How CancerLinQ Patient Intelligence 360 Makes Real-World Oncology Data Ready for Use

When ASCO launched CancerLinQ nearly a decade ago, patient data was very difficult to access because it was siloed away in file cabinets and unconnected servers. Now with leadership in the field, the adoption of Fast Healthcare Interoperability Resources (FHIR) standards, and development of application programming interfaces (APIs) that enable data exchange between practices, we are starting to see the walls coming down in the data ecosystem. However, this new era presents its own set of challenges.

Today, data are more freely available to anyone. For example, patients can connect their smartphone to a feed from their practice’s electronic health record (EHR) system and receive structured data. What data aren’t is easily interpretable for everyone, including patients, clinicians, and researchers.

That’s where CancerLinQ Patient Intelligence 360 comes in.

As Director of Data and Bioinformatics, my job is to make CancerLinQ’s real world oncology data ready for use by clinicians and researchers through solving key challenges with the interpretability and the contextualization of real-world data. CancerLinQ Patient Intelligence 360 is our new and innovative approach we use for doing this.

Data currently collected in the structured fields of EHRs are transactional, decontextualized, and difficult to interpret. In addition, data scientists still have to piece together several disparate systems and data sources to compile a complete picture of the patient’s care experience. Despite this meticulous work, they still encounter conflicting and missing information. This creates challenges and delays in conducting research and generating findings and insights that are fit for publication or real-world application.

I liken the process to cleaning a messy house. You put things back where they go and remove the clutter, but in the end, it is still the same house.  

CancerLinQ Patient Intelligence 360 is more akin to interior design and home improvement. It is a data model with supporting algorithms that consolidates the data received through CancerLinQ’s various sources into a simple, clinically driven data model based on the patient’s phases of disease.

Each phase represents the patient's disease state and treatment setting (e.g., Initial Diagnosis, Maintenance, Metastatic, Subsequent Metastatic), contextualizing the clinical data in the CancerLinQ database in language and concepts familiar to clinicians and researchers. At each disease phase, CancerLinQ captures the most important clinical details related to the patient’s journey, including comorbidities, biomarkers, and line of therapy. Where these data are not captured directly in the EHR, CancerLinQ is developing algorithmic approaches to bring historically collected data into alignment with current standards.

With Patient Intelligence 360 and corresponding clinical tools, providers at the point of care will be able to more quickly understand the historical treatment and outcomes of a given patient, which will assist in clinical and shared decision making. For researchers, Patient Intelligence 360 will make CancerLinQ Discovery data more efficient to query and interpret.

The reason we are able to do this at CancerLinQ is because we bring both oncology and data science expertise to each patient’s EHR. Through Patient Intelligence 360, we can use the clinical insight we have here at ASCO to expertly curate the best interpretations of the data so that it can be used as effectively as possible.

I joined the CancerLinQ team because I am passionate improving society using data, so I am very excited about our future with Patient Intelligence 360. If you are interested in learning more, please email me at