SciDevNet: “FundaGeek, TechMoola and RocketHub have more in common than just their curious names. These are all the monikers of crowdsourcing websites that are dedicated to raising money for science and technology projects. As the coffers that were traditionally used to fund research and development have been squeezed in recent years, several such sites have sprouted up.
In 2013, general crowdsourcing site Kickstarter saw a total of US$480 million pledged to its projects by three million backers. That’s up from US$320 million in 2012, US$99 million in 2011 and just US$28million in 2010. Kickstarter expects the figures to climb further this year, and not just for popular projects such as films and books.
Science and technology projects — particularly those involving simple designs — are starting to make waves on these sites. And new sites, such as those bizarrely named ones, are now catering specifically for scientific projects, widening the choice of platforms on offer and raising crowdsourcing’s profile among the global scientific community online.
All this means that crowdsourcing is fast becoming one of the most significant innovations in funding the development of technology that can aid poor communities….
A good example of how crowdsourcing can help the developing world is the GravityLight, a product launched on Indiegogo over a year ago that uses gravity to create light. Not only did UK design company Therefore massively exceed its initial funding target — ultimately raising $US400,000 instead of a planned US$55,000 — it amassed a global network of investors and distributors that has allowed the light to be trialled in 26 countries as of last December.
The light was developed in-house after Therefore was given a brief to produce a cheap solar-powered lamp by private clients. Although this project faltered, the team independently set out to produce a lamp to replace the ubiquitous and dangerous kerosene lamps widely used in remote areas in Africa. After several months of development, Therefore had designed a product that is powered by a rope with a heavy weight on its end being slowly drawn through the light’s gears (see video)…
Crowdfunding is not always related to a specific product. Earlier this year, Indiegogo hosted a project hoping to build a clean energy store in a Ugandan village. The idea is to create an ongoing supply chain for technologies such as cleaner-burning stoves, water filters and solar lights that will improve or save lives, according to ENVenture, the project’s creators. [1] The US$2,000 target was comfortably exceeded…”
The Universe Is Programmable. We Need an API for Everything
Keith Axline in Wired: “Think about it like this: In the Book of Genesis, God is the ultimate programmer, creating all of existence in a monster six-day hackathon.
Or, if you don’t like Biblical metaphors, you can think about it in simpler terms. Robert Moses was a programmer, shaping and re-shaping the layout of New York City for more than 50 years. Drug developers are programmers, twiddling enzymes to cure what ails us. Even pickup artists and conmen are programmers, running social scripts on people to elicit certain emotional results.
Keith Axline in Wired: “Everyone is becoming a programmer. The next step is to realize that everything is a program.
The point is that, much like the computer on your desk or the iPhone in your hand, the entire Universe is programmable. Just as you can build apps for your smartphones and new services for the internet, so can you shape and re-shape almost anything in this world, from landscapes and buildings to medicines and surgeries to, well, ideas — as long as you know the code.
That may sound like little more than an exercise in semantics. But it’s actually a meaningful shift in thinking. If we look at the Universe as programmable, we can start treating it like software. In short, we can improve almost everything we do with the same simple techniques that have remade the creation of software in recent years, things like APIs, open source code, and the massively popular code-sharing service GitHub.
The great thing about the modern software world is that you don’t have to build everything from scratch. Apple provides APIs, or application programming interfaces, that can help you build apps on their devices. And though Tim Cook and company only give you part of what you need, you can find all sorts of other helpful tools elsewhere, thanks to the open source software community.
The same is true if you’re building, say, an online social network. There are countless open source software tools you can use as the basic building blocks — many of them open sourced by Facebook. If you’re creating almost any piece of software, you can find tools and documentation that will help you fashion at least a small part of it. Chances are, someone has been there before, and they’ve left some instructions for you.
Now we need to discover and document the APIs for the Universe. We need a standard way of organizing our knowledge and sharing it with the world at large, a problem for which programmers already have good solutions. We need to give everyone a way of handling tasks the way we build software. Such a system, if it can ever exist, is still years away — decades at the very least — and the average Joe is hardly ready for it. But this is changing. Nowadays, programming skills and the DIY ethos are slowly spreading throughout the population. Everyone is becoming a programmer. The next step is to realize that everything is a program.
What Is an API?
The API may sound like just another arcane computer acronym. But it’s really one of the most profound metaphors of our time, an idea hiding beneath the surface of each piece of tech we use everyday, from iPhone apps to Facebook. To understand what APIs are and why they’re useful, let’s look at how programmers operate.
If I’m building a smartphone app, I’m gonna need — among so many other things — a way of validating a signup form on a webpage to make sure a user doesn’t, say, mistype their email address. That validation has nothing to do with the guts of my app, and it’s surprisingly complicated, so I don’t really want to build it from scratch. Apple doesn’t help me with that, so I start looking on the web for software frameworks, plugins, Software Developer Kits (SDKs) — anything that will help me build my signup tool.
Hopefully, I’ll find one. And if I do, chances are it will include some sort of documentation or “Readme file” explaining how this piece of code is supposed to be used so that I can tailor it to my app. This Readme file should contain installation instructions as well as the API for the code. Basically, an API lays out the code’s inputs and outputs. It shows what me what I have to send the code and what it will spit back out. It shows how I bolt it onto my signup form. So the name is actually quite explanatory: Application Programming Interface. An API is essentially an instruction manual for a piece of software.
Now, let’s combine this with the idea that everything is an application: molecules, galaxies, dogs, people, emotional states, abstract concepts like chaos. If you do something to any these things, they’ll respond in some way. Like software, they have inputs and outputs. What we need to do is discover and document their APIs.
We aren’t dealing with software code here. Inputs and outputs can themselves be anything. But we can closely document these inputs and their outputs — take what we know about how we interface with something and record it in a standard way that it can be used over and over again. We can create a Readme file for everything.
We can start by doing this in small, relatively easy ways. How about APIs for our cities? New Zealand just open sourced aerial images of about 95 percent of its land. We could write APIs for what we know about building in those areas, from properties of the soil to seasonal weather patterns to zoning laws. All this knowledge exists but it hasn’t been organized and packaged for use by anyone who is interested. And we could go still further — much further.
For example, between the science community, the medical industry and the billions of human experiences, we could probably have a pretty extensive API mapped out of the human stomach — one that I’d love to access when I’m up at 3am with abdominal pains. Maybe my microbiome is out of whack and there’s something I have on-hand that I could ingest to make it better. Or what if we cracked the API for the signals between our eyes and our brain? We wouldn’t need to worry about looking like Glassholes to get access to always-on augmented reality. We could just get an implant. Yes, these APIs will be slightly different for everyone, but that brings me to the next thing we need.
A GitHub for Everything
We don’t just need a Readme for the Universe. We need a way of sharing this Readme and changing it as need be. In short, we need a system like GitHub, the popular online service that lets people share and collaborate on software code.
Let’s go back to the form validator I found earlier. Say I made some modifications to it that I think other programmers would find useful. If the validator is on GitHub, I can create a separate but related version — a fork — that people can find and contribute to, in the same way I first did with the original software.
This creates a tree of knowledge, with giant groups of people creating and merging branches, working on their small section and then giving it back to the whole.
GitHub not only enables this collaboration, but every change is logged into separate versions. If someone were so inclined, they could go back and replay the building of the validator, from the very first save all the way up to my changes and whoever changes it after me. This creates a tree of knowledge, with giant groups of people creating and merging branches, working on their small section and then giving it back to the whole.
We should be able to funnel all existing knowledge of how things work — not just software code — into a similar system. That way, if my brain-eye interface needs to be different, I (or my personal eye technician) can “fork” the API. In a way, this sort of thing is already starting to happen. People are using GitHub to share government laws, policy documents, Gregorian chants, and the list goes on. The ultimate goal should be to share everything.
Yes, this idea is similar to what you see on sites like Wikipedia, but the stuff that’s shared on Wikipedia doesn’t let you build much more than another piece of text. We don’t just need to know what things are. We need to know how they work in ways that let us operate on them.
The Open Source Epiphany
If you’ve never programmed, all this can sound a bit, well, abstract. But once you enter the coding world, getting a loose grasp on the fundamentals of programming, you instantly see the utility of open source software. “Oooohhh, I don’t have to build this all myself,” you say. “Thank God for the open source community.” Because so many smart people contribute to open source, it helps get the less knowledgeable up to speed quickly. Those acolytes then pay it forward with their own contributions once they’ve learned enough.
Today, more and more people are jumping on this train. More and more people are becoming programmers of some shape or form. It wasn’t so long ago that basic knowledge of HTML was considered specialized geek speak. But now, it’s a common requirement for almost any desk job. Gone are the days when kids made fun of their parents for not being able to set the clock on the VCR. Now they get mocked for mis-cropping their Facebook profile photos.
These changes are all part of the tech takeover of our lives that is trickling down to the masses. It’s like how the widespread use of cars brought a general mechanical understanding of engines to dads everywhere. And this general increase in aptitude is accelerating along with the technology itself.
Steps are being taken to make programming a skill that most kids get early in school along with general reading, writing, and math. In the not too distant future, people will need to program in some form for their daily lives. Imagine the world before the average person knew how to write a letter, or divide two numbers, compared to now. A similar leap is around the corner…”
Innovation Contests
Paper by David Pérez Castrillo and David Wettstein: “We study innovation contests with asymmetric information and identical contestants, where contestants’ efforts and innate abilities generate inventions of varying qualities. The designer offers a reward to the contestant achieving the highest quality and receives the revenue generated by the innovation. We characterize the equilibrium behavior, outcomes and payoffs for both nondiscriminatory and discriminatory (where the reward is contestant-dependent) contests. We derive conditions under which the designer obtains a larger payoff when using a discriminatory contest and describe settings where these conditions are satisfied.”
EU: Have your say on Future and Emerging Technologies!
European Commission: “Do you have a great idea for a new technology that is not possible yet? Do you think it can become realistic by putting Europe’s best minds on the task? Share your view and the European Commission – via the Future and Emerging Technologies (FET) programme@fet_eu#FET_eu– can make it happen. The consultation is open till 15 June 2014.
The aim of the public consultation launched today is to identify promising and potentially game-changing directions for future research in any technological domain.
Vice-President of the European Commission @NeelieKroesEU, responsible for the Digital Agenda, said: “From protecting the environment to curing disease – the choices and investments we make today will make a difference to the jobs and lives we enjoy tomorrow. Researchers and entrepreneurs, innovators, creators or interested bystanders – whoever you are, I hope you will take this opportunity to take part in determining Europe’s future“.
The consultation is organised as a series of discussions, in which contributors can suggest ideas for a new FET Proactive initiative or discuss the 9 research topics identified in the previous consultation to determine whether they are still relevant today.
The ideas collected via the public consultation will contribute to future FET work programmes, notably the next one (2016-17). This participative process has already been used to draft the current work programme (2014-15).
Background
€2,7 billion will be invested in Future and Emerging Technologies (FET) under the new research programme Horizon 2020#H2020 (2014-2020). This represents a nearly threefold increase in budget compared to the previous research programme, FP7. FET actions are part of the Excellent science pillar of Horizon 2020.
The objective of FET is to foster radical new technologies by exploring novel and high-risk ideas building on scientific foundations. By providing flexible support to goal-oriented and interdisciplinary collaborative research, and by adopting innovative research practices, FET research seizes the opportunities that will deliver long-term benefit for our society and economy.
FET Proactive initiatives aim to mobilise interdisciplinary communities around promising long-term technological visions. They build up the necessary base of knowledge and know-how for kick-starting a future technology line that will benefit Europe’s future industries and citizens in the decades to come. FET Proactive initiatives complement FET Open scheme, which funds small-scale projects on future technology, and FET Flagships, which are large-scale initiatives to tackle ambitious interdisciplinary science and technology goals.
FET previously launched an online consultation (2012-13) to identify research topics for the current work programme. Around 160 ideas were submitted. The European Commission did an exhaustive analysis and produced an informal clustering of these ideas into broad topics. 9 topics were identified as candidates for a FET Proactive initiative. Three are included in the current programme, namely Global Systems Science; Knowing, Doing, Being; and Quantum Simulation.”
Findings of the Big Data and Privacy Working Group Review
John Podesta at the White House Blog: “Over the past several days, severe storms have battered Arkansas, Oklahoma, Mississippi and other states. Dozens of people have been killed and entire neighborhoods turned to rubble and debris as tornadoes have touched down across the region. Natural disasters like these present a host of challenges for first responders. How many people are affected, injured, or dead? Where can they find food, shelter, and medical attention? What critical infrastructure might have been damaged?
Drawing on open government data sources, including Census demographics and NOAA weather data, along with their own demographic databases, Esri, a geospatial technology company, has created a real-time map showing where the twisters have been spotted and how the storm systems are moving. They have also used these data to show how many people live in the affected area, and summarize potential impacts from the storms. It’s a powerful tool for emergency services and communities. And it’s driven by big data technology.
In January, President Obama asked me to lead a wide-ranging review of “big data” and privacy—to explore how these technologies are changing our economy, our government, and our society, and to consider their implications for our personal privacy. Together with Secretary of Commerce Penny Pritzker, Secretary of Energy Ernest Moniz, the President’s Science Advisor John Holdren, the President’s Economic Advisor Jeff Zients, and other senior officials, our review sought to understand what is genuinely new and different about big data and to consider how best to encourage the potential of these technologies while minimizing risks to privacy and core American values.
Over the course of 90 days, we met with academic researchers and privacy advocates, with regulators and the technology industry, with advertisers and civil rights groups. The President’s Council of Advisors for Science and Technology conducted a parallel study of the technological trends underpinning big data. The White House Office of Science and Technology Policy jointly organized three university conferences at MIT, NYU, and U.C. Berkeley. We issued a formal Request for Information seeking public comment, and hosted a survey to generate even more public input.
Today, we presented our findings to the President. We knew better than to try to answer every question about big data in three months. But we are able to draw important conclusions and make concrete recommendations for Administration attention and policy development in a few key areas.
There are a few technological trends that bear drawing out. The declining cost of collection, storage, and processing of data, combined with new sources of data like sensors, cameras, and geospatial technologies, mean that we live in a world of near-ubiquitous data collection. All this data is being crunched at a speed that is increasingly approaching real-time, meaning that big data algorithms could soon have immediate effects on decisions being made about our lives.
The big data revolution presents incredible opportunities in virtually every sector of the economy and every corner of society.
Big data is saving lives. Infections are dangerous—even deadly—for many babies born prematurely. By collecting and analyzing millions of data points from a NICU, one study was able to identify factors, like slight increases in body temperature and heart rate, that serve as early warning signs an infection may be taking root—subtle changes that even the most experienced doctors wouldn’t have noticed on their own.
Big data is making the economy work better. Jet engines and delivery trucks now come outfitted with sensors that continuously monitor hundreds of data points and send automatic alerts when maintenance is needed. Utility companies are starting to use big data to predict periods of peak electric demand, adjusting the grid to be more efficient and potentially averting brown-outs.
Big data is making government work better and saving taxpayer dollars. The Centers for Medicare and Medicaid Services have begun using predictive analytics—a big data technique—to flag likely instances of reimbursement fraud before claims are paid. The Fraud Prevention System helps identify the highest-risk health care providers for waste, fraud, and abuse in real time and has already stopped, prevented, or identified $115 million in fraudulent payments.
But big data raises serious questions, too, about how we protect our privacy and other values in a world where data collection is increasingly ubiquitous and where analysis is conducted at speeds approaching real time. In particular, our review raised the question of whether the “notice and consent” framework, in which a user grants permission for a service to collect and use information about them, still allows us to meaningfully control our privacy as data about us is increasingly used and reused in ways that could not have been anticipated when it was collected.
Big data raises other concerns, as well. One significant finding of our review was the potential for big data analytics to lead to discriminatory outcomes and to circumvent longstanding civil rights protections in housing, employment, credit, and the consumer marketplace.
No matter how quickly technology advances, it remains within our power to ensure that we both encourage innovation and protect our values through law, policy, and the practices we encourage in the public and private sector. To that end, we make six actionable policy recommendations in our report to the President:
Advance the Consumer Privacy Bill of Rights. Consumers deserve clear, understandable, reasonable standards for how their personal information is used in the big data era. We recommend the Department of Commerce take appropriate consultative steps to seek stakeholder and public comment on what changes, if any, are needed to the Consumer Privacy Bill of Rights, first proposed by the President in 2012, and to prepare draft legislative text for consideration by stakeholders and submission by the President to Congress.
Pass National Data Breach Legislation. Big data technologies make it possible to store significantly more data, and further derive intimate insights into a person’s character, habits, preferences, and activities. That makes the potential impacts of data breaches at businesses or other organizations even more serious. A patchwork of state laws currently governs requirements for reporting data breaches. Congress should pass legislation that provides for a single national data breach standard, along the lines of the Administration’s 2011 Cybersecurity legislative proposal.
Extend Privacy Protections to non-U.S. Persons. Privacy is a worldwide value that should be reflected in how the federal government handles personally identifiable information about non-U.S. citizens. The Office of Management and Budget should work with departments and agencies to apply the Privacy Act of 1974 to non-U.S. persons where practicable, or to establish alternative privacy policies that apply appropriate and meaningful protections to personal information regardless of a person’s nationality.
Ensure Data Collected on Students in School is used for Educational Purposes. Big data and other technological innovations, including new online course platforms that provide students real time feedback, promise to transform education by personalizing learning. At the same time, the federal government must ensure educational data linked to individual students gathered in school is used for educational purposes, and protect students against their data being shared or used inappropriately.
Expand Technical Expertise to Stop Discrimination. The detailed personal profiles held about many consumers, combined with automated, algorithm-driven decision-making, could lead—intentionally or inadvertently—to discriminatory outcomes, or what some are already calling “digital redlining.” The federal government’s lead civil rights and consumer protection agencies should expand their technical expertise to be able to identify practices and outcomes facilitated by big data analytics that have a discriminatory impact on protected classes, and develop a plan for investigating and resolving violations of law.
Amend the Electronic Communications Privacy Act. The laws that govern protections afforded to our communications were written before email, the internet, and cloud computing came into wide use. Congress should amend ECPA to ensure the standard of protection for online, digital content is consistent with that afforded in the physical world—including by removing archaic distinctions between email left unread or over a certain age.
We also identify several broader areas ripe for further study, debate, and public engagement that, collectively, we hope will spark a national conversation about how to harness big data for the public good. We conclude that we must find a way to preserve our privacy values in both the domestic and international marketplace. We urgently need to build capacity in the federal government to identify and prevent new modes of discrimination that could be enabled by big data. We must ensure that law enforcement agencies using big data technologies do so responsibly, and that our fundamental privacy rights remain protected. Finally, we recognize that data is a valuable public resource, and call for continuing the Administration’s efforts to open more government data sources and make investments in research and technology.
While big data presents new challenges, it also presents immense opportunities to improve lives, the United States is perhaps better suited to lead this conversation than any other nation on earth. Our innovative spirit, technological know-how, and deep commitment to values of privacy, fairness, non-discrimination, and self-determination will help us harness the benefits of the big data revolution and encourage the free flow of information while working with our international partners to protect personal privacy. This review is but one piece of that effort, and we hope it spurs a conversation about big data across the country and around the world.
Read the Big Data Report.
See the fact sheet from today’s announcement.“
Saving Big Data from Big Mouths
Cesar A. Hidalgo in Scientific American: “It has become fashionable to bad-mouth big data. In recent weeks the New York Times, Financial Times, Wired and other outlets have all run pieces bashing this new technological movement. To be fair, many of the critiques have a point: There has been a lot of hype about big data and it is important not to inflate our expectations about what it can do.
But little of this hype has come from the actual people working with large data sets. Instead, it has come from people who see “big data” as a buzzword and a marketing opportunity—consultants, event organizers and opportunistic academics looking for their 15 minutes of fame.
Most of the recent criticism, however, has been weak and misguided. Naysayers have been attacking straw men, focusing on worst practices, post hoc failures and secondary sources. The common theme has been to a great extent obvious: “Correlation does not imply causation,” and “data has biases.”
Critics of big data have been making three important mistakes:
First, they have misunderstood big data, framing it narrowly as a failed revolution in social science hypothesis testing. In doing so they ignore areas where big data has made substantial progress, such as data-rich Web sites, information visualization and machine learning. If there is one group of big-data practitioners that the critics should worship, they are the big-data engineers building the social media sites where their platitudes spread. Engineering a site rich in data, like Facebook, YouTube, Vimeo or Twitter, is extremely challenging. These sites are possible because of advances made quietly over the past five years, including improvements in database technologies and Web development frameworks.
Big data has also contributed to machine learning and computer vision. Thanks to big data, Facebook algorithms can now match faces almost as accurately as humans do.
And detractors have overlooked big data’s role in the proliferation of computational design, data journalism and new forms of artistic expression. Computational artists, journalists and designers—the kinds of people who congregate at meetings like Eyeo—are using huge sets of data to give us online experiences that are unlike anything we experienced in paper. If we step away from hypothesis testing, we find that big data has made big contributions.
The second mistake critics often make is to confuse the limitations of prototypes with fatal flaws. This is something I have experienced often. For example, in Place Pulse—a project I created with my team the M.I.T. Media Lab—we used Google Street View images and crowdsourced visual surveys to map people’s perception of a city’s safety and wealth. The original method was rife with limitations that we dutifully acknowledged in our paper. Google Street View images are taken at arbitrary times of the day and showed cities from the perspective of a car. City boundaries were also arbitrary. To overcome these limitations, however, we needed a first data set. Producing that first limited version of Place Pulse was a necessary part of the process of making a working prototype.
A year has passed since we published Place Pulse’s first data set. Now, thanks to our focus on “making,” we have computer vision and machine-learning algorithms that we can use to correct for some of these easy-to-spot distortions. Making is allowing us to correct for time of the day and dynamically define urban boundaries. Also, we are collecting new data to extend the method to new geographical boundaries.
Those who fail to understand that the process of making is iterative are in danger of being too quick to condemn promising technologies. In 1920 the New York Times published a prediction that a rocket would never be able to leave atmosphere. Similarly erroneous predictions were made about the car or, more recently, about iPhone’s market share. In 1969 the Times had to publish a retraction of their 1920 claim. What similar retractions will need to be published in the year 2069?
Finally, the doubters have relied too heavily on secondary sources. For instance, they made a piñata out of the 2008 Wired piece by Chris Anderson framing big data as “the end of theory.” Others have criticized projects for claims that their creators never made. A couple of weeks ago, for example, Gary Marcus and Ernest Davis published a piece on big data in the Times. There they wrote about another of one of my group’s projects, Pantheon, which is an effort to collect, visualize and analyze data on historical cultural production. Marcus and Davis wrote that Pantheon “suggests a misleading degree of scientific precision.” As an author of the project, I have been unable to find where I made such a claim. Pantheon’s method section clearly states that: “Pantheon will always be—by construction—an incomplete resource.” That same section contains a long list of limitations and caveats as well as the statement that “we interpret this data set narrowly, as the view of global cultural production that emerges from the multilingual expression of historical figures in Wikipedia as of May 2013.”
Bickering is easy, but it is not of much help. So I invite the critics of big data to lead by example. Stop writing op–eds and start developing tools that improve on the state of the art. They are much appreciated. What we need are projects that are worth imitating and that we can build on, not obvious advice such as “correlation does not imply causation.” After all, true progress is not something that is written, but made.”
Using data to treat the sickest and most expensive patients
Dan Gorenstein for Marketplace (radio): “Driving to a big data conference a few weeks back, Dr. Jeffrey Brenner brought his compact SUV to a full stop – in the middle of a short highway entrance ramp in downtown Philadelphia…
Here’s what you need to know about Dr. Jeffrey Brenner: He really likes to figure out how things work. And he’s willing to go to extremes to do it – so far that he’s risking his health policy celebrity status.
Perhaps it’s not the smartest move from a guy who just last fall was named a MacArthur Genius, but this month, Brenner began to test his theory for treating some of the sickest and most expensive patients.
“We can actually take the sickest and most complicated patients, go to their bedside, go to their home, go with them to their appointments and help them for about 90 days and dramatically improve outcomes and reduce cost,” he says.
That’s the theory anyway. Like many ideas when it comes to treating the sickest patients, there’s little data to back up that it works.
Brenner’s willing to risk his reputation precisely because he’s not positive his approach for treating folks who cycle in and out of the healthcare system — “super-utilizers” — actually works.
“It’s really easy for me at this point having gotten a MacArthur award to simply declare what we do works and to drive this work forward without rigorously testing it,” Brenner said. “We are not going to do that,” he said. “We don’t think that’s the right thing to do. So we are going to do a randomized controlled trial on our work and prove whether it works and how well it works.”
Helping lower costs and improve care for the super-utilizers is one of the most pressing policy questions in healthcare today. And given its importance, there is a striking lack of data in the field.
People like to call randomized controlled trials (RCTs) the gold standard of scientific testing because two groups are randomly assigned – one gets the treatment, while the other doesn’t – and researchers closely monitor differences.
But a 2012 British Medical Journal article found over the last 25 years, a total of six RCTs have focused on care delivery for super-utilizers.
Perhaps it’s not the smartest move from a guy who just last fall was named a MacArthur Genius, but this month, Brenner began to test his theory for treating some of the sickest and most expensive patients.
“We can actually take the sickest and most complicated patients, go to their bedside, go to their home, go with them to their appointments and help them for about 90 days and dramatically improve outcomes and reduce cost,” he says.
That’s the theory anyway. Like many ideas when it comes to treating the sickest patients, there’s little data to back up that it works.
Brenner’s willing to risk his reputation precisely because he’s not positive his approach for treating folks who cycle in and out of the healthcare system — “super-utilizers” — actually works.
“It’s really easy for me at this point having gotten a MacArthur award to simply declare what we do works and to drive this work forward without rigorously testing it,” Brenner said. “We are not going to do that,” he said. “We don’t think that’s the right thing to do. So we are going to do a randomized controlled trial on our work and prove whether it works and how well it works.”
Helping lower costs and improve care for the super-utilizers is one of the most pressing policy questions in healthcare today. And given its importance, there is a striking lack of data in the field.
People like to call randomized controlled trials (RCTs) the gold standard of scientific testing because two groups are randomly assigned – one gets the treatment, while the other doesn’t – and researchers closely monitor differences.
But a 2012 British Medical Journal article found over the last 25 years, a total of six RCTs have focused on care delivery for super-utilizers.
…Every major health insurance company – Medicare and Medicaid, too – has spent billions on programs for super-utilizers. The absence of rigorous evidence raises the question: Is all this effort built on health policy quicksand?
Not being 100 percent sure can be dangerous, says Duke behavioral scientist Peter Ubel, particularly in healthcare.
Ubel said back in the 1980s and 90s doctors prescribed certain drugs for irregular heartbeats. The medication, he said, made those weird rhythms go away, leaving beautiful-looking EKGs.
“But no one had tested whether people receiving these drugs actually lived longer, and many people thought, ‘Why would you do that? We can look at their cardiogram and see that they’re getting better,’” Ubel said. “Finally when somebody put that evidence to the test of a randomized trial, it turned out that these drugs killed people.”
WellPoint’s Nussbaum said he hoped Brenner’s project would inspire others to follow his lead and insert data into the discussion.
“I believe more people should be bold in challenging the status quo of our delivery system,” Nussbaum said. “The Jeff Brenners of the world should be embraced. We should be advocating for them to take on these studies.”
So why aren’t more healthcare luminaries putting their brilliance to the test? There are a couple of reasons.
Harvard economist Kate Baicker said until now there have been few personal incentives pushing people.
“If you’re focused on branding and spreading your brand, you have no incentive to say, ‘How good is my brand after all?’” she said.
And Venrock healthcare venture capitalist Bob Kocher said no one would fault Brenner if he put his brand before science, an age-old practice in this business.
“Healthcare has benefitted from the fact that you don’t understand it. It’s a bit of an art, and it hasn’t been a science,” he said. “You made money in healthcare by putting a banner outside your building saying you are a top something without having to justify whether you really are top at whatever you do.”
Duke’s Ubel said it’s too easy – and frankly, wrong – to say the main reason doctors avoid these rigorous studies is because they’re afraid to lose money and status. He said doctors aren’t immune from the very human trap of being sure their own ideas are right.
He says psychologists call it confirmation bias.
“Everything you see is filtered through your hopes, your expectations and your pre-existing beliefs,” Ubel said. “And that’s why I might look at a grilled cheese sandwich and see a grilled cheese sandwich and you might see an image of Jesus,” he says.
Even with all these hurdles, MIT economist Amy Finkelstein – who is running the RCT with Brenner – sees change coming.
“Providers have a lot more incentive now than they use to,” she said. “They have much more skin in the game.”
Finkelstein said hospital readmission penalties and new ways to pay doctors are bringing market incentives that have long been missing.
Brenner said he accepts that the truth of what he’s doing in Camden may be messier than the myth.
Feds see innovation decline within government
Federal Times: “Support for innovation is declining across the government, according to a report by the Partnership for Public Service released April 23.
Federal employee answers to three innovation-related questions on the annual Federal Employee Viewpoint Survey dropped from 61.5 out of 100 in 2012 to 59.4 out of 100, according to the report, produced in partnership with Deloitte.
Federal employee answers to three innovation-related questions on the annual Federal Employee Viewpoint Survey dropped from 61.5 out of 100 in 2012 to 59.4 out of 100, according to the report, produced in partnership with Deloitte.
This chart, extracted from the Partnership for Public Service report, shows the slow but steady decline of innovation measures. (Partnership for Public Service)
While 90 percent of employees surveyed report they are always looking for better ways to do their jobs only 54.7 percent feel encouraged to do so and only 33.4 percent believe their agency rewards creativity and innovation.
“The bottom line is that federal workers are motivated to improve the way they do their work, but they do not feel supported by their organizations,” the report said.
Dave Dye, a director of human capital at Deloitte, LLP, said the report is a message to agency leaders to pay attention and have discussions on innovation and make concerted efforts to enhance innovation in their areas.
“It’s not that leaders have to be innovative in their own right it means they need to set up environments for people to feel that innovation Is encouraged, rewarded and respected,” Dye said.
Most agencies saw a decline in their “innovation score” according to the report, including:
■ The Army saw one of the largest drops in its innovation score – from 64.2 out of 100 I 2012 to 60.1 out of 100 in 2013.
■ NASA – which had the highest score at 76.0 out of 100 in 2013 – also dropped from 76.5 in 2012.
■ The Financial Crimes Enforcement Network at the Treasury Department saw one of the largest drops among component agencies, from 63.8 out of 100 in 2012 to 52.0 in 2013.
Some agencies that have shown improvement are the National Science Foundation and the Peace Corps. Some NASA facilities also saw improvement, including the John C. Stennis Space Center in Mississippi and the George C. Marshall Space Flight Center in Alabama.
The ongoing effects of sequestration, budget cuts and threat of furloughs may also have had a dampening effect on federal employees, Dye said.
“When people feel safer or more sure about whats going on they are going to better focus on the mission,” he said.
Agency managers should also work to improve their work environments to build trust and confidence in their workforce by showing concerns about people’s careers and supporting development opportunities while recognizing good work, according to Dye.
The report recommends that agencies recognize employees at team meetings or with more formal awards to highlight innovation and creativity and reward success. Managers should make sure to share specific goals, provide a forum for open discussion and work to build trust among the workforce that is needed to help spur innovation.”
Paying Farmers to Welcome Birds
Jim Robbins in The New York Times: “The Central Valley was once one of North America’s most productive wildlife habitats, a 450-mile-long expanse marbled with meandering streams and lush wetlands that provided an ideal stop for migratory shorebirds on their annual journeys from South America and Mexico to the Arctic and back.
Farmers and engineers have long since tamed the valley. Of the wetlands that existed before the valley was settled, about 95 percent are gone, and the number of migratory birds has declined drastically. But now an unusual alliance of conservationists, bird watchers and farmers have joined in an innovative plan to restore essential habitat for the migrating birds.
The program, called BirdReturns, starts with data from eBird, the pioneering citizen science project that asks birders to record sightings on a smartphone app and send the information to the Cornell Lab of Ornithology in upstate New York.
By crunching data from the Central Valley, eBird can generate maps showing where virtually every species congregates in the remaining wetlands. Then, by overlaying those maps on aerial views of existing surface water, it can determine where the birds’ need for habitat is greatest….
BirdReturns is an example of the growing movement called reconciliation ecology, in which ecosystems dominated by humans are managed to increase biodiversity.
“It’s a new ‘Moneyball,’ ” said Eric Hallstein, an economist with the Nature Conservancy and a designer of the auctions, referring to the book and movie about the Oakland Athletics’ data-driven approach to baseball. “We’re disrupting the conservation industry by taking a new kind of data, crunching it differently and contracting differently.”
The Transformative Impact of Data and Communication on Governance
Steven Livingston at Brookings: “How do digital technologies affect governance in areas of limited statehood – places and circumstances characterized by the absence of state provisioning of public goods and the enforcement of binding rules with a monopoly of legitimate force? In the first post in this series I introduced the limited statehood concept and then described the tremendous growth in mobile telephony, GIS, and other technologies in the developing world. In the second post I offered examples of the use of ICT in initiatives intended to fill at least some of the governance vacuum created by limited statehood. With mobile phones, for example, farmers are informed of market conditions, have access to liquidity through M-Pesa and similar mobile money platforms….
This brings to mind another type of ICT governance initiative. Rather than fill in for or even displace the state some ICT initiatives can strengthen governance capacity. Digital government – the use of digital technology by the state itself — is one important possibility. Other initiatives strengthen the state by exerting pressure. Countries with weak governance sometimes take the form of extractive states or those, which cater to the needs of an elite, leaving the majority of the population in poverty and without basic public services. This is what Daron Acemoglu and James A. Robinson call extractive political and economic institutions. Inclusive states, on the other hand, are pluralistic, bound by the rule of law, respectful of property rights, and, in general, accountable. Accountability mechanisms such as a free press and competitive multiparty elections are instrumental to discourage extractive institutions. What ICT-based initiatives might lend a hand in strengthening accountability? We can point to three examples.
Example One: Using ICT to Protect Human Rights
Nonstate actors now use commercial, high-resolution remote sensing satellites to monitor weapons programs and human rights violations. Amnesty International’s Remote Sensing for Human Rights offers one example, and Satellite Sentinel offers another. Both use imagery from DigitalGlobe, an American remote sensing and geospatial content company. Other organizations have used commercially available remote sensing imagery to monitor weapons proliferation. The Institute for Science and International Security, a Washington-based NGO, revealed the Iranian nuclear weapons program in 2003 using commercial satellite imagery…
Example Two: Crowdsourcing Election Observation
Others have used mobile phones and GIS to crowdsource election observation. For the 2011 elections in Nigeria, The Community Life Project, a civil society organization, created ReclaimNaija, an elections process monitoring system that relied on GIS and amateur observers with mobile phones to monitor the elections. Each of the red dots represents an aggregation of geo-located incidents reported to the ReclaimNaija platform. In a live map, clicking on a dot disaggregates the reports, eventually taking the reader to individual reports. Rigorous statistical analysis of ReclaimNaija results and the elections suggest it contributed to the effectiveness of the election process.
ReclaimNaija: Election Incident Reporting System Map
Example Three: Using Genetic Analysis to Identify War Crimes
In recent years, more powerful computers have led to major breakthroughs in biomedical science. The reduction in cost of analyzing the human genome has actually outpaced Moore’s Law. This has opened up new possibilities for the use of genetic analysis in forensic anthropology. In Guatemala, the Balkans, Argentina, Peru and in several other places where mass executions and genocides took place, forensic anthropologists are using genetic analysis to find evidence that is used to hold the killers – often state actors – accountable…”