The TRIPOD-LLM reporting guideline for studies using large language models.

Large language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion.

Impact of a Clinical Decision Support System on Computed Tomographic Pulmonary Angiogram Yield and Utilization in Hospitalized Patients.

Objective: To determine whether point-of-order clinical decision support (CDS) based on the Wells Criteria improves CT pulmonary angiogram (CTPA) yield and utilization in hospitalized patients in an enterprise-wide health system and identify yield-related factors.

Methods: This retrospective IRB-approved cross-sectional study in an urban, multi-institution health system included hospitalized patients undergoing CTPA 12 months before and after CDS implementation (entire cohort). Chi-square test was used to compare PE yield in patients in whom providers overrode vs.

Establishing responsible use of AI guidelines: a comprehensive case study for healthcare institutions.

This report presents a comprehensive case study for the responsible integration of artificial intelligence (AI) into healthcare settings. Recognizing the rapid advancement of AI technologies and their potential to transform healthcare delivery, we propose a set of guidelines emphasizing fairness, robustness, privacy, safety, transparency, explainability, accountability, and benefit. Through a multidisciplinary collaboration, we developed and operationalized these guidelines within a healthcare system, highlighting a case study on ambient documentation to demonstrate the practical application and challenges of implementing generative AI in clinical environments.