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The study sought to develop a criteria-based scoring tool for assessing drug-disease knowledge base content and creation of a subset and to implement the subset across multiple Kaiser Permanente (KP) regions.

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.

Patient portal functionalities, such as patient-physician e-communication, can benefit patients by improving clinical outcomes. Utilization has historically been low but may have increased in recent years due to the implementation of Stage 2 Meaningful Use for electronic health records. This study has 2 objectives: 1) to compare patient portal utilization rates before Stage 2 (2011-2013) and after Stage 2 (2014-2017), and 2) to examine whether disparities in patient portal utilization [...]

Despite increased use of electronic health records (EHRs), the clinical impact of system downtime is unknown.

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

Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article, we assessed the ability of natural language processing (NLP) systems to unlock DDC information from clinical narratives automatically.

To assess measurement practice in clinical decision support evaluation studies.

The study sought to examine whether provider encouragement is associated with improvements in engaging patients with their healthcare processes using online portals.

Pleiotropy, where 1 genetic locus affects multiple phenotypes, can offer significant insights in understanding the complex genotype-phenotype relationship. Although individual genotype-phenotype associations have been thoroughly explored, seemingly unrelated phenotypes can be connected genetically through common pleiotropic loci or genes. However, current analyses of pleiotropy have been challenged by both methodologic limitations and a lack of available suitable data sources.