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SXSW: Open Data as an Open Challenge

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Open data has worked like a charm with weather and geolocation data. But healthcare is tricky and a different sort of market. Explore how to use open data to make create value and public good in a session at SXSW with Josh Rosenthal, Bryan Sivak and Fred Trotter

Published in: Healthcare
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SXSW: Open Data as an Open Challenge

  1. 1. Zac Jiwa - Joshua Rosenthal, PhD - Bryan Sivak - Fred Trotter
  2. 2. Government is releasing lots of data* * Expertly captained by
  3. 3. Need market to adopt – use to create value Cf. Weather & Geo-Location data Thanks, government!
  4. 4. Context Exit Exit w/ Good Multiple Idea Prototype Funded 1 %* 1 %* 1 %* 1 %* *Health Care Start Ups fail at astounding, disproportionate rates
  5. 5. Most ‘Successes’, Aren’t Measuring Value Creation
  6. 6. Measuring Value Creation
  7. 7. User Guide (ALT) Consultants / Professional Services, Providers SaaS-based data / analytic platforms Measuring Value Creation
  8. 8. Health care has not done so well “Just wait ‘till next year Financial Services & Energy!” In this race vs. other verticals
  9. 9. EasyHard Low Biz Value High Biz Value ? ? Most: Cool Tech Complex Data Figure out how to create value from tech / data Start with Biz Problem, figure out data / tech Comp Sci. Interests VC / Accelerator Public DataBig Data Challenge: Starting Hard with Cool Tech
  10. 10. *Direct-to-Consumer Note: People don’t like to pay out of pocket for something they don’t like to do or don’t want to know about Challenge: Direct to Consumer Apps
  11. 11. Speaking at a major health care conference near you Challenge: Fluff in nice suits
  12. 12. I have better engineering / architecture Hmm, ‘fixing the pipes’ was not the answer Challenge: Noise from Tech
  13. 13. I have better design & experience Hmm, the pretty colors on my social app didn’t stop me Challenge: Bubbles (design)
  14. 14. My data is bigger than yours Hmm, this fixation indicates... Silly boys Challenge: Buzz (cf. big data)
  15. 15. * Source: Dartmouth Atlas for Unwarranted Variation * Challenge: Perverse Incentives
  16. 16. Perverse Incentives: Fee for Service Payers aggregate – but some have not historically been “health care” “Actually, I make more money off of bad drivers.”* (Read w/ accent) * Note: Affordable Care Act changes this Cf. Medicare Advantage
  17. 17. Some Hospitals/Providers may historically generated revenue by filling rooms* Keep patients away?!? I was trying to book you for an extra night! * Note: Affordable Care Act changes this Cf. Medicare Advantage Perverse Incentives: Fee for Service
  18. 18. Perverse Incentives: Disrupting Status Quos David Wennberg, MD RowdMap Advisory Board Open Health Data Outperforms Claims and Electronic / Personal Health Records, & Devices for Risk & Cost
  19. 19. Challenge: Interpretation of Data
  20. 20. Causal? Then again… Maybe there’s something to it?
  21. 21. Challenge: Interpretation of Data
  22. 22. A new Prescription? = Live to be 126 years old? Then again… Maybe there’s something to it?
  23. 23. Review Health Care Start Ups fail at astounding, disproportionate rates FAIL
  24. 24. OPEN SOLUTION - CONNECT DATA TO BIZ MODEL Solution: NEW INCENTIVES Government Announces Sun-setting of Fee for Services Government Announces New Pay-for-Value Models
  25. 25. OPEN SOLUTION - CONNECT DATA TO BIZ MODEL New Government Released Referral Data (Patient flows between PCPS, specialists, hospitals and post acute centers) Dartmouth Atlas for Unwarranted Variation (Decades of research and data on unwarranted variation by condition and geography to keep things apples-to-apples for comparisons, hence “Unwarranted” in the name) New Government Released Performance Data (Individual providers, groups, hospitals and post acute centers including the new part B&D) Provider Pattern Intensity Profiles and Risk Readiness for every provider, hospital, post acute center in the US. All preloaded with no IT. Solution: NEW DATA Affordable Care Act data to determine Risk-Readiness of Providers / Networks
  26. 26. If Dr. Berlin had same ratio as Dr. Milan: • His decompression rate would drop from 6.01 to 0.436 per patient. • Which translates to 2,608 fewer decompressions per year. • At an average cost of $332 per decompression, this represents potential savings of over $850K If Dr. Berlin's decompression to fusion rate were average for orthopedic surgeons: • He would have 1629 fewer decompressions for a potential savings of $540K. For every 10 back fusions Dr. Berlin* does 103 decompressions For every 10 back fusions Dr. Milan* does 2 decompressions. OPEN SOLUTION - CONNECT DATA TO BIZ MODEL
  27. 27. OPEN SOLUTION - CONNECT DATA TO BIZ MODEL Answering the Open Challenge: Connecting Open Data to an Meaningful Business Model DIY it! Guide: http://tinyurl.com/l2nxvw9 Sources: http://tinyurl.com/ko7jnfa Game: http://tinyurl.com/kspxr4e

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