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To determine whether statewide health information exchange (HIE) data can support practice-level prediction of short-term psychiatric emergency presentation, and to compare a locally trained model with general-purpose clinical risk scores.

The Code Map Services/Common Data Model Harmonization Phase III (CDMH-III) project aims to create services allowing researchers to streamline and establish standardized model-to-model/data standards mappings and transformation rules leveraging common data models (CDMs) and common data elements (CDEs) to address the challenge of repeated mapping efforts.

Extract infant breast milk feeding status from electronic health record clinical notes to support observational drug-safety studies.

We sought to evaluate the accuracy and suitability of a transformer-based model (TM) for indexing clinical study designs, in comparison to National Library of Medicine (NLM) indexing.

[This corrects the article DOI: 10.1093/jamiaopen/ooag056.].

BACKGROUND: Scribes help physicians decrease electronic medical record documentation burden. There is transition from virtual to artificial intelligence (AI) scribes. A gap exists in our understanding of parent perspectives on technology-based scribe use at pediatric medical visits.

We describe a new point of care randomization (POCR) engine developed at UCSF and implemented at UCLA that supports randomization of patients, encounters, clinics, or any other "object" in Epic, with programmable ratios, strata, and randomly varying block sizes.

To harmonize pregnancy medication records across heterogeneous real-world data sources and assess the comparability of recorded medication utilization.

To examine clinicians' experiences using ambient documentation technology (ADT) in ambulatory practice, with a focus on impacts on documentation workflows, perceived cognitive burden, and clinical reasoning.

Large language model (LLM) chatbots show promise for pre-visit planning, but their English-centric development raises equity concerns for multilingual deployment. We evaluated the multilingual capabilities of the Primary Care Pre-visit Chatbot (PCP-Bot), a GPT-4o-based pre-visit chatbot, across English, Mandarin Chinese, Spanish, and Hindi.