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Direct Secure Messaging (DSM) is a communication standard for exchanging information between health care entities and practitioners. It relies on access to an address directory. When directory entry is incomplete, health information exchange breaks down. There is an urgent need for standardized DSM address directory management and synchronization workflows that support universal access in a timely manner.Our objective was to develop best practices for maintenance of DSM address directories and [...]

Our objective was to identify barriers to implementing a custom clinical decision support (CDS) alert to randomize individuals in a pragmatic study, specifically those with a positive antinuclear antibody (ANA) test.We integrated a validated logistic regression model into the electronic health record to predict the risk of developing autoimmune disease for individuals with a positive ANA (titer ≥ 1:80). A custom CDS alert was created to randomize eligible individuals into [...]

Long COVID, characterized by persistent or recurring symptoms post-COVID-19 infection, poses challenges for pediatric care and research due to the lack of a standardized clinical definition. Adult-focused phenotypes do not translate well to children, given developmental and physiological differences, and pediatric-specific phenotypes have not been compared with chart review.This study introduces and evaluates a pediatric-specific rule-based computable phenotype (CP) to identify long COVID using electronic health record data. We compare [...]

The widespread adoption of health information technology (HIT) has deepened hospitals' reliance on electronic health records (EHR). However, EHR downtime events, which refer to partial or complete system failures, can disrupt hospital operations and threaten patient safety. Systematic research on HIT downtime events in China remains limited.This study aims to identify and classify reported EHR downtime events in a Chinese hospital, assess their frequency and severity, and propose improvement recommendations [...]

The digital availability of health data not only improves processes in primary care, but it also facilitates the evaluation of healthcare delivery. Nevertheless, the preprocessing of data for secondary use is still time-consuming and expensive, particularly in head and neck cancer (HNC), where patients undergo complex multidisciplinary treatment trajectories. Therefore, we have looked further into the effects on data quantity and quality following the implementation of structured care pathways. Leveraging [...]

To evaluate predictive diagnostic performance of open- and closed-source large language models (LLMs) in emergency medicine, addressing the urgent need for innovative clinical decision support tools amid rising patient volumes and staffing shortages.

The Bridge2AI program is establishing rules of practice for creating ethically sourced health data repositories to support the effective use of ML/AI in biomedical and behavioral research. Given the initially undefined nature of ethically sourced data, this work concurrently developed definitions and guidelines alongside repository creation, grounded in a practical, operational framework.

To develop and evaluate a patient-centric medication module within a personal health record (PHR) app for capturing medication use, focusing on accuracy, usability, and concordance.

To develop ECG-FM, an open-weight foundation model for electrocardiogram (ECG) analysis, rigorously evaluate its performance on clinically salient tasks, and openly release it alongside a public benchmark.

Severe maternal morbidity and mortality are higher in the United States than in other high-income countries, and unacceptable disparities persist. To facilitate research on these outcomes, we developed a standardized approach for extracting perinatal data from electronic health records (EHRs).