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Implementing target trial emulation (TTE) studies as standardized, reproducible analytic workflows is technically demanding. We developed Text-guided Health-study Estimation and Specification Engine Using Strategus (THESEUS), which uses large language models (LLMs) to translate free-text study descriptions into structured analytic specifications and Strategus R scripts within the Observational Health Data Sciences and Informatics (OHDSI) ecosystem.

Clinicians' adoption of interoperability tools influences care quality, but evidence of actual use is limited. We analyze clinicians' use of outside records delivered via Epic Care Everywhere (CE), focusing on use frequency and predictors such as gender, experience, specialty, and role. Differences between pre-pandemic (2018-2019) and pandemic (2020-2021) periods are also examined to see how COVID-19 affected use of outside records.

Develop a near-comprehensive opioid medications valueset for population measures of opioid related treatments and outcomes. The opioid valueset should be free, open source, and conform to the RxNorm standard federally mandated in every US-certified electronic health record.

This study aims to develop comprehensive computable phenotyping algorithms that integrate multiple domains of electronic health record (EHR) data within the All of Us (AoU) Researcher Workbench to identify sexually transmitted infection (STI) cases and characterize STI patterns.

To design the provider-facing side of an application that collects and displays contextual patient-generated health data (PGHD) as a means of facilitating patient-centered care for older adults with chronic pain in the Veterans Health Administration (VHA).

To investigate the performance of artificial intelligence (AI) scribes and their impact on clinical documentation time.

This address was delivered by Eric Horvitz, MD, PhD, at the 2026 graduation ceremony of Columbia University School of Nursing on May 19, 2026, where he received the Second Century Award for Excellence in Health Care. The address considers the responsibilities of clinicians in shaping the future of artificial intelligence in medicine. It frames health care as an "open world," where information is incomplete, time is limited, and decisions are [...]

Dr. Kevin B. Johnson delivered this address on May 16, 2026, at the Commencement Ceremony of The D. Bradley McWilliams School of Biomedical Informatics, UTHealth Houston, to the graduating class of 2026. The address uses the concept of "The Big Mo" (compounding momentum) as a frame for understanding the current inflection point in AI and medicine. Drawing on his own career arc from paper-based clinical practice at Johns Hopkins through [...]

Clarify disciplinary foundations and internal structure of biomedical informatics.

To develop the first public-facing dashboard that translates genomic sequencing data from wastewater into accessible and actionable community information concerning human pathogenic viruses, representing a shift to sequencing-based public health wastewater monitoring.