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Rheumatoid and Psoriatic Arthritis (RA and PsA) are autoimmune diseases that cause debilitating joint pain. Disease-modifying antirheumatic drugs (DMARDs) are recommended for the treatment of both conditions. However, real-world evidence studies would help characterize compliance with these recommendations. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) standardizes electronic health record (EHR) data, allowing for research that incorporates multiple data sources. We are interested in determining whether OMOP CDM [...]

We report on using electronic health records (EHRs) and other health information technology (IT) (eg, REDCap, Excel, and population-health tools) for tracking patients and managing interventions to improve colorectal screening (CRC) among primary care practices who participated in the National Cancer Institute's Accelerating Colorectal Cancer Screening and Follow-up through Implementation Science (ACCSIS) program.

Enabling the unambiguous communication of cancer genetic testing results and the corresponding therapeutic implications of identified genetic variants is of major clinical importance. In this report, we assess the adequacy of the Health Level Seven Fast Healthcare Interoperability Resources (FHIR) Genomics Reporting Implementation Guide, version 3 (also known as "FHIR Genomics") for the structured communication of semantic objects typically appearing in real-world somatic testing reports.

To describe the development and early implementation of the Digital Health Equity & Literacy Program (D-HELP), a student-led quality improvement initiative to promote digital health engagement in the emergency department (ED).

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.

To assess the performance, generalizability, and computational efficiency of instruction-tuned Large Language Model Meta AI (LLaMA)-2 and LLaMA-3 models compared to bidirectional encoder representations from transformers (BERT) for clinical information extraction (IE) tasks, specifically named entity recognition (NER) and relation extraction (RE).

Accurate phenotyping is an essential task for researchers utilizing electronic health record (EHR)-linked biobank programs like the All of Us Research Program to study human genetics. However, little guidance is available on how to select an EHR-based phenotyping procedure that maximizes downstream statistical power. This study aims to estimate accuracy of three phenotype definitions of ovarian, female breast, and colorectal cancers in All of Us (v7 release) and determine which [...]