Building a Rapid Learning Health Care System for Oncology

Building a Rapid Learning Health Care System for
Oncology: The Regulatory Framework of CancerLinQ
Richard L. Schilsky, Dina L. Michels, Amy H. Kearbey, Peter Paul Yu, and Clifford A. Hudis
Richard L. Schilsky, Dina L. Michels, Peter Paul Yu (president elect), and Clif-
ford A. Hudis (president), American Society of Clinical Oncology, Alexandria,
VA; Amy H. Kearbey, McDermott Will & Emery, Washington, DC; Peter Paul
Yu, Palo Alto Medical Foundation, Palo Alto, CA; and Clifford A. Hudis, Memo-
rial Sloan Kettering Cancer Center, New York, NY.
Published online ahead of print at www.jco.org on June 9, 2014.
Authors’ disclosures of potential conflicts of interest and author contribu-
tions are found at the end of this article.
Corresponding author: Richard L. Schilsky,MD, FACP, FASCO, American Society
of Clinical Oncology, 2318 Mill Rd,Suite 800, Alexandria, VA 22314;
e-mail: richard.schilsky@asco.org.
© 2014 by American Society of Clinical
Oncology
0732-183X/14/3299-1/$20.00
DOI: 10.1200/JCO.2014.56.2124

ABSTRACT

Today is a time of unprecedented opportunity and challenge in health care generally and cancer care in particular.

An explosion of scientific knowledge, the rapid introduction of new drugs and technologies, and the unprecedented escalation in the cost of health care challenge physicians to quickly assimilate new information and appropriately deploy new advances while also delivering efficient and high-quality care to a rapidly growing and aging patient population.

At the same time, big data, with its potential to drive rapid understanding and innovation, promises to transform the health care industry, as it has many others already.

CancerLinQ is an initiative of the American Society of Clinical Oncology (ASCO) and its Institute for Quality, developed to build on these opportunities and address these challenges by collecting information from the electronic health records of large numbers of patients with cancer.

CancerLinQ is, first and foremost, a quality measurement and reporting system through which oncologists can harness the depth and power of their patients’ clinical records and other data to improve the care they deliver. The development and deployment of CancerLinQ raises many important questions about the use of big data in
health care.

This article focuses on the US federal regulatory pathway by which CancerLinQ will accept patient records and the approach of ASCO toward stewardship of the information.
J Clin Oncol 32. © 2014 by American Society of Clinical Oncology

INTRODUCTION

More than 1.6 million Americans are diagnosed with cancer each year. By 2030, the incidence of cancer will rise to 2.3 million cases per year, largely as
a result of the aging of the US population and control of competing causes of mortality such as heart disease.

Some 14 million people in the United States are cancer survivors, and that number will rise to 18 million by 2030. These patients with cancer and cancer survivors have complex medical and psychosocial needs.

Many are older and have other illnesses that complicate coordination of their cancer care, increase the risks of medical interventions, and limit their access
to participation in clinical trials. As a consequence, we often have scant evidence to guide treatment recommendations for the older individuals who comprise the largest segment of the population affected by cancer.

We frequently lack information on other identifiable subpopulations, including patients with other chronic illnesses and organ dysfunction. Clinical trials, by design, enroll relatively homogeneous patient populations, isolating the impact of experimental variables (new treatments) but typically excluding the heterogeneity that clinicians manage in day-to-day practice. This raises questions about the broad applicability of experimental results. CancerLinQ is designed to help close the gap between what can work and what does work.

Cancer treatment requires frequent interaction among multiple medical specialists. Communicating across different care settings, providers are challenged to coordinate care in an efficient and cost-effective fashion. Inefficiencies in health care
delivery, unnecessary testing, excessive administrative costs, and high prices for innovative products are all acknowledged as key drivers of health care costs.

These forces may be magnified in patients with cancer by many factors, including the multidisciplinary nature of cancer care, the high cost of many cancer drugs and other treatments, and the suboptimal use of hospice services near the end of life.

The management of patients with cancer is further complicated by the recent recognition that many apparently similar cancers actually vary greatly at the genomic level. This biologic heterogeneity gives rise to cancers that vary in clinical presentation and clinical course even when their histologic appearance is the same.

Increasingly, oncology professionals are challenged to recognize the molecular
subsets of common cancers, interpret results of complex molecular diagnostic tests, develop appropriate treatment plans, and deliver state-of-the-art care when clinical guidelines and clinical decision support services are either lacking or outdated.

Tumor heterogeneity also challenges our ability to develop new cancer treatments through traditional prospective clinical trials.

As common tumors are divided into rare molecular subtypes, it is increasingly challenging to identify eligible patients and complete recruitment to clinical trials in a timely fashion.
Rates of enrollment of adult patients with cancer onto clinical trials remain stagnant at no morethan3%to5%.

Drugdevelopment remains risky and inefficient, with the vast majority of agents that enter human testing failing to achieve approval for marketing.
With more tumor types, more drugs, fewer eligible patients, and strained research budgets, it will no longer be possible to learn everything that still needs to be learned in cancer treatment through the conduct of conventional clinical trials.