There is no doubt eHealth can aid in patient self-management and creating effective education systems to aid in that management. However, we have a long way to go in figuring out where intervention is most cost effective and provides the best outcomes. If we are facing such skyrocketing costs in our lifetime, there should be some rational metric for allocating funding. And to create those metrics, we have to come to some basic agreement on what drives behavioral change.
Thomas Goetz’s video (It's time to redesign medical data) has some weak conclusions. For example, he claims that fear is not a motivating factor in behavioral change, and then uses an example of speeding signs, which most likely are effective due to the fear of consequences. People don’t need a belief in their efficacy to stop speeding. Similarly, dental care comes with the fear of shaming.
The role of efficacy can be equated with the ability to delay gratification, as in the oft-cited marshmallow experiments (See the amusing Ted Talk Don't eat the marshmallow!). This is a behavior that can often be traced to early childhood development, when individuals are exposed to conditions that either lead them to fear that their needs will not be met, or provide them with the assurance that their actions will provide rewards.
If the development experts are to be believed, this is extremely difficult conditioning to overcome later in life. In a nutshell, fear (of legal consequences, of being shamed, of being outcast, etc.) is the dominant motivator in cultures of scarcity, where the likelihood of there being resources in the future is low. Efficacy is only realistically developed in people who are not subjected to constant scarcity. So at the least, we’re talking about trying to motivate two groups with entirely different motivations.
A recent article describing attempts to impact texting while driving is one of the clearest examples of people’s inability to make healthy changes ("Trying to Hit the Brake on Texting While Driving"). The risk is of killing yourself or committing manslaughter. The benefit is to get a short message that in 99.99% of cases can wait until you stop your car. It must be the largest risk versus smallest reward in the history of risk and reward. Yet people still do it.
Using drunk driving as an example, the article states, it was “education campaigns combined with tough, enforced laws” which led to the reduction of this deadly habit. And it’s only been a reduction. As Mother’s Against Drunk Driving (MADD) statistics report, “In 2012, 10,322 people died in drunk driving crashes - one every 51 minutes - and 290,000 were injured in drunk driving crashes…..At the cost of 199 billion dollars a year.” (http://www.madd.org/statistics/). In some subcultures, there appears be more shame in bad breath, than in killing someone because getting high feels good. But if enforcement had an impact, fear is a motivating factor.
Some researchers believe that eHealth may have immediate benefits, but that the data on long-term change is less hopeful. Perhaps those interventions that don’t show long-term progress should not be invested in. What about the interventions that cannot document either short or long-term change?
While many initiatives may be cost effective, we will have to start rank ordering that effectiveness, if we hope to rationally allocate our resources. To do that requires consensus on how to alter behavior. We don’t simply want to be catching the low hanging fruit because it’s there.