My barista, while clovering a cup of Komodo, said he doesn’t want to get a flu vaccination because he thinks it’ll make him sick. I resisted getting the shot myself – I appear to be allergic to the preservative thimerosal (aka mercurochrome), but found a preservative-free option, so I went for it. Seeing the chart below, I’m glad I did…
As a follower of the “Quantified Self” work catalyzed by Kevin Kelly et al, I was eager to see Laurie Frick’s exhibit “Quantify Me” at “women and Their Work” – Marsha and I hung out there last night exploring the aesthetic representation of Frick’s mind.
Using her background in engineering and technology she explores self-tracking and compulsive organization. She creates life’s most basic patterns as color coded charts. Steps walked, calories expended, weight, sleep, time-online, gps location, daily mood as color, micro-journal of food ingested are all part of her daily tracking. She collects personal data using gadgets that point toward a time where complete self-surveillance will be the norm.
Though I’m interested in the subject, I’m not into self-surveillance because it takes too much metatime. I’m a cyborg at heart, but not particularly organized about my cyborganic data. Building a project like this around it is a way to make it more attractive to track and evaluate processes of body and mind.
The human brain is always evolving, and that evolution is accelerating. Consider “superplasticity,” described as “the ability of each mind to plug into the minds and experiences of countless others through culture or technology.”
The next stage of brainpower enhancement could be technological – through genetic engineering or brain prostheses. Because the gene variants pivotal to intellectual brilliance have yet to be discovered, boosting brainpower by altering genes may still be some way off, or even impossible. Prostheses are much closer, especially as the technology for wiring brains into computers is already being tested (see “Dawn of the cyborgs”). Indeed, futurist and inventor Ray Kurzweil believes the time when humans merge with machines will arrive as early as 2045 (New Scientist, 9 May, p 26).
In the future, will there be a sort of “class division” between those whose brains are enhanced, and those who don’t want or can’t afford enhancement?
The guiding principle, perhaps, could be to make sure the technology is cheap enough to be open to all, much as books, computers and cellphones are today, at least in richer countries. “If this stuff can be produced cheaply and resonates with what people want to do anyway, it could take off,” says Chris Gosden, an archaeologist at the University of Oxford.
John Dupré at the University of Exeter, UK says “There will be a lot of evolution, but it won’t be classic neo-Darwinist changes in the genome. It will be changes in the environment, in technology and in the availability of good education. I don’t think souping up people’s genomes is the way to go.” [Link]
A PHR (Personal Health Records) system like Google Health supposedly “puts you in charge of your health information,” but where do you start? ePatient Dave e-patients.net, decided to take the plunge and move his considerable (after bouts with cancer) health data to Google’s system. His hospital was already supporting easy upload of patient records to Google Health, a matter of specifying options and clicking a button at the patient portal.
The result? “…it transmitted everything I’ve ever had. With almost no dates attached.” So you couldn’t tell, for instance, that the diagnosis of anxiety was related to chemotherapy-induced nausea: “… the ‘anxiety’ diagnosis was when I was puking my guts out during my cancer treatment. I got medicated for that, justified by the intelligent observation (diagnosis) that I was anxious. But you wouldn’t know that from looking at this.”
Where there was supposed to be “more info” about conditions listed, the information wasn’t particularly robust, and some conditions were listed that Dave never had.
I’ve been discussing this with the docs in the back room here, and they quickly figured out what was going on before I confirmed it: the system transmitted insurance billing codes to Google Health, not doctors’ diagnoses. And as those in the know are well aware, in our system today, insurance billing codes bear no resemblance to reality.
All this raises the question, and the point of Dave’s post: do you know what’s in your medical records? Is it accurate information? If some physician down the line was reading it, would (s)he make an accurate assessment of your history?
Think about THAT. I mean, some EMR pontificators are saying “Online data in the hospital won’t do any good at the scene of a car crash.” Well, GOOD: you think I’d want the EMTs to think I have an aneurysm, anxiety, migraines and brain mets?? Yet if I hadn’t punched that button, I never would have known my data in the system was erroneous.
Dave realized that the records transmitted to Google Health were in some cases erroneous, and overall incomplete.
So I went back and looked at the boxes I’d checked for what data to send, and son of a gun, there were only three boxes: diagnoses, medications, and allergies. So I went back and looked at the boxes I’d checked for what data to send, and son of a gun, there were only three boxes: diagnoses, medications, and allergies. Nothing about lab data, nothing about vital signs.
Dave goes on to make a rather long and magnificent post, which you should read (here’s the link again). The bottom line is that patients need working, interoperable data, and patients should be accessing and reviewing, and there should be methods for correcting factual inaccuracies.
We’re saying this having heard that most hospitals aren’t storing data digitally, anyway. This is new territory and we know we have to go there. Salient points:
- Get the records online
- Make sure they’re accurate
- Have interoperable data standards and a way to show a complete and accurate history for any patient
- Have clarity about who can change and who can annotate records
That’s just a first few thoughts – much more to consider. If you’re interested in this subject, read e-patients.net regularly.
I used to tell people that “I’m a multitasking fool,” and in recent years, I’ve seen greater emphasis on “fool” – yes, I was good at balancing many tasks, I could keep a lot of balls in the air without dropping them. As I matured, I realized that depth has more value than breadth, and in recent years I’ve been trying to learn to focus and do a few things well.
Alina Tugend in The New York Times notes a multitasking trend since the 1990s, saying that “while multitasking may seem to be saving time, psychologists, neuroscientists and others are finding that it can put us under a great deal of stress and actually make us less efficient.” As a good case study who’s thought about it a lot, I felt real resonance with the quote from Edward Hallowell, author of CrazyBusy: Overstretched, Overbooked, and About to Snap!: “Multitasking is shifting focus from one task to another in rapid succession. It gives the illusion that we’re simultaneously tasking, but we’re really not. It’s like playing tennis with three balls.”
….despite what many of us think, you cannot simultaneously e-mail and talk on the phone. I think we’re all familiar with what Dr. Hallowell calls “e-mail voice,” when someone you’re talking to on the phone suddenly sounds, well, disengaged.
“You cannot divide your attention like that,” he said. “It’s a big illusion. You can shift back and forth.”
The article goes on to discuss overload, fragmentation, and the neural overhead of task-switching.
Dr. Hallowell has termed this effort to multitask “attention deficit trait.” Unlike attention deficit disorder, which he has studied for years and has a neurological basis, attention deficit trait “springs entirely from the environment,” he wrote in a 2005 Harvard Business Review article, “Overloaded Circuits: Why Smart People Underperform.”
“As our minds fill with noise — feckless synaptic events signifying nothing — the brain gradually loses its capacity to attend fully and gradually to anything,” he wrote. Desperately trying to keep up with a multitude of jobs, we “feel a constant low level of panic and guilt.”
Does the brain look like a koosh ball? Indeed so, when seen via diffusion spectrum imaging, which “analyzes magnetic resonance imaging (MRI) data in new ways, letting scientists map the nerve fibers that carry information between cells.”
Neural fibers in the brain are too tiny to image directly, so scientists map them by measuring the diffusion of water molecules along their length. The scientists first break the MRI image into “voxels,” or three-dimensional pixels, and calculate the speed at which water is moving through each voxel in every direction. Those data are represented here as peanut-shaped blobs. From each shape, the researchers can infer the most likely path of the various nerve fibers (red and blue lines) passing through that spot.