general public. However, many dashboards have not achieved their full potential due to design complexities that are not optimized to users' needs.

This scoping review aims to address a gap in the literature on community engagement in developing data visualizations intended to improve population health. The review objectives are to: (1) synthesize literature on the types of community engagement activities conducted by researchers working with community partners and (2) characterize instances of "creative data literacy" within data visualizations developed in community-researcher partnerships.

Data visualization style guides are standards for formatting and designing representations of information, like charts, graphs, tables, and diagrams. To assist researchers communicate their visual content in better and more effective ways, this article accomplishes two tasks. First, we take a detailed look at a data visualization style guide and its components-what it is and what it should include. Second, we create a detailed template for the color section of [...]

Although interactive data visualizations are increasingly popular for health communication, it remains to be seen what design features improve psychological and behavioral targets. This study experimentally tested how interactivity and descriptive titles may influence perceived susceptibility to the flu, intention to vaccinate, and information recall, particularly among older adults.