Making Precision Medicine a Reality

When hospitals and ambulatory care practices think about precision care, they might see stars. Forget best practices and how to fine-tune the initiative as time goes on. Where to even begin?

Joel Diamond, MD, has a few ideas. He’s an adjunct associate professor of biomedical informatics at the University of Pittsburgh, practicing in its acclaimed health system, and the chief medical officer of 2bPrecise, a genomics-driven precision medicine platform company that has linked arms with Mayo Clinic.

Here, he shares with Healthcare Analytics News™ his 4 targets that medical groups should hit to launch and beef up their precision medicine efforts.

Locate and Consolidate Genetic Data

First, health systems and ambulatory practices face different challenges in this realm. “They’re just willy-nilly,” Diamond says of the ambulatory side. “It’s the wild west out there.”

Hospitals, of course, also struggle with data problems, he says.

He often hears staffers say they don’t have much genetic data—a foundation of precision medicine—or know where to find it. Indeed, the information is scattered across each institution, in various departments and from any number of laboratories, Diamond says. In some cases, employees don’t even understand that tests they order contain genetic panels.

By tapping existing data wells and developing protocols for future storage, health systems can leap forward.

Make the Data Accessible

This is all about new technologies and workflow tools, Diamond says.

Much of the genomic data that come into hospitals arrive on paper—like through a radiology report. “When this paper’s coming in, there’s not a central place where it’s going where it can be reused,” Diamond adds.

Instead, the documents end up just about everywhere, wiping out their potential to power analytics, clinical support, population stratification, and more. For example, if an OBGYN or an oncologist orders a gene test on a woman with breast cancer, the results probably won’t inform providers of her risk for ovarian cancer, Diamond says. Paper also bars data-based decisions regarding cost and quality, the tenets of value-based care. So health systems must aim to digitize genomic data.

Further, Diamond notes, they must implement “everyday usability features.” Electronic health records systems typically warn providers when a patient allergy is going to clash with a new prescription, he says.

The same kind of built-in response can apply to pharmacogenomics, like, say, to determine whether a patient with depression is incapable of metabolizing a certain drug. “That’s an area where I think it’s not hard to do,” he adds. “People are hungry for it. Primary care doctors are asking about it.”

Consumer demand could push advances in this area, Diamond says. When someone pays hundreds of dollars to get a full exome, they likely want advice and medical tests related to their risk factors. Healthcare must soon learn to meet that growing demand, he says.

Educate Providers

Physicians and other providers might be hesitant to once again hit the books. But they don’t need to read up too much, Diamond argues. He says providers keep up on all sorts of developments in the industry, whether they be new drugs, imaging, or lab tests. Learning more about genomics doesn’t require pressing the restart button on their medical education, he says.

Healthcare organizations can encourage providers to absorb the new material by highlighting the practical benefits. The American College of Medical Genetics and Genomics maintains a list of actionable genes, meaning they’re related to certain conditions. That can help guide treatments, Diamond says.

Education is important because some patients should undergo genetic testing. Specialists, for example, should know new markers and keep tabs on developments that can help their patients. “It’s almost sinful,” Diamond says of those who don’t, “and we would expect better from such people.”

Teach How, When, and Why to Order Genetic Tests

These assessments can be expensive, though Diamond says they ultimately lower costs. Even so, physicians must know when to order tests and relevant resources, like labs and other research facilities.

Algorithms and other technologies exist to help physicians with this piece of the puzzle, Diamond says. What’s critical, he adds, is that the education is available at the point of care.