Today on Health in 2 Point 00, Jess and I report from a hedgehog cafe in Tokyo. In this episode, Jess asks me about Bright Health’s $200 million raise and the significance of Amazon’s new EMR product. We also talk about Health 2.0 Asia-Japan, which is happening right now (December 4-5) in Tokyo, showing us the health care market outside of the U.S. Look forward to hearing from some great speakers at the conference, including John Bass from Hashed Health on blockchain, Fred Trotter on security, David Ewing Duncan on the new wellness and personalized medicine, and Adam Pellegrini from Fitbit. And, of course, Jess will be interviewing just about everyone—including a hedgehog—about innovation for WTF Health —Matthew Holt
Any DuRoss is one of the more charming and remarkable characters in the health tech world. She lead the campaign for Proposition 71 in 2004 which funded and established the California Institute for Regenerative Medicine. Later on she was a key player at early genetics company Navigenics, and more recently after time at GE Ventures she founded Vineti, which today raised $33.4m in Series B funding. Vineti is a new kind of pharma supply chain company helping deliver gene therapy, but what does that mean? I asked Amy and she told me!
Human beings are big data. We aren’t just 175 pounds of meat and bone. We aren’t just piles of hydrogen and carbon and oxygen. What makes us all different is how it’s all organized and that is information.
We can no longer treat people based on simple numbers like weight, pulse, blood pressure, and temperature. What makes us different is much more complicated than that.
We’ve known for decades that we are all slightly different genetically, but now we can increasingly see those differences. The Hippocratic oath will require doctors to take this genetic variability into account.
I’m not saying there isn’t a place for hands-on medicine, empathy, psychology and moral support. But the personalized handling of each patient is becoming much more complicated. The more data we can gather, the more each individual is different from others.
In our genome, we have approximately 3 billion base pairs in each of our trillions of cells. We have more than 25,000 genes in that genome, sometimes called the exome. Each gene contains instructions on how to make a useful protein. And then there are long stretches of our genomes that regulate those protein-manufacturing genes.
In the early days, some researchers called this “junk DNA” because they didn’t know what it did. But this was foolish because why would evolution conserve these DNA sequences between genes if they did nothing? Now we know they too do things that make us unique.
Genetic testing is a powerful tool. Two years ago, with the help of my colleagues, it was this tool that helped us identify a new disease. The disease, called Ogden Syndrome, caused the death of a four-month old child named Max. But the rules and regulations for genetic testing in the US, laid down in the CLIA (Clinical Laboratory Improvement Amendments), meant I could not share the results of the family’s genetic tests with them.
Since that time, I have advocated performing all genetic testing involving humans such that results can be returned to research participants. This I believe should extend beyond research, and some private companies, like 23andMe, are helping to do just that.
For as little as US $99, people around the world can send a sample of their saliva to 23andMe to get their DNA sequenced. Their Personal Genome Service (PGS) analyses parts of a person’s genome. This data is then compared with related scientific data and 23andMe’s own database of hundreds of thousands of individuals to spot genetic markers, which the company claims “reports on 240 health condition and traits”.
Earlier this month, however, as I had feared, the US Food and Drug Administration (FDA) has ordered 23andMe to stop marketing their service. In a warning letter, FDA said: “23andMe must immediately discontinue marketing the PGS until such time as it receives FDA marketing authorisation for the device.” By calling PGS “a device”, the FDA fears that people may self-medicate based on results they receive from 23andMe.
Somehow the US and UK governments find it acceptable to store massive amounts of data about their own citizens and that of the rest of the world. They are happy spending billions on such mass surveillance. But if the same people want to spend their own money to advance genomic medicine and possibly improve their own health in the process, they want to stop them.
As we grapple with provider shortages, the surge in chronic illness and the quality to price (QPR as they say in the wine business) challenge in US healthcare delivery, it’s hard to imagine a future that does not include some sort of guideline or algorithm-driven care. As providers take on more financial risk, one common strategy involves team-based care, and the attendant increase in decision-making and care delivery by non-physician clinicians. If the je ne sais quoi feature of a quintessentially great doctor is clinical judgment and instinct, one of the challenges of this transition to team-based care is how to harness that trait and use it efficiently.
Care decisions that are unassailable at a population level (e.g., women should have regular, routine PAP smears or smoking is bad for your health) or are algorithmic in nature (e.g., titration of treatment for uncomplicated hypertension or therapy for mild to moderate teenage acne) can all be effectively reduced to guidelines. This, in turn, allows a physician to delegate certain therapeutic decisions to non-physician providers while maintaining a high degree of care quality. It is also thought that this type of uniformity of care delivery will improve the QPR too, by decreasing variability.
How do we come up with guidelines? Typically they are based on large-scale, randomized, controlled clinical studies. As is nicely articulated in a recent JAMA opinion piece by Drs. Jeffrey Goldberg and Alfred Buxton (JAMA, June 26, 2013—Vol 309, No. 24, pg 2559), guidelines are formulated based on the inclusion criteria for these trials. This process gives us comfort that guidelines are based on rigorous science — and that is a good thing. The challenge arises when we realize that individuals do not reflect populations exactly. Clinical research is much more complex than wet lab work because people are complex and indeed unique. Every clinician has had the experience of prescribing a therapy to a patient who fit guideline criteria exactly and having the opposite outcome of what the guideline predicts.
While we’re busy debating the pros and cons of clinical genome sequencing and tossing around buzzwords like “personalized” and “translational” medicine, I’ve recently caught some health care providers ignoring the archaic skills of communication and common sense. So while we await genome analysis apps on our smartphones and DNA sequence annotators in our doctors’ offices, here are 3 suggestions on how to provide personalized medicine right now:
1. Read the patient’s chart (paper or digital)
2. Listen to the patient
3. Look at the patient
Disclaimer: Today’s blog is anecdotal and non-scientific, but may identify a trend.
My Missing Thyroid
A few weeks ago, I had a long-overdue check-up, with a nurse practitioner. It was my first visit to the practice, which had provided excellent urgent care.
On the medical history form, I described my circa 1993 thyroid cancer in intimate histological detail: papillary in left lobe, follicular in the right.
The NP spent an impressive 45 minutes asking questions and listening to me – or so I thought. During the brief physical exam, I told her all about my thyroid cancer, my daily Synthroid dose, and even brought her hand to my throat, having noticed that dentists get very excited at my lack of a thyroid gland. No thyroid tests needed, said I. My endocrinologist had recently done them.
So I was surprised when, early the next morning, a Saturday, my cell phone quacked.
This past week, Google had its annual developers conference, Google I/O. One of the more provocative talks, called “The End of Search as We Know It,” was by Amit Singhal, who is in charge of search for Google.
The vision, as described by Amit, is that instead of typing words into a box on a website or mobile app, we will have conversations with Google, enabling a much more personalized, refined experience. The holy grail, of course, is that Google analytics become both predictive and prescriptive, serving you content that is just right for you and anticipates your needs.
It seems there is a race on now to achieve this vision. One could argue that Amazon, Apple, Facebook, Pandora and others are all in the same mode. Best I can tell, the promise these companies are floating to advertisers is that their ads will be served up to that focused slice of the population that will find their product relevant in the moment.
If you apply this thinking to healthcare, several controversies/topics come to the fore.
Is Google competing with IBM’s Watson? Undoubtedly yes. On the other hand, I’m guessing Google is disenchanted with the consumer health space after the demise of its personal health record (PHR). And IBM seems to be focused on clinician decision support. So early in the game, with respect to healthcare anyway, maybe there is not much competition. The path for clinician decision support is clear and the market obvious, whereas the path and market for consumer health decision support are blurry.
The 30,000 member American Society of Clinical Oncology is the world’s leading group of cancer physicians. ASCO is dedicated to curing cancer, supporting research, quality care, reducing treatment disparities and a heightened national focus on value. This month they released their annual Report on Progress Against Cancer, which highlights research, drug development and cancer care innovations. This hundred-page document is important reading for anyone who wants to be up-to-date regarding cancer care.
Cancer related deaths in the United States are dropping, but still totaled 577,000 in 2012. While world cancer research funding is rising, in the USA it continues to decrease, with the purchasing power of the largest funding source, the National Cancer Institute, having fallen 20% in the last decade, and a further 8% cut slated for January 1, 2013. Development is dependent on government and private funding, as well as the willingness of more than 25,000 patients a year who volunteer to be involved in cancer trials. All these critical supports are threatened. The Federal Clinical Trials Cooperative of the National Cancer Institute (FCLC, NCI) supports research at 3100 institutions in the USA.
The report discusses the many types of cancer which continue to be naturally resistant to cancer treatment, particularly chemotherapy. In some cases, drugs do not penetrate a part of the body, such as the brain, in other cases even when they reach the tumor, they are not effective. In such cancers the genetic code of the cancer cells has mutated (changed) such that the particular drug does not kill the cancer. In 2012, there was increased interest in attacking each cancer cell at multiple targets either by using a single drug, which attacks in several different ways, or multiple drugs at the same time. This concept improved cancer killing in GIST, colon cancer, certain lymphomas (ALCL) and medullary thyroid cancer. In addition, unique targeted compounds, such as “tyrosine kinase inhibitors,” show increasing benefit in leukemia, sarcoma and breast cancer.
At 69 years old, he is a quiet man who was often told in his younger days that he resembled Muhammad Ali. He immigrated in his twenties to Canada from the small Caribbean nation of Antigua to look for opportunities beyond sugar cane and the tourism trade.
My father became a chemical technician for well-known oil refineries, while staying true to his real passion in life – playing organ music. Every Sunday, as he has since I can first remember, he plays the largest church organ in Sarnia, near Lake Huron, where he lives with my mother.
Like many men of his generation, he has always been wary for the medical system. For decades he avoided the test, known as PSA, that screens for prostate cancer. In September of this year, driven by pain he could no longer ignore, he went to his doctor who discovered a rock-hard prostate gland. The diagnosis, stage III prostate cancer, means that the cancer has already begun to spread, but is still potentially treatable.
Now retired, his long hours practicing the organ are punctuated with doctor visits to receive Lupron hormone therapy. The good news? The therapy is working. For now.
We don’t know what lies ahead. The first round of Lupron therapy is often effective, but a significant number of patients later develop a resistance to the drug.
The battle against my father’s cancer has only just begun.
This is where Big Data in healthcare can become a true lifesaver. Typically, in medicine, we know only what works for the majority of patients, not what will work for an individual. However, with enough data from enough people – we are talking hundreds of thousands, and sometimes, even millions of patients – we can apply analytics to build predictive models to discover which interventions will work. For the last twelve years, it has been my job to make that happen.
As CEO and founder of GNS Healthcare, I oversee a team of mathematicians, biologists, and data scientists as they crunch and decode healthcare data to unlock the mysteries of what treatment will work for specific patients.
My father’s cancer has given these efforts a new urgency and has raised a new question: Can I use Big Data to save my father’s life?
Previously, I wrote about some wondrous developments that are taking place in medical science. Implantable or attachable devices already exist — or soon will exist — that can monitor the conditions of diabetics, asthmatics, heart patients and patients with numerous other chronic conditions. These devices will allow patients and doctors to modify therapeutic regimes and tailor treatments to individual needs and responses. Genetic testing is reaching the point where patients can be directed to take certain drugs or avoid other drugs, based solely on the patient’s own genes.
Almost all HIV treatment these days involves therapy cocktails tailored for each individual patient. The FDA has approved a breast cancer drug only for women with a particular genetic makeup. Patients are being advised to steer clear of an ADHD drug and certain blood thinners if they have particular genetic variations.
We are entering the age of personalized medicine, where the therapy that’s best for you will be based on your physiology and genetic makeup — and may not be right for any other patient.
Yet standing in the way of this boundless potential is an Obama administration whose entire approach to health reform revolves around the idea that patients are not unique and that bureaucrats can develop standardized treatments that will apply to almost everybody with a given condition. When former White House health adviser Ezekiel Emanuel told CNN recently that “personalized medicine is a myth,” he was fully reflecting the worldview of the authors of health reform.