Using a combinatorial algorithm comprised of quantitative EEG features and at least one pharmacogenomic variable, a significantly higher predictive accuracy and usability is achieved as compared to other current methods of clinical decision support for guided pharmacotherapy. The method produces a report with actionable findings for the treating physician, recommending for and/or against multiple drug classes and agents from among the available treatments for mental health disorders. While predictive accuracy for pharmacogenomic testing averages 73%, the presently disclosed combinatorial algorithms achieve a significantly higher rate of accuracy at 91 %.
