CancerLinQ Big Data Analytics a “Powerful Tool” for Oncology

The American Society of Clinical Oncology (ASCO) isn’t the only one attempting to bring “learning” big data analytics capabilities to clinicians at the point of care, but they are among the most successful organizations focused on helping providers make informed, accurate, and effective decisions for oncology patients.

The CancerLinQ initiative, which uses electronic health record data and other information to produce insights accessible by clinicians, researchers, and even patients, has seen rapid growth and development since its inception in 2013.

In an article for the American Journal of Managed Care’s Evidence-Based Oncology publication, Robert S. Miller, MD, FACP, FASCO, Medical Director of CancerLinQ at the ASCO, provides the industry with an update on the system’s progress and a peek into how the “powerful” big data analytics tool delivers clinical decision support for some of the most complex patients.

“The promotion of the highest quality cancer care has long been foundational to the mission of the American Society of Clinical Oncology,” Miller writes.  CancerLinQ is an extension of that mission, he added, founded on care quality principles outlined by the Institute of Medicine (IOM), which encourage oncology providers to deliver patient-centered, evidence-based care.

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“CancerLinQ’s primary objectives are to provide real-time quality feedback to oncologists to enable them to measure the care they render against clinical guidelines and that of their peers, to deliver personalized insights at the point of care, and to accelerate the generation of new research hypotheses by uncovering patterns in patient and tumor characteristics, therapies, and outcomes that require massive data sets and real-world evidence,” he added.

The system, built on big data analytics technology provided by SAP’s HANA platform, integratescutting-edge data lake infrastructure, which holds disparate data sources in a single “staging area,” where it can be queried by users on the fly. 

Structured and unstructured data, from electronic health records and elsewhere, are standardized through the use of natural language processing and rules engines, which then return permissions-based results to users through a web browser interface.

“Product features include a set of clinical quality performance indicators based on ASCO-developed electronically specified clinical quality measures (eCQMs); the [CancerLinQ Insights data exploration tool] for customized cohort and data exploration; a patient timeline tool to visually represent oncologic milestones in the patient history; and a suite of parameterized analytic reports,” Miller explains.

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In addition to allowing oncologists to better visualize their patients’ treatment patterns, access clinical decision support features, and engage in the emerging school of precision medicine, CancerLinQ is also likely to become an important part of helping providers to meet clinical quality measures.

“The ASCO Board of Directors, from the time of its earliest strategic decisions to create CancerLinQ as a learning health system for oncology, envisioned that the primary function of the platform would be as an extension of ASCO’s quality portfolio, most notably the Quality Oncology Practice Initiative,” which is the Society’s assessment program for outpatient hematology-oncology practices, Miller said.

The program is intended to “create a culture of self-examination” through regular assessments of performance on established measures linked to high-quality cancer care.

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