As precision medicine and its related technologies take off in healthcare with rocket-like speed, many players in the space are advocating for a balance between innovation and regulation. Without policies in place, there are major mistakes that hospitals, researchers, clinicians, and policymakers will need to avoid to ensure that the healthcare system remains available to all, according to speakers at last week's HIMSS Precision Medicine Summit in Washington DC.
Dulin, a physician-patient who himself has benefitted from precision medicine, cautioned that there are enormous mistakes to avoid.
"Our healthcare system is broken," he said. "It's inefficient, and precision medicine is an amazing tool but if we layer it on top of a broken system we can actually make things worse. Health disparities can get worse, we need to be very proactive when we're thinking about how to integrate this into our delivery system."
Sacred responsibility of design
Right now the technologies, including artificial intelligence and machine learning, are outpacing policy — and that puts a whole new degree of accountability squarely on the shoulders of hospitals, IT vendors, developers, and others.
"There is an increased responsibility for designers, developers, specialists to build the technology in a good, reflective way," Paul Ford, director of the Center for Bioethics at the Cleveland Clinic Foundation, said. "It's our responsibility to try and protect against challenges because policy isn't there to guide us."
That starts with talking to patients to find out what's most important to them because it might not be what designers think it is. A person with Parkinson's disease, for instance, could simply want to be able to eat soup in public above all else.
"We need to create consumer experiences that are fun and engaging to make you participate in your own care," Aviva Debeer, Global Solutions Executive at IBM Watson Health, said. "That begins with design.
AI and machine learning in healthcare
If there are any technologies that bring promise on the scale of precision medicine they would have to be the dynamic duo of machine learning and artificial intelligence. But with them, risks arise too.
The problem is the black box behind all those algorithms and the potential for false positives and false negatives in decision making conducted with little visibility for clinicians.
"There's a cost, not only financial but also to the health of the person, in acting on false positives and false negatives," Dr. Sujay Kakarmath, a post-doctoral research fellow at Partners Connected Health and Harvard Medical School, said. "AI is not the same in other diagnostic systems because they learn in time. The black box gives you a prediction but doesn't tell how it came to the conclusion."
IBM's Debeer added that AI and machine learning systems need to be trained with clean data, which is the current bottleneck.
"It's a misconception that AI is going to be an out-of-the-box solution for everything, it takes time," Debeer said. "Pick a project where you can start implementing AI that is consumable and then start scaling that."
Cleveland Clinic's Ford pointed out that hospitals and other care providers also have challenges distinct from other industries.
"Idiosyncrasies of our healthcare system can affect the performance of AI tools in unexpected ways," Ford said. "Precision medicine sometimes gets treated as one thing: Precision medicine is good. We're worried that there's also a subset that isn't going to meet our expectations. There's real risk of harm in intervention."
Ethics, access, and affordability
As emerging technologies enable more health systems to deliver precision medicine practices and programs to patients, the matters of infrastructure to support it and widespread access will become increasingly critical to ensure that it's not just for the wealthy in urban areas.
"Patient activation is an important consideration in chronic disease, " Dr. Richard Milani, chief clinical transformation officer at Ochsner Health System. "Does changing behavior change outcomes? The answer is you can."
Milani pointed to longitudinal research spanning the five decades from 1960-2010, in which reducing smoking in America added an average 1.25 years to every person's life as just one example.
But to affect such behavior change, hospitals must be able to connect with patients and the infrastructure for that is not entirely here yet, though it's coming.
"[Hospital] connectivity amongst each other is important but what's more important is our connectivity with patients," Milani said. "We need connectivity with our patients."
5G networking, in fact, will enable the transport of large data from multiple sources to create a connected care continuum, thus making the delivery of precision medicine more practicable.
"We have to bring the full environment to the patient," Derek Cothran, senior vice president of client strategy and development at EnvoyHealth, said. "We have to address affordability and social aspects. We're patiently waiting on 5G to enable that."
Which gives everyone — hospital executives, entrepreneurs and designers, CIOs and IT pros, as well as patients — the opportunity to start ironing out ethical issues associated with precision medicine. At least until the policy catches up.
"There is only so much resources that can be given to one patient without taking it away from another," Cleveland Clinic's Ford said. "There are so many people in the industry who do good work but all of our disciplines have people who pray on our goodwill."
The next HIMSS Precision Medicine Summit will take place at HIMSS19 in Orlando on Feb. 11, 2019.
