Case Study: Amgen achieves scalable discovery of referral networks and influential providers with TigerGraph

Amgen Improving the Quality of Healthcare by Identifying Influencers and Referral Networks

Amgen, a global biotechnology leader, faced the challenge of mining terabytes of EMR, claims and provider data to identify patient referrals and influential prescribers—a task that was slow or infeasible in RDBMSs and that their initial graph vendor could not scale. To solve this, Amgen turned to TigerGraph, using its scalable graph database and analytics to surface relationships and inferences across complex healthcare data.

TigerGraph delivered the speed and scale Amgen needed, handling datasets of roughly 5 billion vertices and 20 billion edges so Amgen could load data much faster and run large-scale graph analytics. With TigerGraph, Amgen identified referral networks, common patients and the most influential providers, enabling marketing and clinical teams with actionable insights and helping inform care decisions that affect millions of patients.

Amgen

Vishnu Maddileti

Director of Data Sciences and Analytics