Ideas Are Cheap

We need to "measure what matters" as the saying goes. As we move to new payment models, we'll need to develop platforms that are designed to measure and learn from a wide array of data points about what works in keeping people healthy. Of course, we'll need health care architectures that can support big data across a wide variety of platforms to enable better algorithms and more learning. There's certainly big opportunity for connecting all these systems.

But it's not just the connection of data in and of itself that will lead to improvements in the triple aim of care, health and costs...Health IT architecture itself can improve the likelihood of cost savings.  We need to look deeper at the IT platform as a risk-reducer that can significantly reduce health care costs. Could we one day have an actuarial field of study in the network science in health care?

What do I mean by this? How do architectures reduce risk? Well, mostly by connecting problems with solutions, but in other ways as well. Let's explore this a bit.

When I say an architecture can reduce risk, I'm largely referring to a web 2.0 approach. http://radar.oreilly.com/2005/10/web-20-compact-definition.html

O'Reilly's short Web 2.0 Definition.

"Web 2.0 is the network as platform, spanning all connected devices; Web 2.0 applications are those that make the most of the intrinsic advantages of that platform: delivering software as a continually-updated service that gets better the more people use it, consuming and remixing data from multiple sources, including individual users, while providing their own data and services in a form that allows remixing by others, creating network effects through an "architecture of participation," and going beyond the page metaphor of Web 1.0 to deliver rich user experiences."

That's all great, but what's missing is how, beyond the data that can be collected, these architectures reduce risk by their very nature of sharing and connecting . This is an area that I expect will be explored deeply and continually quantiifed as we move to new payment mechanisms in health care. I believe 2.0 architecture and platforms will be required for accountable care to succeed. Here's why.

How do these platform architectures reduce risk?

They create a kind of planned serendipity where problems and solutions come together.  We'll need to find a way to measure this effect.

To understand this a little better,  let's tak a look at the Birthday Paradox.(This is something I learned back in my Probability and Statistics 101 and Clay Shirky also writes about this concept in Here Comes Everybody, The Power of Organizing without Organizations) The Birthday Paradox goes a long way to explaining why social media, markets, open source and more open platform architectures work.  Ironically, Accountable Care Organizations will be dependent on this type of organizing without organizations. Here it is.

What are the chances that you and another person chosen at random have the same birthday? 

OK, pretty easy one. It's more or less 1 in 365 (not including off chance of a leap year birthday).

Now, take 36 people and put them in a room. What are the chances that there are 2 people in the room with the same birthday?

If you're like most people, you'd take a back o' the napkin guess of about 10-30%, but once again, our statistical intuitions betray us.  We tend to think of individuals rather than matching pairs. Yes, it's about a 10% chance that YOU will find someone else in the system with your birthday, but it's an 80% chance that there will be one pair with the same birthday in the group, an increase in a likelihood of 1 in 365, or 0.27%, to a likelihood of 80% by connecting (by putting them in the same group) 36 few people. That's a 300-fold increase in probability of at least one match in the group.

The likelihood of finding a pair rises with the square of the number in the group, it's a principle of markets, of social networks and collaborative systems design.

A 300-fold or a million-fold increase in probability means the Birthday Paradox has a real quantifiable value, and that's just the value of the first step of finding each other.

Note: Of course, in most real-world examples, we don't have precisely known probabilities (what are the chances of finding a match), so we don't know exactly where the "tipping point" is. Still, the principle applies, and that connections enable us to solve problems by the square of  the transaction costs to participate in the platform. The paradoxical part is that we underestimate the numerator, the potential solutions that are presented and look solely at the denominator, the low probabilities. Our minds are naturally loss-averse, and we tend to maximize loss potential.

Beyond Connection: High-Probability Platforms

These new high probability platforms architectures will allow a general structure where:

• people and services to find each other,
• where opportunities connect with solutions, take actions,
• participants can share information and
• collaborate on new solutions and try new approaches,
• connect what works and what doesn't (big data analytics) and
• buildi a common body of knowledge, or praxis, that can be constantly refined (eventually I suspect, we'll have a topo map of human health that defines how multipel health measures are connected)

Collaborative platforms are driven by the same statistics as the birthday paradox for connecting on the ability to solve problems, but they then add the ability to modularize large problems into workable, connectable chunks, thereby further reducing risk, and allow for aggregation of data across a wide array of sources, reducing risk even further. It's a triple threat to improving Triple Aim. By matching people, problems and solutions on a platform that enables them to find each other and get work done effectively, amazing things happen with very little top-down control.

Tim O'Reilly puts it aptly in talking about the iPhone in the context of Obama buying into the idea of platforms:

"Before the iPhone, smart phones worked a lot like government procurement. The manufacturers and the carriers got together in a back room and figured out what they thought people needed. Phones came with 20 or 30 apps. But when Apple figured out how to turn the phone into a platform, there were hundreds of thousands of apps delivering ideas that no one at Apple had imagined."

Healthcare today is still in the days of "pre-smartphone" EHRs. When I hear "The manufacturers and the carriers got together in a back room and figured out what they thought people needed. Phones came with 20 or 30 apps." I think of an EHR.

With all the numerous  leaks of time and resources in health care, we need an architecture that can support thousands of apps that we can pick or choose, connected over a high-probability architecture. When we provide a platform to provide them at a time and place that's convenient (in mobile that's anytime and almost anyplace), apps find their niche. Because these niches are uncovered through more, better information, increased specialization occurs as developers are fixing smaller and smaller leaks.

Michael Nielsen, in Reinventing Discovery, calls this concept "planned serendipity". Deloitte's John Hagel calls it the "Power of Pull". When this happens, we all benefit from the 80% probability instead of the 10%, all with very little cost of entering the market. Luck is something we make.

So what does this mean for health care IT?

Lower costs on the order of billions of dollars, better care and a better patient experience (what patient doesn't want to connect with the right solution?). It's the Triple Aim of Care, Health and Cost. With the right incentives in place, new architectures can patch the massive number of leaks of time, administration and resources.

One example, ZocDoc, works by putting patients and appointments into a network so that they can find each other. A simple model of leak-fixing with platforms now valued at $700 million.

Then there's everyheartbeat.org, which seeks to track and monitor every heartbeat in the world. What could we find out about our connections when we have this kind of connection? We don't know, but I do know that the birthday paradox will have a role in connecting people's hearts (which may in fact, be inefficient, if not leaking) to find the right heart specialists, and will add up to 1000's of lives saved and millions of dollars working off of the simple math of the birthday paradox.

Simple model: share, connect, collaborate, make better decisions. It's bankable.

What are some of the ways networked health and social media can improve health and make accountable care models successful? Here's just a few, but the possiblities are impossible to predict:

• Finding the right knowledge in the right specialist or expert.
• Collaborating specialists on complex cases.
• Motivation through feedback and social circles for measuring and improving health.
• Finding right disease, right info, right decision and right intervention at the right time. Collective wisdom can match any one wisdom.
• Flexible EHRs and patient-centered platforms allow following the patient and being alerted to interventions beyond the clinic, while allowing for interoperability within it.
• Population health studies that can connect efforts like every heartbeat.org to all sorts of other factors. We could have a real-time picture of how our population health is changing, minute-by-minute.

What don't people get about platforms and social media: connections, information and refinement, combined the right way, mean that problems almost have to find solutions. That often comes across as touchy-feely when people talk excitedly about the opportunities with open source, open data, and social media, but it's really just math. The more you share, the more likely you are to find a match.

It's not until they connect meaningfully with the people who need them that they become valuable.

Dave Chase (@chasedave), CEO of Avado, spoke at the Collaborative Health Consortium's weekly Pilots and Collaborations call last Friday.

Dave led with the quote from Dr. Josh Umbehr: 

A good scalpel makes a better surgeon. Good communication makes a better doctor.”

Communication (and understanding how information flows) is the critical tool for physicians to get the information they need to make the best choices they've been trained to make.

On the same day, Dr. Jim Yong Kim was named as President Obama's choice as the new head of the World Bank. Just last night I watched an interview that Dr. Kim did in 2009 with Bill Moyers that focuses largely on health care. During the interview, Dr. Kim talked about Southwest Airlines and how what they're thinking might do for medicine:

"they have taken seriously the human science of how you transfer simple information from one person to the next...What we need now is a whole new cadre of people who understand the science, who really are committed to patient care. But then also think about how to make those human systems work effectively. We've been calling it, aspirationally, the science of health care delivery."

Dr. Kim is talking about many things here, social networks, health care experience design, network science and in other parts of the interview he talks about the need for reducing variability with such thing as Kiazen or Lean. It's risk reduction in care delivery through continuous feedback, learning and understanding information flows in networks of people, systems and care delivery processes.

Patient Engagement Means Helping Patients (and their Physicians) Make Better Decisions

It struck me that Dr. Kim and Dave Chase are talking about something very similar, if not the same thing: networks, communication flows and decision-making.

Dave Chase talked about the need for patient engagement and "control" in this brilliant slide from Avado:

You can see the rest of the slides Dave has given us permission to post here (great presentation).

When we talk about patient engagement and control, we're largely talking about who has control over decision making, how to engage them, and how to help influence that decision-making through information with flows and feedback. 

In the graph above to the left in the "At Home/Low Acuity" area, this is where ACOs and new payment models' success or failure will be determined. As Dave notes, this is ultimately 75% of health care costs that are behavioral, based on decisions that patients and families make day in and day out.  Understanding behavior networks in health care is critical. Fowler and Christakis' Connected that does a deep dive into how behavior patterns transfer through real social networks (not just the online variety).

While Dr. Kim and the Dartmouth school of Care Delivery are be focused on the right side of the graph, in a patient's accute phase when they are in the clinic or in the hosptial, but the realization is the same:

We need to understand what engages people, what information is needed and when to help patients and their care team make the right decision and reduce the risk of a bad outcome.

It's Network Science for health care.

Network Science in Health Care

The fledgling field of Network Science has been studied and applied in fields such as UX design, big data (scaled learning) CRM systems (be sure to read Michael Wu, @mich8elwu,'s posts on this), social network analysis, lean (and lean startups), Kaizen, open source, open innovation and supply chain logistics, and yes, Moneyball and now ACOs. It's a network perspective to systemic learning, with accelerated, scaleable learning as the critical measure of success. It's a matter of understanding connections, decisions, engagmement and human factors, information flows and how they all fit together all enabled through feedback. It's the new dialectic.

(For more on this subject, along with Connnected, I highly recommend The Information by Gleick, Thinking, Fast and Slow, by Kahneman, Where Good Ideas Come From by Steven Johnson, and the collected writings of Clay Shirky and John Hagel III to pursue this subject further.)

The Moneyball approach to baseball is a network and systems approach where statistics and critical measures, such as on-base-percentage, or how to approach a specific batter in a specific situation are found to matter more than nuance physical or mental characteristics of the players.

Payment reform, at long last aligning incentives of patient, physician and insurer, we hope, can only be successful with a continuous learning and statistics driven approach similar to what Moneyball did for baseball. Network science and big data are the science of figuring out what works on a large scale. Once systems are connected and health information is digitized, both through payment reform and initiatives such as Stage II meaningful use, we'll be able to make better decisions in medicine. As long as everyone is covered, that's a good thing. It means insureres will focus on keeping well rather than restricting coverage on those who need it most. It a networked world, it means personal responsibility and universal coverage, something both conservatives and liberals could love!

We Need People and Systems that Understand Network Science in Health Care

Dr. Kim is right, we need a whole new cadre of people who understand netowrks in health care.  This is the science of reducing risk through the understanding of how information moves with various types of networks. We need people who understand the fledgling field of network science in health care. Network Science is the key to driving innovation while reducing costs because it is ultimately about accelerating organizational and systemic learning. New payment models need to find out what works in health care and fast, and both Dr. Kim and Dave Chase understand that what's happeing is that networks of organizations, people, care delivery and technologies can lead to better care and reduced risks --  if we understand how they work.

Looking at network effects and information transfer across a wide variety of disciplines, we are rapidly gaining new insights into risk reduction from a network perspective.

Network science, the science of care delivery, patient engagement, social network analysis, customer/patient relationship management, user experience design, big data, and the algorithms being used now in baseball, are all part of a whole new way of looking at risk and probabilites across a wide variety of disciplines. In medical school and hospitals, as Dr. Kim pointed out, we currently do it ad hoc. For better outcomes, we need to understand these information flows better, so we can learn what works.

ACOs will need to understand very well Jim Yong Kim's research on variation, Dave Chase's work at Avado and even Moneyball. Scaleable learning is rapidly becoming the new basis of competion, even in health care. It's the rocket science of health care.

Next up: Why We Need Decision-Support in Health Care (Hint: we're all really bad at intuitive statistics)

We need health care platforms that all of us can access to make better every day. Why? When you can access and change a system, it has the opportunity to learn.

Accessibility is a kind of perceptive system. The people that know what's broken are the ones that can identify and fix the problem, the very people using the system are the often the ones best suited to fixing it.

But that's not whare I'm at today. We've been struggling with what happens when systems don't learn. When they're inaccessible, the right feedback mechanisms can't take hold.

My team, our partners and I have been struggling with a system for the last four months. People who need to use it can't get it to work as expected, including customers. It's mission critical, and yet here we are at the mercy of a 3rd party.

We can't make changes to the system. It's not our system. It's not even our contract. We can't do any scenario testing, we don't have test accounts.  All we have is the same thing anyone else with a browser has: a web page to visit.

We can, on occasion, with our own made up data, verify that one scenario or another works, but beyond that, we have to wait until someone has a problem with the system (usually a customer) before we know what's working and what's not, raise the issues as best we can, then trust that the problem has been fixed, which is running about a 50/50 chance.

We'll be successful on this project, but the system is a major hurdle we continue to have to overcome on a near-daily basis.

The issues we need to resolve are not complicated, the real problem is access. That's the name of the game in platforms.

In our case, the people who could really help to fix the system and make it better (us) can't and won't get access the system. And the crazy thing is, the vendor then has to pay to have someone on their team fix it! Wouldn't it be easier if we (in a very controlled setting) could fix it ourselves?

One industry leader who's been struggling with the same nameless system aptly put it this way: "Certain ironies here around the difficulties of software development: Imagine that we are patients trying to (use the system) for a health care program at a hospital."

This has really driven the point home in regards to healthcare and health IT: It's broken in large part because users and outside developers can't make changes to health IT.  This is the reason why the architecture and the focus of Health IT must and will change from institutions to patients.  We need to be in closer contact with the systems that are intended to make all of us patients better (yes, we're all patients).

Can your physican make changes to his EMR? Not likely. He'll have to go through his consultant, who will have to work with the vendor, who will have to talk to customer support, etc., etc., etc. Physicians who love your EHR, raise your hand! ;) Even after all that, needed changes are highly unlikely.

Physicians notoriously hate EHRs, but they love their iPhones and their range of helpful medical apps. Physicians have control over what goes on their iPhones and they can select what works for them. Developers can add new apps and make changes to existing apps without changing iOS.

In most cases, those that need to change the system are several layers removed from their ability to make changes.

Shahid Shah, who will be delivering a capstone session at the eCollaboration Forum uses this simple rule, borrowed from Marc Andreeson, that states simply: "if you can't develop or make changes to the system without contacting the system's internal development team, it's not a platform."

We need platforms for every participant in the health care system, so that everyone in the health care ecosystem has the power to change the system.

Patients can't access their own data, and they can't really add to their data, despite the recent study showing that patient-entered data is as accurate as physician-entered data.

So, in a nutshell, I've relearned in the last several months one of the core values of the Collaborative Health Consortium: "Solutions must be developed in conjunction with the people that will use them. They must be accessible"

Right now, the majority of health IT solutions are overly complex, monolithic, and not flexible enough to be developed with the people who must use them in the wide variety of settings they must be used. I sense this will change as soon as providers have more at stake in having systems that work the way they want them to.

And ultimately, it's for this very reason that the Collaborative Health Consortium is hosting the eCollaboration Forum to bring attention to the need for more open systems. Systems that can learn.

We know about platforms from some of the brightest stars of tech. Amazon, SalesForce, Facebook are all platforms that derive a significant source of their revenue via APIs, capitalizing on what Tim O'Reilly called "architectures of participation". Salesforce does 300 million transactons a day just in API calls, about half their more than 600 million/day total transaction volume. The broad technology community "gets" platforms.

Platforms are successful because of the interplay they create between of connectivity, contribution and benefits. In a system where most everyone can connect to, participate in, and benefit from a system, the value grows as more and more people use, develop and extend the system via network effects. The platform can then provide value from a much broader array of information and functionality from a much broader sources than any one company, organization or system could provide on their own.

The same thing will happen in health care, in large part due to changes in payment reform. In fact, it's already started.
One key example: Payers like Aetna making platforms a core part of their strategy.  If payers are figuring it out, we're all going to be using health platforms much sooner than we may think.

Accountable care models are creating new ways for particpants in the care delivery ecosystem to particpate in keeping people healthy. Each player will have need to keep people out of high-cost centers of care and we believe platforms will become a key part of these initiatives.

To address this shift, The Collaborative Health Consortium is co-hosting the inaugural eCollaboration Forum at HIMSS12 this year on Feb. 23rd. in Las Vegas.

With payment reform looming, it's vitally important that health care IT folks "get" platforms, too.

We seek to provide a full array of perspectives on collaborative health platforms (payers, patients, providers, government, technologists and investors). We've assembled an A-list of leading-edge executives to talk about the topic in an intimate setting at HIMSS. Space is very limited, so register soon via HIMSS registration. Speakers confirmed include:

• John Mattison, MD – Opening Keynote, Assistant Medical Director and CMIO of Kaiser Permanente, SCAL  “Consumer-centric Collaboration for Wellness”
• Farzad Mostashari, MD, ScM – National Coordinator for Health Information Technology
• Esther Dyson – Principal at EDventure Holdings
• Mark Blatt, MD, MBA – Worldwide Medical Director, Intel, “Collaborative Care: An Economic Imperative for Care Delivery Systems”
• David Whitlinger – Executive Director, NY eHealth Collaborative “Supporting New Models of Care Through Collaboration with States & Vendors”
• Steve Adams – President and Chairman, Collaborative Health Consortium; EVP Collaborative Care, Alere
• David Kibbe, MD, MBA – The Kibbe Group and American Academy of Family Physicians “Developing Trust in the Health Internet as a Platform”
• Vince Kuraitis – Principal, Better Health Technologies “The Future of Collaborative Health Platforms”
• Shahid N. Shah – CEO, Netspective and Blogger at HealthcareGuy.com “The Future of Collaborative Health Platforms”
• Brian Ahier – Health IT Evangelist, Mid-Columbia Medical Center
• Joshua Newman, MD, MSHS – Director of Product Management and Health Strategy, Salesforce.com
• West Shell III – Chairman and CEO, Healthline
• Scott Rea – Vice President GOV/EDU Relations and Senior PKI Architect, DigiCert
• Joe Miller – Director of eBusiness, AmeriHealth Mercy
• Jordan Shlain, MD – CEO, HealthLoop

If you care about health care, technology, business and how they're all going to fit together in the years to come, we hope to see you at the eCollaboration Forum. Up-to-the-minute info is at collaborativehc.org/eCollab12.

If you can't attend the live event, we'll have webinar access as well.

For any questions on the event, please leave a comment!

Many have heard Socrates' famous quote about the unexamined life, but you may not have heard an interesting bit of philosophical history that I've run across on multiple occasions recently: Socrates was distrustful of the written word.

I guess our elders are always going to be distrustful of the new media. 

Of course, it's one of the ultimate ironies that we only know his name and his work because his student Plato was the first student to take written notes on the dialogues. Writing and the Greek Alphabet were relatively new technologies then.

I've run across this curious fact about Socrates' distrust of text on three separate occasions in the last month:

1. The Information, by James Gleick.
2. Proust and the Squid, The Story and Science of the Reading Brain, by Maryanne Wolf
3. @DonaldClark brought up Plato's (Socrates' student) distrust of unchallenged narrative in a response to a great post on context, storytelling and narratives by John Hagel. 

For the sake of getting to the point I won't go deep into any of these, but I'd recommend the for anyone interested in how we assimilate knowledge and how it's changing.

It's not an accident that smart people are talking about Socrates and his distrust of writing. Our modes of consuming and synthesizing information are perhaps changing faster than they have since Socrates' time. His objections to writing seem prescient and worth another look.

What were the objections Socrates had to reading and the written word?

Maryanne Wolf highlights each of the following:
1. Inflexibility - Socrates thought the only truth could come through expressing knowledge (synthesis) and actively questioning (analysis) of that knowledge. For him the written word was too static, too inflexible.  Words in oratory come and go in an instant, yet the traces lingered. Our minds would hold the essence of the logic, and continually refine it. In this way, words received via oratory were like a clay, the written word like an uncarvable stone.
2. Loss of Memory - we would become lazy if we didn't have to memorize our ideas and understanding. When the word is written, Socrates felt that  the page holds it, not the mind. You can just read it and forget it. So for Socrates, external word permanence led to mental impermanence.
3. Loss of Control of Language - knowledge would not come with the requisite understanding and might lose context. There wouldn't be enough feedback during our consumption of thought and knowledge. The context of oratory was king, and for Socrates, the context was lost on the written word. As Dr. Wolf writes in Proust and the Squid, " Ultimately, Socrates did not fear reading. He feared the superfluidity of knowledge and it's corrollary -- superficial understanding."  

To sum it up, Socrates thought we would lead less examined lives if we relied on writing over oration. Oration allowed for iteratiion, ever-changing structures getting closer of truth. Living in stasis of belief is the unexamined life. To learn, we need ongoing and consistent feedback on our ideas, a consistent context perhaps?

In Socrates belief in oration and dialectic we find the the foundations of many of the institutions we now hold dear, including: higher education, scientific research and the scientific method, our political process and the courts (to name just a few). They each have their roots in the Socrates' dialectical method, in testing our knowledge and our models against our peers and the outside reality we are trying to model.

A hallmark of the Socratic method is the the union of analysis and synthesis, and this, perhaps is a key clue to where we're heading. Socrates distrusted the written word because it separated analysis from synthesis, reader from author. In the social sphere, this is no longer true.

Another important change (I believe) is that dialectics are moving in parallel. The story of an idea can now live in several parallel universes, so we have a societal dialectic and a societal narrative moving in parrallel. And that's why Hagel's post on narrative and context is so important. It seems we've moved from an individual, one to one dialectic to a societal dialectic, a broader story. If an idea doesn't make sense in one domain, it may have a life in another. Ideas can get feedback in a variety of contexts and find its niche.

The New Dialectic:

Social media, in a sense, is a new form of massive peer to peer oratory and a new spin on a new dialectic, continually evolving with continuous feedbacd. And it matters deeply because what's changing in multiple different directions is our process of learning, our processes for examining truth. We have many new types of dialectic systems enabled by technology and the web. We comment on blogs, we ask questions on Quora, a new type of non-real-time dialectic.

But I don't think it ends there.

Our technology itself is becoming dialectic because it's a more effective way to develop a new system. Open source, lean startups, UX design (based on user feedback), groupware, open standards and open anything nowadays all have their foundations in first and foremost as feedback systems, ways of organizing group learning. Importantly, each of them achieve this by reuniting analysis and synthesis.

Iteration is in vogue everywhere because the web makes it low cost everywhere. Feedback is approaching free. Feedback creates diversity of solution for new niches.

We're just seeing the beginning of the effects in the health care industry (see #HCSMgate). For changes in healthcare see these posts by Susannah Fox and Seattle Mama Doc. Parallel societal and technological dialectics are just beginning to have an impact, just beginning to take shape, but the results so far are astounding. There will be many bumps in the road as our inflexible modes of understanding move to perpetual learning. We are beginning to see learning at scale and I believe we will benefit tremendously.

So let's make sure these words don't remain static and isolated in context. Tell me what you think.

Honored to have my old post reposted today on opensource.com. Post was originally posted on HL7standards.com. I'll post it here, too, for the record. Would love to hear your thoughts:

What a difference three years makes. It seems quaint now that in the 2008 NEJM there were concerns raised about the flow of health information onto the web. Back then there was but a faint trickle of what could be entered, mostly by hand, and accessed on the web. Before HITECH and health care reform, exchanging health data online seemed blasphemous to many hospitals, patients, and physicians alike.

Fast forward to today and where we are now:

• Around 75% of physicians have smart phones (the web in their pocket), and will reach 80% in 2012.
• Major vendors have opened or are preparing to open their APIs in some fashion.
• Almost every major EHR vendor has or is working on an iPad application (a web tool).
• HealthVault has already begun to receive info via The Direct Project for the Care360 EHR.
• Connectivity and interoperability are quasi-law.
• Web-based EHRs have come to the forefront for many practices.

It’s great progress, and this is an amazing jump from where we were, but it’s far from an economy of health information. The problem is that there is still little patient data to pull from. None of the top 20 iPad health care applications even have connections to EHRs.

If health information is a sort of currency, then what we are seeing is that physicians are beginning to recognize its value. Physicians (and patients, too) are pulling for new functionality and opportunities to use health data, but for the data that really matters, patient data, they’re coming up empty.

What we need to achieve a health information economy

In 2009, in a follow-up to the NEJM article, Mandle and Kohanne (the same authors that wrote the 2008 NEJM paper) describe what they believe is required to develop a robust health information economy:

1. Liquidity of data (access and exchange)
2. Substitutability of applications
3. Open standards
4. Competition and diversity of applications over functionality, not data.

I like this, and it’s similar to what I’ve found over the years. As a personal mission, I’ve been researching information economies for almost a decade, and it’s clear that there is a repeated pattern in their development:

Information economies must be put into a single system where information can be found, accessed, trusted, exchanged, and then recombined. These elements, together, allow information to flow to where it’s needed in a form where it can be easily acted upon that fits the job to be done (Christensen's cornerstone of value creation and disruptive innovation) at that moment.

Similar to Mandle and Kohanne, my definition begins with what is essentially data liquidity, which happens via access and exchange (but also requires systemic trust). Once we have access and exchange, competition will drive better, more innovative products to deliver information where and when it’s needed.

Why we’re not there

It’s certainly no surpise to anyone reading this that data liquidity is sorely lacking in health care. Too long, competition among those providing and consuming health care information has been driven by restricting access (via data lock-in) to information. It’s the major reason we have big, monolithic EMRs that are poorly designed, confusing, difficult to use, and rarely (if ever) customized to the needs of that doctor and that patient at that time. Without access to data, there is no basis for competition to drive better designed software. You simply can’t compete without the data.

Holding back the power of 2.0 and collaboration

For all the talk of Health 2.0, lack of data liquidity is significantly preventing collaboration. Several companies have built great physician networks, but without any way to exchange the health information that matters: information about real, current cases. These networks have had to rely on reentry of data or, in many cases, limiting content discussions out of fear of HIPAA or FDA violations. So there’s still no way to collaborate effectively around the jobs they have at the moment: treating patients. Successful collaborative tools in medicine simply must:

• allow physicians to collaborate on actual cases in at trusted environment of peers
• do so without requiring data reentry
• have systemic trust (no fear of sharing for security or regulatory reasons)
• be worked into their current workflow

HIPAA, for better or for worse, has given providers cover for locking in data, and that’s only led to high-friction (not liquid) exchange of data via fax, email, and phone. A combination of fear and mistrust has driven valuable data into places where it has little use beyond where it’s called from: paper charts, monolithic systems, the minds of patients, or within one clinic on the far side of town. In order to gain access, much less exchange information, you have to know what data is available, where it is, and you have to ask for it. So mostly physicians work on their own without relevant data, or worse, recreate it through additonal testing at enormous costs.

Systems that have open exchange, such as Kaiser, even $5 billion of investment in HIT, are reaping rewards. When all providers can compete in an open network of information, they can compete on how they use the information rather than on hoarding information.

Things are changing

Fortunately, meaningful use is providing the incentive for many institutions that previously had none for digitizing and freeing health info, while the Direct Project or others may be a significant step in providing the means for all to exchange health info.

Stage I of Meaningful Use was largely focused on capture and exchange of health data. Stages II and III are focused on using that information in a meaningful way in clinical workflows. While I’m sure that stage II and III will have the desired effects of speeding industry adoption of Meaningful Use of EHRs (even if there’s debate on the directions), but I also wonder how much stages II and III are needed once data is liberated. We’ve seen in many instances before that once data is liberated, it will find its way to where it’s needed.

And that’s the real benefit I see with the Direct Project: it may allow for new companies and new business models for managing health data. Although designed for point-to-point transmissions to replace fax and phone, it may also make data easier to consolidate. Business models for technology companies may arise for making sense of the data, possibly on a population level and personalized level, then delivering it where and when it’s needed.

The floodgates of health information capital may be starting to open--it’ll be interesting to see what forces now pull at the data.

Meanwhile, health care reform may start to reduce the amount of mistrust and fear that exists around health data. If you can’t lose your insurance (the part that both parties like), will you still be as afraid that your health data gets out? Will people feel like it’s just data again, akin to financial statements? It’s still too early to measure the impact, but if PatientsLikeMe is already working, and people are sharing data with drug companies and anyone else who wants to know, then the potential that will exist when people are no longer fearful of losing insurance will be even greater. Trust is easier when what you share can’t be used against you.

Where are we headed?

To get to a true health information economy, health info has to travel from its vast untapped repositories to where it’s needed. Once it’s liberated, data will flow to help patients and physicians make better choices and continue learning while technologists use that data to provide better solutions.

In The Power of Pull, John Hagel III, John Seely Brown and Lang Davison at Deloiitte’s Center for the Edge describe how access, trust, and collaboration enabled through Web 2.0 are quickly accelerating advances in many companies and in many fields. The first step is access. Through access come the connection, exchange, and trust that drive the emergence of higher order innovations. One of the key points highlighted by the Power of Pull authors and others is that sharing information drives Pull. Pull in a connected world lets solutions find you. Once physicians and patients can exchange health information in a meaningful way online, they will. The benefits in outcomes are just too big to ignore.

Of course, in true counterintuitive fashion, health data will have a chance to experience the Power of Pull, but enabled via Push technologies in the Direct Project, but it’s a big step forward.

PatientsLikeMe is a prime example. Sharing becomes a small price to pay for better decision-making ability. Even though PatientsLikeMe is very openly funded by pharma, patients share openly. Part of that is the sense of community, but more of it is surprisingly and refreshingly data-centric. People share because they want results. They recognize they can increase the knowledge researchers, physicians, and fellow patients have of disease. Data liquidity will make it even more so, and better outcomes will result. It’s like an investment and spending of currency in a thriving economy. You spend it because you trust that you or someone you love will get more in return.

Better outcomes find us when we can find better information to make decisions without managing that information. That, in essence, is what a true health information economy will look like. I have high hopes that we’ll remember 2011, through health care reform, meaningful use and new chances for interoperability, as the year that health data became truly liquid.