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Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP).

Video telehealth technology has the potential to enhance access for patients with clinical, social, and geographic barriers to care. We evaluated the implementation of a US Department of Veterans Affairs (VA) initiative to distribute tablets to high-need Veterans with access barriers.

This case study describes the implementation of the Research Electronic Data Capture (REDCap) software at the United States Department of Veterans Affairs Veterans Health Administration (VA). VA REDCap enables secure and standardized data collection, fosters collaboration with external researchers through use of a widely used data management tool, facilitates multisite studies through use of data forms that can be shared across sites within and outside the VA, is well suited [...]

The risk of medical errors increases upon transfer out of the intensive care unit (ICU). Discrepancies in the documented care plan between notes at the time of transfer may contribute to communication errors. We sought to determine the frequency of clinically meaningful discrepancies in the documented care plan for patients transferred from the pediatric ICU to the medical wards and identified risk factors.

The purpose of this article is to describe the current nursing problem list subset of Systematized Nomenclature of Medicine Clinical Terms (NPLS) coverage of the American Nurses Association (ANA) recognized standardized nursing terminologies (SNTs) and to identify potential ways to expand and enhance the utility of this list.

Identifying new relations between medical entities, such as drugs, diseases, and side effects, is typically a resource-intensive task, involving experimentation and clinical trials. The increased availability of related data and curated knowledge enables a computational approach to this task, notably by training models to predict likely relations. Such models rely on meaningful representations of the medical entities being studied. We propose a generic features vector representation that leverages co-occurrences of [...]

Structured diagnosis (DX) are crucial for secondary use of electronic health record (EHR) data. However, they are often suboptimally recorded. Our previous work showed initial evidence of variable DX recording patterns in oncology charts even after biopsy records are available.