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Oncology EHR and real-world data platforms

Databases built from millions of real patient records, used to see how treatments work outside trials and to run studies without new trials.

Flatiron Health (Roche; oncology EHR OncoEMR plus the Flatiron-Foundation clinico-genomic database), Tempus (multimodal clinical-molecular data), ConcertAI, COTA, Syapse, TriNetX, Komodo Health, Optum, and Datavant (tokenised linkage) assemble and curate real-world oncology data. Used for external control arms, label expansions (FDA's RWE framework), health-economic models, and biomarker discovery; standardisation via OMOP/OHDSI and mCODE (HL7 FHIR) is the interoperability layer.

Generic schematic · not to scale · placeholder for the ai computation front
Flagged finding · Neural network

How it works

Structured and abstracted EHR data, claims, genomics, and mortality linked with privacy-preserving tokens; curated to common data models and analysed with target-trial emulation methods.

Strengths
  • Scale and speed
  • Populations trials exclude (older, sicker, rarer)
Limitations
  • Confounding and missing data
  • Inconsistent endpoints (real-world progression)
  • Access and cost

Latest papers

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Query for this technology: (TITLE:"Oncology EHR and real-world data platforms" OR ABSTRACT:"Oncology EHR and real-world data platforms") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Oncology EHR and real-world data platforms, not a curated reading list.

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