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 Due to fear of stigma, patients want more control over the sharing of sensitive medical records. The Substance Abuse and Mental Health Administration (SAMHSA) and the Office of the National Coordinator (ONC) supported the development of standards-compliant, consent-respecting medical record exchange technology using metadata labeling (e.g., substance use information). Existing technologies must be updated with newer standards and support more than binary-sensitive categorizations to better align with how physicians categorize [...]

 Interoperability between electronic health records (EHR) and immunization information systems (IIS) may positively influence data quality, affecting timeliness, completeness, and accuracy of these data. However, the extent to which EHR/IIS interoperability may influence the day-to-day vaccination workflow and related recordkeeping tasks performed at medical practices is unclear.

 Commercially available large language models such as Chat Generative Pre-Trained Transformer (ChatGPT) cannot be applied to real patient data for data protection reasons. At the same time, de-identification of clinical unstructured data is a tedious and time-consuming task when done manually. Since transformer models can efficiently process and analyze large amounts of text data, our study aims to explore the impact of a large training dataset on the performance of [...]

There is rapidly growing interest in learning health systems (LHSs) nationally and globally. While the critical role of informatics is recognized, the informatics community has been relatively slow to formalize LHS as a priority area.

 Data exploration in modern electronic health records (EHRs) is often aided by user-friendly graphical interfaces providing "self-service" tools for end users to extract data for quality improvement, patient safety, and research without prerequisite training in database querying. Other resources within the same institution, such as Honest Brokers, may extract data sourced from the same EHR but obtain different results leading to questions of data completeness and correctness.

 This study aimed to bridge the educational gap in clinical informatics (CI) at the residency level and stimulate interest in CI as a rewarding career path.

We aim to use large language models (LLMs) to detect mentions of nuanced psychotherapeutic outcomes and impacts than previously considered in transcripts of interviews with adolescent depression. Our clinical authors previously created a novel coding framework containing fine-grained therapy outcomes beyond the binary classification (eg, depression vs control) based on qualitative analysis embedded within a clinical study of depression. Moreover, we seek to demonstrate that embeddings from LLMs are informative [...]

To illustrate the utility of the All of Us Research Program for studying military and veteran health.

This case study describes how an All of Us engagement project returned value to community by strengthening high school students' capacity to serve as health advocates.