Report OPEN HEALTH DATA MOVEMENT: Adolescence as Transformation and Disruption RowdMap www.RowdMap.com Open Health Data Movement Health DataPalooza brought together thousands of people from academia, government, and the public sector, all of whom are radically committed to one goal: promoting access to and the innovative use of health data to increase the overall health of Americans and to improve the delivery and quality of health care. RowdMap was smack in the center, sponsoring the event, organizing the technical track, moderating sessions across analytics, visualization and business applications of the new data and receiving a shout out from NPR about our take on the adolescence of the Open Health Data movement. But the real power of the event was around how others are jumping on the train towards using government data to run government businesses in order to create market value and improve public health. This means transformation for some, but disruption for others. The Open Health Data Movement is gaining steam. Not only have a host of new technologies, products, services and business started using open data, businesses have found unexpectedly powerful uses of this data, transforming those with business models nimble enough to accept and adopt, while disrupting others unable to escape their own gravity. Read on to see what's going on with all this and how it will The Open Health Data Movement is transforming businesses with models nimble enough to accept and adopt it, while disrupting others unable to escape their own gravity. affect you. RowdMap www.RowdMap.com Pag e |1 Adolescence, A Time of Change The open data movement is coming of age and it turns out that maturity means outperforming a number of traditional Fee for Service models. For example, David Wennberg was on hand to showcase new research using longstanding, well-known and widely accessible data sets with new impact. Wennberg, CTO of the Dartmouth Institute for Health Policy and Clinical Practice, recently published an article in the British Medical Journal entitled, "A population health approach to reducing observational intensity bias in health risk adjustment." He demonstrated how a traditional public data set, from the Behavioral Risk Factor Surveillance System, actually outperforms claims-based risk models for government programs such as Medicare Advantage. Wennberg delivered a presentation uncovering "a fundamental This public data set outperforms claims-based risk models for government programs such as Medicare Advantage. flaw" in observation bias, something that affects data from both claims and Electronic Health Records. Rather than leaving us high and dry, he went on to demonstrate a better approach using public government data. In some ways this is even more groundbreaking than the work on supply driving demand with the Dartmouth Atlas for Unwarranted Variation or the cost and experience work around End of Life care. Claims and EHR based models have a fundamental flaw around observational intensity bias. This public data set opens up a better approach, one grounded in population health. For those who can apply a population health approach, this data has potential to transform risk modeling, opportunity assessment, resource allocation and intervention prioritization. One notable application comes in the form of minimizing the "data delay" of traditional claims or EHR lag when beginning to work with a new population of members of patients. RowdMap www.RowdMap.com Pag e |2 Such a use of this data has far reaching potential to disrupt with staggering impact as claims-based models were the traditional default of the Legacy Fee for Service system and the base on which virtually all traditional industry leaders have built their methods, systems and platforms. Transformative Disruption from New Data Transformation and disruption from traditional public data is only part of the story. Perhaps the greatest potential for either comes from newly released data. This year's Health DataPalooza came on the heels of two major data releases. After 30 years of litigation from physician groups, CMS released two massive data sets covering millions of providers and naming names spanning payments, practices and prescriptions. CMS released data covering millions of providers, naming names spanning payments, practices and prescriptions. Of course, this made typical headlines in mainstream media around things we already know - cf. The New York Times and Wall Street Journal explaining how some doctors prescribe more than others. But that's just the tip of the iceberg. Using this data, combined with additional sets like the Dartmouth Atlas, you can see actual practice and patterns. You can tell which doctors are operating within geographic norms You can see actual practice patterns and tell which providers are within geographic norms and which are outliers. and which are outliers, either positive or negative. This data shows a picture of the natural topography of the landscape of care and how the patients flow between providers. This gives all parties visibility not only into the contracted networks, but what's actually happening on the ground as individuals follow geographic, topological paths, often the routes of least resistance. RowdMap www.RowdMap.com Pag e |3 Finally, this data allows you to start with population benchmarks, working top-down from the patterns of care, looking at how some geographic areas have large pockets of unwarranted variation and much higher associated costs, then drilling into the details against which you can compare any provider in the nation. This sort of approach was a hallmark of research in university settings decades ago and proved remarkably effective. But it was limited by the nature and scope of the available data, usually coming from select hospital or provider groups participating in specific studies often with conflicting methodology. Now, thanks to HHS, you can apply this type of approach to the entire US population using publicly available data sets. Specifically, you can use the new Part B and Part D data releases, informed by the Dartmouth Atlas, to determine the key markers of care along a funnel. You can then determine how a given geography, network or provider is doing compared to how they should be doing - whether a provider is habitually practicing or avoiding unwarranted surgery or over prescription. The kicker is you don't have to come up with a fancy methodology, but simply use standard CMS definitions and you don't have to dig through claims or embark on a massive EHR project, but simply use the new data sets that CMS publically You don't have to dig through claims or embark on a massive EHR project. released. That allows you to score providers out of the gate using CMS benchmarks and indexes. On one hand, in less than savvy hands, this information could paint incomplete or inaccurate pictures, which was what the AMA stated as a concern, and indeed some of that has happened. But the data is so powerful that as of late the AMA has become much more positive about using government data for transparency in government programs. RowdMap www.RowdMap.com Pag e |4 In some ways, this newly released data has the greatest potential to transform or disrupt. In any case, it has the potential to radically transform the business model paradigm of plans interested in intelligent growth, purpose-built products and curated networks. For providers it means opportunities for immediate visibility into a network, group or individual provider for selecting risk and payment models, defining and optimizing a network from general practitioner to specialist to skilled nursing facility and identifying and managing leakage. For organizations committed to preserving legacy infrastructure, whether grounded in technology or personnel, this data has For organizations committed to preserving legacy infrastructure, this data has unprecedented power to disrupt. unprecedented power to disrupt. Innovate or die; embrace and transform or resist and disrupt are classic tropes. In perversely incentivized markets, such as healthcare, resistance and preservation sometimes win. At this point in the Open Health Data movement's maturation, however, the train may already be out of the gate. #Hdpalooza Technical Track The technical track of HDI was held against the backdrop of a steady stream of newly public data releases. Then Health and Human Services chief Kathleen Sebelius announced another major breakthrough in the health data movement at this year's Health DataPalooza , the FDA's newest health data initiative, openFDA. According to the organization's press release, "openFDA will encourage the innovative use of the agency’s publicly available data by highlighting potential data applications and providing a place for community interaction with each other and with FDA domain experts." With this context of a rolling train of data releases, the technical track focused on using this new data to transform both extant RowdMap www.RowdMap.com Pag e |5 and new technologies and the products, services and business models that they are supporting. One of our esteemed co-founders, Joshua Rosenthal (did we mention Chief Technology Officer of the US, Todd Park, called Josh a "Visionary Genius" in his key note speech), organized the event's Technical Track. The goal of the tech track was not to be all about Apps, but about how government, research, academics, policy, and the public market are coming together to use health data in a meaningful way. Health data is really, really "big", but that's not enough; the key is making it understandable and actionable through interpretation, visualization, and comparison then directly applying it to business models through practice. Not only did Josh organize the technical track, but he moderated four of the sessions: one on the importance of visualization, one on analytics, an entrepreneur's shark tank, It's about making open health data understandable and actionable through interpretation, visualization, and comparison then directly applying it to business models through practice. and finally the healthcare entrepreneurs boot camp (a favorite of event- goers). Practice- The Sessions The content was pretty awesome! (Shout out to all who presented/participated) "When KISS Isn't Simple, or Stupid, Enough" A Session on Data Visualization Hilary Wall and Linda Roesch of the CDC discussed the role data visualization has played in measuring alignment, reporting, and performance in the organization's Million Hearts initiative. Also on the panel were Christine Carmichael and Ben Jones of Tableau. They discussed the value visualization brings to open RowdMap www.RowdMap.com Pag e |6 data and shared some of the best health data visualizations from Tableau Public. What we learned: • The number of health data sources available to researches, innovators, businesses, and consumers have seen exponential growth, but how do you make sense of it all? • Never underestimate the power of visualization in storytelling. • Hypothesis generating data > hypothesis driven data • On putting something out there (direct to consumer style), "It was messy, but if I waited for it to be perfect, I'd be here forever" - Hilary Wall. "Strong Correlation... Close Enough?" A Session on Data Analytics We heard about analytics from the clinical end to scientific applications to the high level business model. Ronald Ozminkowski of Optum, Inc. began the discussion with his view that data is not big enough. Gurjeet Singh, PhD, Sujata Bhatia, MD, PhD, PE, and Suchi Saria, PhD followed by explaining how understanding and visualizing big data can generate new hypotheses that could not be predicted by humans. What we learned: • You can never have too many PhD's on one panel (or can you?). • Big data is great, but it's what you do with it that really matters. • New discoveries in the data will increase the importance of balancing the efforts of research with the business or clinical needs of the industry. RowdMap www.RowdMap.com Pag e |7 • We need to ask ourselves if the data is really the question we're trying to answer? Is the solution valid outside the context of the analysis? Will it have a meaningful impact? • ACA is a whole new business paradigm - requires "new data". • Don't underestimate the importance of a business model and ROI, or your idea will never get absorbed. And finally.... • Accidental deaths and Nick Cage movies: causal or merely corollary? Entrepreneurs - "The Shark Tank" We had a board of top-notch sharks who included Krishana Yeshwant of Google Ventures to Adam Goulburn of Lux Capital and Christina White of Thrive Capital. The products the brave men and women serving as "bait" pitched ranged from a nutrition - tracker, to activity and health monitors for children and one for dogs (think FitBit for your pet). What we learned: • Disintermediation of funding and lower capital requirements means adding value is key to survival. • "Never underestimate the [process of the] consumerization of a product [this] never comes from a doctor office" - your product may have the science, but will people use it? • "America we're fat, and so are our dogs!" • Capital must not be commodity: only enter the trenches with people you want to be there with. The largest returns often come on those [startups] that are boot-strapped. Raising lots of money doesn't guarantee success. RowdMap www.RowdMap.com Pag e |8 • Capital as intervention is changing in post ACA world where talent trumps technology. The market is ripe for disruption: how will industry icons react? And the Main Event... Healthcare Entrepreneur's BootCamp "Strategy, Practice, & Games for Using Public Data to Build, Scale, and Deliver Value" Healthcare start-ups fail at astounding, disproportionate rates. This is no surprise due to the complexity of this dynamic market. How do you go from a data-based tech product to a company with a meaningful value proposition? It takes practice. The BootCamp brought together a talented, experienced, and good-looking, group of industry leaders with expertise in using data to drive business strategy. Participants worked in teams to come up with a mock business pitch that asswers these four questions (i.e. key questions any entreprenuer, or seasoned busniess vet. should be asking): What market is your product reaching? What business need does it address? What data will it use? What is your competitve edge over potential barriers? Given the new data we're all entrepreneurs, using new stuff The healthcare business is drastically changing, and the key is who can create real value - this isn't just for entrepreneurs, how industry icons react will be very telling. Business to business is the way of the past; it's all direct - to -consumer from here. Data is just the start, tying action to data is the key. Those that do may experience wonderfully positive transformation; those that can't will face disruption. RowdMap www.RowdMap.com Pag e |9 Report RowdMap www.RowdMap.com Open Health Data Movement: Adolescence as Transformation and Disruption RowdMap’s Board of Advisors include Dave Dickey (Second Story Sales, previously co-founder RedBrick Health), Kyle Rolfing (Principal at Savvysherpa, Inc., previously co-founder Definity Health), Abir Sen (Co-founder & CEO Gravie, previously cofounder Bloom Health), Marshall Votta (Leverage Health Solutions, previously NaviNet) and David Wennberg (CEO Northern New England Accountable Care Collaborative & CTO Dartmouth Institute for Health Policy and Clinical Practice, previously co-founder Health Dialog Analytic Solutions). RowdMap, Inc. provides this report for information purposes only. It is not intended to be advice for a particular situation or legal advice. Consult with an appropriate professional for your situation. The information in this document is subject to change without notice. This document contains proprietary information, which is protected by U.S. and international copyright. All rights are reserved. No part of this documentation may be reproduced or transmitted in any form or by any means, electronic or mechanical, without the express permission of RowdMap. Copyright 2014 RowdMap. RowdMap and its respective marks including Health Profit Intelligence are trademarks of RowdMap, Inc. All other brand and product names and marks are property of their respective owners. © 2014 RowdMap, Inc. www.RowdMap.com Report
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