Abstract
Genome-guided precision medicine applies consensus recommendations to the care of patients with particular genetic variants. As electronic health records begin to include patients' genomic data, recommendations will be formulated at an increasing rate. This study examined recommendations related to the current list of 73 actionable genes compiled by the American College of Medical Genetics and Genomics and found that conditions fall generally into five classes (cardiovascular, medication interactions, metabolic, neoplastic, and structural), with recommendations falling into seven categories (actions or circumstances to avoid, evaluation of relatives at risk, pregnancy management, prevention of primary manifestations, prevention of secondary complications, surveillance, and treatment of manifestations). This study represents a first step in facilitating automated, scalable clinical decision support and provides direction on formal representation of the contexts and actions for clinical recommendations derived from genome-informed learning health systems.
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