RxINSIGHTS Machine-Learning generated ‘hidden patterns of associations and deep learning insights’ detect causal behavioral and other associative factors that are not easily detected and/or immediately obvious to human analysts.
Our machine learning, pattern recognition and deep learning modules effectively identify the most likely reason why a patient is “at-risk” of becoming non-adherent along with other associative factors that help design custom interventions to prevent non-adherence before it starts.
These insights (see sample insights below) are presented in a highly visual (tabular and graphic) form to facilitate the composition of proactive, customized, interventions by patient by prescribed therapy and drug class.
RxINSIGHTS considers various factors include a combination of patient and therapy characteristics (cross-sectional data) along with past patient medication adherence behavior (longitudinal data) to provide unforeseen insights for future intervention for each patient for each class of drug prescribed.
RxINSIGHTS Deep Learning Modules are customizable to provide higher levels of confidence for Targeting Patient Segments, Disease Type and Drug Class for proactive intervention.
For more information on our RxINSIGHTS Pattern Detection & Deep Learning Modules:
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