Chorbev et. al describe in the Journal of Telemedicine and Applications a plausible model for improved diabetes through group share. They set up a platform where:
We have developed a healthcare social network that provides methods for distance learning; opportunities for creation of virtual self-help groups where patients can get information and establish interactions among each other in order to exchange important healthcare-related information; discussion forums; patient-to-healthcare specialist communication. The mission of our virtual community is to increase the independence of people with diabetes, self-management, empower them to take care of themselves, make their everyday activities easier, enrich their medical knowledge, and improve their health condition, make them more productive, and improve their communication with other patients with similar diagnoses.
On one hand, one of the flaws with this is that this network captures those who already are invested in improving their care - the self-selection bias. If you're online and have the choice between TMZ (Humpdashian!) versus your HbA1C, even with marginal costs, the uninterested patient will choose Humpdashian. But on the other hand, the Gladwell understanding of the social network model, would argue that given the low cost of interaction (send some emails, perhaps check your sugars more often or take your insulin more regularly), even with low motivation, the participation of these patients should be high. So while each patient doesn't have to do so much, the fact that many are doing a bit improves substantially the median health outcome.
More systematically, the Gladwell argument discounts the power of networks to find answers. The beginning examples of chaos theory generally use the patterns of birds or fish as the analogy to describe the complex patterns developed without hierarchy:
Chaos theory looks at how very simple things can generate very complex outcomes that could not be predicted by just looking at the parts by themselves.
You may have noticed the wonderful swirling patterns of birds flying together in the sky or fish schooling in the oceans. At first glance we would think the birds would have to be rather intelligent to work out how to fly in formation like that. We would probably also assume there must be a 'bird in charge' giving instructions to all the others.
Research into swarms has shown, however, that all that is required is for each bird to maintain the distance between itself and its neighbours and fly in the average direction of its neighbours. From this alone the wonderful, swirling, complex patterns the birds or fish make are seen. Simple rules can generate complex behaviours that just seem to emerge out of nowhere. While each individual agent does not need much intelligence, the is swarm intelligence which resides with the collective.
And this is the argument put forth by the social network as improved health model. It's actually the feature (rather than the bug) of this model that it's non-hierarchical. In this way, simple modifications to the program or to the rules set forth to the patients can have large, cascading effects. And done well, these can still be inexpensive in cost to the patients (effort) and to society ($$).
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