29.7.09

PHR Business Model Cheat Sheet, and Why I'm So Hung Up on Infoviz

If you're in the market of trying to help consumers improve overall health and wellness, one microchoice at a time, then you are armpit-deep in the data market, my friend.

Personal Health Records (PHRs) providers are, in essence, next-gen health data companies. 

Yes, this is a vast oversimplification, due to the 'sensitive' nature and uniquely weighted values of health data. Not having info about the cheapest used bicycle for your next Holland tulip tour may not be a life or death issue, while knowing about the latest treatment modality for your type of pancreatic cancer may be. 

But for the sake of argument, and injecting a healthy dose of common sense before it's legislated right out of the personal health data market, let's take the 'PHR providers = data companies' at face value (at least for now).

If you're still reading, and agree to consider the data company angle, this means that once you understand the challenges/opportunities facing next-gen data companies, you can easily extrapolate clear, useful information about what's coming down the pipe, at a macro level, for personal health information (PHI) platforms, and all without gazing into a crystal ball or opening a vein under a full moon. 

Consider it my gift to you, without making you sign a patient-centric info manifesto in blood. 

In all seriousness, this isn't fortune-telling, but we've been treating healthcare futurism like it's an occult art. Done right, it's not. Let's take a critical look at business models, current provisions, and market opportunities for data companies, from 30,000 feet. 

If you're a next-gen, '3.0' data company, you've essentially got 4 business model choices. You can:

1. store data - charge $ somehow
2. sell data - charge $ somehow
3. get consumers to pay you to A. store data (number 1) or B. NOT sell data (number 2)
4. analyze data - charge $ somehow

Current PHR companies, including the "Big 2" Google Health and Microsoft HealthVault (which are really just data companies), are organized loosely as rather inefficient answers to business model option 1. 

A developer friend working on an interesting problem wading through a pedestrian infrastructure solution today made a remark about 'dirty code.' 

Looking at PHRs as a business model solution to 'storing data,' option 1 above, is a model, but it's an ugly-duckling one. It's necessary, but it's dirty code that doesn't illuminate elegant solutions in a simple, Ruby-on-Rails type manner. 

But that ain't all bad...let's take a look at what will happen next. 

Next, PHR companies will pull a Twitter, and figure out their largest asset is all that PHI. 
When PHR providers figure out they can sell all that chewy personal data (even if anonymized, a la Patients Like Me), they're going to go after business model option 2 - sell data. 

Now, if you're following, right about now the 'aha! Holy sh*^!' lightbulb should pop on just above your frontal lobe and hover...Option 3 is the holy grail of PHRs.

Everyone (or at least a goodly chunk of govt, insurers, and HC reform types) want to get consumers engaged in their healthcare so we cost the system less overall (supposedly anyway).

But how to do this? We have to get people interacting with personal health data and 'taking ownership' - which means we want them to give us their data so we can figure out how to make money in one of the ways above. 

The smart money is on designing for business model option number 3; building something so beautiful and intuitive in terms of visualization and data presentation, that consumers will actually pay either to use it or to restrict how we use it. Add a little functionality, a little meaningful-use, interoperability juice and you've got the fountain of youth, or as near as HIT is going to get us. 

But the really, really, really, really smart money (and VCs your saliva glands should be in overdrive right about now) is on the sort of rare organization that designs for number 3 but builds for number 4-from Day 1. 

Without building in a backend analytics platform so crisp you could bounce a quarterweight reduction of the national, bloated BMI off of it, we won't reach critical mass.

It is exceedingly well designed analytics that will accelerate us, cold fusion style, towards critical mass adoption of a consumer health platform, guided by super elegant infoviz design that makes string theory look like kloogey code.

So what is the penultimate, next-gen PHR model? Look for business model option 3, backend stealth style data analysis integration, and KISS infoviz.

Only with all these elements in place will we be able to trick, ahem, talk, consumers into the kind of healthcare decision-making process necessary to change your mind, my mind, and Grandma Nagy's mind away from serving that protean-continent sized slice of pie for desert. 

You can't manage what you can't measure, and we're doing a pretty good job of mangling even option 1, or storing health data effectively enough to charge w/out a common spec. 

I don't need to tote at Tarot deck to see the Reaper and the Fool having a field day with our sector. I also, however, don't need runes to read that a bright future is possible with one strange turn of the cards. 

Jen S. McCabe
@jensmccabe

CEO/Founder:

Contagion Health 
CoFounder: NextHealth (NL)

Consulting/Chief Patient Advocate (social media): 

OrganizedWisdom Health

LinkedIn: Jen McCabe 
Skype: jenmccabe

iPhone: 301.904.5136 
Dutch Mobile:  +31655585351

jennifermccabegorman@yahoo.com

Posted via email from Jen's Posterous

1 comment:

Brenda F. Bell said...

Leaving aside the very big issues of information privacy (can an employer or potential employer find you may be at greater health risk than another candidate, and fire/not-hire you because of that) and medical identity theft, in a utopic world, the Health Data Manager would:
(1) Store your basic data (possibly for free)
(2) Integrate two-way health-related communications with your identified health care team, and allow you to "accept" inbound communications from health care providers who have tended to you before you pre-accept them (e.g., emergency room or trauma center -- they will need to be able to view your records to treat you appropriately in the first place); (3) provide backend analytics in the broadscale and sell these to researchers, pharma, hospitals, insurers, etc.; (4) sell the ability to do custom searches of the depersonalized data at a time- and resource-dependent rate (much like early generation online databases); (5) automatically provide you and your healthcare providers with warnings if analytics including and specific to your health record indicate an urgent threat to your health; (6) provide more detailed personal health analytics to you and your healthcare providers, or more types and levels communications between you and those providers, for a fee -- like the "Premium Membership" options on diet and exercise sites (e.g. Livestrong/The Daily Plate, Map My Ride, etc).