2015 Health-Tech Progress Report (Part I)
Technology likes to show off. It's easy to see when the latest innovation has arrived because when technology gets better, we notice. In education-tech we had the arrival of the SMART Board and interactive learning, government-tech has made known its ability of very advanced surveillance, and every time you see a stunning new Pixar movie you're beholding entertainment-tech at its current best.
But how far have we come in the sector of health-tech? Think about the last time you visited your doctor. It probably looked pretty similar to the way it looked back when you were excited to get that sick day home from school. You signed in on a clipboard chained to the front desk, filled out your brick of paperwork on another clipboard, and followed the nurse down the hall to the room where she hung the clipboard on the door. I imagine the world was lawless chaos before the clipboard was invented, but I digress.
So aside from a few extra computers and iPads at your doctor’s office, where are we seeing technology affect positive change in health care? The ones I’m excited about are a little behind the scenes. This week let's tackle one of them.
Big Data and personalized medicine
Everyone knows the marketing world loves to collect data about us. They love to know our likes and our patterns. It helps them sell the right stuff to the right people. By drawing from a huge pool of data, these marketing people are able to make very informed decisions. This is Big Data in the commercial world.
Big Data in healthcare is trying to benefit your health with that same kind of insight—but with less pop-up ads. The problem for so long though was the data was on that clipboard and needed to be turned into digital information. In the past 6 years, a sudden widespread adoption of the electronic medical record (EMR) has provided enough digital medical data to benefit from data analysis. It went from data to Big Data.
It’s easy to see how evidence-based medicine is immediately bolstered by Big Data: the pool of evidence instantly becomes so much bigger. Doctors now can electronically compare patients’ conditions to similar patients and their respective health outcomes. This leads to better diagnoses and better treatment plans because you’re working with better intel. Your doctor’s perspective is no longer limited to what they’re most familiar with. Medical decisions can be more tailored and less standardized. This is the gateway for personalized medicine.
Personalized medicine is still taking shape but has the capacity to really change the game of healthcare. A key tenant of personalized medicine is that the genetic information inside each of us maps out the diseases we are most susceptible to. Therefore researchers have begun recording the specific genes of their patients, aka “sequencing their genomes.” Combine this genetic info with a personal narrative (diet, behaviors, health history, traumas) and a map legend begins to be formed.
What exactly do all these patients with this very specific type of cancer have in common? What drugs do they respond best to? Big Data could answer this.
But is data analysis really the highest level of general development for health-tech? Is this really state-of-the-art? You’d be surprised. These are huge amounts of data we’re talking about.
Petabytes.
The Washington Post estimates that the current amount of human genomic data in existence is around 25 petabytes. That’s 2,500 times more data than every piece of text in the Library of Congress. Within the next decade it’s estimated that genomic data will take up more data space than every video currently stored on YouTube. This is all raw data that has to be extracted, curated, compressed, stored, and ultimately made sense of. Only recently has the technology—the algorithms, the processors, the bandwidth—reached a benchmark that could carry such a weight.
It ain't cheap either. But innovation has dramatically lowered the cost. During his battle with pancreatic cancer, Steve Jobs had the genome of his tumor sequenced multiple times to help decide which drug therapy to use. According to the New York Times, each sequence cost him $100,000. A decade earlier, in 2001, it would have cost $100 million per sequence. Now, just 4 years after his death, it costs barely over $1000.
That is a remarkable decrease in cost resulting purely from an improvement in technology.
Not only is DNA sequencing more efficient and cost-effective than ever before, but it's also becoming more share-friendly. Fast Company reports that just last month the FDA released a website, precision.fda.org, that makes it easier for researchers to explore the existing community-based genomic information. This DNA library makes it easy for scientists to collaborate with each other, share genomes they’ve sequenced, and build off of each other’s discoveries. This socialization of genomic research, combined with the power of Big Data is important. Some experts believe it's the way we're going to cure the big diseases.
That'll do it for this week. Watch your feed. Next up we're talking sensors. Your Fitbit is just the beginning.