Skip Wally World
HHS’ Health Data Initiative’s
Healthcare Entrepreneurs’ BootCamp
It’s getting near vacation time.
Rather than heading out with the Griswold family for Wally World, consider stopping by the Department of Health and Human Services (HHS), the Centers for Medicare and Medicaid services (CMS) and the Institute of Medicine (IOM)’s fourth annual Health Data Initiative conference, otherwise know as Health Datapalooza.
Our fine friends have asked us to put on a couple of sessions.
One of them is a secret – a very cool surprise that’s literally fun and games.
The other session is a Healthcare Entrepreneurs’ BootCamp.
The only logo ever with a Combat Boot and a Stethoscope together…
… with a Pink Background
Last year we did a form of this and exceeded fire capacity and broke the Applause-O-Meter.
Yes, that’s our session, Pew Scholars, game cards, crayons and cotton candy!
This year’s session promises to be bigger and better than ever.
It’s based on a bootcamp we’ve run at Harvard, Johns Hopkins and other places with crests in their logos.
Rather than your typical hack-a-thon where you start with some tech, play around and get a Chuck E. Cheese prize, this is about connecting ideas with real market value with public data and real world experience.
(Of course some hack-a-thons are very nifty and don’t fall into this, like the inaugural MIT one we did a stint at.)
Congratulation on your hack-a-thon finish…
… and please accept some office space, advice and a nice line on your resume
We’re packing the room with absolute experts from every part of the healthcare landscape – along with folks who have founded and scaled some of the most innovative healthcare companies in the past decade – and a super bonus of market leaders and the best venture, private equity and accelerator folks in the space.
So pack up the Truckster and take your idea on down to DC for some fun and games.
Pea green is retro!
Oh yeah, here’s the current lineup with all the FAQ you’ll ever need:
“Health Care Entrepreneurs’ BootCamp: A Real-World Crash Course in Everything You Didn’t Lean in Business School about Using Public Data to Create Market Value, Navigate Perverse Incentives and Deliver Public & Social Good”
An interactive, games-based BootCamp designed to get participants up and running the same day with their own real-world portfolio covering how to use public data to create market value, how to navigate perverse incentives in the industry and how to deliver public/social good. Based on grass-roots, student-initiated workshops at elite universities’ biz, med, gov and comp sci schools, this very different take on ‘education’ covers theory & practice, resources & real examples in a fun environment for anyone even remotely interesting in how to turn a data-based idea into a product, service, company or non-profit. No pull-ups, but good faith efforts required (& some dancing.)
Joshua Rosenthal, PhD, Co-Founder, RowdMap
Sergeants at Arms:
Sujata Bhatia, PhD, MD, Harvard University
Marshall Votta, Vice President, Leverage Health Solutions
Khin-Kyemon Aung, President, Harvard University Premedical Society [Clinical]
Aman Bhandari, Health IT & Data Partnerships, Business Development and Strategy, Merck [Pharma]
Lily Bradley, Presidential Innovation Fellow, HHS [National Government]
Zen Chu, MBA, Entrepreneur in Residence, Massachusetts Institute of Technology [Devices]
David Dickey, Co-Founder, RedBrick Health; CEO, Second Story Sales [Story Telling]
M. Chris Gibbons, Johns Hopkins Urban Health Institute [Social & Public Good]
Evon Holliday, Vice President Business Intelligence, Catholic Health Initiatives [Hospitals]
Lissy Hu, Co-Founder, CarePort Health [Health System Navigation]
Owen Johnson, Co-Founder and Managing Partner, BetaSpring [Start Ups]
Mohit Kaushal, MD, MBA, Partner, Aberdare Ventures [Strategy]
Adam Kushner, MD, MPH, Johns Hopkins & Columbia; Founder, Surgeons OverSeas [Non Profit]
Jack Lewin, MD, Founder, MEDePASS; Board Member National Coalition on Health Care [Policy]
Richard Lungen, Managing Partner, Leverage Health Solutions [Sales & Corporate Development]
Jay Nagy, PISPS, Associate Principal, The Advisory Board Company [Services]
Mohan Nair, Chief Innovation Officer, Cambria Health Solutions [Organizational Change]
Kyle Rolfing, MBA, Co-Founder, Definity & RedBrick Health; Principal, Savvy Sherpa [Employers]
Kevin Ryan, VP, Business Development and Marketing, McKesson [Market Navigation]
Abir Sen, MBA, Co-Founder, Definity, RedBrick, Bloom Health & Idego [Payers]
Burak Sezen, MBA, Co-Founder, RowdMap [Analytics]
Ted Smith, PhD, Chief Economic Growth and Innovation, Louisville Metro [Local Government]
Jordan Shlain, MD, Commissioner, San Francisco Health Services; Founder, HealthLoop [Physicians]
Randy Stoughton, President, Compass Rose Benefits Group [Defense & Federal Populations / Programs]
David Wennberg, MD, Co-Founder, Health Dialog; CTO, The Dartmouth Institute; CEO NNEACC [Data]
Richard Dale, Chief Operating Officer, Optum Labs
Brad Fluegel, Senior Vice President & Chief Strategy Officer, Walgreens
Anna Haghgooie, Managing Partner, Sand Box / Blue Cross Blue Shield Ventures
David Jones, Jr. , Member of the Board, Humana; Chairman, Chrysalis Ventures
Les McPhearson, Innovation & Business Development Executive, Florida Blue, HealthBox
[former Lieutenant, United States Navy]
Mark Tomaino, JD, MBA, Senior Operating Executive, Welsh Carson Anderson & Stowe
Bill Wray, Chief Operating Officer, Blue Cross Blue Shield Rhode Island
[United States Military Academy, West Point]
How to Speak in Public
This is what matters
(Pro Tip: It’s a killer tutorial on how to speak in public)
Why are you in health care?
You are – it may not be a business – but in one way or another, you’re a player in ‘The System’. You or a family member. And if you’re not now, you will be.
We get asked this pretty often – not sure if that’s a compliment or not, perhaps we don’t look the part.
It’s a good question – and if folks can’t answer it, it’s worth giving serious consideration whether you want to do business with them.
Kant was wrong, any separation between who you are and what you do is an artificial construct designed to preserve self image at the expense of core identity (we’re big Kierkegaard fans.)
Here’s why we’re in health care.
Obviously it’s a cluster and a travesty that the system doesn’t work efficiently – too many perverse incentives in a complex array.
Part of that is from limited supply but unlimited demand (tip of the hat to you MPH-ers), part of that is psychological with the individual believing they are the exception by default (for you behavioral folks).
But at the end of the day, it’s one of the few areas where you can really help people, more than selling them a widget (admittedly it depends on the widget : - )
And with the new paradigm (Medicare Advantage, Medicaid managed, individual exchanges, etc.) it’s one of the few areas where the market incentives are very much aligned with helping people – helping them get the care they need as well as the service they need – all to give them wonderful customer satisfaction.
We work in information and even data – from a top down approach where we’re starting with populations.
But at the end of the day, as cliché as it may sound, it’s really about individuals – you, not as a number, but as an individual.
An individual who matters – and that’s, quite honestly, the only thing that matters.
The key to any of that – is actually caring about the people you serve, as human beings. Celebrating their triumphs, supporting their efforts, grieving at their losses and everything in between.
So we’d like to share a little series of vignettes. About not just who we are, but more importantly why we do this – what really matters to us.
The first little picture comes from Kyle, a good friend who sits on our board of advisers.
Here’s a video of his son, Alex, giving a little speech.
Kyle’s not only one of the better business folks we know, but one of the better human beings (puts us to shame for sure).
After you watch the video, you’ll see why (although admittedly most of the credit no doubt goes to his wife : – )
Trust us. Watch the video. It will make your day, restore your faith in humanity even – seriously.
All we can say is congrats Alex; you’re an inspiration to us all.
On a more formal note.
We attend a lot of health care events and have heard a lot of folks attempt to speak in public.
Sometimes it’s good. Most often it’s painful.
What we love about Alex’s speech is not just that he did it, but that’s it’s objectively good.
- It has a meaningful point
- It is clear and builds to the point
- It cites examples that people can relate to support the point
- It plays to the audience, and brings them along employing classical pathos
- The speaker has self-awareness, poise and a sense of humor
If only all the speeches we heard lived up to this standard.
So Alex, here’s to you. And if you’re interested in creating a business around helping healthcare folks communicate, we’ll be in your corner from day one – and your first client.
What Medicare Advantage Can Learn from College Sports
What Changes to CMS Rates Mean for You
Tips and tricks from recruiting high school kids and sports betting
playing to a winning record
your own zero-sum healthcare competition
Figure this out, and Healthcare is a breeze
This week the healthcare world is all abuzz about CMS cutting the reimbursement rate for Medicare Advantage.
We’ve already explained how Medicare & Medicaid is the future of healthcare, regardless of policy, legislation and legal decisions. Demographics is driving reform, and ensuring that we’ll do more with less in a Value-Based, Pay-for-Performance-Based… Ah, call it what you like.
While Health Care’s players are dizzy-ing themselves trying to figure out what all this means, financial analysts are already adjusting plans’ and providers’ stock prices.
Regardless, the real action, and the most important event, for all this happened a week or so ago.
Last week or so was National Signing Day for football recruits.
Translation: That means recruits said where they are going to play.
The following explanation won’t tell you what CMS rebates means for you – or what will happen with CMS, or Medicare… or basically anything.
It will however, give you everything you need to navigate these changes, no matter what form they take.
Revenue & Profit
And, you may not know, football is kind of a big deal, makes a lot of money, drives university enrollment in some places, funds entire athletic programs, and basically acts as a minor league system for the NFL (vs. say baseball’s minor league system).
Hundred bucks a head, few times a year…
… dwarfed by the secondary ROI from application bump
And note, writing this from Louisville, we could say the same thing for basketball, but since UofL just won the Sugar Bowl, we’ll stick with football.
This one wasn’t in the numbers, but the context…
… (in this scenario, bet them to cover & you win)
At this point, you are one of two types of people – you either care wildly about this sort of stuff, or you couldn’t care less.
But if you work in health care, or even interact with the system (maybe family members?), here’s why you should pay attention and what you can learn.
College sports is a big business, none more than football, at every level. So here’s a few things to consider.
Virtuous Cycles of ROI
First of all, how much money do I make if my team does well? Good question. Revenue from ticket sales? How about merchandise sales? That’s pretty straight forward.
The real money is in the secondary ROI. Do you think winning and TV exposure translates into more student applications? You betcha. It’s modeled out in detail (really interesting biz BTW). Every time your school is mentioned on ESPN GameDay that’s another handful of applicants, allowing you to expand (increase revenue), increase the pool but be more selective % wise (driving your US News & World Report ranking and thereby creating more demand from a different student pool), or increase tuition/cut financial aid (increase profit).
In any case good football performance creates a much broader ‘virtuous’ cycle allowing you to expand broadly and create more revenue (more people), transfer your equity into profit (through some lever wielding) or diversify your membership profiles (different products, hedging risk, etc.).
Zero-Sum Games (plural)
The funny thing about this is that it’s zero-sum on a few different levels. You win, the other guy loses and vice-versa. Simple enough.
In the recruiting game, there is a fixed pool of talent, and when you take it, it bolsters your team. Simple enough.
Pro Tip: if you take recruits that were going elsewhere in your conference, you do it at your conference rivals’ direct expense, hitting them twice (increasing your odds of beating them when you play head-to-head and decreasing the odds that they will beat anyone else in your conference).
Which denominator? Are #1 & #4: Market Comp or Peers?
(What about #2 & #5)
National powers need to dominate a market of talent – their region. But they also play another game, vying for a limited number of 5-Star recruits against their group (not the conference but the other potential national championship teams scattered across the country). But note the zero-sum dynamic is the same there. If Alabama gets a recruit that’s not only one more for them, but one less for Oregon… who they may have to play come bowl / soon-to-be play-off time . Double bonus if you take them from LSU or Florida who are not only your Peers (one zero-sum denominator), but also in your same conference or Market (another zero-sum denominator, but directly related to the likelihood of getting through to play your Peers in the big game).
If I’m building a management platform, this is in my dashboard
Here’s another dynamic to ponder. There is a fixed amount of money for performance. If you get to a bowl game you get $X. If it’s a BCS Bowl, it’s $Y; a nationally championship $Z. And often the individual parties are comp-ed on these performance metrics. Some of these metrics may be based on absolute triggers (graduation rates – okay, okay, seriously… how about game ticket sales), but even these are grounded in relative metrics (wins, bowl appearance, championships, ticket sales).
Which brings us to the absolute dynamic that piggy backs on the relative, zero-sum dynamic. You compete for money against your peers and market. But, in some way, your group is incentived to improve collectively. You are in a zero-sum game with your conference’s schools, but you want them to do well in their out-of-conference games and bowl games (makes your wins look better, causes the computers to rate you higher). Same thing for the entire system. Goal is to take advertising dollars from sponsors away from basketball or NASCAR – to have the kid buy the NCAA football XBOX game rather than the NFL game – relative. But of course, if the kid buys and likes the NCAA football game, he’s more likely to buy the NFL one – absolute.
For context, just like with Netflix or Amazon, 1 and 2 stars is bad, 4 and 5 stars is good.
So if I’m running a business on this, I need to score my individual components, the recruits I’m bringing in, all sorted out into a taxonomy (Wide Receiver belongs to Skill Position and to Offense, etc.) And I need to quantify them – say using five stars. Not only is my recruiting org comp-ed on these metrics as outcomes, but these measures basically dictate impact (how this ultimately works out in win / loss records).
How many 3 star candidates, how many 4 or 5 stars? How about my conference rivals; how about the national folks I compete against? If your incoming class is 3 star but all your conference rivals are 5 stars, your odds go down for having a successful season, much less a championship (but not necessarily a bowl game win, since that’s a different denominator with a perverse incentive). This isn’t theory. Go to Vegas. Play a little. Look at recruits being signed and watch the lines move. In real time. Based on as much ‘science’ as ‘art’.
Note that these formulas are subject to change, driven by ‘rule changes’ whether from policy, legislation or governing body ‘interventions’.
This is not the stock market (or is it?)
If there’s money and metrics, there are bound to be formulas (algorithms even). Every recruit is given a star (1-5). Some folks use an absolute system, much like Netflix or Amazon, where every movie or product could, theoretically, be five stars (a potentially unlimited number of 5 Star quarterbacks if they all have the same talent). Some folks use a relative system, much like grading on a bell curve with so many A-s and so many F-s (only so many 5 star quarterbacks are possible in any given class).
Then you tally it all up. This another layer of calculation, which can likewise be relative or absolute. Most folks do this on an absolute scale. Each five star recruit is worth 100 points, each 4 star, less and so on. Then add it up and rank each schools recruiting class. Some really sophisticated folks, weight the scores based on the meta data in the taxonomy (a 5 star Quarterback [cf. Skill Position AND Offense] is worth more than a 5 star Guard [Lineman AND Offense]).
If only healthcare data apps had this
The funny thing is, when you translate these objective star metrics into organizational rankings, you get ‘magic’. All of a sudden, an incoming class with a bunch of 3 star recruits may earn a higher ranking than a class with a few 5 stars. Newbie Tip: The value of this is objectively debatable. But nonetheless, once the calculation is ‘contextualized’ for a team there are huge pockets of opportunity to exploit. Say if a team is stocked with 5 stars and only needs a couple of key positions – and they get them – they will have a lower star ranking than a team with a boatload of 2 and 3 stars. This is before we even get into zero-sum context.
This isn’t theoretical or esoteric – it really can wreak havoc with recruiting and overall team ranking, all based on star scores. For instance, the University of Louisville (Again, your 2012 Sugar Bowl winners after stomping SEC powerhouse Florida, thank you). UofL has a very low ranking from basically everybody – over 100th in the standings. That’s because they only have a few scholarships to give out this year so it’s a small class. But if you take the weighted average (not based on every single star being worth a point, but only how high an average star score the class has across the board), they move up into say around 35th place (high for skill players if your break it out by metric domain)
That’s not a trifle. If I’m acting on this information it makes a huge difference.
It makes a difference
(Pro Tip: They didn’t build this on luck)
If I have to put money down somewhere, let’s say I’m going to bet on them winning another BCS bowl this year, knowing whether their recruiting performance is in bottom half out of every school (and de facto bottom tier for ranked teams) or in say the top quintile for the same denominator, has a direct effect on how I bet my money – er, allocate resources. Even more so if I know how effective my team is at interventions and I can do some basic prediction from that (e.g. UofL Coach Charlie Strong tends to coach up defensive positions really well, so even though they are in the bottom of the class he can improve them disproportionately, which makes the weighted class score even higher).
Top-down vs. bottom-up
There are two ways to approach the problem – to get more meaningful information to act on.
First is bottom up. Get more detailed information on every player and make better individual-level projections. Maybe Rivals.com has 1 player out of 10 different than ESPN, say a 3 star vs 4 star difference for a given lineman. Then I could try and spin all the pieces of hay in the stack into some kind of intelligence. Totally possible, but not our take.
Other option is top down. Let’s assume that Rivals and ESPN are basically the same – at least pretty close. One has U of L at 100th let’s say and one as 101st. I could go in and rank them by average star score. Or I could weight the positions differently (say quarterback vs. lineman). Or look at how they did compared to their conference/ market and national rivals / peers. Maybe assess whether their class plays to their coaching profile’s strengths or weakness.
In our opinion in any one of thoses far outweighs the bottom up approach. Let others do that for you. And if they do a good job, so much the better. But if I’m putting money down in Vegas, whether a given lineman on my team is a 4 or 5 star recruit is not driving my bet. Whether my team got the class they needed, and one they can coach up, at the direct expense of their competition, however, is.
At this point, I should draw out all the connections for you.
But I won’t.
There’s really no point.
If you get what’s going on in healthcare (entire locus of immediate profit is in Medicare Advantage and slightly further out Medicaid, zero sum games, using metrics with star scores, based on relative and absolute dynamics, playing in different markets and against still different peers), then you already get all the analogies and can see it all pretty clearly. Heck, we even used some of the healthcare terms in our sports and gambling story.
And if you don’t get all that, well hopefully you now have better odds of making a good bet on the next BCS champion.
“I’m thinking 5-team parlay all to cover?”
Pro tip: when you go to Vegas, take a healthcare person who understands Medicare Advantage, its STAR rankings, and how to change their bet when the line/rebate formula changes, then tag along with their bets.
An Open House at BoatHouse – You’re invited!
- or -
Louisville, Kentucky for (belated) Valentine’s Day Blowout
Looking to take that special someone somewhere they’ll really remember this Valentine’s Day?
A LoveBoat cruise, for your health care data
Well here you go!
Join us as we officially open up BoatHouse Interactive Analytic Studios…
RowdMap’s Offices, in the heart of Whiskey Row, Louisville, KY
… with an evening of the 4 “B”s:
Nothing says romance like brisket…
… well, maybe a good banjo
… and (paradigm) “B”-usting Healthcare data.
How many “B”s is that now?
So save the date: February 21, 7pm
And swing by RowdMap’s BoatHouse at 101 North 7th Street; Louisville, KY 40202
Or ping us if you’d like some more details: Josh@RowdMap.com
Federal Performance-Based Initiatives
- with -
the HHS and CMS Powers-that-Be:
A View into the New Value-Based Paradigm and What It Means
- for -
Your Profitability, Long Term Value and Stock Price (or Equivalent Metric)
- using -
A ‘tiny’, ‘Uncomfortable’ Device
Well, since the world didn’t end – either from the Mayan thing or the ‘Single Payer’ / Affordable Care Act thing – we thought we’d do a little post, since apparently we’re all going to be around for a while and the whole Value-Based thing is going to keep clipping on.
Now, many loyal readers have said, “RowdMap, we really wish you take your time and spell things out, go on at length and quit being so serious… and… we’d like a treat, something that mixes booze and candy.” Well, what can we say, we’re here to please…
This was a full fledged healthcare event, the World Healthcare Innovation and Technology Congress, all about Accelerating the Adoption, Implementation and Sustainability of Health IT. You know, held at the Ritz in Pentagon City, loaded with uber high level decision makers at the largest plans, hospitals systems, PAC, ACO and all the other acronyms along with professors at elite institutions. Heavily vetted suit-and-tie type stuff, sponsored by folks like Microsoft, Oracle, Verizon, Kaiser Permanente, etc. So, out of respect we’ll try to minimize our standard silliness in this post.
‘Silliness’ is relative, after all
Rather than expecting folks to listen to us blather the whole time, we’ve always found it more fun, and entertaining, to put together teams and this one had Bryan Sivak, The Chief Technology Officer of the United States Department of Health and Human Services (Todd Park’s very worthy successor), Niall Brennan, Director of the Centers for Medicaid and Medicare Services Policy and Data Analysis Group (the person behind not only things like Medicare Advantage but the newly formed dedicated information products and services business units) and Tom Morrison, Co-founder of NaviNet (acquired by Lumeris / Highmark / Independence Blue Cross / Horizon Blue Cross Blue Shield this year) and currently Senior Adviser to Leverage Health Solutions and even the illustrious Marshall Votta, who stepped in for Tom (whose own arc includes NaviNet and now Leverage with Tom as well as serving on RowdMap’s board of Advisers).
The illustrated avatar can only do so much given the source ‘data’
So a great group in general – but especially perfect for our topic: Federal HIT Initiatives to Accelerate the Movement from Volume to Value Based Care. The funny thing was this was basically the day after the election, so one might think the outcome might very well have dictated message and prospective impact. But, as we’ve explained before, the particulars of administration, legislation et. al. don’t matter – the value based paradigm (call it “reform” or whatever else you like) – is inevitable.
The only thing you need to remember about ‘reform’
Rather than going through point-by-point of the several fascinating doosies that were discussed, I’ll simply offer some summary observations.
Bryan and Niall are fantastic (Marshall’s not too shabby either : – )
But there’s a specific point to note about movement for data liberation. First, data liberation is merely one side of the performance or value-based coin. Programs like Medicare Advantage hang on the fact that the crucial data is public and that there’s real visibility across the market into checking performance.
Now just because data is public doesn’t mean it is being used. Remember such brilliant data as the Dartmouth Atlas for Unwarranted Variation sat on the shelf, with everyone ‘already having it’ until someone came along and created market value from it and thereby fundamentally changed the health care industry.
*Dartmouth Atlas for Unwarranted Variation in a nutshell
Now MA performance data, in some ways fundamentally based on the Dartmouth rubrics (even down to the file layouts), is pubic, but its meaningful usage not necessarily deeply penetrating the very folks that it measures (i.e. anything beyond the most basic pro forma use by the folks for whom it determines performance, rebates and even profitability).
Part of that is because data in health care has largely been ‘big data’ throughout the historical Fee-for-Service epoch (cf. the gap right between the Paleozoic an Mesozoic eras).
FeeforService-asaurus heading off into the sunset…
at the end of the CostSavings-ozic Era
Historically speaking, that paleontological data was either clinical – ultimately not so helpful for folks outside limited applications despite all the hype and promise or financial risk. Or the cretaceous data was financial – as the what the clinical stratification was often translated into something to predict financial trend and then pass it along to employers or individuals, with the risk broker frequently remaining performance agnostic (i.e. paid a fee for a service at the end of the day).
But, with federal value-based indicatives, such as Medicare Advantage, and the broader sweep into Medicaid, duals and even commercial and individual (exchanges, etc.), the federal Powers-that-Be have incentivized the market with both a carrot and a stick. The carrot being rebate and reimbursement, which ultimately means profitability and value (and stock price, etc.); the stick being contract consolidation as in a GE like fire-the-bottom 10% (and note this is more than an idle threat when one views the initial contracts consolidated last year as the first point of a trend).
The data behind the Post Ice Age’s value-based federal performance initiatives is ‘tiny’ – that is, calculated at the contract level. And this new data is public – that is, sitting out there for anyone to use, and just as with Dartmouth Atlas, waiting for someone to use it meaningfully and create market value from it. Ironically, while ‘Big Data’ is all the rage and buzz, mostly from folks without deep domain expertise, the data behind the volcanic eruptions that signal the end of the Fee-for-Service dinosaurs is ‘tiny’ – as in fits on a thumb drive.
We use Bossy Bear
(mammalian & a good personality fit)
Or course it’s not that easy. There are always challenges – and the data challenges of this era are about making meaning from the ‘tiny’ data, across grains, P&Ls, topologies (it’s no longer about size, speed, reconciliation or adjudication but dispara-tion, abstraction and business-driven taxonomy).
The good news is not only that the feds have incentives the market – but that the financial market has recently begun adopting this ‘tiny’ data value-based paradigm to evaluate the market value (stock price or your ‘non-profit’s’ corresponding metrics).
In other words, your performance in the new performance paradigm not only controls your profit, but also your stock price – and financial analyst calls are now drilling into this in great detail.
“What is your Medicare Advantage projection by metric? How will you compete? Using what performance strategy? What is your bid/rebate strategy? How are you using your performance profile to inform your growth strategy while balancing sustained profitability? Based on what data to support your conclusions?”
So secret we shouldn’t even show it to you
(Psst… It doesn’t matter if you’re non-profit)
Major financial houses making buy and sell recommendations based on your answers to these questions. Directly affecting leadership and operations.
Hope you’ve made the investment – and not in that Claims-o-lithic system re-packaged for the post-ice age thaw.
If you have it’s very good times ahead. If not… bad news is they know your name:
“Oh… I get it. Frick.”
One other uber kicker – slightly esoteric, but something to think about. These new performance metrics make a zero-sum game. Your competition goes up, you go down, and vice versa. If you go down, so does your stock price and even your future prospects.
In other words, not only is not competing not a strategy, your competition can affect your stock price in a new, specific and powerful way. The good news is that you can do it to them before they do it to you. How do you like them apples?
The other point to note from this conference session is that regardless of the election, this shift is real and continuing and accelerating. Don’t believe us? Take a look at the M&A activity and try and come up with a alternative market thesis.
Next point; the shift is not merely something that flowed from Todd Park. He’s definitely the bee’s knees.
… we’re taking Todd Park over Chuck
But the HHS and CMS bench is uber deep with some of the finest folks we ever had the pleasure of knowing, much less speaking with on these topics at these types of events.
Final point. This is a huge shift. The legacy re-wrappings, or rehashing of the old era’s efforts and hallmarks (big data, machine learning, algorithmic hamster wheels) aren’t nearly as applicable. They’re great for marketing materials and checking boxes on a big org to do list if you’re predicting financial trend and passing it on while remaining performance agnostic (trust us, we’ve been there, done that with the best of them).
Would be far easier if folks wore buttons…
… or their ‘platforms’ had badges
But if you’re going to compete based on performance, against your market competition, and peers. And your going to try and do it while throttling your organic growth and being very smart about your inorganic options, all while building your value over time, well then your going to need something very different. Something purpose built for this new age. And that, and the folks that bring it to you, will look and feel different from the fossil imprints. It even may be quirky, simple and ‘low-tech’.
We call ours: Health Profit Intelligence
At this conference, we put our slides/message/information/data on a quirky little device – an old-school View Master. The images were tiny. You had to squint, to look hard – really think about what you were seeing.
Note this was the polar opposite of most other presentations with uber data gonculators and neon light shows…
Newest HIT / Data / BI / Big Data ‘app’ demo…
… at an HIT event near you
… or the typical Best Practices / Case Studies / Lesson Learned from Uber-consultants:
Prototypical HIT / Strategy / Management / Data consultant…
… premium price due for the “Genius” title
As silly as it was to have folks in silk suits at the Ritz in a session on the future of HIT looking through little plastic children’s toys…
… the feedback was tremendous.
Very high levels of engagement…
… and this was after 3 days of ‘conferencing’
Some folks were merely entertained.
Some caught the analogy – that competitive advantage in this new paradigm should feel different and requires going outside the traditional hallmarks of the previous age, even if it means going outside your comfort zone.
Indeed, it should.
Wait, stop the presses. We can hear you saying already: “RowdMap, what about the booze & candy thing you promised?”
Okay, okay. Since our ‘tiny’ Data Freud finger puppet contest went over so well… here’s the next one:
Seriously, these are real….
… and we want to buy stock
Send us a note, comment, antidote or story about Federal Performance Based Initiatives and if it makes us smile or spit out our coffee we’ll send you a surprise that will make surviving the Mayan/Single Payer Apocalypse a little bit sweeter.
Not to long ago, we spoke at a comp sci and HIT conference all about the Meaningful Use of Complex Medical Data (MUCMD), chalk full of rocket scientists and did an interactive game session as well as a presentation entitled, “It’s not the Size but What You Do with It: ‘tiny’ Data and Business Value in a ‘Perverse’ Market.”
While most folks were focused on Big Data, we talked about ‘tiny’ Data, and gave a monster explanation here, using Netflix as an example of the limits of big data in healthcare.
You can find the slide at SlideShare here, or embedded in the post below:
This is pretty much geared towards engineers and very smart folks doing big data, especially folks starting out in the space (big of small). So it sketches out how to go about evaluating HIT and start up opportunities, comments on the VC / Accelerator options and drivers, then makes a case for the uniquely, often perverse, drivers in health care. It goes through the massive change on the business side of health care (P4P for payers too, note just providers) and talks about how the demographic shift is driving the government incentives that are shifting the market value. Finally it addresses the data behind this New Value Paradigm: ‘tiny’ Data and shows some ‘head-to-head’ difference between this and the sources of the current big data bubble in healthcare (as well as exploring some of the reasons for that bubble).
But wait, there’s more.
Here’s a glimpse of some of the sausage making (and a data-driven member engagement example, if you will).
We put these slides out in various channels, like SlideShare above.
When we first put this up, we did it with a minimal (boring) slide template and had about 5 views.
Then we changed the picture to a little Freud puppet…
You know, this guy
… and had about 200 views in 5 minutes, even getting hot on LinkedIn
Funny, huh? LinkedIn, who would have thought?
… and making SlideShare’s front page, which in turn drove even more views/engagement:
That’s the little guy!
(red arrow above)
Now, this doesn’t necessarily speak to the quality of the content (in a previous life, we had 10,000 YouTube views of carving a giant gummy bear – Thanksgiving-turkey-style, for Valentine’s Day, so, uh…)
But if folks don’t look at the message / intervention, they’ll never learn / perform and action.
In this case, it meant having a specific business goal, taking an action, looking at the data (for good or for ill) and changing even something as silly as an approach / hook / wrapper.
And then of course looking for change and most importantly, learning.
For here on out, we’re all about silly pictures and little Freud puppets : – )
And if you’re really interested in working the process, pushing it a bit further to create even interaction.
* Note 1: the ‘data’ behind this example is very, very tiny (it’s not the size but what you do with it).
* Note 2: won’t bore you with rambling, but think about the analogy and DIY it yourself
* Note 3: if you’re interested, ping us with what you’d do with him and we’ll send you the Freud puppet!
It’s a finger puppet – ‘tiny’, get it : – )
Unleashing ‘tiny’ Data – CMS, ONC and VA, ‘Oh my’
Why Economics Determines almost Everything
… psst …
Economics is Basically Demographics
Usually we don’t do guest posts.
Our stuff is sort of ‘audience specific’ – that’s a nice way of saying a little too ‘out there’ for most places, and we don’t want to sully our friends’ fine reputations.
Also, rarely is there something that really forces us to come out of our cave and sort of calls out for extra attention and explanation (e.g. something that’s really valuable with an importance that may not be readily apparent at first glance).
Well, the conference below is one of those things. We feel it’s one of the most important conferences in the health care space – seriously. The reasons for that claim may be a little beneath the surface, so we attempt to do a little diving and explore that in the post – and the fine folks there were gracious enough to share our little post here.
It’s also below in its full glory (with pictures : – )
We were graciously invited to speak at the Workshop on Health IT and Economics (WHITE), a production of the Center for Health Information and Decision Systems (CHIDS) of the University of Maryland’s Robert H. Smith Biz School as well as the Agency for Healthcare Research and Quality (AHRQ), a federal agency tied to National Advisory Council for Healthcare Research and Quality and the Department of Health and Human Services.
What separates WHITE from from most academic of HIT-ish things is not just the notable HHS / CMS / ONC / VA ecosystem, but that it’s about as interdisciplinary as its gets.
We ended up addressing the data behind all this, alongside an interdisciplinary crew:
Niall Brennan, Director, Policy and Data Analysis Group, CMS
Basit Chaudhry, Medical Scientist, IBM Research
Seth Eisen, Director, VA Health Services Research and Development (HSR&D)
Joshua Rosenthal, Co-Founder and Chief Scientific Officer, RowdMap
Moderator: Jennifer King, Acting Chief of Research and Evaluation, ONC
But before we get into the data, let’s take it from the top. In other words, the conference takes economics serious (hey, it’s in the title). Which means that it’s socio-economic in it’s scope, which means that demographics is uber important.
One one hand that’s obvious, aging populations, under-served populations and all the other important stuff you’d expect.
Where it gets interesting is where that demographic shift meets the market (i.e. Medicare, Medicaid and ACOs and the commercial changes like the ACA’s impact, defined benefit/contribution, exchanges and all that).
So let’s do a bit of policy. As the population ages, the trend is unsustainable and barring a Single Payer, that means engaging the market and trying to create improved outcomes and impact, both clinical and patient/member experience, using financial incentives. The current form is Medicare Advantage (aka STAR) but regardless of form that will expand, one way or another (Medicaid, MTM, D, Commercial). No ifs ands or buts. The demographics is driving the economics, which is driving the market… and, in turn, the data.
For the academics, here’s a fun little interactive population pyramid gadget to play with:
(draw your own conclusions)
For the biz students, here’s a quick test about that’s shift’s market impact:
5-minutes Healthcare concentration MBA
For our part, we did a little thing on the data behind this – the ‘tiny’ data – and how it’s very different from the Big Data that powered the previous paradigm (Fee-for-Service).
Now, that’s breaking news for the folks in the room – they make policy decisions based on action groups (contracts, cohorts, populations) which means that data is aggregated, so they’re all well aware.
But the extension of this is where it gets interesting. In an effort to keep things fair in the new Zero-Sum performance game, folks need to compete against their peers. Sure this relativizes historical advantage but it also makes the additional ‘tiny’ data (anything at the ecological or geographic level) incredibly important for the policy/rebate/incentive side. On the market side, this data is paramount as (smart) folks will use their inherent strengths to compete against their peers in different geographies. It also means that (smart) folks will try and mitigate their inherent weaknesses against their peers.
The market upshot is that they ‘tiny’ data is now the currency of the currency – whereas before it made for ‘interesting’ research questions and served as fodder for dissertations, it is now driving the market – who will grow, who will lose find themselves on the wrong side of consolidation and who will essentially be paid via rebating to make a land grab.
The social / public good upshot is that these incentivized market forces are now turned to improving specific performance metrics (tiny) for specific populations (tiny), essentially transforming the secondary market (risk where big data was in the service of clinical / financial stratification), transforming perversely ‘neutral’ parties into meaningfully participants in the healthcare delivery system.
One of those rare win-win scenarios in the space – the smart folks who are both intelligent and aggressive will get paid, at the direct expense of their less-intelligent or more complacent competition (‘peers’). By “intelligent” we mean folks who understand their ‘tiny’ data and ‘take advantage’ of it and by “aggressive” we mean folks who act specifically on these ‘tiny’ (local) action groups to improve clinical outcomes and patient / member satisfaction using their absolute ‘tiny’ advantages.
The research academic upshot of all this, is that just as (smart) businesses (primarily payers) are now shift their focus to the tiny data that powers the new market (even if it means disrupting themselves and investing in areas outside of their historical infrastructure), academics are a little slower in the adoption (a natural occurrence considering the distinct market vs. research adoption curves). The good institutes and research centers will (are already) starting to shift their own resources to focus on this new data and these new questions.
The good news for academics, is that they already have a number of good cards in their hands and have already sort of done this thing before. All that Dartmouth Atlas stuff, in considering specifically defined metrics and comparing them to specific aggregated groups across geography is the basis for a chunk of the ‘tiny’ data and New Value Paradigm. They may know it by a different name, with different nomenclature, but the good news is that far from relativizing that sort of historic research (back then geared to the market via cost savings), now it’s even more important geared to contract performance (likewise, a map, er Atlas). Time to dust off all those “ecological” studies and “topographical” models.
The reaction? Incredibly positive. There’s nothing like sharing with policy folks that they’ve already laid a fantastic foundation and played the real-world cards the have in the best possible hand the could come up with. Nothing to generate a great response with academics as to explain that their research is even more relevant, provided they give it a twist or two. Finally, nothing like pulling together the policy drivers, the market forces and the research impact for an interdisciplinary gig.
And even the most serious of folks seem to respond well to the Freud puppet.
A natural fit for an interdisciplinary conference
Okay, this is an admittedly ‘weighty’ post compared to our typical schtick.
But in the research-driven spirit of all this, we’ll leave you with our favorite graph ever about the limits and motivates for far too much analysis and research, admittedly from a silly (or incredibly serious depending upon your perspective) post on the decline effect, but nonetheless sums this all up:
In case you can’t read the caption from The Last Psychiatrist:
“We were surprised to find the data fit well within the two axes. Further research is needed.”
The Morning After:
- or -
RowdMap at the World Healthcare Innovation & Technology Congress
The Day after the Election with CMS and HHS Folks
Talking about Federal, Value-Based, Initiatives… & Stuff
We’ve saved you a spot
Howdy. There’s this election coming up. Lots of interest in it from the health care space.
We’re big fans and voted early
(#10 still has our support)
But it won’t really affect healthcare. As we’ve explained elsewhere, that ship has sailed, and it’s demographics powering it down the inevitable value-based, pay-for-performance road, despite whatever twists and turns the journey takes.
Navigating the twists and turns is part of the fun. And so we invite you to a morning after party. Day after the election, we’re in DC speaking at the World Healthcare Innovation & Technology Congress (WHIT), one of the swanky major industry events.
Yes, he’ll be there too
Sure they’ll have some interesting things to say.
Topic is on federal… uh, value… um… something, uh, initiatives…
Oh, never mind, just tune in for some fun and games… and surprises!
You won’t want to miss this… (we’ve been known to put on a show), so join us there or check back on the blog.
Okay. Since you asked, here’s a hint:
Seriously, this is a great hint.
‘tiny’ Data, Netflix & Healthcare’s Big Data Fail?
- or -
‘tiny’ Data and the New Value Paradigm
- and -
What Neflix’s Failure can Teach Us
- about -
the Limits of Big Data in Health Care
Above – the most important screen for HIT
Big data is all the rage.
We just finished speaking at Meaningful Use of Complex Medical Data (MUCMD) at the Saban Center at Children’s Hospital of Los Angeles.
There are worse places to dig for big data than Hollywood
We mentioned before about the ‘hardcore’ nature of the folks who attend this and found ourselves alongside all the rocket scientists (literally, the JPL & NASA folks), along with the Big Data gurus (Cloudera & Hadoop) and a host of the health care data academic (MIT, Harvard, Hopkins, Cal Tech, et al) and pure clinicians (National Institute of Health) all looking to unlock the power of big data for health care.
Yes, we had a ‘class’ picture!
Back Row (From Left) Susan Murphy, Roby Khemani, Hector Corrada, Dan Lizotte,
Dave Kale, Katrina Ligett, Warren Sandberg, Benjamin Marlin, Josh Rosenthal, Peter Szolowitz
Seated (From Left) Joydeep Ghosh, Noemie elhaddad, Katherine Homann,
Carla Brodley, Randall Wetzel, Heather Duncan, Peter Van Manen, Suchi Saria
The talk was entitled: “It’s Not the Size but What You Do with It: ‘tiny data’ and Business Value in a ‘Perverse’ Market” and then we followed it up with an interactive game session entitled “Meaningful Business Use of Clinical Data.”
The topic? Big Data, of course. It’s a hot topic right now. When Big Data is on the cover of the Harvard Business Review it’s officially a mainstream fad. In fact, HBR just named “Data Scientist” the “Sexiest Job of the 21st Century.” (No, we’re not making this up – seriously. Aside from any issue about confidentially projecting out the next 88 years, one can only imagine the nature of the ‘research’.)
Consultants love it. For them it means a lot of billable hours building systems without specific business goals, simply to find ‘insight’ – that’s one company’s vision of a smarter world.
Whoops – wrong logo
Healthcare legacy folks love it too, because it reminds them of the time their business was run around claims and how that gave them an absolute advantage in preserving status quo.
Historically speaking, not an effective strategy for capitalizing on change
Young tech start ups love it because it allows them to keep the business model simple: “be smart, look in folks’ data, find valuable things, share” and avoid the whole ‘product’ or ‘defined business need’ thing (double bonus for silicon VC and media, who love this because it is health care AND data. Get it?… can’t lose).
Dude, we’re totally into uh, HIT, bro
And of course everybody loves it in general because it’s Big (not ‘small’)… just like a Smart phone is better than a ‘dumb’ one (note the same thing works with a bunch of other adjectives but smart and ‘big’ are the classics, appealing to different issues with their own literature).
Yes, him again
So RowdMap spoke at a little comp sci conference on Big Data (done something like this at MIT, Harvard and elsewhere). We took a different tact, talking about the limits of big data, and more importantly how the new data source of the New Value Paradigm in healthcare is all about ‘tiny data’.
Tiny, the new ‘big’
(PS we love Tumbleweed!)
The funny thing about all this is that the healthcare system has a new business model, one around a new value paradigm where plans, hospitals and others compete on metrics form Medicare (soon Medicaid and everything else). The data for the new business of healthcare is ‘tiny’, fits on a thumb drive – and it has different problems. It’s not as much about size or speed or reconciliation, but about making meaning information for the specific business problems: how do I grow my business against my market competition, how do I improve my performance against my peers and how to I create value for my members and my boss/shareholders?
What happens if you actually catch what you’re fishing for?
This isn’t a big data problem, requiring a fishing exploration or mining for golden nuggets. It’s a business discipline problem that requires a purpose built product to manage your business intelligently (using data for more than ad hoc-ism and more than traditional risk stratifications, but rather intelligently allocating resources, using interventions and pricing and bidding). The key is that this isn’t an academic exercise where you start with ‘cool stuff’ in the data then figure out how to use it – that doesn’t work (and note this isn’t just the standard playbook for academics but a host of BI folks and healthcare execs, partially because they’re interested in the problems for their own sake and have build organizations, and business models, based on this sort of exploration).
We did a session on this for our friends at CMS/HHS and IOM, all about how to turn data into relevant information for the New Value Paradigm rolling out from Medicare and Medicaid to MTM, Part D and even Commercial. We did a little game with folks (did something similar at MIT and Harvard) – all to great response:
“They put on a graduate level seminar that had crowds coming up to us saying this was the best session of lives.” Todd Park, United States Chief Technology Officer.
So of course tried it with the big data comp sci folks at MUCMD.
Likewise to a fantastic response – and it showed folks how very different the exercise is when you start with a business goal, then bring the data to bear on it (vs. the fishing approach). It’s a different process, takes different skills, and frankly has a much better success rate.
In a nutshell, if you’re after PR or want to do something cool, new and sexy, then we’ll gladly refer you to a host of other folks, conferences, debates & discussions, reading (both academic lit and market blurbs) and general go-ings on.
But, if you want to create strategic value in healthcare, you need to start from your business goals, and define the problem in a way that you can actually act on it (i.e. get up and running asap and tie specific actions and interventions to the data) – and this means you need a purpose-built platform, not an idea, a white paper, a research project, or an IT initiative. Oh yeah, if it’s intuitive, personalized and even beautiful, then that’s a bonus. Double bonus if you can pull it up and answer your key questions in a meeting on the fly on your iPad at the snap of your fingers.
RowdMap’s take is to do all this with something that’s real, and up-and-running, today. A platform that allows you to do it all very quickly in a web-based data-system that has national, market and peer-based benchmarks so you can see your realistic opportunities to maximize the value of your business by increasing Growth (organic or exploration for inorganic opportunities), improving Performance from chronic to wellness to customer satisfaction (apples-to-apples as this is, after all, a zero sum game) and creating Value through price/bid/rebate and contracting.
The RowdMap Health Profit Intelligence (HPI) platform is currently loaded with all this, for every single payer, hospital, nursing home, etc. All your market data, your performance data, your key driver data and even social and Sentiment data, all organized into meaningful information (indexes, peer-benchmarks, predictions, action groups, etc.) and specifically designed to tie your information to specific, concrete action (sales, marketing, clinical, financial, etc.) all at various levels from member to contract to enterprise.
Oh yeah, your competition’s data and information is in there too – all baked up nicely and on a platter – crazy stuff – you wouldn’t believe it.
Thanks for reading.
Oh wait, Netflix, that’s right. What do they have to do with this?
Well, back at the beginning of some of the big data craze, crowd-sourcing become very hot. Netflix was the go-to example for anyone who had read a Malcom Gladwell book (i.e. executives, hipsters and the TED-erati). You see Netflix wanted to improve their recommendation algorithm, so they released sample data and had a contest giving $1MM to anyone who won. Lots of PR and press from all the usual suspects (try to find a TED talk without mentioning it, we dare you).
Classic big data exercise. Bunch of data, find a better algorithm and use it to improve a business ‘thing’. And classic big data hype. Of course it failed. In a sense. It showed how cool and innovative Netflix is and they more than made their money back in PR and brand recognition. And it highlighted the fact that they have all this big data, which should be an advantage. But they didn’t use it. See, even though they were trying to use data to solve a real biz issue (make recommendations better), they didn’t make it a requirement that the results be operational. In other words, it was completely unfeasible for them to try and deploy the solution in the wild.
A couple of things to note. Netflix is smart. Very likely, smarter than you or the folks working on your big data or considering it. If Netflix failed to get something that they can actually use, what are they odds that you will? Maybe it doesn’t matter, if you’re after PR or showcasing that you have data, regardless of how well you can use it. And note that Netflix’s data is directly related to their core business model in a specific concrete way – whereas the same isn’t necessarily true about your legacy data in healthcare’s New Value Paradigm… psst remember it’s not claims or E/PHR but performance and payment metrics at the contract level – ‘tiny’ Data.
Other thing to note. The operationalizing of this as a requirement never occurred to Netflix, even though they were incentived to actually use it. What are the odds that your internal team or consultants, who have very different interests and incentives, will ensure that your data project isn’t a complete scratch. In the interim of course, you can have analysts try and weave files and use XL, SAS, R or Tableau to tie the spaghetti together.
That’s why a Product is helpful. A platform-based Software as a Service (SASS) product means that the thing is up, ready running and designed to do what you need it to.
Size, complexity and fishing are not the solutions to running your business and creating value in the new paradigm. The solution is a purpose-built platform.
Friends at HHS/CMS/IOM asked us to do a show and we pulled together an all star cast from throughout vastly range of pockets in the industry.
Reaction was so positive the US CTO said incredibly nice things about it during some public testimony, evidence of the nature and sophistication of the data and need to provide an educational layer around it as part of the liberation efforts.
You can find the slide at SlideShare here or embedded in this post below:
They are a little silly, so here’s some more context.
The session was all about how to turn data into actionable information, something easier said than done judging by our history as an industry and the failure rate of health care start ups, using data.
Rather than simply amassing data or playing around with cool visuals or tech, we started form the other end, identifying market opportunities then matching them with the data as an app/product/business.
The session was all about practicing this and had a portion of traditional presentation (Strategy), then some examples of industry leaders turning data into info to solve specific business needs (Practice), followed up with the Games.
The Games had participants filling out Mad Libs and doing some Speed Dating, aided by White Hats, at the mercy of Judges, eating cotton candy, dodging Cracker Jacks whizzing by and dancing to some pounding electronic music… you know, your typical health care affair.
The slides are from the Strategy portion and sketch out how government has created access to data and incentived the market – but… the key to this whole thing working is around the market transforming the data into information that creates real value… and that’s the key whether you’re a historical icon in the space, a young upstart bent on taking the world, or someone who simply want to make it a better place.
FRIENDS & ACTIVITIES
TagsAcademics BBQ Big Data Bluegrass BoatHouse Interactive Analytic Studios Bourbon Breakn' In CMS Comp Sci Critical Thinking Demographics Economics H@cking Medicine Health Data Initiative Health Informatics HHS KDI Kids Knowledge Discovery Infrastructure Life Market Map Medicare Advantage MIT Navigating the System Office ONC Paradigm-Busting Healthcare Data Party People Policy Public Speaking RowdMap Slides Tiny Data Updates What Matters