Realizing the Promise of Real-World Data at Scale: Using Clinical-Expert Trained AI for a Complete View of US Health

The promise of improving patient care and outcomes by utilizing healthcare data at an unprecedented scale is achievable, but the sheer volume and complexity of real-world data from disparate data sources and disease-state silos can make addressing this promise difficult to realize. Researchers need comprehensive data linked across sources that cover the full diversity of the U.S. across age, geography, race, ethnicity, gender, and social drivers of health to unlock new discoveries for diseases and understand the safety and effectiveness of every drug or device.

Like other industries, U.S. healthcare is experiencing a data revolution that’s broadly impacting every aspect of the system—this is where clinical expertise-led AI shines. By using AI to unlock the power of these novel datasets, researchers can ask and answer complex medical questions with computable clinical concepts for a real-time, fully transparent view of U.S. health.

During this session, Truveta and its partners share how researchers can:

- Address key evidence gaps with a massive, normalized dataset of nearly 80 million patients with data across conditions, drugs, and devices

- Quickly assess precise populations of interest with computable clinical definitions that represent complex clinical scenarios

- Uniquely power use cases like clinical trial design, label expansion, safety monitoring and rare disease research with daily care data

Seating is limited.

Sponsor: Truveta