Concepts
Canonical, plain-language definitions of the terms that define this field - what each one is, why it matters, and how Travis Osterman's work connects to it. Written to be the reference an oncologist, an engineer, or an AI agent can cite.
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What is mCODE (minimal Common Oncology Data Elements)?
mCODE is the open-source, FHIR-based oncology data standard implemented at 70+ institutions in six countries and the only data-submission path for the CMS Enhancing Oncology Model. Chaired by Travis Osterman.
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Enhancing Oncology Model (EOM), explained | Travis Osterman
The Enhancing Oncology Model (EOM) is CMS's voluntary value-based care program for oncology, and mCODE is its only data-submission path. Travis Osterman chairs the mCODE standard behind it.
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FHIR in oncology: HL7 FHIR and mCODE for cancer data
FHIR (Fast Healthcare Interoperability Resources) applied to cancer care: resource-based data exchange and mCODE, the FHIR Implementation Guide for oncology, whose Executive Committee is chaired by Dr. Travis Osterman.
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Real-world data and EHR-derived endpoints in oncology
Real-world data (RWD) in oncology is evidence from routine EHR care rather than trials, and EHR-derived endpoints are the outcomes computed from it. Definition, why it matters, and Travis Osterman's real-world-data research in immunotherapy.
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Clinical AI in oncology — definition, applications, and governance
Clinical AI in oncology is machine learning, NLP, and LLMs applied to cancer care, plus the governance they require. Dr. Travis Osterman's peer-reviewed record and expertise.
Related: areas of expertise · publications · case studies.