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We analyzed trends in adoption of advanced patient engagement and clinical data analytics functionalities among critical access hospitals (CAHs) and non-CAHs to assess how historical gaps have changed.

To understand how health-related social needs (HRSN) data are collected at US hospitals and implications for use.

Traditional methods for medical device post-market surveillance often fail to accurately account for operator learning effects, leading to biased assessments of device safety. These methods struggle with non-linearity, complex learning curves, and time-varying covariates, such as physician experience. To address these limitations, we sought to develop a machine learning (ML) framework to detect and adjust for operator learning effects.

 Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to coprescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low.

Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments due to numerous hurdles impeding its translation into practice. The few existing real-world FL initiatives rarely communicate specific measures taken to overcome these hurdles. To bridge this significant knowledge gap, we propose a comprehensive guide for real-world FL in radiology. Minding efforts to implement real-world FL, there is [...]

 Dental informatics (DI) is an emerging discipline. Although the accreditation agency governing dental education programs asserts the importance of informatics as foundational knowledge, no well-defined DI courses currently exist within the standard predoctoral dental curriculum. There is a nationwide lack of DI academic programs. This training gap is due to a lack of qualified dental informaticians to impart knowledge on DI.

Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented in narrative clinical notes rather than as structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labor-intensive process of extraction of such information.

 The Supplemental Nutrition Assistance Program (SNAP) is one of the most successful national programs to reduce poverty and improve health outcomes, but millions of Americans who qualify still do not have access to SNAP, and limited data are available to determine how referrals to the program can be completed successfully.