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Federal healthcare legislation has played a central role in shaping the digital transformation of U.S. healthcare. Key legislative milestones-including the Health Security Act of 1993, the Health Insurance Portability and Accountability Act (HIPAA), the Health Information Technology for Economic and Clinical Health (HITECH) Act, the Patient Protection and Affordable Care Act (ACA), and the 21st Century Cures Act-collectively accelerated the adoption of electronic health records (EHRs), promoted interoperability, and expanded [...]

People with physical disabilities are one of the largest subgroups of people with disabilities, and this group experiences significant health disparities. Given the risk of preventable multimorbidity among this group, there is an opportunity to improve primary care for this population.The goal of this study was to use a clinical decision support (CDS) tool to improve preventive screenings in primary care for people with physical disabilities.We used a convergent mixed [...]

In recent years, there has been an emerging wave of artificial intelligence (AI) and digital tools in healthcare, thereby revolutionizing clinical practice. As health systems are increasingly utilizing these tools as a means to improve clinical and operational performance outcomes, it becomes imperative to train and professionally develop key frontline stakeholders, such as clinicians, in digital health and clinical AI to ensure seamless and responsible adoption within healthcare settings.This paper [...]

Clinical informatics (CI) fellowship training equips physicians to design, implement, and evaluate health information systems in support of patient care. While core curricula emphasize academic health system experiences, fellows may benefit from exposure to industry settings where much health technology innovation originates.This study aimed to characterize the structure, perceived value, and logistical challenges of industry electives among CI fellowship programs and to synthesize best practices for integrating these experiences into [...]

This study aimed to explore the performance of ChatGPT version 4.0 (GPT-4) and Gemini Advanced (Gemini) large language models (LLMs) in addressing common patient questions after gynecology surgery with regards to accuracy, relevance, helpfulness to the average patient, and readability.In this cross-sectional study, the two LLMs were prompted to generate answers to postoperative patient questions after gynecologic surgery. Postoperative patient questions were developed to simulate common patient questions after gynecologic [...]

This scoping review aimed to (1) map current applications of transformers and large language models (LLMs) for extracting social drivers of health (SDOH) from clinical text, (2) benchmark model performance across SDOH domains, and (3) evaluate methodological rigor to identify research gaps and inform clinical deployment.

Trafficked persons experience adverse health consequences and seek help, but many go unrecognized by health-care professionals. This study explored professionals' perspectives on current approaches toward identifying and supporting trafficked persons in health-care settings, highlighting current technology roles, gaps, and future directions.

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.