The Promise of Big Data Gets Closer to Fulfillment

Tony Berberabe, MPH @OncBiz_Wiz
Published: Tuesday, Oct 21, 2014
Anne-Marie Meyer,PhD

Anne-Marie Meyer,PhD

It seems like big data is everywhere these days. It’s being touted as a solution for physicians and practices who would like to participate in Accountable Care Organizations (ACOs) and accountable care-like contracts with payers. But what is it and how can it help practicing oncologists and hematologists?

Big data is a term used to describe both structured and unstructured data that can be obtained from multiple sources: patient records, insurer databases, physician offices, hospitals, Medicare/Medicaid records, and even personal sensors and smartphones. The data that are collected can be used to help physicians make more intelligent decisions about quality, treatment protocols, reimbursement, and even improve their own practice’s efficiencies. With the advances in information technology and data computing, population-based research can take advantage of these linked databases that can lead to discoveries and insights.1

Big data promises “to deliver better research at the population level for comparative effectiveness and outcomes research—and to better understand issues concerning disparities in care, access, and burden of disease,” said Anne-Marie Meyer, PhD, an assistant professor in the department of epidemiology at the Gillings School of Global Public Health at the University of North Carolina. Meyer is the faculty director of the North Carolina’s Integrated Cancer Information and Surveillance System (ICISS).

ICISS assembles, links, and harmonizes big data to facilitate high impact, cancer-focused research that spans all facets of the cancer continuum by relating data sets, systems, and methods. One advantage big data may have over other forms of data collections—for example, clinical trials—is access. Meyer points out that patients who are enrolled in a clinical trial have access to care. “These are patients who are already interfacing with the health care system in a very high-quality way,” said Meyer.

With big data, however, researchers can “look at populations who are not represented in clinical trials and who may not be represented in cohort studies or other types of clinical or epidemiologic design studies,” she emphasized.

Peter Yu, MD, FACP, FASCO, a practicing hematologist/ oncologist at the Palo Alto Medical Foundation in California and president of the American Society of Clinical Oncology (ASCO) concurs.

“We know that only 3% of cancer patients go on clinical trials and hence that data is nonrepresentative of the entire cancer population,” he said. “For example, clinical trials tend to draw a younger patient population with fewer comorbid medical problems. By studying how closely the findings of clinical trials are replicated in real world patients, we will be better able to determine the true value of treatments and understand what is the best way to adapt those treatments, potentially leading to better overall results,” said Yu.


In today’s healthcare reform environment, practicing oncologists and hematologists are being asked to document that they are delivering quality care to their patients.

“In order to provide and demonstrate value-based care, oncologists need to understand and have access to data that are not currently available, said Bobby Green, MD, vice president of oncology for Flatiron Health, a health care technology company based in New York City.

The problem with these data is that it exists in different forms, is often unstructured, and is stored in different places in the treatment continuum. Some reside in a practice’s electronic medical record or billing system, some in a hospital system, and some with the payers.

“All this information is stored in silos,” said Green. “It’s in all these different areas and sometimes a lot of it sits in the unstructured notes of the physician, making it difficult to collect and analyze.” Green said that the silos have no inherent reason to share, and that it’s very important when sharing data to strictly adhere to patient privacy laws, but that this creates barriers. “That’s the landscape that we have to navigate. So it’s much easier to share what you bought on Amazon, rather than any part of a patient’s medical records—and appropriately so,” he added. “But we have to find a way to aggregate the data, and at the same time, respect patient privacy.”

It’s an overwhelming challenge to collect and analyze big data. But finding a way to use it can be a powerful tool on many levels: clinical, operational, and financial.

“For clinicians, if they are going to be making clinical decisions, they will want to know the source of the data, if it’s complete, if it’s trustworthy, and if it’s accurate,” said Sean Hogan, vice president of health care at IBM.

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