Some medical technologies that use artificial intelligence might benefit patients but result in a drop in health system revenues. This could make widespread adoption of AI in medicine a tough sell.
Healthcare is a world of perverse
incentives. One person's waste is another person's annual bonus. If you have
shares in Novo Nordisk, you don't really want people to eat more fruits
and vegetables, because then sales of diabetes meds might drop. The same is
true on a larger scale for hospital systems that get paid to conduct tests and
perform surgeries instead of keeping people healthy.
It
doesn't pay—yet—to keep people healthy. Many entrepreneurs and government
leaders are dragging the American healthcare system away from the
fee-for-service model, but the road to pay for performance medical care is long
and winding.
HeartFlow is
the perfect example of how a positive change for patients could mean a drop in
health system revenues. The company's goal is to improve care for heart disease
by avoiding both under- and over-treatment. HeartFlow takes data from a CT scan
and turns it into a 3D model of the veins and arteries that supply blood to the
heart.
"If
our system is adopted, the net annual savings would be $2 billion for one
commercial payer," said John Stevens, MD and president of HeartFlow.
"We could avoid 250,000 unnecessary procedures and even save 30,000
lives." Stevens shared these shocking numbers at HLTH 2018 in early May in Las Vegas.
Currently
when a doctor is treating a person with heart trouble, he has to make an
educated guess about the severity and location of a blockage that may be
causing blood flow problems. The most common diagnostic test is a heart
catheterization, and this is where the waste and inefficiency enters the
picture. In many cases, the doctor who recommends this procedure also gets
paid for conducting it.
A 2013 study published in JAMA compared
two groups of people who had heart caths: One in New York City and one in
Ontario, Canada. More people in the New York group received heart caths than
the Ontario group, even though the New Yorkers were younger and showed fewer
symptoms of heart disease. According to these findings, "one might
reasonably conclude that a more selective use of cardiac catheterization should
be implemented to reduce its associated costs and to improve its diagnostic
efficiency."
A
US News & World Report analysis studied Medicare data on heart
catheterizations. The results showed that doctors in rural areas were more
likely to prescribe the test, despite the fact that heart attack rates were not
higher in those areas. A small study of doctor-patient conversations showed
that doctors don't often mention alternatives to catheterization or
discuss the test's limitations.
The HeartFlow
software combines computational fluid dynamics with an analysis of a patient's
anatomy and physiology to create a 3D model of the
patient's heart. Coronary segmentation algorithms
are trained using data collected from clinical trials and refined by HeartFlow
cardiologists. The algorithms that build the color-coded map of the coronary
arteries take into account the many factors affecting blood flow, including
total blood flow and flow to different parts of the heart. The software also
solves millions of equations to assess the impact that blockages have on blood
flow; this helps doctors understand if a blockage in an artery is serious
enough to require surgery. In addition to the 3D model of the patient's
heart, HeartFlow analysis recommends treatment options to the physician to help
make the decision between more invasive tests and possibly surgery or
medication.
The
company is making significant progress in expanding access to its diagnostic
services. UnitedHealthcare just announced that it will cover the HeartFlow
analysis for its 45 million customers.
Earlier
this year, HeartFlow scored a big win recently in the UK. The NHS
will start using HeartFlow this year to treat the 2.3 million people in England
with heart disease. HeartFlow is one of four new technologies that will be
fast-tracked into use through the health system's Innovation and Technology
Payment program. Simon Stevens, chief executive of NHS England, said that these
technologies will improve patient safety and potentially reduce the need for
invasive and expensive tests. The Innovation and Technology Payment program
speeds up the adoption process for new technologies by making reimbursement
easier—that is a huge barrier in America for entrepreneurs working in
healthcare. If there is no ICD-10 code for a device or a procedure, insurance
companies won't pay for doctors to use a new method.
Just
as a lack of reimbursement slows down tech adoption rates, fee-for-service health
systems are also skeptical of new technologies that would change current
revenue sources, like emergency room visits.
Many analyses of promising AI technology
focus on applications with the most money-saving promise without
connecting those savings to a hospital's bottom line. Another HLTH speaker—Leonard
D'Avolio, PhD, CEO of Cyft—did make the connection during a panel
discussion and in an excellent blog post. Cyft's goal is to keep people
out of the hospital by analyzing data from multiple sources—call center
transcripts, EHR, care management notes—to identify people most likely to
benefit from a specific intervention. D'Avolio said that between 5% and 12% of
the total healthcare delivery market is value-based, meaning that doctors and
hospitals get paid for keeping a person healthy. "The other 90% gets paid
only when someone lands in the hospital," he said. "What's the
incentive to protect the older persons from a fall when that's $12,000 out of
my pocket? It doesn't pay to keep people healthy."
Healthcare
has always been slow to adopt new technology. The current worry around
artificial intelligence is that robots will replace doctors. If AI represents a
threat to a hospital's bottom line, it may be even harder to get widespread
adoption. Stevens of HeartFlow says the challenge is to strike the right
balance between high tech and high touch.
"Personal
interaction is vital to healing," he said. "If we can we optimize the
encounters, we can do more with a lot less money."



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