This didactic panel will describe how real-world data, traditionally defined as those data derived from a source other than a traditional clinical trial, can generate real-world evidence and can be used to facilitate research and inform clinical care. Focusing on the field of oncology and the collection, aggregation, and transformation of cancer data predominantly but not exclusively contained within electronic health records, panelists representing four platforms currently delivering solutions – CancerLinQ®, COTA, GENIE, and ORIEN – will provide their perspectives on what it will take to improve cancer data interoperability and make meaningful progress in knowledge- and data-sharing to benefit patients. The panelists will discuss the need for alignment on data standards, challenges around curating and incorporating rich clinical data sourced from unstructured documents and free-text, and the particular data needs of precision oncology.
Learning Objective: After participating in this session, the learner should be able to:
1. Identify possible solutions to augment evidence traditionally obtained via clinical trials by leveraging real world data.
2. Understand inherent biases in real world datasets and be able to discuss caveats of using such datasets to inform clinical care and research.
3. Recognize quality issues for data derived through manual and automated methods for curation and describe the potential impact on clinical care and research.
4. Identify challenges of utilizing real world data in the absence of a common data model for oncology or interoperability standards, and articulate possible solutions.
5. Understand the current challenges in integrating clinical cancer genetics data with clinical outcomes and other phenotypic data, and articulate solutions that their own health organization can help promote.
Robert Miller (Presenter)
American Society of Clinical Oncology
Andrew Norden (Presenter)
Shawn Sweeney (Presenter)
American Association for Cancer Research
William Dalton (Presenter)
Oncology Research Information Exchange Network