Sxswhealth2015 150317154955-conversion-gate01
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Sxswhealth2015 150317154955-conversion-gate01
- 1. #SxSW @timoreilly By People, For People Reinventing Healthcare to Serve People, Not Institutions Tim O’Reilly SxSW March 16, 2015
- 2. @timoreilly “The skill of writing is to create a context in which other people can think.” -Edwin Schlossberg
- 3. @timoreilly
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- 5. @timoreilly
- 6. @timoreilly
- 7. @timoreilly The smartphone is the most widely distributed “Internet of Things” platform.
- 8. @timoreilly
- 9. @timoreilly The Apple Store is magical!
- 11. @timoreilly
- 12. @timoreilly
- 13. @timoreilly Uber and Lyft and Cover are magical!
- 14. @timoreilly
- 15. @timoreilly
- 16. @timoreilly
- 17. @timoreilly Google Now is magical!
- 18. @timoreilly Lesson #1: Use technology to give people super powers
- 19. @timoreilly Our Phones Used to Be the Tool of Superheroes Dick Tracy: 1946 Star Trek: 1964
- 20. @timoreilly An Everyday Modern Superpower
- 21. @timoreilly This is the key question How do we use the capabilities of our devices to build better human experiences?
- 23. @timoreilly How often have you filled out some version of this form?
- 24. @timoreilly 20th Century Vital Sign Monitoring
- 26. @timoreilly
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- 29. @timoreilly Look At Everything Uber Does For Me Lets me call a car from anywhere Automatically tells available drivers where I am Lets me know how long it will be till my car arrives Lets me contact the driver by text or voice - anonymously Lets me pay without having to pull out my wallet Gives me a detailed receipt showing exactly where I went and how long it took - which lets me complain if the driver didn’t go the optimal route (and Uber gives refunds) Lets me rate my driver, and uses that rating to manage the quality of service
- 30. @timoreilly How a Doctor’s Visit Ought to Work •Phone detected on entry to office, hospital, or ER •Insurance automatically checked •Medical history automatically loaded into system •Vitals and other quantified self info automatically loaded •Data automatically used to sort queue and give wait times •If ER, possible discharge to available nearby outpatient clinic or doctor’s office •Portable medical record updated as patient exits •(Aside: We also need payment reform!!!) •Lets me rate my experience, and uses that rating to manage the quality of service
- 31. @timoreilly
- 32. @timoreilly Lesson #4: Build software “above the level of a single device”
- 33. @timoreilly “Why be distracted into looking backwards by the commodity cloners of open source?...There is a new frontier, where software "collectives" are being built with ad hoc protocols and with clustered devices. Robotics and automation of all sorts is exposing a demand for sophisticated new ways of thinking....Useful software written above the level of the single device will command high margins for a long time to come.” - Dave Stutz, On Leaving Microsoft, February 2003 http://www.synthesist.net/writing/onleavingms.html
- 34. @timoreilly Data At the Heart of the Uber System Real-time location tracking Dispatch Trip tracking Names and faces Payment Dynamic Pricing Reputation senger Driver
- 35. @timoreilly Many of these data services are not run by Uber
- 36. @timoreilly Something about state of interoperability
- 37. @timoreilly Lesson #5: Measure and Respond
- 39. @timoreilly Minimum Viable Product “that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” - Eric Ries
- 40. @timoreilly We’ve taken this for granted in web applications. But now, with Internet of Things applications powered by big data back ends, Lean Startup principles apply to every real world service!
- 41. Text @timoreilly “Only 1% of healthcare spend now goes to diagnosis. We need to shift from the idea that you do diagnosis at the start, followed by treatment, to a cycle of diagnosis, treatment, diagnosis...as we explore what works.” -Pascale Witz, GE Medical Diagnostics
- 42. Text @timoreilly “Half the money I spend on advertising is wasted; the trouble is I don't know which half.” - John Wanamaker (1838-1922)
- 43. @timoreilly Lesson #6: These are systems made up of computers and humans working together
- 45. @timoreilly
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- 48. @timoreilly “We know about all these new technologies. What we don’t know is how to organize ourselves to use them effectively.” - An IT executive at Fidelity, during Q&A after a talk I gave there in 2008
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- 52. #VelocityConf @VelocityConf @timoreilly@conference @timoreilly
- 53. @timoreilly
- 54. @timoreilly Are New Ways of Organizing People
- 57. @timoreilly “Uber is a $3.5 billion lesson in building for how the world *should* work instead of optimizing for how the world *does* work” - Aaron Levie of Box.net
- 58. @timoreilly That’s the bar we need to set for reinventing healthcare and health insurance
- 59. @timoreilly Adding Digital To The Way the World Works Now
- 60. @timoreilly Lesson #7: Rethink Workflows and Experiences!
- 64. @timoreilly
- 67. @timoreilly Rescuing healthcare.gov A team of engineers. They came in and worked tech wizardry, right? Maybe some of that, but a lot of the work was debugging the communications failures that led the contractors to build software components that didn’t work together.
- 68. @timoreilly 17 hour days 100 days straight Standup meetings focused on why people weren’t able to keep the promises they’d made to each other Mikey Dickerson Google Site Reliability Engineer Mikey Dickerson
- 71. @timoreilly
- 72. @timoreilly “…one privilege the insured and well-off have is to excuse the terrible quality of services the government routinely delivers to the poor. Too often, the press ignores — or simply never knows — the pain and trouble of interfacing with government bureaucracies that the poor struggle with daily.” —Ezra Klein
- 73. @timoreilly
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- 75. @timoreilly
- 76. @timoreilly “User needs. An empathetic service would ground itself in the concrete needs of concrete people. It’s not about innovation, big data, government-as-a-platform, transparency, crowd-funding, open data, or civic tech. It’s about people. Learning to prioritize people and their needs will be a long slog. It’s the kind of change that happens slowly, one person at a time. But we should start.”
- 79. [CLEAN]
- 81. 82
- 84. @timoreilly “Unboxing” MediCal Alan Williams 2012 Startup engineer 2013 Code for America Fellow 2014 On Food Stamps and MediCal
- 86. @timoreilly
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- 100. @timoreilly GDS
- 101. What we are going to cover today Header 1 • Header 2 • Bullet 1 Blah blah blah • Bullet 2 Blah blah blah • Bullet 3 Blah blah blah
- 102. @timoreilly Government can work for the people, by the people, in the 21st century, if we make it so.Jennifer Pahlka
- 105. by people
- 106. @timoreilly Build 21st century services of people, by people, for people
- 107. @timoreilly Learn More About How You Can Help Meetup tomorrow morning 9 am - 11 am Halcyon, at 4th and Lavaca c4a.me/sxsw15 codeforamerica.org/talent whitehouse.gov/usds
Hinweis der Redaktion
- The title of this talk is lifted from Lincoln’s Gettysburg Address, by way of the Code for America mission statement, but it’s a great way to think about one of the most important problems facing technologists today. I’m actually not going to talk all that much about healthcare, so much as I’m going to talk about what we learn from consumer technology about what our expectations for healthcare technology *ought* to be.
- Edwin Schlossberg once said “The skill of writing is to create a context in which other people can think.” I want to give you some context for thinking about the next big revolution in technology: the Internet of Things. The very name shows that we’re not thinking about it right. It’s actually an internet of things and humans. Framing it that way will give you much deeper insight into how to design products and services. I’ll be talking about sensors, but also about service design, and about the role of data in the applications that will power this next wave of innovation.
- When you hear about the Internet of Things, you probably think about new devices, like the Apple Watch.
- Or the Nest Thermostat. It’s easy to focus on the device, but ultimately, these are deeply data-connected. What we’re really talking about are internet services and systems whose primary user interface are new kinds of sensors and actuators.
- The Moto X is my favorite smartphone (so far) for this very reason. They’ve used the sensors in the phone in a variety of creative ways, from the feature shown here, that you can wake up your phone and ask it to do something without touching it, to the shake gesture to open the camera. But what I love best are features like that it notices when I’m driving. If I get a text, it says, “You just got a text? Would you like me to read it to you?” And of course, then asks me if I want to reply. What a great way to get you using speech features regularly, but also a great way to rethink the UI using the new superpowers given to my phone, and by extension to me, by clever use of the sensors.
- And new devices, like the Android Wear watches, like the Samsung Gear watch I’m wearing now, or the Moto 360, pictured here, are really “Google Now” devices. They are a connection to a predictive agent, that is constantly reminding you of things, providing context, and giving you easy access to internet services.
- The watch is really just a peripheral for the smartphone. And it’s super important to remember that the smartphone is the most widely distributed “Internet of Things” platform. It is packed with sensors - it can see, it can hear, it knows where it is, whether it is moving, and in what direction - and it can report these things not only to the person who is holding it but to other applications. And it has other “senses” too! It can “listen” to real time databases, and report in to them. And of course, it can interface with humans. And so the real potential of the Internet of Things isn’t about some hot new device. It’s about how connected sensors and the data they provide call allow us to rethink the way we do things.
- Consider the Apple Store. Apple used the smartphone to rethink the workflow of an industry that we’ve always taken for granted: the retail store. Where most stores (at least in America) have used technology to eliminate salespeople, Apple has used it to augment them. Apple used the phone to give superpowers to its salespeople, eliminating the cash register in the process. Each store is flooded with smartphone-wielding salespeople who are able to help customers with everything from technical questions to purchase and checkout. And the workflow of the store is completely rethought. You look at the items on the showroom floor, all alive and working, not in boxes. You ask questions of one of the many helpful workers, and when you’ve made your decision, the staff member asks for your email address. If you’ve ever bought anything from Apple, in the store or online, your cc is already available. Your package is summoned from the back, handed to you, and you walk out. Your receipt is emailed to you. Former US CTO Todd Park foresees a future in which health workers will be part of a feedback loop including sensors to track patient data coupled with systems that alert them when a patient needs to be checked up on. The augmented home health worker will allow relatively unskilled workers to be empowered with the much deeper knowledge held in the cloud.
- The Apple Store is a magical retail experience. That’s the real measure of a transformative technology: it makes a magical experience. And it became magical because it used technology to enable people, not to replace them!
- Or consider Uber. Most people don’t think of it as an IoT app, but that’s precisely why we need to start there. It is an application that is entirely made possible by sensors in the phone, connected to data services in the cloud. And there are some really great lessons here.
- How many of you have used Uber or Lyft? If you have, you know how transformational it is to be able to know just how long it will take for a car to pick you up - to summon one whenever you need one, with the confidence that it will actually show up when and where you want it.
- A couple of other apps that are playing in the “hey, let’s use sensors to change the workflow and let the user do less” include Cover, which brings an Uber-like experience to restaurants - “dine and dash” becomes the norm, with payment happening automatically. “Sensors” of course include location, but again, stored data like your face, name, and credit card are provided automatically for verification. (Disclosure: OATV is an investor in Cover.) In the process, these applications are completely changing user expectations about how easy services ought to be to use.
- Uber and Lyft and Cover are magical. And it is worth noting once again that Uber and Lyft use technology to enable people, not to replace them! Uber and Lyft allow more people to become drivers, and more people to use on-demand transportation. They don’t just take costs out of an existing system.
- One of the biggest changes in user expectation that technology will bring into our everyday lives in the next few years is going to be via “agents” like Siri and Google Now, which will bring predictive analytics to bear on routine tasks that we already depend on our computers for. Google Now routinely alerts me to leave early for work when traffic is bad,
- And when I’m traveling, automatically assembles everything from my boarding pass to alerts about the weather and even events at my destination.
- You can even tell Google Now to automatically remember where you parked your car. No action required beyond the additional setup. Sensors in your phone identify when you were driving, when you stopped, and when you began to walk. That you parked is an easy inference. And of course, your phone knew exactly where you were!
- Google Now is magical. And that magic changes our expectations forever.
- So here’s my first lesson: Use technology to give people super powers.
- This kind of superpowers. Our phones used to be the tool of superheroes.
- The first role of AIs is to give super-powers to humans. We don’t think of GPS-based navigation as “AI”, but it is a kind of Artificial or Augmented Intelligence. Think about it. Drop a smartphone enabled human in a strange city and they can still find their way around. (Of course, we could do this with a much earlier augmentation, the printed map, but the key characteristic of modern technology is that information access is much faster, and more complete. And the downside - we are much more dependent on it!)
- So this is the key question. How do we use...
- So what else do we learn from these applications? Do less! Less UI that requires the user to interact with the application. Use the sensors in the device to provide context to the application. Use stored data about the user rather than asking them for it again and again. Think of that magical moment when you walk out of the Apple Store, or the Uber, without ever pulling out your wallet! That’s part of what makes them magical experiences.
- Now contrast your experience in healthcare. How often have you filled out some version of this form?
- https://www.flickr.com/photos/navymedicine/15084211290 And if you’ve ever been in the hospital, you probably remember how hard it was to sleep. Someone was always waking you up to check your vital signs. That’s really not necessary in the 21st century. (There are lots of other customer-hostile features of hospitals, where everything is designed for the convenience of the staff rather than the patients.)
- Not surprisingly, my second lesson could be reframed as “Do More.” Do more for the user, with less interaction. Take a look, for example, at the receipt that I get from Uber!
- Uber collects information automatically from the phone’s sensors, and packages up in a useful format to confirm the details of your trip. And that’s just the beginning.
- But that’s not all! Now, through integration with Expensify, you can not only have your receipt automatically turn into an expense report, if you’ve forwarded your flight details to Expensify, it can automatically have an Uber waiting for you when you arrive!!! This example highlights another key point: namely, that the new inputs to the systems we build are often internet data services, not just data from sensors. In the end, it’s not just local sensing that matters, its sensors connected to a big data back end.
- So what do I think when, weeks after my visit to the doctor, I get something like this in the mail. I may or may not have received a bill from my doctor or hospital in the meantime, but I don’t know whether to pay it until I get the insurance confirmation. Truly broken. Truly user hostile. So let’s compare the Uber experience with what we will soon expect from our healthcare experience.
- Look at everything that Uber does for me.
- Here’s how a doctor’s visit ought to work. Of course, I’m leaving aside the most magical aspect of Uber and Lyft - that they come to you. We’ll talk about that later in this presentation.
- I promised an aside on payment reform. If you’ve never taken a look at ClearHealthCosts.com, you should. It’s shocking how far our healthcare system is from a true market system. Costs vary by an order of magnitude within only a few miles. And there’s all kinds of gaming of the reimbursement system. That needs a systemic fix.
- There’s another lesson here. When you think about Uber, it’s easy to see that it isn’t just a smartphone app. It’s an entire system, with different apps for passenger and driver, and a big data backend that does dispatch and billing. Healthcare is also a system. And what’s important to realize is that you can build great user experiences even when you don’t control every bit of the service. In fact, today’s web apps are almost all composed out of services that are sometimes run by others.
- I first heard this wonderful formulation of the essence of the technology future from Microsoft’s one-time open source software leader, Dave Stutz, when he retired from Microsoft in 2003. His parting advice is still worth reading.
- This “software above the level of a single device” is a SYSTEM with multiple users on multiple devices. And ultimately, it’s a system built on a big data back end! Some of that data is from sensors. Some of it is from stored memory (e.g. names and faces of driver and passenger, payment credentials). Some of it is calculated and reported in real time. And some of it (e.g. reputation) comes from explicit user input.
- It’s really important to understand that the internet of today is a vast web of data services you can build on. And of course that the applications of the future are not just multiplexing data services, they are multiplexing real world services!Don’t just think about building tools for managing data. Build actual data services that people can build on. Many of the components of the system, such as anonymized communications between you and the driver by text message or voice, or cashless billing, are made possible by third party providers (in this case Twilio and Braintree) The internet really is becoming an “operating system”, as I first claimed nearly fifteen years ago. Use its capabilities! Mapping, identity, payment are only a few of the many things that we can now take for granted when building online services. But Uber is a great example of how to assemble these into more than the sum of their parts. Don’t build everything from scratch. There are so many useful services available by API.
- By contrast, even the simplest forms of interoperability still seem to be an enormous challenge in healthcare. We’ve made great progress in sharing digital medical records, with big incentives from the US Federal government driving a lot of change. But in general, the state of composable services in healthcare is pretty miserable. There’s a lot of opportunity here for entrepreneurs.
- My next lesson from consumer technology for healthcare is to take a leaf from the way that web apps constantly measure everything from performance to the details of what people use, try to discern why, and then make changes to optimize the experience.
- This kind of thinking is expressed very well in books like The Lean Startup by Eric Ries. Eric spoke earlier today here at SxSW.
- One of the key ideas of the Lean Startup is of the “Minimum Viable Product”, which Eric Ries defines as “that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” And it really is at the core of most modern startups, who view their product as an ongoing series of experiments. These products are really produced through what is called “continuous deployment”, in which a series of minimum viable products are deployed in sequence.
- We’ve taken this for granted in web applications. But now, with Internet of Things applications powered by big data back ends, Lean Startup principles apply to every real world service!
- One obvious area is in personalized medicine, which requires new kinds of diagnostic feedback loops. Pascale Witz of GE Medical Diagnostics explained how “Only 1% of healthcare spend now goes to diagnosis. We need to shift from the idea that you do diagnosis at the start, followed by treatment, to a cycle of diagnosis, treatment, diagnosis...as we explore what works.”
- I wrote a paper a few years ago about the increasing role of big data and feedback loops in healthcare. I described how healthcare is now solving what advertisers call “the Wanamaker problem” after 19th century department store magnate John Wanamaker, who said “Half the money I spend on advertising is wasted; the trouble is I don't know which half.” What Google did with pay-per-click advertising was to solve the Wanamaker problem, by building a business model that only charged advertisers when consumers clicked on their ads, and harnessing collective intelligence to predict which of those ads would be most likely be clicked on. That’s what we’re now doing with data for health - genetics and data from various kinds of sensors can be used to provide smarter care, and public health statistics and models can be used to manage better usage and cost controls.
- Another really important lesson from consumer technology is that the systems we are building are not only for the benefit of people, but are in some fundamental ways still made of people...
- When you use Google Maps these days, your route is influenced by real-time traffic data. In this case, you can see that traffic from Oakland to San Francisco is really backed up on the Bay Bridge itself. There’s no really good alternative.
- But on another day, when traffic was particularly bad on the approach to the bridge rather than the bridge itself
- Google automatically re-routed us to another route that is longer in miles but shorter in time. Google Maps is constantly learning from everyone who uses the service. We already knew about this shortcut, but usually don’t know when to take it. Now we do. My fiance had an even more remarkable experience when driving recently in Texas. She was using navigation, in an unfamiliar environment. She was told to get on a freeway and drive 9 miles. A mile into the route, the navigation app on her phone told her to get off at the next exit. She did, and saw from the exit ramp an accident up ahead. The app had re-routed her in real time. A huge part of “closing the loop” is learning from your users, paying attention to what they do and responding to it. I’ve often said that one of the key competencies of web applications has got to be “harnessing collective intelligence.” Sensors let Google and Uber do this in real time, but there are lots of other ways you can do this.
- That experience my fiance had was made possible by Waze, acquired recently by Google. Again, internet enabled smartphones, building a real time database... I particularly love how their home page emphasizes the role of people in building the collective database. This notion of collective intelligence has been my theme song since the Web 2.0 days. And pretty early on, I started saying that in the future (that is, now), those collective intelligence applications would be driven by sensors. Or even better, humans and sensors working in concert! Waze drivers report incidents, but their phones report traffic speed and location!
- Ultimately, there’s a thread that ties together the Apple Store, Uber and Lyft, and real time traffic intelligence, and that is that they are all putting together technology and humans in creative new ways to deliver great new experiences. The challenge companies and other institutions face was well expressed by this quote from an IT executive at Fidelity investments, during a Q&A after a talk I gave there in 2008. “We know about all these new technologies. What we don’t know is how to organize ourselves to use them effectively.”
- Because of course, every new technology involves massive changes in how people are organized. From factory assembly lines....
- through more modern examples like open source software
- as well as new services like AirBnb
- Uber
- And the Apple Store
- are all based on new ways of using technology to organize people and the work that they do for each other. Think about how Uber and the Apple Store have both completely rethought the workflow of their respective industries - hailing a cab, and the retail store - by using the sensors and connectivity of smartphones to augment and empower the people using them. In a way, these services are actually made OF PEOPLE and computers in a new kind of symbiosis.
- And in health care - new services like 23andMe
- and PatientsLikeMe are also creative new ways of collecting data from massive numbers of people, and making it possible to extract insight, and eventually fulfill the promise of personalized medicine. What a shame that our regulatory system is working hard to hold back a service like 23AndMe! It’s quite clear that we need some fresh thinking on healthcare data and privacy. Most people are quite willing to share their health data - what they are worried about is adverse selection by insurers and employers! Instead of regulating to prevent these abuses, we try to keep the information secret. That’s not the right approach any more!
- In the end, the challenge before us is to completely reimagine the way healthcare (and other services) ought to work. box.net founder Aaron Levie put it perfectly in a tweet. “Uber is a $3.5 billion lesson in building for how the world should work instead of optimizing for how the world does work.” I believe their latest valuation was $40 billion, but you get the idea.
- That’s the bar we need to set for reinventing healthcare and health insurance. What we’re really talking about, whether with data science, or the internet of things, is how to put technology to work making great human experiences. Technology isn’t interesting for its own sake. It only matters if it makes a better world for all of us.
- We’re not talking about just adding digital and connectivity to the way services work now. Putting network connected credit card readers into taxicabs didn’t radically change the taxi experience. What Uber and Lyft have put together are game changing.
- What we really need to do is to completely rethink workflows and experiences. Sensor-driven devices, and the data-backed services they enable, give us power to rethink the way things work in the real world. We don’t have to duplicate what went before.
- We see a few steps in the right direction in healthcare. It’s not a mobile, on-demand app like Uber, but if you’ve ever needed a doctor in a hurry, or in a strange location, Zocdoc is a godsend. It lets you find someone nearby, in the specialty you need, who might have an open appointment.
- Sherpaa, an OATV portfolio company, is trying to build a concierge-like online service for healthcare. Using a mobile or web app, you can consult with a doctor online, or get health insurance questions answered.
- Todd Park, formerly White House chief technology officer, and still a special adviser to the President (and before that HHS CTO, and before that, co-founder of both AthenaHealth and Castlight Health), pointed me earlier this morning to a Florida company called ChenMed. Because of changes brought by the Affordable Care Act, which focuses on paying for outcomes rather than for procedures, ChenMed has found that they can actually provide in-person concierge-like services (like delivering medications, and other home-care visits) for low-income patients with two or more chronic conditions, who were previously “frequent flyers” at emergency rooms, for less than the cost of their original care. That’s the closest I’ve heard yet to an “Uber for health care.” I want to learn more!
- I’ve had a personal experience with this recently. A long time friend with Parkinson’s disease recently had to enter an assisted living facility, leaving her beloved apartment in New York, because she needed someone to make sure she takes her medications every three hours. In an ideal world, she’d have had someone come do that at her home. As our population ages, there are going to be more and more people needing this kind of care. Ironically, at the same time, there are many people out of work. An uber-like concierge service could solve both problems at once, and, for many patients, at lower cost than the current institutional approach.
- The last topic I want to talk about, at some length, is what we learn from failure. That’s a big topic in Silicon Valley, and it ought to be a topic in healthcare as well.
- We had a big failure in 2013 that got a lot of people’s attention, when healthcare.gov was launched with much fanfare, and then proved not to work.
- Mikey Dickerson (That’s him, third from the right, on the cover of Time.), one of the key players in the healthcare.gov rescue will be speaking at 5 pm upstairs here at SxSW, along with Jennifer Pahlka, founder of Code for America, and former deputy CTO of the US. I was struck by Mikey’s story, the first time I heard it, about how it was as much about debugging the human processes as it was about fixing the technology.
- Mikey put 17 hour days 100 days straight. A big part of what he did was to run what in Silicon Valley we call “stand up meetings” focused on why people weren’t able to keep the promises they’d made to each other
- Meanwhile, another team built healthcare.gov 2.0. The site enrolled millions of Americans, and now works very well.
- Many of the team members stayed on, and are now the core of the new United States Digital Service, a team of the best and brightest who are now working to bring modern technology to many of the nation’s most challenging problems.
- Here’s info on Jen and Mikey’s session.
- But there’s another dimension. I want to explicate the size of the problem. One of the most important pieces about the healthcare.gov rescue was written by Washington Post columnist (now vox.com) Ezra Klein. He wrote about how healthcare.gov was not an exception, but the rule, when it came to government services.
- Recently, I heard an eye opening segment on the radio show Marketplace. Do you know that a huge proportion of food stamp dollars are spent at stores like Walmart between midnight and 1 am on the one night that people’s SNAP cards are electronically refilled? Who goes food shopping at midnight? People who haven’t eaten for a few days, that’s who. So it really matters when you show up at the front of the line, and suddenly your SNAP card doesn’t work because you didn’t know how to respond to a letter you received in the mail.
- And that brings me to the work we do at Code for America (codeforamerica.org). We engage civic hackers around the world to help local governments find solutions to thorny problems. One of our programs sends small fellowship teams - essentially, a civic startup in a box - to work with a city for a year. Last year, one of the Fellowship teams went to work in partnership with the Human Services Agency in San Francisco on a problem with Food Stamps - now known as the Supplemental Nutrition Assistance Program, or SNAP. It turns out that one third of food stamp clients were being unnecessarily cut from benefits due to bureaucratic snafus. Essentially, they’d failed to properly fill out a necessary form or to submit it on time. Fellows went to work on this problem in 2013,
- These letters sent out by the social services department can be truly confusing. Aha, missed that QR7, did you? The fellows replaced them with a text message saying, essentially, “There’s a problem with your benefits. Call the office.”
- Jake Solomon, one of the Fellows, wrote an amazing piece about his experience, entitled People, Not Data. In it, he describes the problem: nobody who was implementing the program had ever themselves tried to comply with the rules and to respond to the instructions, until the Code for America fellows did that. As Jake said, ““User needs. An empathetic service would ground itself in the concrete needs of concrete people. It’s not about innovation, big data, government-as-a-platform, transparency, crowd-funding, open data, or civic tech. It’s about people. Learning to prioritize people and their needs will be a long slog. It’s the kind of change that happens slowly, one person at a time. But we should start.”
- Jake also did an amazing presentation called The Big Thing About Small Things. https://www.youtube.com/watch?v=yViYA8IG36U I’ve used some of his slides for the rest of this talk. He points out that 3.5 million people in California are eligible for CalFresh (Food Stamps) but not getting it.
- You start to understand why when you experience the sign-on process. Here is an animation that Jake made showing what it takes to apply online to the food stamps program. And that’s just the beginning. It gets you an in-person interview to determine if you’re eligible.
- The Fellows replaced this with a service they call Clean - six screens, and it signs you up for MediCal as well.
- They uncovered other problems as well. To check the balance on your EBT card costs 0.75 at an ATM. Banks in California charged welfare recipients $20 million last year - and that’s after also charging fees to the state for issuing and managing the cards!
- The Fellows built an app called Balance, that lets you check your EBT balance with a text message.
- These are small things. But as Jake says,
- The big thing about small things is that they add up. Here’s someone at the San Francisco social services office trying to fill out a paper form with a pencil that’s too short, on a wall that isn’t smooth.
- It didn’t stop there. After finishing his own fellowship year, another Code for America fellow, Alan Williams, decided to join the team, who’d continued working on social services in San Francisco. Alan did it in an unconventional way. He decided that rather than getting a new job, he’d actually go on unemployment, food stamps, and MediCal, to really understand the system from the inside out. (After that experiment he is now working on the Health and Social Services focus area team at Code for America.)
- You’ve probably all seen those “unboxing a new iPhone” articles. Well, here’s Alan’s take on “unboxing MediCal.” All of the quotes on the slides are as he reported them on Slack as he was doing the “unboxing.” It starts with a paper brochure.
- With an important letter hidden inside. You must respond within a month, or your application will be void.
- There are a lot of paper forms in the book.
- It’s like the SATs!
- This is probably the most depressing slide in the bunch. He’s given a choice of two plans. And there is even rating information. But guess what! When it comes to things that really matter, both plans are below average. That’s right, in our enrollment materials, we tell MediCal recipients that their choice is between a bad plan and a worse one. Remember what Ezra Klein said about the quality of social services for the poor, and healthcare.gov not being an exception, but the rule.
- After making some progress on the forms, Alan takes a look at the provider directory.
- It looks like a phone book. In the age of Yelp and TripAdvisor, this is pretty lame.
- Alan can’t figure things out, so he decides to call for help.
- Here’s a nice feature that not all services have - you can request a call back.
- Notice that we’re now an hour into the process. The person Alan has reached on the phone can’t help him and says he must call another office.
- And this office doesn’t have a call back feature. Wait time is 40 minutes.
- Low income families - who can least afford the time (or, since they are likely on phone plans without unlimited service, the minutes), are asked to wait on hold endlessly.
- Finally, at 38 minutes, Alan finally reaches someone. But the system is down. Can you call us back - try this afternoon, or tomorrow morning?
- It turns out that the healthcare.gov “system is down at the moment” message was not an exception. For many government services, this is the norm. The code for america team has been monitoring uptime at social service sites around the country, and they are unavailable at a level that would bring public shaming to any commercial internet application. If google or Amazon were to have service levels like this, they’d be out of business.
- The team has been running tests to figure out where people fall out of the social services funnel, as a guide to understanding where the process is broken. Unfortunately, it’s at almost every level. The point is that we really need to change the system. We can’t just sprinkle a few apps on the front end and think they will lead to deep change.
- Government, in many countries, is the one institution that is supposed to work for all of us. But it often does that work so badly that we lose trust in it. It’s essential that we bring government up to par with the best services of the private sector. One of the places that is doing this is the UK Government Digital Service. Their Design Principles should be one of the bibles of user centered design for the internet of things era. Start with needs. Do less. Design with data. Iterate. Then iterate again. Build for inclusion. Understand context. Build digital services, not websites. Be consistent, not uniform. Make things open: It makes things better. It’s about technology, yes, but far more importantly, it’s about putting technology to work for humans, not the other way around. This is a huge cultural change for government, and that’s one reason it’s so interesting and challenging a set of problems to work on.
- That’s also at the heart of the work we do at Code for America. Our Fellowship team works with cities to identify promising areas of work and to show what’s possible with technology. Our volunteer Brigades help bring local talent to work on interesting problems. And our focus area teams drill deep in areas like core digital infrastructure for cities, health and human services, criminal justice, and economic development.
- We think those values are represented pretty well in the mission statement that serves as our sort of North Star, our guiding light, at Code for America. Jennifer Pahlka, the founder of Code for America, adapted it from the Gettysburg Address by Abraham Lincoln.
- For the people by the people isn’t just a dusty line from the Gettysburg address. Most of the people I’ve met who work in government went into public service in the first place because of what this line represents: they wanted to serve the public. But there’s another way to say this…
- For the people also really means FOR PEOPLE. And it’s also what you should be thinking about in every application you write.
- I haven’t talked as much today about the notion of “by the people,” but if you’ve followed my work for the past decade, you know that I’ve talked nearly incessantly about the role of collective intelligence, expressed either explicitly through new forms of cooperation, or implicitly by the data we contribute simply by interacting with modern applications, or increasingly, implicitly, via the data shadows we leave with sensor-driven applications.
- Taken together, I think that this is a pretty good mission statement for people outside government too! Technology trends tells us that we still will build services of people, and by people when we are using 21st century technology, but it’s essential that we also build services for people.
- Here are some ways you can learn more.