AI Case Study – How IQVIA Increased Target Patient Identification 15X

Healthcare clients needed to quickly identify and segment the right patients and HCPs with precision and speed. IQVIA applied artificial intelligence and machine learning combined with its Real World Data portfolio and proprietary algorithms. Verbatim results cited: "Increased precision of patient identification by 15x and increased precision of HCP linkage by 10x," a "dramatically increased rate of patient initiation by HCPs identified by the algorithm," and a "treatment transition rate of 28% over three months." The page also states AI/ML can identify patients "before they are diagnosed." This is a gated landing page; full detail is behind a PDF download.

The customer is anonymised in IQVIA’s own case study — not withheld by us.

IQVIA is the largest combined real-world-data and commercial-intelligence company in healthcare — its legacy IMS prescription and claims data underpins much of the industry's analytics.

This sits in the Build stage of the AI use-case lifecycle: Named examples from the foundation-model labs and platforms pharma teams use to actually construct, train and generate the model or application.