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Knowledgebases are needed to clarify correlations observed in real-world electronic health record (EHR) data. We posit design principles, present a unifying framework, and report a test of concept.

As the real-world electronic health record (EHR) data continue to grow exponentially, novel methodologies involving artificial intelligence (AI) are becoming increasingly applied to enable efficient data-driven learning and, ultimately, to advance healthcare. Our objective is to provide readers with an understanding of evolving computational methods and help in deciding on methods to pursue.

To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, identify implementation barriers, enablers, and key decisions and then map these to a novel end-to-end clinical AI implementation framework.

The 21st Century Cures Act (Cures Act) information blocking regulations mandate timely patient access to their electronic health information. In most healthcare systems, this technically requires immediate electronic release of test results and clinical notes directly to patients. Patients could potentially be distressed by receiving upsetting results through an electronic portal rather than from a clinician. We present a case from 2018, several years prior to the implementation of the [...]

We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds.

To examine the real-world safety problems involving machine learning (ML)-enabled medical devices.

To design and validate a novel deep generative model for seismocardiogram (SCG) dataset augmentation. SCG is a noninvasively acquired cardiomechanical signal used in a wide range of cardivascular monitoring tasks; however, these approaches are limited due to the scarcity of SCG data.

The objective was to develop a dataset definition, information model, and FHIR® specification for key data elements contained in a German molecular genomics (MolGen) report to facilitate genomic and phenotype integration in electronic health records.

The 21st Century Cures Act Final Rule's information blocking provisions, which prohibited practices likely to interfere with, prevent, or materially discourage access, exchange, or use of electronic health information (EHI), began to apply to a limited set of data elements in April 2021 and expanded to all EHI in October 2022. We sought to describe hospital leaders' perceptions of the prevalence of practices that may constitute information blocking, by actor [...]