The Algorithm Will See You Now
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
Time to visit your TikTok doc? The good and bad of doctors on social media
Rakhi Patel has carved a hobby out of reviewing pizza — her favorite food — on Instagram. In a nod to her preferred topping, she calls herself thepepperoniqueen. Photos and videos show her savoring slices from scores of pizzerias. In some of them, she’s wearing scrubs — her attire as an inpatient neurology physician associate at Tufts Medical Center in Boston.
“Depending on how you dress your pizza, it can be more nutritious,” said Patel, who suggests a thin crust, sugarless tomato sauce and vegetables galore as healthier alternatives. “There are no boundaries for a health care professional to enjoy pizza.”
Beyond that, “pizza fuels my mental health and makes me happy, especially when loaded with pepperoni,” she said. “If I’m going to be a pizza connoisseur, then I also need to take care of my physical health by ensuring that I get at least three days of exercise per week and eat nutritiously when I’m not eating pizza.”
She’s among an increasing number of health care professionals, including doctors and nurses, who maintain an active persona on social media, according to bioethics researchers. They share their hobbies and interests with people inside and outside the world of medicine, helping patients and the public become acquainted with the humans behind the scrubs or white coats. Other health care experts limit their posts to medical topics, while some opt for a combination of personal and professional commentaries. Depending on the posts, ethical issues may come into play.
“Health care professionals are quite prevalent on social media,” said Mercer Gary, a postdoctoral researcher at The Hastings Center, an independent bioethics research institute in Garrison, New York. “They’ve been posting on #medTwitter for many years, mainly to communicate with one another, but, of course, anyone can see the threads. Most recently, doctors and nurses have become a presence on TikTok.”
On social media, many health care providers perceive themselves to be “humanizing” their profession by coming across as more approachable — “reminding patients that providers are people and workers, as well as repositories of medical expertise,” Gary said. As a result, she noted that patients who are often intimidated by clinicians may feel comfortable enough to overcome barriers to scheduling health care appointments. The use of TikTok in particular may help doctors and nurses connect with younger followers.
When health care providers post on social media, they must bear in mind that they have legal and ethical duties to their patients, profession and society, said Elizabeth Levy, founder and director of Physicians for Justice.
While enduring three years of pandemic conditions, many health care professionals have struggled with burnout, exhaustion and moral distress. “Much health care provider content on social media seeks to expose the difficulties of the work,” Gary added. “TikTok and Instagram reels have shown health care providers crying after losing a patient or exhausted after a night shift in the emergency department.”
A study conducted in Beijing, China and published last year found that TikTok is the world’s most rapidly growing video application, amassing 1.6 billion users in 2021. “More and more patients are searching for information on genitourinary cancers via TikTok,” the study’s authors wrote in Frontiers in Oncology, referring to cancers of the urinary tracts and male reproductive organs. Among the 61 sample videos examined by the researchers, health care practitioners contributed the content in 29, or 47 percent, of them. Yet, 22 posts, 36 percent, were misinformative, mostly due to outdated information.
More than half of the videos offered good content on disease symptoms and examinations. The authors concluded that “most videos on genitourinary cancers on TikTok are of poor to medium quality and reliability. However, videos posted by media agencies enjoyed great public attention and interaction. Medical practitioners could improve the video quality by cooperating with media agencies and avoiding unexplained terminologies.”
When health care providers post on social media, they must bear in mind that they have legal and ethical duties to their patients, profession and society, said Elizabeth Levy, founder and director of Physicians for Justice in Irvine, Calif., a nonprofit network of volunteer physicians partnering with public interest lawyers to address the social determinants of health.
“Providers are also responsible for understanding the mechanics of their posts,” such as who can see these messages and how long they stay up, Levy said. As a starting point for figuring what’s acceptable, providers could look at social media guidelines put out by their professional associations. Even beyond that, though, they must exercise prudent judgment. “As social media continues to evolve, providers will also need to stay updated with the changing risks and benefits of participation.”
Patients often research their providers online, so finding them on social media can help inform about values and approaches to care, said M. Sara Rosenthal, a professor and founding director of the program for bioethics and chair of the hospital ethics committee at the University of Kentucky College of Medicine.
Health care providers’ posts on social media also could promote patient education. They can advance informed consent and help patients navigate the risks and benefits of various treatments or preventive options. However, providers could violate ethical principles if they espouse “harmful, risky or questionable therapies or medical advice that is contrary to clinical practice guidelines or accepted standards of care,” Rosenthal said.
Inappropriate self-disclosure also can affect a provider’s reputation, said Kelly Michelson, a professor of pediatrics and director of the Center for Bioethics and Medical Humanities at Northwestern University’s Feinberg School of Medicine. A clinician’s obligations to professionalism extend beyond those moments when they are directly taking care of their patients, she said. “Many experts recommend against clinicians ‘friending’ patients or the families on social media because it blurs the patient-clinician boundary.”
Meanwhile, clinicians need to adhere closely to confidentiality. In sharing a patient’s case online for educational purposes, safeguarding identity becomes paramount. Removing names and changing minor details is insufficient, Michelson said.
“The patient-clinician relationship is sacred, and it can only be effective if patients have 100 percent confidence that all that happens with their clinician is kept in the strictest of confidence,” she said, adding that health care providers also should avoid obtaining information about their patients from social media because it can lead to bias and risk jeopardizing objectivity.
Academic clinicians can use social media as a recruitment tool to expand the pool of research participants for their studies, Michelson said. Because the majority of clinical research is conducted at academic medical centers, large segments of the population are excluded. “This affects the quality of the data and knowledge we gain from research,” she said.
Don S. Dizon, a professor of medicine and surgery at the Warren Alpert Medical School of Brown University in Providence, Rhode Island, uses LinkedIn and Doximity, as well as Twitter, Instagram, TikTok, Facebook, and most recently, YouTube and Post. He’s on Twitter nearly every day, where he interacts with the oncology community and his medical colleagues.
Also, he said, “I really like Instagram. It’s where you will see a hybrid of who I am professionally and personally. I’ve become comfortable sharing both up to a limit, but where else can I combine my appreciation of clothes with my professional life?” On that site, he’s seen sporting shirts with polka dots or stripes and an occasional bow-tie. He also posts photos of his cats.
Don S. Dizon, a professor of medicine and surgery at Brown, started using TikTok several years ago, telling medical stories in short-form videos.
Don S. Dizon
Dizon started using TikTok several years ago, telling medical stories in short-form videos. He may talk about an inspirational patient, his views on end-of-life care and death, or memories of people who have passed. But he is careful not to divulge any details that would identify anyone.
Recently, some people have become his patients after viewing his content on social media or on the Internet in general, which he clearly states isn’t a forum for medical advice. “In both situations, they are so much more relaxed when we meet, because it’s as if they have a sense of who I am as a person,” Dizon said. “I think that has helped so much in talking through a cancer diagnosis and a treatment plan, and yes, even discussions about prognosis.”
He also posts about equity and diversity. “I have found myself more likely to repost or react to issues that are inherently political, including racism, homophobia, transphobia and lack-of-access issues, because medicine is not isolated from society, and I truly believe that medicine is a social justice issue,” said Dizon, who is vice chair of diversity, equity, inclusion and professional integrity at the SWOG Cancer Research Network.
Through it all, Dizon likes “to break through the notion of doctor as infallible and all-knowing, the doctor as deity,” he said. “Humanizing what I do, especially in oncology, is something that challenges me on social media, and I appreciate the opportunities to do it on TikTok.”
Could this habit related to eating slow down rates of aging?
Last Thursday, scientists at Columbia University published a new study finding that cutting down on calories could lead to longer, healthier lives. In the phase 2 trial, 220 healthy people without obesity dropped their calories significantly and, at least according to one test, their rate of biological aging slowed by 2 to 3 percent in over a couple of years. Small though that may seem, the researchers estimate that it would translate into a decline of about 10 percent in the risk of death as people get older. That's basically the same as quitting smoking.
Previous research has shown that restricting calories results in longer lives for mice, worms and flies. This research is unique because it applies those findings to people. It was published in Nature Aging.
But what did the researchers actually show? Why did two other tests indicate that the biological age of the research participants didn't budge? Does the new paper point to anything people should be doing for more years of healthy living? Spoiler alert: Maybe, but don't try anything before talking with a medical expert about it. I had the chance to chat with someone with inside knowledge of the research -- Dr. Evan Hadley, director of the National Institute of Aging's Division of Geriatrics and Clinical Gerontology, which funded the study. Dr. Hadley describes how the research participants went about reducing their calories, as well as the risks and benefits involved. He also explains the "aging clock" used to measure the benefits.
Evan Hadley, Director of the Division of Geriatrics and Clinical Gerontology at the National Institute of Aging
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