Powering Unbiased Outcomes Research with Longitudinal Data

A medical device company preparing a product launch needed to compare outcomes between cemented and uncemented knee arthroplasties, but claims data alone showed an artificial downtrend because surgeries had shifted to outpatient settings using "generic CPT codes" instead of detailed ICD-10-PCS codes. Norstella integrated EHR data with claims records using NorstellaLinQ and the Instant Health Data platform. Within eight weeks, the company had comprehensive longitudinal arthroplasty data spanning inpatient and outpatient procedures, letting it complete its health-economics study and support the device launch with stronger real-world evidence.

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

Norstella is a holding company merging several pharma-intelligence brands — Citeline (trial intelligence), Evaluate (forecasting), MMIT (payer/formulary data) and Panalgo (real-world analytics) — into one data asset.

This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.