In different ways, these organizations are all putting in tremendous effort to provide the benefits of computing to more people of all walks of life and to preserve the vigor and creativity of computing platforms. I found out through my meetings what sorts of systemic change is required to achieve these goals and saw these organizations grapple with a variety of strategies to get there. This report is not a statement from any of these groups, just my personal observations.

USACM Public Policy Council

The Association for Computing Machinery (ACM) has been around almost as long as electronic computers: it was founded in 1948. I joined in the 1980s but was mostly a passive recipient of information. Although last week’s policy meeting was the first I had ever attended at ACM, many of the attendees were familiar to me from previous work on either technical or policy problems.

As we met, open data was in the news thanks to a White House memo reiterating its call for open government data in machine-readable form. Although the movement for these data sets has been congealing from many directions over the past few years, USACM was out in front back in early 2009 with a policy recommendation for consumable data.

USACM weighs in on such policy issues as copyrights and patents, accessibility, privacy, innovation, and the various other topics on which you’d expect computer scientists to have professional opinions. I felt that the group’s domestic scope is oddly out of sync with the larger ACM, which has been assiduously expanding overseas for many years. A majority of ACM members now live outside the United States.

In fact, many of today’s issues have international reach: cybersecurity, accessibility, and copyright, to name some obvious ones. Although USACM has submitted comments on ACTA and the Trans-Pacific Partnership, they don’t maintain regular contacts work with organizations outside the country. Perhaps they’ll have the cycles to add more international connections in the future. Eugene Spafford, security expert and current chair of the policy committee, pointed out that many state-level projects in the US would be worth commenting on as well.

It’s also time to recognize that policy is made by non-governmental organizations as well as governments. Facebook and Google, for example, are setting policies about privacy. The book The End of Power: From Boardrooms to Battlefields and Churches to States, Why Being In Charge Isn’t What It Used To Be by Moisés Naím claims that power is becoming more widely distributed (not ending, really) and that a bigger set of actors should be taken into account by people hoping to effect change.

USACM represents a technical organization, so it seeks to educate policy decision-makers on issues where there is an intersection of computing technology and public policy. Their principles derive from the ACM Code of Ethics and Professional Conduct, which evolved from input by many ACM members and the organization’s experience. USACM papers usually focus on pointing out the technical implications of legislative or regulatory choices.

When the notorious SOPA and PIPA bills came up, for instance, the USACM didn’t issue the kind of blanket condemnation many other groups put out, supported by appeals to vague concepts such as freedom and innovation. Instead, they put the microscope to the bills’ provisions and issued brief comments about negative effects on the functioning of the Internet, with a focus on DNS. Spafford commented, “We also met privately with Congressional staff and provided tutorials on how DNS and similar mechanisms worked. That helped them understand why their proposals would fail."

Open Technology Institute

NAF is a flexible and innovative think tank proposing new strategies for dozens of national and international issues. Mostly progressive, in my view, it is committed to considering a wide range of possible solutions and finding rational solutions that all sides can accept. On computing and Internet issues, it features the Open Technology Institute, a rare example of a non-profit group that is firmly engaged in both technology production and policy-making. This reflects the multi-disciplinary expertise of OTI director Sascha Meinrath.

Known best for advocating strong policies to promote high-bandwidth Internet access, the OTI also concerns itself with the familiar range of policies in copyright, patents, privacy, and security. Google executive chairman Eric Schmidt is chair of the NAF board, and Google has been generous in its donations to NAF, including storage for the massive amounts of data the OTI has collected on bandwidth worldwide through its Measurement Lab, or M-Lab.

M-Lab measures Internet traffic around the world, using crowdsourcing to produce realistic reports about bandwidth, chokepoints, and other aspects of traffic. People can download the M-Lab tools to check for traffic shaping by providers and other characteristic of their connection, and send results back to M-Lab for storage. (They now have 700 terabytes of such data.) Other sites offer speed testing for uploads and downloads, but M-Lab is unique in storing and visualizing the results. The FCC, among others, has used M-Lab to determine the uneven progress of bandwidth in different regions. Like all OTI software projects, Measurement Lab is open source software.

Open Source Initiative

For my last meeting of the day, I dropped by for the last few sessions of Open Source Initiative’s Open Source Community Summit and talked to Deborah Bryant, Simon Phipps, and Bruno Souza. OSI’s recent changes represent yet another strategy for pushing change in the computer field.

OSI is best known for approving open source licenses and seems to be universally recognized as an honest and dependable judge in that area, but they want to branch out from this narrow task. About a year ago, they completely revamped their structure and redefined themselves as a membership organization. (I plunked down some cash as one of their first individual members, having heard of the change from Simon at a Community Leadership Summit).

When they announced the summit, they opened up a wiki for discussion about what to cover. The winner hands down was an all-day workshop on licensing — I guess you can tell when you’re in Washington. (The location was the Library of Congress.)

They also held an unconference that attracted a nice mix of open-source and proprietary software companies, software uses, and government workers. I heard working group summaries that covered such basic advice as getting ownership of the code that you contract out to companies to create for you, using open source to attract and retain staff, and justifying the investment in open source by thinking more broadly than the agency’s immediate needs and priorities.

Organizers used the conference to roll out Working Groups, a new procedure for starting projects. Two such projects, launched by members, are the development of a FAQ and the creation of a speaker’s bureau. Anybody with an idea that fits the mission of promoting and adopting open source software can propose a project, but the process requires strict deadlines and plans for fiscally sustaining the project.

OSI is trying to change government and society by changing the way they make and consume software. USACM is trying to improve the institutions’ understanding of software as well as the environment in which it is made. NAF is trying to extend computing to everyone, and using software as a research tool in pursuit of that goal. Each organization, starting from a different place, is expanding its options and changing itself in order to change others.

Such is the confluence of old and new at LISA. I also heard of the continued relevance of magnetic tape–its storage costs are orders of magnitude below those of disks–and of new developements on NFS. Think of NFS as a protocol, not a filesystem: it can now connect many different filesystems, including the favorites of modern distributed system users.

LISA, and the USENIX organization that valiantly unveils it each year, are communities at least as resilient as the systems that their adherents spend their lives humming. Familiar speakers return each year. Members crowd a conference room in the evening to pepper the staff with questions about organizational issues. Attendees exchange their t-shirts for tuxes to attend a three-hour reception aboard a boat on the San Diego harbor, which this time was experiencing unseasonably brisk weather. (Full disclosure: I skipped the reception and wrote this article instead.) Let no one claim that computer administrators are anti-social.

Again in the spirit of full disclosure, let me admit that I perform several key operations on a Solaris system. When it goes away (which someday it will), I’ll have to alter some workflows.

The continued resilience of LISA

Conferences, like books, have a hard go of it in the age of instant online information. I wasn’t around in the days when people would attend conferences to exchange magnetic tapes with their free software, but I remember the days when companies would plan their releases to occur on the first day of a conference and would make major announcements there. The tradition of using conferences to propel technical innovation is not dead; for instance, OpenStack was announced at an O’Reilly Open Source convention.

But as pointed out by Thomas Limoncelli, an O’Reilly author (Time Management for System Administrators) and a very popular LISA speaker, the Internet has altered the equation for product announcements in two profound ways. First of all, companies and open source projects can achieve notoriety in other ways without leveraging conferences. Second, and more subtly, the philosophy of “release early, release often” launches new features multiple times a year and reduces the impact of major versions. The conferences need a different justification.

Limoncelli says that LISA has survived by getting known as the place you can get training that you can get nowhere else. “You can learn about a tool from the person who created the tool,” he says. Indeed, at the BOFs it was impressive to hear the creator of a major open source tool reveal his plans for a major overhaul that would permit plugin modules. It was sobering though to hear him complain about a lack of funds to do the job, and discuss with the audience some options for getting financial support.

LISA is not only a conference for the recognized stars of computing, but a place to show off students who can create a complete user administration interface in their spare time, or design a generalized extension of common Unix tools (grep, diff, and so forth) that work on structured blocks of text instead of individual lines.

Another long-time attendee told me that companies don’t expect anyone here to whip out a checkbook in the exhibition hall, but they still come. They have a valuable chance at LISA to talk to people who don’t have direct purchasing authority but possess the technical expertise to explain to their bosses the importance of new products. LISA is also a place where people can delve as deep as the please into technical discussions of products.

I noticed good attendance at vendor-sponsored Bird-of-a-Feather sessions, even those lacking beer. For instance, two Ceph staff signed up for a BOF at 10 in the evening, and were surprised to see over 30 attendees. It was in my mind a perfect BOF. The audience talked more than the speakers, and the speakers asked questions as well as delivering answers.

But many BOFs didn’t fit the casual format I used to know. Often, the leader turned up with a full set of slides and took up a full hour going through a list of new features. There were still audience comments, but no more than at a conference session.

Memorable keynotes

One undeniable highlight of LISA was the keynote by Internet pioneer Vint Cerf. After years in Washington, DC, Cerf took visible pleasure in geeking out with people who could understand the technical implications of the movements he likes to track. His talk ranged from the depth of his wine cellar (which he is gradually outfitting with sensors for quality and security) to interplanetary travel.

The early part of his talk danced over general topics that I think were already adequately understood by his audience, such as the value of DNSSEC. But he often raised useful issues for further consideration, such as who will manage the billions of devices that will be attached to the Internet over the next few years. It can be useful to delegate read access and even write access (to change device state) to a third party when the device owner is unavailable. In trying to imagine a model for sets of device, Cerf suggested the familiar Internet concept of an autonomous system, which obviously has scaled well and allowed us to distinguish routers running different protocols.

The smart grid (for electricity) is another concern of Cerf’s. While he acknowledged known issues of security and privacy, he suggested that the biggest problem will be the classic problem of coordinated distributed systems. In an environment where individual homes come and go off the grid, adding energy to it along with removing energy, it will be hard to predict what people need and produce just the right amount at any time. One strategy involves microgrids: letting neighborhoods manage their own energy needs to avoid letting failures cascade through a large geographic area.

Cerf did not omit to warn us of the current stumbling efforts in the UN to institute more governance for the Internet. He acknowledged that abuse of the Internet is a problem, but said the ITU needs an “excuse to continue” as radio, TV, etc. migrate to the Internet and the ITU’s standards see decreasing relevance.

Cerf also touted the Digital Vellum project for the preservation of data and software. He suggested that we need a legal framework that would require software developers to provide enough information for people to continue getting access to their own documents as old formats and software are replaced. “If we don’t do this,” he warned, “our 22nd-century descendants won’t know much about us.”

Talking about OpenFlow and Software Defined Networking, he found its most exciting opportunity is to let us use content to direct network traffic in addition to, or instead of, addresses.

Another fine keynote was delivered by Matt Blaze on a project he and colleagues conducted to assess the security of the P25 mobile systems used everywhere by security forces, including local police and fire departments, soldiers in the field, FBI and CIA staff conducting surveillance, and executive bodyguards. Ironically, there are so many problems with these communication systems that the talk was disappointing.

I should in no way diminish the intelligence and care invested by these researchers from the University of Pennsylvania. It’s just the history of P25 makes security lapses seem inevitable. Because it was old, and was designed to accommodate devices that were even older, it failed to implement basic technologies such as asymmetric encryption that we now take for granted. Furthermore, most of the users of these devices are more concerned with getting messages to their intended destinations (so that personnel can respond to an emergency) than in preventing potential enemies from gaining access. Putting all this together, instead of saying “What impressive research,” we tend to say, “What else would you expect?”

Random insights

Attendees certainly had their choice of virtualization and cloud solutions at the conference. A very basic introduction to OpenStack was offered, along with another by developers of CloudStack. Although the latter is older and more settled, it is losing the battle of mindshare. One developer explained that CloudStack has a smaller scope than OpenStack, because CloudStack is focused on high-computing environments. However, he claimed, CloudStack works on really huge deployments where he hasn’t seen other successful solutions. Yet another open source virtuallization platform presented was Google’s Ganeti.

I also attended talks and had chats with developers working on the latest generation of data stores: massive distributed file systems like Hadoop’s HDFS, and high-performance tools such as HBase and Impala, for accessing the data it stores. There seems be accordion effect in data stores: developers start with simple flat or key-value structures. Then they find the need over time–depending on their particular applications–for more hierarchy or delimited data, and either make their data stores more heavyweight or jerry-rig the structure through conventions such as defining fields for certain purposes. Finally we’re back at something mimicking the features of a relational database, and someone rebels and starts another bare-bones project.

One such developer told me hoped his project never turns into a behemoth like CORBA or (lamentably) what WS-* specifications seem to have wrought.

CORBA is universally recognized as dead–perhaps stillborn, because I never heard of major systems deployed in production. In fact, I never knew of an implementation that caught up with the constant new layers of complexity thrown on by the standards committee.

In contrast, WS-* specifications teeter on the edge of acceptability, as a number of organizations swear by it.

I pointed out to my colleague that most modern cloud or PC systems are unlikely to suffer from the weight of CORBA or WS-*, because the latter two systems were created for environments without trust. They were meant to tie together organizations with conflicting goals, and were designed by consortia of large vendors jockeying for market share. For both of these reasons, they have to negotiate all sorts of parameters and add many assurances to every communication.

Recently we’ve seen an increase of interest in functional programming. It occurred to me this week that many aspects of functional programming go nicely with virtualization and the cloud. When you write code with no side effects and no global lack of state, you can recover more easily when instances of your servers disappear. It’s fascinating to see how technologies coming from many different places push each other forward–and sometimes hold each other back.

In the current opinion torrent, Clay Shirky treats MOOCs in a recent article, and Joseph E. Aoun, president of Northeastern University, writes (in a Boston Globe subscription-only article) that traditional colleges will have to deal with the MOOC challenge. Jon Bruner points out on Radar that non-elite American institutions could use a good scare (although I know a lot of people whose lives were dramatically improved by attending such colleges). The December issue of Communications of the ACM offers Professor Richard A. DeMillo from the Georgia Institute of Technology assessing the possible role of MOOCs in changing education, along with an editorial by editor-in-chief Moshe Y. Vardi culminating with, “If I had my wish, I would wave a wand and make MOOCs disappear.”

There’s a popular metaphor for this early stage of innovation: we look back to the time when film-makers made the first moving pictures with professional performers by setting up cameras before stages in theaters. This era didn’t last long before visionaries such as Georges Méliès, D. W. Griffith, Sergei Eisenstein, and Luis Buñuel uncovered what the new medium could do for itself. How soon will colleges get tired of putting lectures online and offer courses that take advantage of new media?

Two more appealing trends are already big. One is DIY courses, as popularized in the book Fab by Neil Gershenfeld at the MIT Media Lab. O’Reilly’s own Make projects are part of this movement. Fab courses represent the polar opposite of MOOCs in many ways. They are delivered in small settings to students whose dedication, inspiration, and talent have to match those of the teacher — the course asks a lot of everybody. But from anecdotal reports, DIY courses have been shown to be very powerful growth mechanisms in environments ranging from the top institutions (like MIT) to slums around the world. Teenagers are even learning to play with biological matter in labs such as BioCurious.

Fundamentally, DIY is a way to capture the theory of learning by doing, which goes back at least to John Dewey at the turn of the 20th century. The availability of 3D makers, cheap materials, fab software, and instructions over the Internet lend the theory a new practice.

“I believe in everything never yet said.”–Rainer Maria Rilke, Das Stunden-Buch

The other major trend cracking the foundations of education is peer-to-peer information exchange. This, like learning by doing, has plenty of history. The symposia of Ancient Greece (illustrated in fictional form by Plato) and the Talmudic discussions that underlay the creation of modern Judaism over 2,000 years ago show that human beings have long been used to learning from each other. Peer information exchange raged on centuries later in cafés and salons, beer halls and sewing circles. Experts were important, and everybody could recognize the arrival of a true expert, but he or she was just first among equals. A lot of students who sign up for MOOCs probably benefit from the online discussion forums as much as from the canned lectures and readings.

Wikipedia is a prominent example of peer-to-peer information exchange, and one that promulgates the contributions of experts, but one that also has trouble with sustainability. (They’re holding one of their fund-raisers now, and it’s a good time to donate.) This leads me to ask what business model colleges can apply in the face of both MOOCs and peer-to-peer knowledge. How do you mobilize a whole community to educate each other, while maintaining the value of expertise?

This challenge — not just a business challenge, but really the challenge of tapping expertise effectively — happens to be one that O’Reilly is dealing with in the field of publishing. We introduced the equivalent of filmed stage shows in the mid-1990s when we created the Safari Bookshelf to provide our books on a subscription-based website. The innovation was in the delivery model, which also delivered a shock to a publishing industry dependent on print sales.

But we knew that Safari Bookshelf barely dipped into the power of the web, which has grown more and more with advances in HTML, JavaScript, and mobile devices. Safari Bookshelf is much more than a collection of web pages with book content now. As a training tool, the web has exploded with other experiments. We offer an interactive school of technology also.

So the field of education will probably see lots of blended models along the way. It’s worth noting that proponents of open content have called for licensing models that reinforce the open promise of the courses. Some courses ask students to write their own textbooks and share them — but one asks where they get the information with which to write their peer-produced textbooks. In an earlier article I examined the difficulties of creating free, open textbooks that are actually usable for teaching. Such dilemmas just show that the investment of large amounts of time by experts are still a critical part of education — but applying the broadcast model to them may be less and less relevant.

Update, December 12: I changed the link text for Clay Shirky’s article because he told me the original did not characterize it properly.

TDD and BDD expand beyond the traditional model of incorporating a test phase into the development process. Most programmers know that ad hoc debugging is not sufficient and that they need to run tests on isolated functions (unit testing) to make sure that a change doesn’t break anything (regression testing). But testing libraries available for Scala, in supporting TDD and BDD, encourage developers to write tests before they even write the code being tested.

Tests can be expressed in human-readable text reminiscent of natural language (although you can’t stretch the comparison too far) so that you are documenting what you want your code to do while expressing the test that ensures that code ultimately will meet your requirements.

Daniel Hinojosa, author of Testing in Scala, describes the frameworks and their use for testing, TDD, and BDD in this interview.

Highlights from our discussion include:

• The special advantages of test frameworks for Scala. [Discussed at the 0:10 mark]
• The two main testing frameworks, ScalaTest and Specs2. It’s worth studying both of these frameworks, but you’ll probably ultimately stick to one based on programming style and how you want to do mocking. [Discussed at the 2:12 mark]
• Mocking simply means removing operations that will take a long time or require outside support, such as a database. When testing, you want to fool your code into believing that the operation took place while actually simulating it. This is especially critical for TDD, because tests are so extensive and run so regularly. [Discussed at the 04:01 mark]
• How the new ScalaMock library extends the abilities to mock parts of the system. This is an emerging technology. [Discussed at the 7:36 mark]
• Generating random input test data. You can actually make your code more robust by throwing garbage values at it rather than by planning what data to input, because a programmer usually fails to anticipate some of the data that will be encountered in production use. For instance, you might not realize how large the input data will be, or might forget to include negative numbers. Scala gives you a full range of control ranging from specifying precise values to allowing completely random input. [Discussed at the 8:24 mark]
• Looking toward the future of Scala testing. [Discussed at the 10:38 mark]

You can view the entire conversation in the following video:

Related:

• Why use Scala
• Editorial Radar: Functional languages
• Subscribe to the free Code podcast through iTunes

SMART, funded by the Office of the National Coordinator in Health and Human Services, is an attempt to slice through the Babel of EHR formats that prevent useful applications from being developed for patient data. Imagine if something like the wealth of mash-ups built on Google Maps (crime sites, disaster markers, restaurant locations) existed for your own health data. This is what SMART hopes to do. They can already showcase some working apps, such as overviews of patient data for doctors, and a real-life implementation of the heart disease user interface proposed by David McCandless in WIRED magazine.

The premise and promise of SMART

At this conference, the presentation that gave me the most far-reaching sense of what SMART can do was by Nich Wattanasin, project manager for i2b2 at Partners. His implementation showed SMART not just as an enabler of individual apps, but as an environment where a user could choose the proper app for his immediate needs. For instance, a doctor could use an app to search for patients in the database matching certain characteristics, then select a particular patient and choose an app that exposes certain clinical information on that patient. In this way, SMART an combine the power of many different apps that had been developed in an uncoordinated fashion, and make a comprehensive data analysis platform from them.

Another illustration of the value of SMART came from lead architect Josh Mandel. He pointed out that knowing a child’s blood pressure means little until one runs it through a formula based on the child’s height and age. Current EHRs can show you the blood pressure reading, but none does the calculation that shows you whether it’s normal or dangerous. A SMART app has been developer to do that. (Another speaker claimed that current EHRs in general neglect the special requirements of child patients.)

SMART is a close companion to the Indivo patient health record. Both of these, aong with the i2b2 data exchange system, were covered in article from an earlier conference at the medical school. Let’s see where platforms for health apps are headed.

How far we’ve come

As I mentioned, this ITdotHealth conference was the second to be held. The first took place in September 2009, and people following health care closely can be encouraged by reading the notes from that earlier instantiation of the discussion.

In September 2009, the HITECH act (part of the American Recovery and Reinvestment Act) had defined the concept of “meaningful use,” but nobody really knew what was expected of health care providers, because the ONC and the Centers for Medicare & Medicaid Services did not release their final Stage 1 rules until more than a year after this conference. Aneesh Chopra, then the Federal CTO, and Todd Park, then the CTO of Health and Human Services, spoke at the conference, but their discussion of health care reform was a “vision.” A surprisingly strong statement for patient access to health records was made, but speakers expected it to be accomplished through the CONNECT Gateway, because there was no Direct. (The first message I could find on the Direct Project forum dated back to November 25, 2009.) Participants had a sophisticated view of EHRs as platforms for applications, but SMART was just a “conceptual framework.”

So in some ways, ONC, Harvard, and many other contributors to modern health care have accomplished an admirable amount over three short years. But some ways we are frustratingly stuck. For instance, few EHR vendors offer API access to patient records, and existing APIs are proprietary. The only SMART implementation for a commercial EHR mentioned at this week’s conference was one created on top of the Cerner API by outsiders (although Cerner was cooperative). Jim Hansen of Dossia told me that there is little point to encourage programmers to create SMART apps while the records are still behind firewalls.

Keynotes

I couldn’t call a report on ITdotHealth complete without an account of the two keynotes by Christiansen and Eric Horvitz, although these took off in different directions from the rest of the conference and served as hints of future developments.

Christiansen is still adding new twists to the theories laid out in c The Innovator’s Dilemma and other books. He has been a backer of the SMART project from the start and spoke at the first ITdotHealth conference. Consistent with his famous theory of disruption, he dismisses hopes that we can reduce costs by reforming the current system of hospitals and clinics. Instead, he projects the way forward through technologies that will enable less trained experts to successively take over tasks that used to be performed in more high-cost settings. Thus, nurse practitioners will be able to do more and more of what doctors do, primary care physicians will do more of what we current delegate to specialists, and ultimately the patients and their families will treat themselves.

He also has a theory about the progression toward openness. Radically new technologies start out tightly integrated, and because they benefit from this integration they tend to be created by proprietary companies with high profit margins. As the industry comes to understand the products better, they move toward modular, open standards and become commoditized. Although one might conclude that EHRs, which have been around for some forty years, are overripe for open solutions, I’m not sure we’re ready for that yet. That’s because the problems the health care field needs to solve are quite different from the ones current EHRs solve. SMART is an open solution all around, but it could serve a marketplace of proprietary solutions and reward some of the venture capitalists pushing health care apps.

While Christiansen laid out the broad environment for change in health care, Horvitz gave us a glimpse of what he hopes the practice of medicine will be in a few years. A distinguished scientist at Microsoft, Horvitz has been using machine learning to extract patterns in sets of patient data. For instance, in a collection of data about equipment uses, ICD codes, vital signs, etc. from 300,000 emergency room visits, they found some variables that predicted a readmission within 14 days. Out of 10,000 variables, they found 500 that were relevant, but because the relational database was strained by retrieving so much data, they reduced the set to 23 variables to roll out as a product.

Another project predicted the likelihood of medical errors from patient states and management actions. This was meant to address a study claiming that most medical errors go unreported.

A study that would make the privacy-conscious squirm was based on the willingness of individuals to provide location data to researchers. The researchers tracked searches on Bing along with visits to hospitals and found out how long it took between searching for information on a health condition and actually going to do something about it. (Horvitz assured us that personally identifiable information was stripped out.)

His goal is go beyond measuring known variables, and to find new ones that could be hidden causes. But he warned that, as is often the case, causality is hard to prove.

As prediction turns up patterns, the data could become a “fabric” on which many different apps are based. Although Horvitz didn’t talk about combining data sets from different researchers, it’s clearly suggested by this progression. But proper de-identification and flexible patient consent become necessities for data combination. Horvitz also hopes to move from predictions to decisions, which he says is needed to truly move to evidence-based health care.

Did the conference promote more application development?

My impression (I have to admit I didn’t check with Dr. Ken Mandl, the organizer of the conference) was that this ITdotHealth aimed to persuade more people to write SMART apps, provide platforms that expose data through SMART, and contribute to the SMART project in general. I saw a few potential app developers at the conference, and a good number of people with their hands on data who were considering the use of SMART. I think they came away favorably impressed–maybe by the presentations, maybe by conversations that the meeting allowed them to have with SMART developers–so we may see SMART in wider use soon. Participants came far for the conference; I talked to one from Geneva, for instance.

The presentations were honest enough, though, to show that SMART development is not for the faint-hearted. On the supply side–that is, for people who have patient data and want to expose it–you have to create a “container” that presents data in the format expected by SMART. Furthermore, you must make sure the data conforms to industry standards, such as SNOMED for diagnoses. This could be a lot of conversion.

On the application side, you may have to deal with SMART’s penchant for Semantic Web technologies such as OWL and SPARQL. This will scare away a number of developers. However, speakers who presented SMART apps at the conference said development was fairly easy. No one matched the developer who said their app was ported in two days (most of which were spent reading the documentation) but development times could usually be measured in months.

Mandl spent some time airing the idea of a consortium to direct SMART. It could offer conformance tests (but probably not certification, which is a heavy-weight endeavor) and interact with the ONC and standards bodies.

After attending two conferences on SMART, I’ve got the impression that one of its most powerful concepts is that of an “app store for health care applications.” But correspondingly, one of the main sticking points is the difficulty of developing such an app store. No one seems to be taking it on. Perhaps SMART adoption is still at too early a stage.

Once again, we are batting our heads up against the walls erected by EHRs to keep data from being extracted for useful analysis. And behind this stands the resistance of providers, the users of EHRs, to give their data to their patients or to researchers. This theme dominated a federal government conference on patient access.

I think SMART will be more widely adopted over time because it is the only useful standard for exposing patient data to applications, and innovation in health care demands these apps. Accountable Care Organizations, smarter clinical trials (I met two representatives of pharmaceutical companies at the conference), and other advances in health care require data crunching, so those apps need to be written. And that’s why people came from as far as Geneva to check out SMART–there’s nowhere else to find what they need. The technical requirements to understand SMART seem to be within the developers’ grasps.

But a formidable phalanx of resistance remains, from those who don’t see the value of data to those who want to stick to limited exchange formats such as CCDs. And as Sean Nolan of Microsoft pointed out, one doesn’t get very far unless the app can fit into a doctor’s existing workflow. Privacy issues were also raised at the conference, because patient fears could stymie attempts at sharing. Given all these impediments, the government is doing what it can; perhaps the marketplace will step in to reward those who choose a flexible software platform for innovation.

Chris takes a very expansive view of project management, stressing the crucial decisions and attitudes that leaders need to take at every stage from the team’s initial mission statement through the design, coding, and testing to the ultimate launch. By merging technical, organizational, and cultural issues, he unravels some of the magic that makes projects successful.

Highlights from the full video interview include:

• Some of the projects Chris has shipped. [Discussed at the 0:30 mark]
• How to listen to your audience while giving a presentation. [Discussed at the 1:24 mark]
• Deadlines and launches. [Discussed at the 6:40 mark]
• Importance of keeping team focused on user experience of launch. [Discussed at the 12:15 mark]
• Creating an API, and its relationship to requirements and Service Oriented Architectures. [Discussed at the 15:27 mark]
• 22:36 What integration testing can accomplish. [Discussed at the 22:36 mark]

You can view the entire conversation in the following video:

Shah will be speaking at Strata Rx in October.

Highlights from the full video interview include:

• Medical science will come unstuck from the clinical trials it has relied on for a couple hundred years, and use data collected in the field [Discussed at the 0:30 mark]

• Failing fast in science [Discussed at the 2:38 mark]

• Why and how patients will endorse the system [Discussed at the 3:00 mark]

• Online patient communities instigating research [Discussed at the 3:55 mark]

• Consumerization of health care [Discussed at the 5:15 mark]

• The pharmaceutical company of the future: how research will get faster [Discussed at the 6:00 mark]

• Medical device integration to preserve critical data [Discussed at the 7:20 mark]

You can view the entire conversation in the following video:

Strata Rx — Strata Rx, being held Oct. 16-17 in San Francisco, is the first conference to bring data science to the urgent issues confronting healthcare.

Save 20% on registration with the code RADAR20

So I was happy to seize the opportunity to ask questions of three researchers from Castlight Health about the service they’ll discuss at the upcoming Strata Rx conference about data in health care.

Castlight casts its work in the framework of a service to employers and consumers. But make no mistake about it: they are a data-rich research operation, and their consumers become empowered patients (e-patients) who can make better choices.

As Arjun Kulothungun, John Zedlewski, and Eugenia Bisignani wrote to me, “Patients become empowered when actionable information is made available to them. In health care, like any other industry, people want high quality services at competitive prices. But in health care, quality and cost are often impossible for an average consumer to determine. We are proud to do the heavy lifting to bring this information to our users.”

Following are more questions and answers from the speakers:

Tell me a bit about what you do at Castlight and at whom you aim your services.

We work together in the Research team at Castlight Health. We provide price and quality information to our users for most common health care services, including those provided by doctors, hospitals, labs, and imaging facilities. This information is provided to patients through a user-friendly web interface and mobile app that shows their different health care options customized to their health care plan. Our research team has built a sophisticated pricing system that factors in a wide variety of data sources to produce accurate prices for our users.

At a higher level, this fits into our company’s drive toward health care transparency, to help users better understand and navigate their health care options. Currently, we sell this product to employers to be offered as a benefit to their employees and their dependents. Our product is attractive to self-insured employers who operate a high-deductible health plan. High-deductible health plans motivate employees to explore their options, since doing so helps them save on their health care costs and find higher quality care. Our product helps patients easily explore those options.

What kinds of data do you use? What are the challenges involved in working with this data and making it available to patients?

We bring in data from a variety of sources to model the financial side of the health care industry, so that we can accurately represent the true cost of care to our users. One of the challenges we face is that the data is often messy. This is due to the complex ways that health care claims are adjudicated, and the largely manual methods of data entry. Additionally, provider data is not highly standardized, so it is often difficult to match data from different sources. Finally, in a lot of cases the data is sparse: some health care procedures are frequent, but others are only seldom performed, so it is more challenging to determine their prices.

The variability of care received also presents a challenge, because the exact care a patient receives during a visit cannot always be predicted ahead of time. A single visit to a doctor can yield a wide array of claim line items, and the patient is subsequently responsible for the sum of these services. Thus, our intent is to convey the full cost of the care patients are to receive. We believe patients are interested in understanding their options in a straightforward way, and that they don’t think in terms of claim line items and provider billing codes. So we spend a lot of time determining the best way to reflect the total cost of care to our users.

How much could a patient save if they used Castlight effectively? What would this mean for larger groups?

For a given procedure or service, the difference in prices in a local area can vary by 100% or more. For instance, right here in San Francisco, we can see that the cost for a particular MRI varies from $450 to nearly $3000, depending on the facility that a patient chooses, while an office visit with a primary care doctor can range from $60 to $180. But a patient may not always wish to choose the lowest cost option. A number of different factors affect how much a patient could save: the availability of options in their vicinity, the quality of the services, the patient’s ability to change the current doctor/hospital for a service, personal preferences, and the insurance benefits provided. Among our customers, the empowerment of patients adds up to employer savings of around 13% in comparison to expected trends.

In addition to cost savings, Castlight also helps drive better quality care. We have shown a 38% reduction in gaps in care for chronic conditions such as diabetes and high blood pressure. This will help drive further savings as individuals adhere to clinically proven treatment schedules.

What other interesting data sets are out there for health care consumers to use? What sorts of data do you wish were available?

Unfortunately, data on prices of health care procedures is still not widely available from government sources and insurers. Data sources that are available publicly are typically too complex and arcane to be actionable for average health care consumers.

However, CMS has recently made a big push to provide data on hospital quality. Their “hospital compare” website is a great resource to access this data. We have integrated the Medicare statistics into the Castlight product, and we’re proud of the role that Castlight co-founder and current CTO of the United States Todd Park played in making it available to the public. Despite this progress on sharing hospital data, the federal government has not made the same degree of progress in sharing information for individual physicians, so we would love to see more publicly collected data in this area.

Are there crowdsourcing opportunities? If patients submitted data, could it be checked for quality, and how could it further improve care and costs?

We believe that engaging consumers by asking them to provide data is a great idea! The most obvious place for users to provide data is by writing reviews of their experiences with different providers, as well as rating those providers on various facets of care. Castlight and other organizations aggregate and report on these reviews as one measure of provider quality.

It is harder to use crowdsourced information to compute costs. There are significant challenges in matching crowdsourced data to providers and especially to services performed, because line items are not identified to consumers by their billing codes. Additionally, rates tend to depend on the consumer’s insurance plan. Nonetheless, we are exploring ways to use crowdsourced pricing data for Castlight.

Strata Rx — Strata Rx, being held Oct. 16-17 in San Francisco, is the first conference to bring data science to the urgent issues confronting health care.

Save 20% on registration with the code RADAR20

In this context, a recent conversation I had with Keith Bergelt, Chief Executive Officer of the Open Invention Network takes on significance. OIN was formed many years ago to protect the vendors, developers, and users of Linux and related open source software against patent infringement. They do this the way companies prepare a defense: accumulating a portfolio of patents of their own.

According to Bergelt, OIN has spent millions of dollars to purchase patents that uniquely enable Linux and open source and have helped free software vendors and developers understand and prepare to defend against lawsuits. All OIN patents are available under a free license to those who agree to forbear suit on Linux grounds and to cross license their own patents that read on OIN’s Linux System Definition. OIN has nearly 500 licensees and is adding a new one every three days, as everyone from individual developers to large multinationals are coming to recognize its role and the value of an OIN license.

The immediate trigger for our call was an announcement by OIN that they are expanding their Linux System Definition to include key mobile Linux software packages such as Dalvik, which expands the scope of the cross licenses under the OIN license. In this way OIN is increasing the freedom of action under which a company can operate under Linux.

OIN’s expansion of its Linux System Definition affects not only Android, which seems to be in Apple’s sights, but any other mobile distribution based on Linux, such as MeeGo and Tizen. They have been interested in this area for some time, but realize that mobile is skyrocketing in importance.

Meanwhile, they are talking to their supporters about new ways of deep mining for prior art in source code. Patent examiners, as well as developers filing patents in good faith, look mostly at existing patents to find prior art. But in software, most innovation is not patented. It might not even appear in the hundreds of journals and conference proceedings that come out in the computer science field each year. It is abstraction that emerges from code, when analyzed.

A GitHub staffer told me it currently hosts approximately 25 TB of data and adds over 65 GB of new data per day. A lot of that stuff is probably hum-drum, but I bet a fraction of it contains techniques that someone else will try to gain a monopoly over someday through patents.

Naturally, inferring innovative processes from source code is a daunting exercise in machine learning. It’s probably harder than most natural language processing, which tries to infer limited meanings or relationships from words. But OIN feels we have to try. Otherwise more and more patents may impinge (which is different from infringe) on free software.

Miles, whom I’ve known for years and consider a mentor in the field of networking, recently started a Kickstarter project called Smart Notebooks. Besides promising a free software implementation based on popular standards, he believes his vision for a collaboration environment will work the way people naturally work together — not how some vendor thinks they should work, as so many tools have done.

A screenshot from the Smart Notebooks project

Miles’ concept of Smart Notebooks is shared documents that stay synchronized across the net. Each person has his or her own copy of a document, but they “talk to each other” using a peer-to-peer protocol. Edit your copy, and everyone else sees the change on their copy. Unlike email attachments, there’s no need to search for the most recent copy of document. Unlike a Google Doc, everyone has their own copy, allowing for private notes and working offline. All of this will be done using standard web browsers, email, and RSS: no new software to install, no walled-garden services, and no accounts to configure on services running in the cloud.

The motivation for the system comes from observations Miles has made in venues as small as a church board of directors and as large as an Air Force operations center. When people come together, they bring copies of documents — agendas, minutes, presentation slides — and receive more documents. They exchange information, discuss issues, and make decisions, recording them as scribbles on their copies of the documents they carry away with them. Smart Notebooks will mimic this process across the Internet (and avoid a lot of manual copying in the process).

Miles draws models from several sources, including one of his favorite tools that died out: Hypercard (he sometimes refers to Smart Notebooks as “HyperCard, for groups, running in a browser”). He also looks to TiddlyWiki (a personal wiki implemented as a single local file, opened and edited in a browser) as a model for smart notebooks, coupled with a peer-to-peer, replicated messaging model inspired by USENET News’ NNTP protocol. The latest HTML5 standards and the new generation of web browsers make the project possible.

Miles’ goal is a system that can let people collaborate in peer-to-peer fashion with minimal reliance on a central system hosted by a company. Users will simply create a document in their browser (like editing a wiki page), then send copies via email. Everyone stores their own copy locally (as a file or in their browser’s HTML5 Web Storage). Changes will be pushed across the net, while notifications will show up as an RSS feed. Opening one’s local copy will automatically pull in changes.

For more details, and to support the project, take a look at the project’s Kickstarter page.

Miles is particularly looking for a couple of larger sponsors — folks organizing an event, a conference, a crowdsourcing project, an issue campaign, a flash mob — who are looking for a better coordination tool and can serve as test cases.

Related:

• The future of publishing is writable