Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Transforming the future of health together: The Learning Health Systems Consensus Action Plan

The Learning Health Community is an emergent global multistakeholder grassroots incipient movement bonded together by a set of consensus Core Values Underlying a National‐Scale Person‐Centered Continuous Learning Health System developed at the 2012 Learning Health System (LHS) Summit. The Learning Health Community’s Second LHS Summit was convened on December 8 to 9, 2016 building upon LHS efforts taking shape in order to achieve consensus on actions that, if taken, will advance LHSs and the LHS vision from what remain appealing concepts to a working reality for improving the health of individuals and populations globally. An iterative half‐year collaborative revision process following the Second LHS Summit led to the development of the Learning Health Systems Consensus Action Plan.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145212/1/lrh210055_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145212/2/lrh210055.pd