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Digital health equity, the opportunity for all to engage with digital health tools to support good health outcomes, is an emerging priority across the world. The field of digital health equity would benefit from a comprehensive and systematic understanding of digital health, digital equity, and health equity, with a focus on real-world applications. We conducted a scoping review to identify and describe published frameworks and concepts relevant to digital health [...]

Modernizing and strengthening the US public health data and information infrastructure requires a strong public health informatics (PHI) workforce. The study objectives were to characterize existing PHI specialists and assess informatics-related training needs.

Objective Experiences sharing complex workflow-integrated clinical decision support (CDS) across health systems are sparse and not well reported. This case study presents the sharing of a hybrid electronic health record (EHR)-native and SMART-compatible CDS tool for automating provision of smoking cessation treatment for caregivers during pediatric visits. Materials & Methods We conducted a comprehensive needs assessment using socio-technical frameworks to identify workflow gaps and technical requirements. A multidisciplinary team of [...]

To assess the prevalence of recommended design elements in implemented electronic health record (EHR) interruptive alerts across pediatric care settings.

Digital health research involves collecting vast amounts of personal health data, making data management practices complex and challenging to convey during informed consent.

The predictive intensive care unit (ICU) scoring system is crucial for predicting patient outcomes, particularly mortality. Traditional scoring systems rely mainly on structured clinical data from electronic health records, which can overlook important clinical information in narratives and images.

To be usable, useful, and sustainable for families of children with medically complex conditions (CMC), digital interventions must account for the complex sociotechnical context in which these families provide care. CMC experience higher neighborhood socioeconomic disadvantage than other child populations, which has associations with CMC health. Neighborhoods may influence the structure and function of the array of caregivers CMC depend upon (ie, the caregiving network).

To develop and validate a machine learning model that helps physician advisors efficiently identify hospital admission denials likely to be overturned on appeal.

This study evaluates the impact of an ambient artificial intelligence (AI) documentation platform on clinicians' perceptions of documentation workflow.

Demonstrate a methodology for improving discoverability of rare disease datasets by enriching source data with biological associations.