ASCO’s CancerLinQ: Building a Transformation in Cancer Care


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Cancer science and information technology are advancing rapidly, but the way we care for patients today cannot fully capitalize on those advances.

The proliferation of scientific results and novel treatments is a growing challenge for all oncology professionals as we enter the era of highly personalized cancer care. Patients are increasingly presenting with “rare cancers,” more narrowly defined by their molecular characteristics, sometimes making the best course of treatment unclear. Today more than ever, oncologists need real-time decision support to help them provide the most effective treatments tailored to their patients’ unique biology and tumors.

Transforming Cancer Care through Real-time Learning

That is why ASCO is embarking on CancerLinQ, a multiphase initiative that promises to change the way cancer is understood and treated. This “rapid learning system” will harness technological advances to connect oncology practices, measure quality and performance, and provide physicians with decision support in real time.

“At the pace that cancer science is moving today, this kind of system will not only be helpful, it will be essential. Oncology practices will see enormous benefits from such a system, and patient care will improve as a result,” said ASCO President Sandra M. Swain, MD.

A rapid learning system, described by the Institute of Medicine in a 2010 report,1 is designed to draw insight from the vast, untapped pool of data on “real-world” patients. Today, we know very little about most patients with cancer—from the molecular characteristics of their tumors to the outcomes of their treatments—because these details are locked away in unconnected electronic and paper records.

ASCO’s vision for CancerLinQ is to assemble and analyze all of that information in a central knowledge base, which will grow “smarter” over time. Specifically, the system will:

  • Upload clinical data stored in electronic health records (EHRs) from patients in multiple practices
  • Aggregate information from EHRs, new clinical trials, and published guidelines
  • Identify trends and associations between myriad variables in order to generate new hypotheses
  • Allow physicians and researchers to evaluate those hypotheses and determine which ones may lead to improved care in real-world settings
  • Enable clinicians and researchers to quickly apply those conclusions, forming a continuous cycle of learning.

“We are now at an inflection point in health care, where scientific and technical advances are making the transformation of cancer care possible. Instead of waiting for clinical trials alone to guide patient care, we can now aggregate and learn from massive quantities of real-world data in ways that we couldn’t have conceived even 20 years ago,” said ASCO Immediate Past President Michael P. Link, MD.

In practice, once the full technology platform is completed, CancerLinQ will:

  • Improve personalized treatment decisions by cancer care teams by capturing patient information in real time at the point of care; providing real-time decision support tailored to each patient and his or her cancer; and automatically reporting on the quality of care compared with clinical guidelines and the outcomes of other patients
  • Educate and empower patients by linking them to their cancer care teams and providing personalized treatment information at their fingertips
  • Create a powerful new data source for use in real-world quality and comparative effectiveness studies, and to generate new ideas for clinical research.

Evolution of ASCO’s Quality Improvement Programs

CancerLinQ represents the next major step in ASCO’s efforts to improve the quality of cancer care in the United States. It builds on ASCO’s unparalleled expertise in oncology quality programs, which is being brought together with CancerLinQ in a new ASCO Institute for Quality established in 2011.

“ASCO’s intensive focus on quality improvement in oncology makes us uniquely suited to develop and offer this service,” said Dr. Link. “All of ASCO’s quality initiatives are converging to make this vision a reality.”

ASCO issued its first clinical practice guideline in 1994. In 2006, ASCO launched QOPI, the first national program to help oncology practices measure and improve the quality of care. QOPI’s rigorous set of more than 90 quality measures allows oncologists to monitor and hold each other accountable to advance their quality of care together. A third of oncology practices in the United States, nearly 700, are registered in the program.

“QOPI has demonstrated the power of oncologist-driven efforts to improve patient care,” said Dr. Link. “Like QOPI, CancerLinQ will be designed by and for oncologists and their patients, with the sole objective of improving patient care,” Dr. Link added.

Assessment Phase: Breast Cancer

CancerLinQ is now entering its assessment phase, focusing on the development of a breast cancer–specific prototype. This prototype will enable ASCO to fully assess the feasibility of a rapid learning system for oncology, and to refine its approach as needed before expanding the initiative to include other cancers. ASCO anticipates completing this prototype by the end of 2012.

ASCO will be calling on you, our members, to help make the assessment phase a success. We will ask you to participate and move the field forward by sharing de-identified information on cases of breast cancer from your own practice.

Taking a phased approach and learning from each phase, ASCO anticipates that the full system will be complete and operating in practices nationwide by the end of the decade. Regular updates will be coming in the months ahead. ■

Reference

1. National Research Council: A Foundation for evidence-driven practice: A rapid learning system for cancer care: Workshop summary. Washington, DC: The National Academies Press, 2010. Available at: http://www.iom.edu/Reports/2010/A-Foundation-for-Evidence-Driven-Practice-A-Rapid-Learning-System-for-Cancer-Care.aspx

© 2012. American Society of Clinical Oncology. All rights reserved.


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