In Cancer, Patient-Empowering AI Begins To Change Care, Relationships

Imagine, if after being diagnosed with cancer, you could access algorithms that would help you find the best treatment, the hospital with the best outcomes and even your likely six-month to five-year chances of survival.

All that is possible today. While doctors excitedly discuss how they might utilize OpenAI’s dazzling new ChatGPT, artificial intelligence (AI) is quietly giving patients the ability to find, create and act upon an unprecedented breadth and depth of authoritative information.

What, then, happens to the role of the doctor?

The essence of medical professionalism has been defined as possessing knowledge inaccessible to the lay public. That knowledge monopoly, however, is rapidly eroding. Medicine is entering an era of new roles, rules and relationships, all of which remain very much in flux.

Perhaps the clearest example of the changes underway is in cancer. Four in ten Americans will be diagnosed with cancer at some point in their lifetime, according to the National Cancer Institute (NCI), with almost two million receiving that dread news each year. The National Academy of Medicine has declared shared decision making as important as technical competence, yet anxious and frightened patients remain so reluctant to challenge their doctor that it’s been compared to a hostage situation.

Enter patient-empowering AI. At its most basic, AI represents a method to make sense out of a deluge of data. The special appeal of ChatGPT lies in its ability to provide a coherent and comprehensive narrative response. The problem, as numerous reviewers have pointed out, is that insights and inaccuracies can seamlessly blend together. Unlike ChatGPT (at least for the moment), the companies discussed below anchor their AI in medical databases, not the Internet, although that doesn’t make either the technology or recommendations flawless.

In cancer, the initial treatment decision is critical. The National Comprehensive Care Network (NCCN), an alliance of 32 leading cancer centers, produces care guidelines based on a critical evaluation of evidence and on the clinical expertise of specialists in areas where high-reliability evidence isn’t available.

Outcomes4Me says it’s developed “the only direct-to-patient platform that integrates with the NCCN clinical practice guidelines in oncology.” The company, founded by former execs with pharma and Google and an oncologist with experience at the NCI, enters comprehensive information from the patient’s medical records into an analytics engine. The potential treatment options are then presented to the patient in plain English, setting the stage for a very different kind of doctor-patient conversation about treatment.

Your doctor claims to already follow the guidelines? Perhaps, but even at academic medical centers adherence varies widely, according to researchers, despite evidence that following the guidelines “leads to improved outcomes;” i.e., can be a matter of life or death. So maybe that big-name hospital advertising on TV isn’t the best place to get care.

A company called PotentiaMetrics promises to apply patients’ personal medical information to “cancer treatment options and outcomes from hospitals across the United States.” Its AI-powered platform purportedly has “the largest cancer outcomes dataset of its kind.” The company also offers personal navigator assistance – once more, significantly changing the traditional dynamic of the doctor-patient dialogue.

There is one hitch: unlike Outcomes4Me, PotentiaMetrics isn’t a direct-to-patient platform. However, one part of its business model illustrates just how much roles, rules and relationships are changing. Cancer has become the top driver of large companies’ health care costs, according to the Business Group on Health. PotentiaMetrics sells its services to employers and health plans that are convinced the most clinically effective care is also the most cost-effective. Importantly, the involvement of employers and plans opens the way to offering this kind of information to a broad swath of the public.

(Both Outcomes4Me and PotentiaMetrics also rely on income from connecting patients to drug company clinical trials, a topic for a different discussion.)

Meanwhile, a group of Canadian researchers recently published findings showing they could predict with 80 to 90 percent accuracy the six-month, three-year and five-year survival rates of patients with a broad variety of cancers. Those predictions were based on an AI-powered review of patients’ complete medical record after the first oncology consult. If the researchers chose to publicly post their algorithm, U.S. regulations related to information sharing and interoperability mean it could quickly be adapted into a patient-facing app that would allow patients to search their own record.

Predictions, of course, are not certainties for any individual patient, and, importantly, we don’t yet know the track record of these companies. It’s also easy to forget that “AI” is a term applied to a variety of learning models and that different databases may provide different answers. Breathless speculation notwithstanding, AI is nowhere close to replacing the doctor.

Still, the predictions that oncologists give to their cancer patients are notoriously inaccurate. Moreover, quantum leaps in AI capabilities are on the way. Google is testing a dedicated question-and-answer chatbot called MedPaLM, while OpenAI, which just rolled out ChatGPT-4, is also said to be planning a medical version.

What is certain is that AI is poised to radically reshape care. With our smartphones, watches and even clothing increasingly bristling with sensors, and with sophisticated peer-to-peer learning sites providing unique information, incorporating patient-reported data into care is essential.

Good medicine needs to become participatory medicine, not least because involving the patient as a partner consistently improves care. In cancer, for instance, incorporating patient-reported outcomes during treatment improved patient survival and quality of life. Elsewhere, I’ve proposed a formal structure for sharing of information, engagement and accountability that I call “collaborative health.”

The transparency that AI is bringing to medicine will highlight the wide variations in medical practice and outcomes. For example, the U.S. spends twice as much on cancer care as the average high-income country, yet patient death rates are only slightly better than average, a Yale-led study found.

A quarter century ago, I wrote a book entitled, Demanding Medical Excellence: Doctors and Accountability in the Information Age. The information age and the demand for accountability seem finally to be arriving, with the turmoil precipitated by ChatGPT making the book’s conclusion even more relevant today:

“The destruction of the old ways of medical practice may be an unavoidable source of anxiety, but it should not be a source of despair. Patients and caregivers alike should celebrate better days ahead. Destruction often precedes renewal, and it is in that renewal that the future of American medicine lies.”