I just returned from the mHealth Summit in Washington, D.C. We’ve been sponsors of the event for 2009 and 2010 – both years it’s been held. Last year there were about 400 people who attended. This year there were about 2,500, including prominent guest speakers like Francis Collins, Bill Gates and Aneesh Chopra, among others. There was also a large hall with lots of exhibitors and an extensive poster session. I guess this means that means mobile health is coming of age.
I liked it a lot, but not for the reason you might think. At most of these types of events the presentations tend to expand on the great things that are going on in the field. Here there was a good, healthy dose of skepticism. And there’s a lot to be skeptical about. There are the “show me” skeptics, the ones that ask for evidence that it actually works. There are the regulation skeptics, the ones who know the problems in getting devices approved by the responsible government agencies. There are the “disruptive innovation won’t work here” skeptics. There are the “who will pay for it?” skeptics, not to mention the standards, open source, proprietary, silo, etc. skeptics. It makes my head spin and wonder how we’ll ever get there.
There are two reasons I’m still optimistic. First, in spite of all this, the field is growing and there are big players in the field. Second, many of the issues are starting to be formally addressed at what seems to be appropriate levels. That’s good. There is an area where I think more can be done, and that’s in developing better methods for validation and evidence. There’s still a huge emphasis on the traditional clinical trials model, which sets up a fixed and structured experiment, collects data over a period of time, consolidates and analyzes the data at the end of the trial, and, after a long period of time (maybe five years), reports the outcome.
The field shouldn’t have to wait five years to understand the effects of what by then will be an obsolete intervention. In addition, this is a field where there should be continuous improvement, where tinkerers thrive, where prototypes are the rule. It makes little sense to freeze development when you learn something that will make it better. One solution might be the type of adaptive trial that pharmaceutical companies are investigating. This is one where results at various stages in a trial can effect changes in the trial model. You might change the sample size, the target population, the delivery method, the formulation, etc., based upon analyzing data internal or external to the experiment. Analysis of this model is complex but can be manageable. In the end you should be able to deliver a safer, more effective product sooner.
That’s the germ of one idea for being able to develop an evidence base for mHealth quicker and better than today. These are my thoughts. I’m sure that there are smart and thoughtful people who have others.