The document discusses challenges facing healthcare startups in utilizing open government data and proposes connecting open data to meaningful business models by releasing new performance and referral data from the government to determine provider risk-readiness and identify unwarranted cost variations between providers. It provides examples of how comparing provider procedure rates using this open data could identify significant potential cost savings.

1. Zac Jiwa - Joshua Rosenthal, PhD - Bryan Sivak - Fred Trotter

3. Government is releasing lots of data*
* Expertly captained by

4. Need market to adopt – use to create value
Cf. Weather & Geo-Location data
Thanks, government!

5. Context
Exit
Exit w/
Good Multiple
Idea
Prototype
Funded
1 %*
1 %*
1 %*
1 %*
*Health Care Start Ups
fail at astounding,
disproportionate rates

6. Most ‘Successes’, Aren’t
Measuring Value Creation

7. Measuring Value Creation

8. User Guide (ALT)
Consultants /
Professional Services,
Providers
SaaS-based
data / analytic
platforms
Measuring Value Creation

9. Health care has not done so well
“Just wait ‘till next year Financial Services & Energy!”
In this race vs. other verticals

10. 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

11. *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

12. Speaking at a major health care conference near you
Challenge: Fluff in nice suits

13. I have better
engineering / architecture
Hmm, ‘fixing the pipes’
was not the answer
Challenge: Noise from Tech

14. I have better
design & experience
Hmm, the pretty colors
on my social app didn’t stop me
Challenge: Bubbles (design)

15. My data is bigger than yours Hmm,
this fixation indicates...
Silly boys
Challenge: Buzz (cf. big data)

16. * Source: Dartmouth Atlas for Unwarranted Variation
*
Challenge: Perverse Incentives

17. 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

18. 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

19. 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

20. Challenge: Interpretation of Data

21. Causal?
Then again… Maybe there’s something to it?

22. Challenge: Interpretation of Data

23. A new Prescription?
= Live to be 126 years old?
Then again… Maybe there’s something to it?

24. Review
Health Care Start Ups
fail at astounding,
disproportionate rates
FAIL

25. 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

26. 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

27. 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

28. 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