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Gradually, Then Suddenly
Lessons from Silicon Valley
for the Future of Healthcare
Tim O’Reilly
Founder and CEO, O’Reilly Media
Genentech Medical Affairs Summit, March 19, 2019
“How did you go bankrupt?”
“Two ways. Gradually, then
suddenly”
Ernest Hemingway
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Sunil Paul had the idea in 1999!
In July 2000, just as GPS was first
opened for commercial use, Sunil
Paul filed a patent that described
almost everything that by 2011 would
become his company Sidecar, and
then Lyft and Uber.
What took so long? And why was
Sunil’s company the loser in the race
to the future?
Sometimes the world just has to catch up
• 2005 – Google launches Google Maps
• 2006 – Amazon launches AWS
• 2007 – Apple introduces the iPhone
• 2007 – Hackers jailbreak the iPhone to
add custom apps
• 2008 – Google launches Android
• 2008 – Apple launches the App Store
and Google launches Android Market
• 2007- 2010 – Braintree, Stripe, Twilio etc.
build out enabling services for mobile apps
(payment, communications, etc.)
“Framing blindness”
We often begin by
imagining the future in
familiar terms, and our
use of new technology is
shaped by what we
already know, and
drawing within the
existing lines.
In 2005, we thought the connected taxicab looked
like this
We knew what the
internet was for:
It’s for showing
content and ads!
And we can read
your credit card too!
New puzzle pieces on the table
2007 – Taxi Magic uses the web to hail taxis
2007 – Zimride matches college students for long drives
2009 – Uber uses SMS to summon black cars
2012 – Sunil finally launches Sidecar – GPS enabled, with drivers
who use their own cars; he is slowed by attempt to work with
regulators, and lack of capital
2012 – Logan Green and John Zimmer ditch Zimride and launch Lyft
2012 – Uber launches UberX to copy the crowdsourced driver model
and pours on the gas
2017 – Bikes and scooters get added to the mix
“A business model is the way that
all of the parts of a business work
together to create competitive
advantage and customer value.”
- Dan and Meredith Beam
A Business Model Map of Uber
• A magical app that lets
drivers and passengers find
each other in real time
• Seamless integration of
data services like location,
communication, and payment
• A networked marketplace
of drivers and passengers
managed by algorithm
• Augmented workers able to
join the market as and when
they wish
Jeff Bezos calls this “the flywheel”
We’re still in the “gradually” stage for healthcare
• Ubiquitous smartphones
• Health outcomes data availability coming together with a shift in
business models, enabling payment for outcomes rather than fee for
service
• Big data, cloud computing, AI, genomics, proteomics, etc. enabling
personalized medicine, drug discovery, and more
• Video calling, remote sensing, enabling telemedicine
• Remote sensing, robotics, and the Internet of Things
• Patients who expect services as easy to use as their smartphone apps
What will it take to get to “suddenly”?
“The value proposition hasn’t yet
overcome the misaligned incentives. But
the value proposition continues to
increase.”
Jamie Heywood, PatientsLikeMe
New sources of data for personalized medicine
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
• Trillions of web pages indexed, in real time
• 5.5 billion searches per day
• 63,000 searches per second
• 50-60 billion ad impressions per day
• Response time of about half a second (reported on every query)
A System of Collective Intelligence
• Every web user contributes to Google’s collective intelligence
• whenever we create a web page
• whenever we link to a web page
• whenever we click on a search result
• whenever we follow maps and directions on our phone…
• Humans build and manage the systems for extracting relevance, for
combating spam, and for keeping things running at greater and
greater scale and speed, but the system is too big and too fast for
traditional “management” or decision making. Google is a giant AI.
• The stakes are very high: Human minds are reflexively shaped by
the knowledge and opinions aggregated there and on other similar
platforms.
Google is a new kind of human-machine hybrid
Gradually, then suddenly
Artificial Intelligence and big data
are enabling fundamentally new
kinds of partnerships between
humans and machine
It’s no longer just in the digital realm
Work on stuff that matters
Gradually, then suddenly
The great internet services are all real-time
matching marketplaces managed by
algorithm. This is a radically new form of
business organization.
Amazon.com
And then of course, there are the warehouse robots
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Algorithms decide “who gets what – and why”
Markets are outcomes. A better
designed marketplace can have
better outcomes.
Google is made up of two overlapping algorithmic
marketplaces
• Google Search: Uses 200+ ranking factors to match up users with
the information they are searching for. Constantly updates its
systems with new data and new, improved algorithms. What
remains constant is the desired outcome: users find what they
want. This is a marketplace where money plays no role in what is
shown.
• Google Ads: Uses an auction model in which the top ad placement
doesn’t go to the highest bidder but to the best combination of price
and projected likelihood that the user will click on the ad (i.e. that it
too is what they want.)
How might this work in healthcare?
• Hundreds of factors – population health data, personalized health
data, outcome data on interventions – are weighed to give the
physician a set of recommendations focused on the best health
results.
• An economic AI engine makes recommendations on the best
combination of health outcomes and costs. Providers compete for
the patient’s business by being the best option.
“The opportunity for AI is to help humans
model and manage complex interacting
systems.”
Paul R. Cohen
University of Pittsburgh
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
“Comprehend Medical is helping to identify patients
for clinical trials who may benefit from specific
cancer therapies. Fred Hutch[inson Cancer Center]
was able to evaluate millions of clinical notes to
extract and index medical conditions, medications,
and choice of cancer therapeutic options, reducing
the time to process each document from hours to
seconds.”
- Dr. Taha A. Kass-Hout and Dr. Matt Wood, Amazon
Taha A. Kass-Hout
Better scheduling and logistics may be the first
value-add
“Patients who need appendectomies are
typically scheduled for an hour in surgery. But
young, otherwise healthy people often need
less time.
‘If I look at a million patients like you, and
discover we only need 25 minutes, wouldn’t
that be better for society? Because now the
OR is the most expensive place in a hospital,’
Halamka said.”
Bloomberg, March 4, 2019
John Halamka, MD
Beth-Israel Deaconess Hospital
Gradually, then suddenly
The system will evolve from
making recommendations to doctors
to a dynamic real time system
designed and managed by doctors.
Working at the scale and
speed required by
personalized medicine
without the help of AI will be
like asking workers to build
a modern city with only
picks and shovels.
Gradually, then suddenly
Software has become a set of
ongoing business processes, not
something you can buy
The front-line “workers” at Google & Amazon are
programs. Software developers are actually their
managers.
Every day, they are inspecting the
performance of their workers and
giving them instruction (in the form of
code) about how to do a better job
A new kind of management
“It’s the difference between
‘playing Caesar’ (deciding which
projects live and die), and ‘playing
the scientist’ (being perpetually
open to search and discovery.)”
- Eric Ries, The Startup Way
New skillsets are needed
• User Centered Design
• Site Reliability Engineering
• Data Science
• Machine Learning
• API Design
• Economics
• Market design
• Data security
Gradually, then suddenly
Knowledge is
available on
demand
Neo: “Can you fly that thing?”
Trinity: “Not yet.”
This isn’t quite what Trinity’s got, but…
What does knowledge on demand
look like for healthcare?
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare
“The No. 1 thing that has made us
successful by far is obsessive
compulsive focus on the customer.”
Jeff Bezos
User-centered design is a superpower
A “magical” app takes advantage of new technology to do something
delightful for customers that previously seemed impossible.
It doesn’t have to be
complicated. Here’s
One Medical,
reinventing
the house call –
on a mobile phone
Applying for food benefits
in California used to be nearly
impossible online and 45% of those
eligible never got the benefit.
Now, GetCalFresh makes it easy
and with over 670,000 people
helped, we’re closing the
participation gap.
A Future Business Model Map of Roche?
• A magical app that lets
patients request care as they
need it. Everyone gets the
right treatment.
• Seamless integration of
personalized patient data
into a health intelligence
platform
• Augmented workers able to
deliver the 21st century
housecall
• A matching marketplace
managed by algorithm
Drug
Discovery
Learning
in real time
Drug
Discovery
Personalized
medicine
Prices so low
everyone gets a
“Cadillac plan”
No waiting
for care Payment is
invisible
Access at the
touch of
a button
Population
Health
Data
Automatic
Ticketing
machines
Personal
Health Data
A health
intelligence
platform
So smart that
paying for outcomes
is more profitable
Magical
User Experience
“Everyone gets the
right treatment”
Augmented
Health
Workers
Care that
shows up
when you
need it
Managed
By
Algorithm
The best specialists are
available to everyone
Physicians and other
frontline health workers
have AI on demand
Doing now what patients need next
This is the future I envision for you
• A dynamic learning system with data-driven
economic incentives
• An internet-scale, algorithmically managed
marketplace
• Focused on better health outcomes
• Augmented health workers serving empowered,
augmented consumers
The puzzle pieces are all on the table
• Putting patients at the center
• The shift to wellness rather than illness
• Collaboration between health systems and health plans
• Increased adoption of virtual care options
• Greater focus on population health
• The collection of patient health data rather than just health care billing
data
• Aligning the financial incentives with the care incentives––or
disconnecting them entirely!
What do the great technology platforms teach us about
the future of business and the economy?
The future isn’t inevitable. It doesn’t
just happen.
It is up to us to build the future we
want.
wtfeconomy.com

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Gradually, Then Suddenly: Lessons from Silicon Valley for the Future of Healthcare

  • 1. Gradually, Then Suddenly Lessons from Silicon Valley for the Future of Healthcare Tim O’Reilly Founder and CEO, O’Reilly Media Genentech Medical Affairs Summit, March 19, 2019
  • 2. “How did you go bankrupt?” “Two ways. Gradually, then suddenly” Ernest Hemingway
  • 4. Sunil Paul had the idea in 1999! In July 2000, just as GPS was first opened for commercial use, Sunil Paul filed a patent that described almost everything that by 2011 would become his company Sidecar, and then Lyft and Uber. What took so long? And why was Sunil’s company the loser in the race to the future?
  • 5. Sometimes the world just has to catch up • 2005 – Google launches Google Maps • 2006 – Amazon launches AWS • 2007 – Apple introduces the iPhone • 2007 – Hackers jailbreak the iPhone to add custom apps • 2008 – Google launches Android • 2008 – Apple launches the App Store and Google launches Android Market • 2007- 2010 – Braintree, Stripe, Twilio etc. build out enabling services for mobile apps (payment, communications, etc.)
  • 6. “Framing blindness” We often begin by imagining the future in familiar terms, and our use of new technology is shaped by what we already know, and drawing within the existing lines.
  • 7. In 2005, we thought the connected taxicab looked like this We knew what the internet was for: It’s for showing content and ads! And we can read your credit card too!
  • 8. New puzzle pieces on the table 2007 – Taxi Magic uses the web to hail taxis 2007 – Zimride matches college students for long drives 2009 – Uber uses SMS to summon black cars 2012 – Sunil finally launches Sidecar – GPS enabled, with drivers who use their own cars; he is slowed by attempt to work with regulators, and lack of capital 2012 – Logan Green and John Zimmer ditch Zimride and launch Lyft 2012 – Uber launches UberX to copy the crowdsourced driver model and pours on the gas 2017 – Bikes and scooters get added to the mix
  • 9. “A business model is the way that all of the parts of a business work together to create competitive advantage and customer value.” - Dan and Meredith Beam
  • 10. A Business Model Map of Uber • A magical app that lets drivers and passengers find each other in real time • Seamless integration of data services like location, communication, and payment • A networked marketplace of drivers and passengers managed by algorithm • Augmented workers able to join the market as and when they wish
  • 11. Jeff Bezos calls this “the flywheel”
  • 12. We’re still in the “gradually” stage for healthcare • Ubiquitous smartphones • Health outcomes data availability coming together with a shift in business models, enabling payment for outcomes rather than fee for service • Big data, cloud computing, AI, genomics, proteomics, etc. enabling personalized medicine, drug discovery, and more • Video calling, remote sensing, enabling telemedicine • Remote sensing, robotics, and the Internet of Things • Patients who expect services as easy to use as their smartphone apps
  • 13. What will it take to get to “suddenly”?
  • 14. “The value proposition hasn’t yet overcome the misaligned incentives. But the value proposition continues to increase.” Jamie Heywood, PatientsLikeMe
  • 15. New sources of data for personalized medicine
  • 19. • Trillions of web pages indexed, in real time • 5.5 billion searches per day • 63,000 searches per second • 50-60 billion ad impressions per day • Response time of about half a second (reported on every query)
  • 20. A System of Collective Intelligence • Every web user contributes to Google’s collective intelligence • whenever we create a web page • whenever we link to a web page • whenever we click on a search result • whenever we follow maps and directions on our phone… • Humans build and manage the systems for extracting relevance, for combating spam, and for keeping things running at greater and greater scale and speed, but the system is too big and too fast for traditional “management” or decision making. Google is a giant AI. • The stakes are very high: Human minds are reflexively shaped by the knowledge and opinions aggregated there and on other similar platforms.
  • 21. Google is a new kind of human-machine hybrid
  • 22. Gradually, then suddenly Artificial Intelligence and big data are enabling fundamentally new kinds of partnerships between humans and machine
  • 23. It’s no longer just in the digital realm
  • 24. Work on stuff that matters
  • 25. Gradually, then suddenly The great internet services are all real-time matching marketplaces managed by algorithm. This is a radically new form of business organization.
  • 27. And then of course, there are the warehouse robots
  • 29. Algorithms decide “who gets what – and why” Markets are outcomes. A better designed marketplace can have better outcomes.
  • 30. Google is made up of two overlapping algorithmic marketplaces • Google Search: Uses 200+ ranking factors to match up users with the information they are searching for. Constantly updates its systems with new data and new, improved algorithms. What remains constant is the desired outcome: users find what they want. This is a marketplace where money plays no role in what is shown. • Google Ads: Uses an auction model in which the top ad placement doesn’t go to the highest bidder but to the best combination of price and projected likelihood that the user will click on the ad (i.e. that it too is what they want.)
  • 31. How might this work in healthcare? • Hundreds of factors – population health data, personalized health data, outcome data on interventions – are weighed to give the physician a set of recommendations focused on the best health results. • An economic AI engine makes recommendations on the best combination of health outcomes and costs. Providers compete for the patient’s business by being the best option.
  • 32. “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen University of Pittsburgh
  • 34. “Comprehend Medical is helping to identify patients for clinical trials who may benefit from specific cancer therapies. Fred Hutch[inson Cancer Center] was able to evaluate millions of clinical notes to extract and index medical conditions, medications, and choice of cancer therapeutic options, reducing the time to process each document from hours to seconds.” - Dr. Taha A. Kass-Hout and Dr. Matt Wood, Amazon Taha A. Kass-Hout
  • 35. Better scheduling and logistics may be the first value-add “Patients who need appendectomies are typically scheduled for an hour in surgery. But young, otherwise healthy people often need less time. ‘If I look at a million patients like you, and discover we only need 25 minutes, wouldn’t that be better for society? Because now the OR is the most expensive place in a hospital,’ Halamka said.” Bloomberg, March 4, 2019 John Halamka, MD Beth-Israel Deaconess Hospital
  • 36. Gradually, then suddenly The system will evolve from making recommendations to doctors to a dynamic real time system designed and managed by doctors.
  • 37. Working at the scale and speed required by personalized medicine without the help of AI will be like asking workers to build a modern city with only picks and shovels.
  • 38. Gradually, then suddenly Software has become a set of ongoing business processes, not something you can buy
  • 39. The front-line “workers” at Google & Amazon are programs. Software developers are actually their managers. Every day, they are inspecting the performance of their workers and giving them instruction (in the form of code) about how to do a better job
  • 40. A new kind of management “It’s the difference between ‘playing Caesar’ (deciding which projects live and die), and ‘playing the scientist’ (being perpetually open to search and discovery.)” - Eric Ries, The Startup Way
  • 41. New skillsets are needed • User Centered Design • Site Reliability Engineering • Data Science • Machine Learning • API Design • Economics • Market design • Data security
  • 42. Gradually, then suddenly Knowledge is available on demand Neo: “Can you fly that thing?” Trinity: “Not yet.”
  • 43. This isn’t quite what Trinity’s got, but…
  • 44. What does knowledge on demand look like for healthcare?
  • 48. “The No. 1 thing that has made us successful by far is obsessive compulsive focus on the customer.” Jeff Bezos
  • 49. User-centered design is a superpower A “magical” app takes advantage of new technology to do something delightful for customers that previously seemed impossible. It doesn’t have to be complicated. Here’s One Medical, reinventing the house call – on a mobile phone
  • 50. Applying for food benefits in California used to be nearly impossible online and 45% of those eligible never got the benefit. Now, GetCalFresh makes it easy and with over 670,000 people helped, we’re closing the participation gap.
  • 51. A Future Business Model Map of Roche? • A magical app that lets patients request care as they need it. Everyone gets the right treatment. • Seamless integration of personalized patient data into a health intelligence platform • Augmented workers able to deliver the 21st century housecall • A matching marketplace managed by algorithm
  • 52. Drug Discovery Learning in real time Drug Discovery Personalized medicine Prices so low everyone gets a “Cadillac plan” No waiting for care Payment is invisible Access at the touch of a button Population Health Data Automatic Ticketing machines Personal Health Data A health intelligence platform So smart that paying for outcomes is more profitable Magical User Experience “Everyone gets the right treatment” Augmented Health Workers Care that shows up when you need it Managed By Algorithm The best specialists are available to everyone Physicians and other frontline health workers have AI on demand Doing now what patients need next
  • 53. This is the future I envision for you • A dynamic learning system with data-driven economic incentives • An internet-scale, algorithmically managed marketplace • Focused on better health outcomes • Augmented health workers serving empowered, augmented consumers
  • 54. The puzzle pieces are all on the table • Putting patients at the center • The shift to wellness rather than illness • Collaboration between health systems and health plans • Increased adoption of virtual care options • Greater focus on population health • The collection of patient health data rather than just health care billing data • Aligning the financial incentives with the care incentives––or disconnecting them entirely!
  • 55. What do the great technology platforms teach us about the future of business and the economy? The future isn’t inevitable. It doesn’t just happen. It is up to us to build the future we want. wtfeconomy.com