Find AI Tools
Flatiron Health screenshot

What is Flatiron Health?

Flatiron Health provides a platform designed to aggregate and analyse cancer patient data for research purposes. The tool collects real-world oncology data from clinical settings and makes it available to researchers, pharmaceutical companies, and healthcare providers who need insights into cancer treatment patterns and outcomes. Rather than relying on traditional clinical trials alone, the platform draws from actual patient records, electronic health records, and treatment histories to identify trends and support evidence-based research. This approach allows researchers to study larger, more diverse patient populations and answer questions about treatment effectiveness in routine practice. The platform is free to access, making it available to academic institutions, hospitals, and research organisations that want to contribute to and benefit from its dataset.

Key Features

Real-world oncology data aggregation

collects deidentified patient records and treatment information from clinical partners

Data analysis tools

enables researchers to query and analyse cancer patient outcomes, treatment patterns, and survival data

Research collaboration

connects researchers with patient cohorts relevant to their studies

EHR integration

pulls data from electronic health records systems used in clinical settings

Outcome tracking

follows patient responses to treatment and long-term outcomes

Pros & Cons

Advantages

  • Free access removes cost barriers for academic and non-profit research institutions
  • Large, real-world dataset reflects actual clinical practice rather than controlled trial conditions
  • Enables analysis of treatment effectiveness across diverse patient populations
  • Data comes from active clinical settings, providing current information

Limitations

  • Data availability depends on participating clinical sites, so geographic or institutional gaps may exist
  • Deidentified data may limit ability to conduct certain longitudinal follow-up studies
  • Requires institutional partnerships and data governance agreements to access full platform capabilities

Use Cases

Academic cancer researchers analysing treatment outcomes and efficacy across patient populations

Pharmaceutical companies studying real-world effectiveness of oncology drugs post-approval

Healthcare systems examining their own treatment patterns and outcomes against broader datasets

Clinical trial designers identifying patient populations and refining eligibility criteria

Health policy organisations researching cancer care access and equity issues