Mobile Health – Value Proposition and the Role of Non-profits 9/26/12

I’ve been thinking about the value proposition for mobile health ahead of a meeting I’m attending at Robert Wood Johnson Foundation (RWJF) later this week. It’s a pretty small event I think, with about 20 people invited. The University of Maryland School of Medicine is co-sponsoring it. The name of the event is "Defining a Value Proposition for Mobile Health (mHealth)," so you can see why I’ve been thinking about the value of mobile health.

The objectives of the one-day meeting are:

  1. To define what "works” in the mHealth space.
  2. To understand what needs to be done (especially by not-for-profit funders) to advance effective mHealth.
  3. To discuss opportunities for mHealth to make big impacts on population health and health care systems.

These are big objectives for a one-day meeting, but so is the overall meeting title of value propositions of mobile health. I’ll try to synthesize my thoughts for each objective and see how far I am from the consensus. The people attending have a broad range of backgrounds, so I’m really not sure what the consensus will be.

In terms of the value proposition for mobile health, it’ something I took a stab at earlier this years on a couple of posts (here and here). To put it simply, mobile = engagement. If you look at statistics about usage of non-health digital services and content (Facebook, Twitter, e-mail reading, news, etc.), mobile users are almost always more engaged. Phones are always with people and typically are always on.

On top of that, sensors and batteries are getting smaller and performing better. We’re even using gastric acids to complete circuits and trigger events when substances hit our GI tract (check out Proteus). If you add to this the increasing adoption of smart phones in the general population — not to mention the extremely high numbers for smart phone adoption in the provider population — mobile seems like a great strategy.

Something else I’ll add to the argument for mobile is big data. When it comes to mobile, big data isn’t about freeing existing data from EMRs or enterprise silos. It’s about passively gathering data and moving it to hosted servers all the time (movement and exercise, blood chemistries, adherences, and many more). You’ve got Fitbit, Nike, Jawbone, Striiv, Withings, iBGStar, Telcare and a number of other hardware makers collecting and storing data. You’ve also apps acting as monitors, with Runkeeper, Nike, and MapMyFitness as the prototypical examples.

You’ve also got gateway aggregators acting as personal health hubs for sending health data and receiving healthy advice. For aggregators, I think of Independa, Intuitive, and before that, MedApps, all sort of mobile. We’ve even got mobile usage trackers, like Ginger.io, which are collecting data about how you use your phone then using that data to detect changes from baseline. It’s interesting and telling to note that Ginger.io, at least from a messaging perspective, did not start out promoting itself as a big data company, but that is core to it now. At some point, hopefully we can unify the data being collected across the myriad of sensors and apps and make it valuable, both at an individual level as well as at a population health level.

Personally there is one more thing I really like about mobile apps versus web apps – no Internet Explorer 7 and 8. Seriously, IE7 and 8 make up a small percentage of all browser usage, but it seems like tons of hospitals still use them. If you have an web app you want docs to use at work, you have to support IE7 and 8. If you have a web app that looks and feels like other current web apps, this is not that easy.

What do I think "works" in mobile health?

Theoretically lots of things, but real evidence is still in short supply. As such, my sense of what works is not necessarily data driven. My list is also somewhat random and not all items on it are comparable.

  • Diabetes management. WellDoc has some good data that gives diabetics FDA-approved feedback on glucose readings works. It’s like having an endocrinologist in your pocket. As WellDoc tries to scale this through payers and healthcare orgs, incentives will be key to promote its usage. Denver Health has good data to show that patients — even underserved ones –  will use SMS for reporting glucose readings. The nice thing about diabetes is blood glucose is easily analyzed, it’s really the only data point that matters (I guess weight as well with Type 2 or non-insulin dependent diabetes and pre-diabetics), and automated advice is possible, closing the feedback loop. Theoretically hypertension would be another good example, but I don’t think daily measurements are as common in HTN as they are in diabetes.
  • Anything pediatric, especially teens. This is a population that is notorious for being non-adherent to treatment. We’re starting to see data, like that from Bant and pediatric diabetic patients, that mobile and gaming are effective ways to target this population. I know there are other good examples in pediatric populations. Can anybody send me some?
  • Aging in place. To me, aging in place means keeping tabs on older family members. Right now we don’t use anything sophisticated to do it. I don’t know if mobile necessarily has to be used by the elderly patient, but it’s certainly a lot more convenient if this is an access point for adult children that want to keep tabs on them. I think leaning on family caregivers, even remote ones, is a great asset that mobile technology helps enable.
  • Research and PRO. I think mobile apps have great potential in research to increase recruitment and retention of studies, as well as more accurately collect subjective outcome data.
  • Socialized. I think targeting user engagement with mobile anything is aided by the addition of a social component. It keeps people interested and accountable.
  • Gamified. Similarly to social aspects, gamifying mobile health apps is a great way to encourage continued use over time. Gaming is something people have grown familiar with as so many other services use aspects of game theory.

What needs to be done to advance mobile health from a non-profit funder perspective?

This is an interesting question, and one I don’t know that much about. With the meeting being hosted at RWJF, I see why this is relevant. I’ve often wondered how you can use non-profit funding — something I usually associate with long, painful grant cycles — in a fast-paced market such as technology, especially mobile technology. I think one-off challenges, like the ones from HHS and others (comprehensive list here) are a great way to use public funds and get independent developers and startups involved.

What I’d love to see is non-traditional funding where non-profits invest, sort of like typical VC or equity investors, in for-profit ventures. Non-profits have missions, and by nature those don’t include profit. But some for-profit ventures in health have real potential to do well by doing good. Some for-profit ventures in health may even help non-profits meet their missions. And non-profit funders in healthcare have very deep pockets.

I’ve heard (though never confirmed) that foundations and other entities with special recognition from the IRS can invest in for-profit ventures. I don’t know how this works legally with entity types and the IRS, but maybe I can learn more this week or maybe somebody might be willing to enlighten me on this subject.

What are the opportunities for big impact of mHealth?

I think I already covered most of this when I discussed the value proposition of mobile health above. On an individual level, I really believe (realizing that it’s mostly still hypothetical) that mobile has the potential in the long term to improve care and lower costs. This isn’t going to happen immediately at a large, system-wide scale, but we’re going to start to see it working in pockets, like within integrated delivery systems, and to a lesser extent, payers.

And no, I don’t think phones are going to replace doctors, though I think mobile phones can replace certain tasks, such as refill requests and repeated questions and calls. Mobile health can aid tremendously in gathering structured, meaningful data about patients, which providers can then act upon to make better, more informed care decisions.

On a population level, we can combine data collected from mobile devices with outcome and cost data. From there, we can start to better understand causation and trends, ultimately leading to more targeted and proactive interventions. In this respect, we’ll likely see the payers leading the way.

What we’re really aiming towards with the hype — or promise, depending on your perspective — of mobile health is the ability to better collect and analyze lifestyle data, or the actions and decisions patients make when they aren’t in front of providers and aren’t inpatients. With this knowledge derived from mobile-collected big data, we can use mobile channels, hopefully along with social and gaming features, to try to help individuals make better lifestyle decisions.

That was helpful. I feel like I’ve got a better sense of my thoughts going into the meeting. I’ll write something this weekend or early next week about the outcome of the meeting.

TGphoto
Travis Good is an MD/MBA involved with health IT startups. More about me.

  • Christopher Wasden

    the problem with non-profit funding for these things is that the money is not sustainable. They end up funding pilots and then when the money dries up the pilots end and nothing comes from them. What we need are sustainable business models that can survive without non-profit financing.

    I was in Switzerland the past two days talking to telcos and providers about mHealth. After I discussed several use cases around readmissions, chronic disease management, remote patient monitoring, wellness, fitness, etc. they said to me, “why would we do any of this stuff? It generates no revenue and if it works as the VA and NHS WSD indicate then it decreases our revenues.  We are paid to treat sickness and the more healthy people are the worse off we are as healthcare providers. We will not respond until there is pressure for us to act differently. The government provides the incentives for the healthcare system and those incentives are to keep people sick and in hospitals. We KNOW we can deliver care for a lot less money and keep people healthier but there is no logic and incentive to do so.”

    Now I know doctors will read this and say that this can’t be true because it suggests that these doctors don’t have the patients best interest at heart. But we need to look at this from a system perspective, not an individual doctor/patient perspective.

    In Europe there are no incentives in any system, except perhaps the UK, to adopt this technology. Whereas in India, Africa, Brazil, China we see rapid adoption. For example, Telefonica has mHealth programs in the UK, Spain and Brazil. The Brazilian program is doing very well while the other two are struggling despite the bold moves of Telefonica to put in all the upfront investment and only get paid if the patients outcomes improve at lower cost. In Spain for example, the healthcare payers biggest concern is that Telefonica will be successful and then they have to pay Telefonica for decreasing costs and increasing outcomes, but still have the fixed costs of hospitals and doctors to pay as well.

    This later point is a big one. For most healthcare systems, the entire system is considered a fixed cost. So you have all of the costs even if you use mHealth to provide cheaper care and create better outcomes. These fixed costs are just not utilized. So to make mHealth work you have to find ways to both deliver better care at lower costs as well as more productively use existing assets and people that are no longer being used for the activities that mHealth has now replaced.

    Intuitively this shouldn’t be a problem if we truly have an over 500,000 shortage in doctors and nurses, but this is not the way the healthcare system thinks so any reduction in utilization due to successful mHealth is viewed as a threat to the current system.

    So, the key question, how do you move the current system to a more productive model while deploying more efficient and effective mHealth solutions?

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