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Despite growing recognition of the critical role of nutrition in promoting population health, clinicians lack access to point-of-care resources to support culturally relevant nutrition services. This study aims to (1) evaluate Registered Dietitian Nutritionists' (RDN) likelihood of using a web-based tool to provide culturally- and medically tailored nutrition services, (2) identify needed or preferred features, and (3) examine concerns related to the development or implementation of a web-based tool.

The main goal is to develop an automated process for connecting Research Electronic Data Capture (REDCap) instances in a clinical trial network to allow for deidentified transfer of research surveys to cloud computing data commons for discovery.

Determine if an electronic documentation tool can reduce documentation queries for malnutrition without impacting diagnostic coding.

We survey clinical document corpora, with a focus on German textual data. Due to rigid data privacy legislation in Germany, these resources, with only few exceptions, are stored in protected clinical data spaces and locked against clinic-external researchers. This situation stands in stark contrast with established workflows in the field of natural language processing, where easy accessibility and reuse of (textual) data collections are common practice. Hence, alternative corpus designs [...]

The objective of the study was to determine, after medication review, the patient risk score threshold that would distinguish between stays with prescriptions triggering pharmacist intervention (PI) and stays with prescriptions not triggering PI.

This work aims to provide a specialized template for integrating diverse study data types with varying sharing restrictions specific to NIH HEAL Initiative chronic pain and substance use research.

This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status.

Data-sharing policies are rapidly evolving toward increased data sharing. However, participants' perspectives are not well understood and could have an adverse impact on participation in research. We evaluated participants' preferences for sharing specific types of data with specific groups, and strategies to enhance trust in data-sharing practices.

Delirium is a severe condition, often underreported and linked to adverse outcomes such as increased mortality and prolonged hospitalization. Despite its significance, delirium prediction is often hindered by underreporting and inconsistent labeling, highlighting the need for models trained on reliably labeled data (ground truth). This review examines (i) practices for determining labels in delirium prediction models and (ii) how study designs affect label quality, aiming to identify key considerations for [...]

Usage of autotext or "dotphrases" is ubiquitous among provider workflows in electronic health records (EHRs). Yet, little is known about the impact of these tools in inpatient settings and among resident physicians. We aimed to evaluate the association between autotext usage and documentation time among resident physicians in an academic medical center using the Cerner EHR.