Case Study: Symphony Post Acute Network achieves faster, more accurate predictive care and cost savings with DataRobot

Symphony Post Acute Network - Customer Case Study

Symphony Post Acute Network, represented by data scientist Nathan Patrick Taylor, struggled with slow, manual predictive modeling that limited how many healthcare problems they could address. Building and updating models took weeks, required repeated trial-and-error, lagged behind new open-source algorithms, risked coding errors in production, and left many internal requests unserved—so Nathan turned to DataRobot and its machine learning automation platform.

DataRobot’s platform (integrating easily with Alteryx and Symphony’s historical data sources) automated model building and deployment, enabling Nathan to produce models in hours or days instead of weeks, deploy them via an enterprise-ready API, and deliver more accurate, explainable predictions. With DataRobot, Symphony can head off patient complications, realize cost savings and new revenue opportunities, and scale a far more ambitious predictive analytics agenda.

Symphony Post Acute Network

Nathan Patrick

Taylor Clinical Informatics Consultant