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To investigate using patient posts in social media as a resource to profile off-label prescriptions of cancer drugs.

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 [...]

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.

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 [...]

To predict 72-h and 9-day emergency department (ED) return by using gradient boosting on an expansive set of clinical variables from the electronic health record.

Access to safe and nutritious food is essential for good health. However, food can become unsafe due to contamination with pathogens, chemicals or toxins, or mislabeling of allergens. Illness resulting from the consumption of unsafe foods is a global health problem. Here, we develop a machine learning approach for detecting reports of unsafe food products in consumer product reviews from Amazon.com.

This study sought to quantify the association between event notifications and subsequent query-based health information exchange (HIE) use among end users of three different community health information organizations.

Zoonotic disease surveillance presents a substantial problem in the management of public health. Globally, zoonoses have the potential to spread and negatively impact population health economic growth, and security. This research was conducted to investigate the current data sources, analytical methods, and limitations for cluster detection and prediction with particular interest in emerging bioinformatics tools and resources to inform the development of zoonotic surveillance spatial decision support systems. We recruited [...]