Bad Actors Getting Your Health Data Is the FBI’s Latest Worry
In February 2015, the health insurer Anthem revealed that criminal hackers had gained access to the company's servers, exposing the personal information of nearly 79 million patients. It's the largest known healthcare breach in history.
FBI agents worry that the vast amounts of healthcare data being generated for precision medicine efforts could leave the U.S. vulnerable to cyber and biological attacks.
That year, the data of millions more would be compromised in one cyberattack after another on American insurers and other healthcare organizations. In fact, for the past several years, the number of reported data breaches has increased each year, from 199 in 2010 to 344 in 2017, according to a September 2018 analysis in the Journal of the American Medical Association.
The FBI's Edward You sees this as a worrying trend. He says hackers aren't just interested in your social security or credit card number. They're increasingly interested in stealing your medical information. Hackers can currently use this information to make fake identities, file fraudulent insurance claims, and order and sell expensive drugs and medical equipment. But beyond that, a new kind of cybersecurity threat is around the corner.
Mr. You and others worry that the vast amounts of healthcare data being generated for precision medicine efforts could leave the U.S. vulnerable to cyber and biological attacks. In the wrong hands, this data could be used to exploit or extort an individual, discriminate against certain groups of people, make targeted bioweapons, or give another country an economic advantage.
Precision medicine, of course, is the idea that medical treatments can be tailored to individuals based on their genetics, environment, lifestyle or other traits. But to do that requires collecting and analyzing huge quantities of health data from diverse populations. One research effort, called All of Us, launched by the U.S. National Institutes of Health last year, aims to collect genomic and other healthcare data from one million participants with the goal of advancing personalized medical care.
Other initiatives are underway by academic institutions and healthcare organizations. Electronic medical records, genetic tests, wearable health trackers, mobile apps, and social media are all sources of valuable healthcare data that a bad actor could potentially use to learn more about an individual or group of people.
"When you aggregate all of that data together, that becomes a very powerful profile of who you are," Mr. You says.
A supervisory special agent in the biological countermeasures unit within the FBI's weapons of mass destruction directorate, it's Mr. You's job to imagine worst-case bioterror scenarios and figure out how to prevent and prepare for them.
That used to mean focusing on threats like anthrax, Ebola, and smallpox—pathogens that could be used to intentionally infect people—"basically the dangerous bugs," as he puts it. In recent years, advances in gene editing and synthetic biology have given rise to fears that rogue, or even well-intentioned, scientists could create a virulent virus that's intentionally, or unintentionally, released outside the lab.
"If a foreign source, especially a criminal one, has your biological information, then they might have some particular insights into what your future medical needs might be and exploit that."
While Mr. You is still tracking those threats, he's been traveling around the country talking to scientists, lawyers, software engineers, cyber security professionals, government officials and CEOs about new security threats—those posed by genetic and other biological data.
Emerging threats
Mr. You says one possible situation he can imagine is the potential for nefarious actors to use an individual's sensitive medical information to extort or blackmail that person.
"If a foreign source, especially a criminal one, has your biological information, then they might have some particular insights into what your future medical needs might be and exploit that," he says. For instance, "what happens if you have a singular medical condition and an outside entity says they have a treatment for your condition?" You could get talked into paying a huge sum of money for a treatment that ends up being bogus.
Or what if hackers got a hold of a politician or high-profile CEO's health records? Say that person had a disease-causing genetic mutation that could affect their ability to carry out their job in the future and hackers threatened to expose that information. These scenarios may seem far-fetched, but Mr. You thinks they're becoming increasingly plausible.
On a wider scale, Kavita Berger, a scientist at Gryphon Scientific, a Washington, D.C.-area life sciences consulting firm, worries that data from different populations could be used to discriminate against certain groups of people, like minorities and immigrants.
For instance, the advocacy group Human Rights Watch in 2017 flagged a concerning trend in China's Xinjiang territory, a region with a history of government repression. Police there had purchased 12 DNA sequencers and were collecting and cataloging DNA samples from people to build a national database.
"The concern is that this particular province has a huge population of the Muslim minority in China," Ms. Berger says. "Now they have a really huge database of genetic sequences. You have to ask, why does a police station need 12 next-generation sequencers?"
Also alarming is the potential that large amounts of data from different groups of people could lead to customized bioweapons if that data ends up in the wrong hands.
Eleonore Pauwels, a research fellow on emerging cybertechnologies at United Nations University's Centre for Policy Research, says new insights gained from genomic and other data will give scientists a better understanding of how diseases occur and why certain people are more susceptible to certain diseases.
"As you get more and more knowledge about the genomic picture and how the microbiome and the immune system of different populations function, you could get a much deeper understanding about how you could target different populations for treatment but also how you could eventually target them with different forms of bioagents," Ms. Pauwels says.
Economic competitiveness
Another reason hackers might want to gain access to large genomic and other healthcare datasets is to give their country a leg up economically. Many large cyber-attacks on U.S. healthcare organizations have been tied to Chinese hacking groups.
"This is a biological space race and we just haven't woken up to the fact that we're in this race."
"It's becoming clear that China is increasingly interested in getting access to massive data sets that come from different countries," Ms. Pauwels says.
A year after U.S. President Barack Obama conceived of the Precision Medicine Initiative in 2015—later renamed All of Us—China followed suit, announcing the launch of a 15-year, $9 billion precision health effort aimed at turning China into a global leader in genomics.
Chinese genomics companies, too, are expanding their reach outside of Asia. One company, WuXi NextCODE, which has offices in Shanghai, Reykjavik, and Cambridge, Massachusetts, has built an extensive library of genomes from the U.S., China and Iceland, and is now setting its sights on Ireland.
Another Chinese company, BGI, has partnered with Children's Hospital of Philadelphia and Sinai Health System in Toronto, and also formed a collaboration with the Smithsonian Institute to sequence all species on the planet. BGI has built its own advanced genomic sequencing machines to compete with U.S.-based Illumina.
Mr. You says having access to all this data could lead to major breakthroughs in healthcare, such as new blockbuster drugs. "Whoever has the largest, most diverse dataset is truly going to win the day and come up with something very profitable," he says.
Some direct-to-consumer genetic testing companies with offices in the U.S., like Dante Labs, also use BGI to process customers' DNA.
Experts worry that China could race ahead the U.S. in precision medicine because of Chinese laws governing data sharing. Currently, China prohibits the exportation of genetic data without explicit permission from the government. Mr. You says this creates an asymmetry in data sharing between the U.S. and China.
"This is a biological space race and we just haven't woken up to the fact that we're in this race," he said in January at an American Society for Microbiology conference in Washington, D.C. "We don't have access to their data. There is absolutely no reciprocity."
Protecting your data
While Mr. You has been stressing the importance of data security to anyone who will listen, the National Academies of Sciences, Engineering, and Medicine, which makes scientific and policy recommendations on issues of national importance, has commissioned a study on "safeguarding the bioeconomy."
In the meantime, Ms. Berger says organizations that deal with people's health data should assess their security risks and identify potential vulnerabilities in their systems.
As for what individuals can do to protect themselves, she urges people to think about the different ways they're sharing healthcare data—such as via mobile health apps and wearables.
"Ask yourself, what's the benefit of sharing this? What are the potential consequences of sharing this?" she says.
Mr. You also cautions people to think twice before taking consumer DNA tests. They may seem harmless, he says, but at the end of the day, most people don't know where their genetic information is going. "If your genetic sequence is taken, once it's gone, it's gone. There's nothing you can do about it."
Should You Bank Your Kid’s Teeth for Stem Cells?
When Karen Davis attended a presentation at a dental conference in 2013, she unexpectedly discovered a service that could help her daughter, Madeline: storing stem cells derived from her teeth that potentially could be used in the future to treat her Crohn's disease.
"Even though this isn't a viable option today, I know how rapidly things can change."
Throughout high school, Madeline suffered from the painful autoimmune disorder, which wreaks havoc on the gastrointestinal system and can lead to life-threatening complications.
"I leave no stone unturned when it comes to medical care and this resonated with me," says Davis, a Dallas-based dental hygienist who was encouraged by advances in stem cell research. Later that year, when Madeline got her wisdom teeth extracted, Davis shipped them off to the Store-A-Tooth company in Massachusetts, where they will be kept frozen until needed. "Even though this isn't a viable option today, I know how rapidly things can change," says Davis. "To me, this was a worthwhile investment—I didn't want to miss out on an opportunity that would provide a pathway to a cure."
Karen Davis pictured with her daughter Madeline.
(Courtesy of Karen Davis)
The process itself was straightforward. Madeline's newly extracted wisdom teeth--baby teeth can be saved, too—were bathed in a special solution, loaded into a Styrofoam container lined with cold packs and sent to the stem cell company. There, a team harvested the dental stem cells from the pulp, then grew them in culture and cryogenically preserved them. Store-A-Tooth charges $1500-1749 for tooth collection and $120 per year for storage, while other dental pulp stem cell tissue banks cost $500-$600 upfront and in the $120 range annually for storage.
The rationale here is that if you missed out on banking your baby's umbilical cord blood, this gives you another chance to harvest their stem cells. "If their child later develops an illness that could be managed or even cured with stem cell therapy, this is an insurance policy," says Amr Moursi, DDS, PhD, chair of the department of pediatric dentistry at New York University College of Dentistry.
But is there a genuine potential here for some effective treatments in the relatively near future—or is this just another trendy fad? Scientific opinion is decidedly mixed. Stem cells have been heralded as the next frontier in medicine because of their versatility: with a little chemical coaxing, they can be transformed into different cell types, such as heart, blood or brain cells, to create tissue that can mend damaged body parts. Because they're taken from your own body, there's little chance of rejection, which means patients don't have to take strong antirejection drugs that can have all sorts of unpleasant side effects for the rest of their lives.
However, while stem cells are immature cells found in different tissues, ranging from abdominal fat to bone marrow, there is a vast difference between the stem cells found in cord blood and in teeth. Cord blood, which is culled from the umbilical cord when a baby is born, contains what are called hematopoietic stem cells (HSCs), which can mature into other blood cells. These type of stem cells have already been approved by the U.S. Food and Drug Administration to treat patients—especially children--with blood cancers, such as leukemias and lymphomas, and certain blood disorders like sickle cell anemia.
In contrast, stem cells in teeth are called mesenchymal stem cells (MSCs), which are found in dental pulp, the tissue in the center of the tooth that's filled with nerves and blood vessels. MSCs are adult stem cells normally found in the bone marrow that can transform into bone, fat, and cartilage cells, and also aid in the formation of blood stem cells.
"Right now we just don't have rigorous evidence that they can be used in that fashion and have real benefit."
Small studies on lab animals suggest that MSCs secrete growth factors—hormonal steroids or proteins—that can nurture ailing cells, act as powerful anti-inflammatory agents that could tame autoimmune disorders like the one that plagues Karen Davis's daughter, and may even generate new nerve and muscle tissue. Preliminary research suggests they potentially could treat medical conditions as varied as heart disease, spinal cord injury and type 1 diabetes by generating new cells, which can replace damaged or dead cells.
But this is all very early research and there's a vast difference between how cells behave in the tightly controlled environment of a lab versus the real world in a diverse population of human patients. "Right now we just don't have rigorous evidence that they can be used in that fashion and have real benefit," says Pamela G. Robey, PhD, chief of the skeletal biology section at the National Institute of Dental and Craniofacial Research at the National Institutes of Health.
Robey should know—she headed the research team that discovered stem cells in human baby teeth and in wisdom teeth more than fifteen years ago. She believes prospects are better using these stem cells for tooth repair: research suggests they may be able to fix cracked teeth, repair bone defects caused by gum disease, or in root canal therapy, where they can be used to replace infected tissue with regenerated healthy pulp.
In the meantime, though, there are no clinical applications for MSCs. "These tooth banking companies aren't doing their own research," says Leigh Turner, a bioethicist at the University of Minnesota who monitors stem cell clinics. "They cobble together reports of early research in humans or from animal studies in an effort to provide a narrative to make it seem like it is evidence based."
Still, in all fairness, tooth banking companies aren't making the kind of extravagant claims made by stem cell clinics, which operate in a gray area of the law and purport to treat everything from chronic lung disease to Alzheimer's. "We don't know when therapies will be available using these cells because the pace of research is hard to predict," says Peter Verlander, PhD, a molecular geneticist and chief scientific officer of Provia Laboratories, the parent company of Store-A-Tooth. "But for parents who regretted not banking their child's cord blood, especially if they later develop a disease like diabetes, this is another opportunity."
But the jury is still out if this is truly a good investment. Moursi, a national spokesperson for the American Academy of Pediatric Dentistry who fields queries about this practice from a dozen or so families a year, concludes: "If you could afford it, and know the risks, benefits and current limitations, then it is something to consider."
The Death Predictor: A Helpful New Tool or an Ethical Morass?
Whenever Eric Karl Oermann has to tell a patient about a terrible prognosis, their first question is always: "how long do I have?" Oermann would like to offer a precise answer, to provide some certainty and help guide treatment. But although he's one of the country's foremost experts in medical artificial intelligence, Oermann is still dependent on a computer algorithm that's often wrong.
Doctors are notoriously terrible at guessing how long their patients will live.
Artificial intelligence, now often called deep learning or neural networks, has radically transformed language and image processing. It's allowed computers to play chess better than the world's grand masters and outwit the best Jeopardy players. But it still can't precisely tell a doctor how long a patient has left – or how to help that person live longer.
Someday, researchers predict, computers will be able to watch a video of a patient to determine their health status. Doctors will no longer have to spend hours inputting data into medical records. And computers will do a better job than specialists at identifying tiny tumors, impending crises, and, yes, figuring out how long the patient has to live. Oermann, a neurosurgeon at Mount Sinai, says all that technology will allow doctors to spend more time doing what they do best: talking with their patients. "I want to see more deep learning and computers in a clinical setting," he says, "so there can be more human interaction." But those days are still at least three to five years off, Oermann and other researchers say.
Doctors are notoriously terrible at guessing how long their patients will live, says Nigam Shah, an associate professor at Stanford University and assistant director of the school's Center for Biomedical Informatics Research. Doctors don't want to believe that their patient – whom they've come to like – will die. "Doctors over-estimate survival many-fold," Shah says. "How do you go into work, in say, oncology, and not be delusionally optimistic? You have to be."
But patients near the end of life will get better treatment – and even live longer – if they are overseen by hospice or palliative care, research shows. So, instead of relying on human bias to select those whose lives are nearing their end, Shah and his colleagues showed that they could use a deep learning algorithm based on medical records to flag incoming patients with a life expectancy of three months to a year. They use that data to indicate who might need palliative care. Then, the palliative care team can reach out to treating physicians proactively, instead of relying on their referrals or taking the time to read extensive medical charts.
But, although the system works well, Shah isn't yet sure if such indicators actually get the appropriate patients into palliative care. He's recently partnered with a palliative care doctor to run a gold-standard clinical trial to test whether patients who are flagged by this algorithm are indeed a better match for palliative care.
"What is effective from a health system perspective might not be effective from a treating physician's perspective and might not be effective from the patient's perspective," Shah notes. "I don't have a good way to guess everybody's reaction without actually studying it." Whether palliative care is appropriate, for instance, depends on more than just the patient's health status. "If the patient's not ready, the family's not ready and the doctor's not ready, then you're just banging your head against the wall," Shah says. "Given limited capacity, it's a waste of resources" to put that person in palliative care.
The algorithm isn't perfect, but "on balance, it leads to better decisions more often."
Alexander Smith and Sei Lee, both palliative care doctors, work together at the University of California, San Francisco, to develop predictions for patients who come to the hospital with a complicated prognosis or a history of decline. Their algorithm, they say, helps decide if this patient's problems – which might include diabetes, heart disease, a slow-growing cancer, and memory issues – make them eligible for hospice. The algorithm isn't perfect, they both agree, but "on balance, it leads to better decisions more often," Smith says.
Bethany Percha, an assistant professor at Mount Sinai, says that an algorithm may tell doctors that their patient is trending downward, but it doesn't do anything to change that trajectory. "Even if you can predict something, what can you do about it?" Algorithms may be able to offer treatment suggestions – but not what specific actions will alter a patient's future, says Percha, also the chief technology officer of Precise Health Enterprise, a product development group within Mount Sinai. And the algorithms remain challenging to develop. Electronic medical records may be great at her hospital, but if the patient dies at a different one, her system won't know. If she wants to be certain a patient has died, she has to merge social security records of death with her system's medical records – a time-consuming and cumbersome process.
An algorithm that learns from biased data will be biased, Shah says. Patients who are poor or African American historically have had worse health outcomes. If researchers train an algorithm on data that includes those biases, they get baked into the algorithms, which can then lead to a self-fulfilling prophesy. Smith and Lee say they've taken race out of their algorithms to avoid this bias.
Age is even trickier. There's no question that someone's risk of illness and death goes up with age. But an 85-year-old who breaks a hip running a marathon should probably be treated very differently than an 85-year-old who breaks a hip trying to get out of a chair in a dementia care unit. That's why the doctor can never be taken out of the equation, Shah says. Human judgment will always be required in medical care and an algorithm should never be followed blindly, he says.
Experts say that the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully.
Researchers are also concerned that their algorithms will be used to ration care, or that insurance companies will use their data to justify a rate increase. If an algorithm predicts a patient is going to end up back in the hospital soon, "who's benefitting from knowing a patient is going to be readmitted? Probably the insurance company," Percha says.
Still, Percha and others say, the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully. "These are new and exciting tools that have a lot of potential uses. We need to be conscious about how to use them going forward, but it doesn't mean we shouldn't go down this road," she says. "I think the potential benefits outweigh the risks, especially because we've barely scratched the surface of what big data can do right now."