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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.

We aimed to investigate bias in applying machine learning to predict real-world individual treatment effects.

This study tested validity, accuracy, and efficiency of the Orthopaedic Minimal Data Set Episode of Care (OME) compared with traditional operative report in arthroscopic surgery for shoulder instability. As of November 2017, OME had successfully captured baseline data on 97% of 18 700 eligible cases.

The study sought to identify barriers to and facilitators of point-of-care information seeking and use of knowledge resources.

We assess working relationships and collaborations within and between diabetes health care provider teams using social network analysis and a multi-scale community detection.

To assess measurement practice in clinical decision support evaluation studies.

Author-centric analyses of fast-growing biomedical reference databases are challenging due to author ambiguity. This problem has been mainly addressed through author disambiguation using supervised machine-learning algorithms. Such algorithms, however, require adequately designed gold standards that reflect the reference database properly. In this study we used MEDLINE to build the first unbiased gold standard in a reference database and improve over the existing state of the art in author disambiguation.