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Implementing Algorithm-Guided Warfarin Dosing in an Ethnically Diverse Patient Population Using Electronic Health
A Owusu Obeng1,2, T Kaszemacher3, N S Abul-Husn3
1The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA. aniwaa.owusu-obeng@mssm.edu.
Abstract:
Implementation of pharmacogenetic-guided warfarin dosing has been hindered by inconsistent results from reported clinical trials and a lack of available algorithms that include alleles prevalent in non-white populations. However, current evidence indicates that algorithm-guided dosing is more accurate than empirical dosing. To facilitate multiethnic algorithm-guided warfarin dosing using preemptive genetic testing, we developed a strategy that accounts for the complexity of race and leverages electronic health records for algorithm variables and deploying point-of-care dose recommendations.
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