Brent Kearney

This recipe is reverse-engineered from Anahata Foods’ Godess Bars, one of my favourites. This is not their exact recipe, it’s my version of it.

Start by stirring these dry ingredients in a mixing bowl:

• ¼ cup sunflower seeds, coarsely chopped
• ¼ cup finely chopped almonds
• 2 tbsp sesame seeds
• 2½ tbsp hemp seeds
• 2 tsp greens concentrate powder
• 1½ tbsp unsulphured (grated) coconut
• 1 tsp matcha green tea
• 2 tbsp raisins
• 2 tbsp unsweetened carob chips

Add the sticky ingredients next, and stir:

• ½ tbsp brown rice syrup
• 3 tbsp almond butter
• ¼ tsp vanilla extract
• 3 tbsp tahini

Once thoroughly mixed, empty the bowl onto a cutting board or other flat surface. Use another flat object — I used the side of a broad kitchen knife — to squish the pile of green goodness until it’s about 1cm thick. Form it into a rectangle, then cut it into bar-sized pieces as desired. Wrap them in cellophane or wax paper.

Enjoy!

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This post started as my reply to another blog post that I came across, Obsoleting Doctors, by software developer Sammy Larbi. After I wrote a couple of paragraphs, I realized that this was an idea that I’ve been thinking about for awhile now, so I moved it here.

Sam’s post muses on the possibility of expert systems (computer software with specialized databases) replacing doctors for the diagnosis of illness. I don’t think that doctors will become obsolete, because I don’t think that disease and injury will vanish, and someone needs to provide care for the sick in an informed and experienced way. However, I agree with Sam that IT can help, and that change is afoot.

The problem with the medical establishment right now, and the way that doctors work, is that the system is so completely focused on pathology. This is an unfortunate irony because if they were focused on preventative care instead, pathologies wouldn’t develop nearly as often in the first place, and we would all live longer and healthier lives.

Today doctor visits are designed to identify symptoms of illness, and to treat “primary complaints”. Diagnostic tests are done to check that your health is within normal parameters. As it turns out “normal” is the same as mediocre. If the goal were optimal health instead, surely fewer health problems would arise, and those that do could be spotted at an earlier stage, where treatment stands a much better chance of success.

Information technology (IT) could help health care in a number of ways. One way IT can help is by recording health and fitness data on an individual level, and making it easily and directly available, so people know exactly where they’re at and where they need to improve in order to reach optimal levels of health and fitness. By “available”, I mean available to the patient. I hate to use the word “patient” because it implies illness, but what I have in mind is a person who is not yet ill, and who wants to stay that way.

For an example of this idea applied to fitness data, see Wired’s articles on Nike and “personal metrics”, Living by the Numbers. The average person isn’t concerned enough with their fitness to get this geeky about it, and the sick-care system, with it’s focus on mediocrity, is in part to blame. As Ray Kurzweil and Terry Grossman ask in their new book Transcend, “when was the last time your doctor counted the number of push-ups and sit-ups that you can do?” Maybe they should.

The real power of fitness data would emerge when combined with clinical data such as cholesterol levels, blood glucose and blood pressure, homocysteine, C-reactive protein, etc., with dietary information including what drugs or supplements you take, and with illness and treatment histories. Family health history should be included, and eventually personal genomic data could also be added. All of this together could form an individuals health profile. The health profile could be anonymously fed into intelligent software that cross-references the data with everyone else’s health profiles to help spot problems and identify trends. This process is known as data mining. It’s value to health care and life sciences would be staggering.

Google and Microsoft have both begun projects that will move us in this direction. Google’s system is called Google Health, and Microsoft’s is HealthVault. (Given Microsoft’s history and culture, the choice for me is clear). The Personal Genome Project is explicitly about data mining, only it is focused entirely on personal genomic data. These efforts represent the beginnings of crowdsourcing for health care.

These technologies, if adopted by large enough numbers of motivated individuals, and taken up by a significant number of researchers and forward-thinking medical practitioners, could bring about the change that is needed to move health care out of it’s rut of pathology obsessiveness and into a era where health is optimized and disease is prevented.

However healthy we try to be, disease will always exist. Information technology can help with that, too. It can be used to reform the badly broken regulatory system, and by being a catalyst in bringing new treatments to medical practice.

A major problem with the medical establishment is that it adopts change at a glacial pace. It is decades behind in technology. For example, as noted in Transcend:

Consider ultrafast CT coronary artery calcium (CAC) scans of the heart. This technology has been available for over a decade and a half, and, even though multiple studies have shown that it is effective at detecting coronary artery disease very early in its course—at a time that effective preventative treatment can still be done—the American Heart Association still does not recommend its use for primary screening.

This sad situation is only going to get worse, since the pace of technology development continues to accelerate, and advances in medical research far outpace the regulatory approval process. The regulatory approval systems in place were conceived of and implemented in a much slower moving era, when major breakthroughs were seldom achieved. Now, science and technology breakthroughs are an almost daily occurrence.

Research is progressing so fast that individual scientific researchers in any given field are almost certainly not aware of all of the developments simultaneously taking place in his or her field. Thanks to amazing advances in communications technology, researchers are vastly more aware than they have been in the past, and many collaborate across the globe. However, the amount of new information is too verbose, diverse, and too fragmented across different systems and different languages that one person cannot keep track of it all. This problem is magnified by orders of magnitude when applied to the institutional level.

Information technology can help aggregate the fire-hose of research data and promote collaboration and communication between the research community and medical establishments. It could be used to streamline the regulatory process and promote more aggressive adoption of new technologies and therapies. The regulatory bodies could—and should—become more democratic, allowing more direct and open input from diverse sources including the research community, practicing doctors, and especially patients.

The hyper-intolerance to risk by the current regulatory bodies is completely out of touch with the reality that patients with real diseases are facing. I suspect that the litigation culture, born and nurtured in the United States, is largely at fault for this state of affairs. It is logically and ethically backwards: to have a fatal disease is itself a huge risk, and that risk should be balanced with the risk of experimental treatments. People suffering from fatal disease should be allowed the opportunity to possibly save themselves, and at the same time benefit science and medicine, whether the treatment works or not.

Encouraging all parties to participate in development and implementation of medical therapies would be to crowdsource medical research and practice. IT would be the medium through which the data would flow, the ideas exchanged, and results mined for further insight.

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