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To analyze oncology nurses' accounts of technology-related safety events and the sociotechnical factors contributing to patient-, workforce-, and system-level harms.

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.

Reuse of shared datasets is often limited by incomplete or inconsistent documentation, hindering interpretation and secondary analysis. We developed DataAtlas, an open-source system for automated generation of data dictionaries from tabular datasets.

To analyze social needs documentation across structured electronic sources in Johns Hopkins Health System, describing practices, patient characteristics, and utility for care, research, and population health.

To describe the Research Electronic Data Capture (REDCap) Consortium's initial implementation of generative artificial intelligence (AI) within the REDCap platform using a minimum viable product (MVP) strategy.