Hope for Healthcare Open Data

Early Innings

HealthyHive’s (www.healthyhive.com) open data project is making modest in-roads in proving how public-private initiatives can come together to drive education and transparency for consumers looking to manage rising out-of-pocket healthcare costs.  Our story is like many entrepreneurial stories out there; an unwavering conviction that our service/product creates value for multiple stakeholders and the world should have already caught on to what we are doing.  We should be registering users in droves, while along the way figuring out a way to monetize the “eyeballs” to create a sustainable business.  After all, we are offering a service that can literally empower millions of Americans, so why wouldn’t we create even more buzz than those sophomoric concepts that fetch billion dollar valuations before the founder turns 20?  Well, it’s actually not that easy – in fact, more than three years into this journey, we’re still wondering if the consumer actually cares about what we are doing.  Are we too early?  Is the space just too damn confusing that consumers don’t know where to begin?  Does the fact that none of us are healthcare policy experts mean we are just plain missing the mark?  Like all entrepreneurial efforts, the path is lined with ambiguity, confusion, frustration, and at times despair.  Yet the passion and conviction are what pushes us forward.  The fact that we are talking about such a complex space actually encourages us:  If our system comprises twice the percentage of GDP compared to other developed nations, and those nations have longer life expectancy, we only need to make a dent to gain traction.  External forces are our friend – cheap computing power, rising deductibles due to the inexorable rise in insurance premiums, and finally, policy that pushes the advancement of open data.  We often hear that if a trend is in the early stage, it is said to be “early innings” using the baseball analogy.  A 9 inning game can last a long time.  So our belief is its very early…“Spring Training” early…for open data in healthcare.  Spring Training is about finding the swing, dropping a few accumulated pounds, re-gaining that lost step down the first base line, and for pitchers, finding the low strike zone.  In short, it’s about “not letting perfect be the enemy of good”.

From Public to Private Sector:  Open Data in Action

So how are we using the healthcare open data?  The core of our site leverages the Medicare Provider Payment & Utilization data to allow consumers to compare the Medicare allowed amount for over 6,000 procedures.  These procedures are referred to as Current Procedural Terminology codes, or CPT® codes for short.  The first curve ball we faced was that technically this data set is not 100% liquid and open data.  The reason is the CPT® codes are the property of the American Medical Association.  In order for us to publish the CMS data along with the CPT® codes, we need to ensure we are not in any intellectual property violation.  (That would not be a good thing for a start up with modest resources.  Talk about “not getting out of the batter’s box”.)  The encouraging news is we have secured a license for consumers to access the consumer-friendly code set after considerable effort from us and the AMA.  We believe the CPT® codes are one of the keys to tying it all together because it gets to the atomic level of what we all as consumers of healthcare do – we receive thousands of different services across dozens of service categories/specialties.  So if we can drill down to the service level, we enable the consumer to compare costs across local providers.  If an MRI for one provider is 50% higher than the same MRI for a provider 4 miles away, that is extremely relevant for consumers.  But before we can just assume that we’ve found the Holy Grail, it is critical to note that 99.9% of the American population have no clue what a CPT® code is.   This point cannot be overstated because until the consumer knows about a CPT® code, he or she won’t know where to begin.  But once armed with the simple knowledge of what they are, they can begin to navigate the maze with a reliable compass.  As it stands today (February 2015), we link all procedural codes to over 820,000 individual provider profiles.  (We categorize providers by their specialty denoted by the NPPES national database.)  When a consumer clicks on an individual code, the next page lists all providers that have performed the same code within a 20 mile radius to the zip code entered by the consumer.  From there we display the relative Medicare Allowed Amount based on the average allowed amount for providers listed in the 20 mile radius.  Here is a screen shot of a particular procedure:



Depending on the relative allowed amount, the dispersion can be considerable.  A quick ballpark estimate of the potential savings to the consumer is to take 20% of the relative allowed amount.  The 20% comes from the coinsurance obligation patients in Original Medicare need to cover.  The highest relative allowed amount for the above procedure was $236.36 and the lowest was -$61.34.  So the extreme example for this procedure would be an estimated cost savings of $59.54 (20% $297.70).   The total out-of-pocket cost for the consumer will depend on how much of the annual deductible is left.  We would love to be able to develop a read-only API for consumers that could show how much of their annual deductible is left.  This would allow for a more precise cost savings estimate.  So if anyone knows who the powers that be are at CMS, please contact us!

Inpatient Example

If someone is going for a costly procedure, it is well worth taking the time to explore.  Even in the competitively priced world of Medicare, there can still be vast differences in out-of-pocket costs.  One study we ran was to look at the range of costs at the procedural level, the amount of times the service was performed at each hospital, and finally do a comparison of the consumer assessment results.  Consider a major joint replacement in New Hampshire:

  • The average out-of-pocket cost difference between the two hospitals that performed the highest number of these procedures (combined they accounted for 40% of the 2,310 total state procedures) was $1,150.
  • 95% of respondents rated the lower cost hospital 7 or higher while 94% did for the more expensive hospital.
  • While the lower cost hospital realized less revenue for performing this procedure, it actually did more of them. In simple terms, the more someone does something, the better is it assumed he or she gets at it.  Call it experience or whatever, but we think the “market share of service count” is a lot more important than the market share of dollars…what’s that Warren Buffett quote?  “Price is what you pay.  Value is what you get”.


Another set of data we present to consumers is the Hospital Consumer Assessment of Healthcare Providers and Systems results.  These data are essentially high quality ratings that in most cases have a respondent rate of at least 300.  So we would argue the survey data is much more relevant that any ratings site.  These are detailed survey results completed by verified consumers that received an inpatient service.  This is critical as it allows consumers to also consider quality of care.

Profit Opportunity

From the pure capitalist perspective, there is something compelling about creating a business where the input costs (the open data) is free of charge and “all” that needs to be accomplished is to refine and provide access for easy interpretation in order for us to find modest success.  The more open data we come across, the more we want to harness and integrate it with the consumer experience to drive more value.  But there comes a point where we ask “Is that too much?” “Will people care?” “Does it confuse the matter?” Etc.  At the end of the day, we will know what works and what doesn’t once we get a large enough number of registered users from whom we can generate feedback.  As it stands now, our revenue model is advertising-based.  It is our hope we can avoid charging a monthly access fee, but we need to test the existing revenue model to assess its sustainability.


Like spring training, it is about experimenting a bit and getting feedback from the coaches.  So we are extremely excited to be experimenting with all and any open data out there.  We are also hoping to receive feedback from the public and government data experts for ways we can create as much value as possible.

Open Federal Data as the Foundation…The Best is yet to Come

Perhaps most exciting about our Medicare open data footprint is the fact that it lays an amazing foundation on which we can build a durable platform at the local level.  Several states have all-payer claims databases, with which we hope to complement the federal data.  We will be working on the NH public claims file over the next few weeks.  We look forward to keeping our Granite State friends up to date about our progress.  NH is the home state to two of us founders, so there it is fair to say we are particularly excited to embark on this project.  The folks at the All Payer Claims Database Council in Durham NH have been extremely helpful in providing insight for us.  In addition, the NH law makes accessing the state file extremely consumer and business-friendly.  If our experience in NH can be replicated in other states, we may just have a chance at making the regular season roster.

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