Communicating with Health Data

Concrete Numbers: Dragging Data into the Everyday

November 5, 2009 · Leave a Comment

At the risk of looking like a Dan and Chip Heath groupie, I liked their posting about data this month in Fast N1111_mcdonalds _tb006Company. To illustrate the importance of attaching data to specific experiences, they work on a statistic from the film Super Size Me comparing the ratio of McDonald’s advertising budget relative to that of “eat-healthy” campaigns.  Ok, good enough, they say, but watch us make a “statistic” meaningful:

So suppose your 5-year-old daughter watches three hours of cartoons every Saturday morning and sees two McDonald’s commercials per hour. Every Saturday, then, Ronald McDonald engages her six times.
How long will it be before your daughter sees a fruits-and-veggies commercial? She’d wait about 14 months to see the first one, and she’d have a driver’s license before she saw 10 of them (the same number of McDonald’s ads she’d see in two Saturdays).

Wow.  Now I really get it and I understand better what is at stake (and what conversations I need to have with my kids begging for french fries).

This thinking is powerful when applied to healthcare data. Most of the time we are talking about very large numbers and rates of increase that don’t sound overwhelming–8% rise? not too scary–when taken in the abstract.  But what if we put that into specific context?:

In 2008, ABC Company has $20 million in fixed costs, of which half is health care. Health care costs rise 8% annually until 2013, reaching nearly $15 million. Holding other expenses flat over this time, ABC must cover an additional $5 million. Say it sells a widget with a contribution margin of $50 per unit. ABC must sell an additional 100,000 widgets in 2013 compared to 2008 just to keep the same profit.

Here’s another example:

Joe, one of the most experienced shop foremen, has a heart attack while watching the Redskins lose to the Lions.  The ambulance ride and his 5 day stay costs $20,000 in medical claims.  He takes 4 weeks of disability and then takes two weeks to transition back to full time.  All in all, the $20,000 in medical costs ends up being dwarfed by the additional costs (estimated at $80,000) including sick-pay, disability pay, lost productivity, and overtime pay to cover replacement workers.

Chip and Dan Heath provide the takeaway:

A good statistic is one that aids a decision or shapes an opinion. For a stat to do either of those, it must be dragged within the everyday. That’s your job — to do the dragging. In our world of billions and trillions, that can be a lot of manual labor. But it’s worth it: A number people can grasp is a number that can make a difference.

In our capacity as people who examine health care data for non-healthcare data-experts, it’s our job (a critical job) to create specific applications for our clients and/or members. The numbers we look at matter, and they need to be presented to our clients in ways that can make a difference.

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Exceptional Presentation: “Let My Dataset Change You Mindset!”

October 19, 2009 · Leave a Comment

271138392_6c8eb4934cI’ve written many times in this blog about how data, presented effectively, can change the way we see problems and think about solutions.  I found an exceptional example of this in a lecture given by Hans Rosling, a professor of global health at Sweden’s Karolinska Institute, to the US State Department this summer.

In case you are not familiar with Rosling, this is an excerpt from his profile on Ted.com:

What sets Rosling apart isn’t just his apt observations of broad social and economic trends, but the stunning way he presents them. Guaranteed: You’ve never seen data presented like this.By any logic, a presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling’s hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.


(Click here for link to presentation.)

Rosling’s presentation shows us overall global trends in health and income across the last 200 years.  His innovative data-bubble software–called  Gapminder–exposes common myths about health care and the developing world. It is an amazing combination of statistics, humor, and subject mastery. If you are like me, you won’t be able to watch it only once.

This presentation is a perfect example of how data, when mined and combined with innovative design, generates learning and knowledge that changes minds and makes a difference.

*Mr. Rosling’s presentation is part of the TED-talks, (TED: Technology, Entertainment, Design).  TED is an invitation-only event where the world’s leading thinkers and doers gather to find inspiration.

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Update from Health 2.0 – San Francisco

October 8, 2009 · Leave a Comment

h20600By Dan West

First a quick definition: what is Health 2.0? Wikipedia tells us that “Health 2.0 is the use of a specific set of Web tools (blogs, podcasts, tagging, search, wikis, etc) by actors in health care including doctors, patients, and scientists, using principles of open source and generation of content by users, and the power of networks in order to personalize health care, collaborate, and promote health education.”

With all the recent media attention on health plan-related incompetencies, it was refreshing to hear from a few health insurance companies taking advantage of modern technology to better serve their customers. Health 2.0 can be an important method by which to educate members and encourage the proper and effective use of their health benefits. For example, the State of Minnesota has offered tiered networks for around 8 years now with layered incentives based on quality. Through Health 2.0 methods, Minnesota is able to better steer its customers to its most effective providers.

Mohan Nair of Regence BlueCross BlueShield emphasized the need to balance medical management with consumer engagement. Thirty percent of its employees use the web, and by leveraging Health 2.0 methods it is more able to “get the consumer to recognize that it’s his money we’re saving.” Chris Ohman, senior VP of health operations at Kaiser Permanente, reiterated this. Kaiser has identified five chronic conditions that contribute roughly 70% of medical costs. Managing those diseases, while partially the responsibility of Kaiser, rests mainly on the customer. By getting lab and test results on the web, it can better encourage its customers to manage their conditions more effectively.

Health 2.0 isn’t just a subset of Search (personalized results), however. Ingrid Lindberg of Cigna pointed out that her company is on Facebook, Twitter and Second Life, all with the goal of facilitating interaction with Cigna. Regence BCBS offers unregulated forums and blogs for customers to connect and air grievances. Rather than deleting negative posts, which would destroy the online community it’s building, it views them as valuable feedback. Negative feedback is just a sign a company isn’t serving its customers needs after all.

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Wanted: Data Geek/Visual Designer

July 5, 2009 · Leave a Comment

I was motivated to get back to blogging by a recent post from Michael E. Driscoll.  (See his great mashup of scatter plots with Andy Warhol’s Marilyn Monroe.) Driscoll takes a quote from a McKinsey Quarterly interview with Hal Varian, Google’s Chief Economist:

“The sexy job in the next ten years will be statisticians… The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill.”

I’ve never really thought of myself as someone with…well…sexy skills.  (I immediately sent this blog to my wife, who also has never really thought of me as having sexy skills.)  I remember in college walking from my advanced statistics class in the math building to my pottery class in the art building.  I remember hoping that my earthy pottery friends wouldn’t see me coming out of the math building and vice-versa. But the need to live two separate lives is over. Now, according to Google’s Chief Economist (and who am I to argue with Google’s Chief Economist?), I can simultaneously and proudly hold the pulse of both art and math.

Data visualization has emerged as a vital area of development. As the amount of data available to us grows exponentially (think petabyte hard drives selling at Costco), our ability to process and utilize the information flowing from all this data depends on its interpretation and presentation.  Data is really only useful if we can expose patterns and correlations in the data and then represent those patterns and relationships in an accessible manner. The visual representations of the patterns and relationships found in data serves to enhance our ability to understand the “story” contained in the data. Surely, there is a meaningful relationship between the explosion of data and the resurgent interest in powerful Design as marked by the number of articles focused on design in magazines like FastCompany and Wired. (In fact, Wired’s latest issue 17.07 is a particularly striking look at how data and design work together in all sorts of venues/markets.  In addition, see these sites pitching Data Visualization for some examples of beautiful renderings of information: Smashing Magazine; Web Designer Depot)

As I say in every blog, the value of data is only as good as its ability to support decision-making. Companies that succeed will do so through sophisticated and compelling analytics. Sophisticated analytics rely on more and more complex algorithms as well as the integration of multiple data sources. Data design and representation–the way charts, graphs, and tables are designed–plays an integral role in allowing readers to analyze and interpret the data in support of decision-making.  The equation looks like this: the data determines its visual design; the visual design supports a competent and complete analysis; competent and complete analyses lead to better business decision-making.

If I were back in college, I would have a newfound level confidence.  I would proudly brandish my calculator in pottery class, and definitely show-off my newest bisque-fired pottery vase to my statistics classmates.  After all, it’s the combination that makes me sexy.

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Doing My Taxes and Fixing Health Care IT

May 28, 2009 · Leave a Comment

Even with a good accountant, most of us consider tax-time brutal. It’s not only that paying our taxes hurts, but organizing the papers, filling out the confusing forms, and thinking through the financial events of the previous year—most of those events are misery too. These are organizational tasks that present huge psychological barriers for many of us.

Over the past 8 months, I have been consulting with one of the premier health care organizations in the country. We are working on a key initiative to extract and integrate data from the various systems across their organization with the objective of creating performance reports for their clients. It is a mission-critical project as they compete to attract and retain their clients (i.e., employers.)

My primary obstacle to moving the project forward has been getting them to confront the barrier of initiating the work required to integrate their data – even at the conceptual level. This conceptual work precedes the data discovery process that will inevitably uncover gaps in data quality, gaps in data availability, and inadequacies in the database structure. Although addressing these data issues requires time and attention, this company has the IT staff to do the heavy lifting with the data. As with my taxes, the hardest step is initiating the organizational process.

My experience has been that integrating these disparate data sources is complicated but achievable. Here is an example:

A health plan wants to be able to demonstrate the performance of their Wellness Programs. The Benefits/HR Manager will want to know the following:

  • How many people are participating in the programs?
  • In what programs are they participating?
  • Does the program participation line up with the company’s employee population health risks?
  • Is the numbers of members participating growing over time and how do these numbers compare to the employee participation for similar employers with similar demographics?
  • Are population risk factors declining over time?
  • Does the data to support a correlation between participation and reduced health risk and higher employee productivity?
  • How much do the Wellness programs cost?

To answer these questions, the health plan will need to draw on data from a number of different sources: program participation records, historical population risk data, change in population risk over time, health care claims data, program costs, and employee productivity measures (estimated or actual.)

This is the point where many health plans freeze or procrastinate. What follows are my recommendations to get past the obstacles. (They might work for tax preparation as well.)

  1. Define the Output: It is much easier to “visualize” how to integrate the data when you know what questions you want answered. The Wellness program questions listed provide the framework for the data integration requirements.
  2. Don’t Be Constrained by Legacy Technology. Too many organizations are shackled to their existing technology. New sophisticated technology for data analysis is emerging so constantly that an easier (and often cheaper) solution may be available.
  3. Know the Data: There is no substitute for understanding the data. In tax preparation, reading bank statements and investment reports is challenging, but doable. Reading health data is the same. From our Wellness example, most of the data sources (e.g., Wellness Program Participation) are very straightforward. Here’s what you should ask for:
    • Database schema. These are the database blueprints that show how the data is organized
    • File layouts. These are the documents that describe what data is supposed to be in each database
    • Meta data. This is data about the data, or in other words, information that describes data volume, data quality, and data idiosyncrasies.
  4. Don’t Overshoot the Data Integration Efforts: Too often health plans are persuaded that in order to answer questions such as the Wellness questions above, they need to build an Enterprise Data Warehouse that allows for all data sources to be linked to all other data sources at the patient level. This is a terrific goal, but economical interim data integration steps exist to answer effectively these types of Wellness questions. If Account Structure fields are consistent across data sets, then data can be efficiently aggregated at the Account/Group level for performance reporting.
  5. Have a Deadline: Data integration projects will not happen without the mental motivation that comes with a hard deadline.

The annoyance of tax season seems to have little lasting benefit aside from forcing me to scrutinize my financial situation. A dedicated effort at organizing data to proof benefits programming, alternately, is a valuable effort and can become an important tool in the toolbox for managing the health and productivity of your workforce.

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Thoughts from Boston Health 2.0 meets Ix Conference

May 2, 2009 · 1 Comment

I attended a terrific conference in Boston about a week ago called Health 2.0 meets Ix.  Although it is a false dichotomy, the debate is sometimes couched in terms of Electronic Medical Records (EMRs) vs. on-line health care participant communities. The conference organizers orchestrated a bit of show around setting these two models as “opposed,” but conversations amongst the panelists and the audience were more sophisticated than that—which I assume the organizers intended. In fact, the most interesting ideas from conference emerged from the combination of models.

For those who may not be familiar with these two “camps” let me give a very brief overview. Health 2.0 is, at its most basic, the use of the social media aspects of Web 2.0 to help patients and other health care stakeholders form communities that empower them to manage health care delivery while getting the most out of the existing health care system. The most exciting patient communities to date have been organized around patients with rare diseases (like Parkinson’s and Multiple Sclerosis) ) or acute conditions (like diabetes) where treatments are rapidly evolving and social support networks play a critical role in health improvement.

Informatics Therapy (Ix) takes a less grassroots, more “within the system” approach to improving health care delivery. This is how “they” define themselves:

Information Therapy (Ix®) is the timely prescription and availability of evidence-based health information to meet individuals’ specific needs and support sound decision making.

The basis for this approach is the idea that aggregating disparate data, running it through smart clinical rules, and using the resulting analyses will help both patients and their physicians make better health decisions. 

After sitting through two days of debates, deep dives, and vendor presentations, here are a few things that made my synapses fire a little faster:

1.  2.0 v. Ix: An audience observation that although Information therapy and Health 2.0 are sometimes treated as though they are mutually exclusive and exhaustive strategies to fix the entire health care system, they are two elements among a much broader set of initiatives (the most ambitious of which is the Health Care X-Prize) emerging to address the needs of the overall health care delivery system. Another participant asked why Health 2.0 approaches shouldn’t be considered another source of data input in the Information Therapy applications.

2.  EMRs: The EMR can be effectively used to capture the “background” of the patient — frame the discussion between patient and physician. So the patient doesn’t have to tell their whole life story at the beginning of every provider visit they have. There was even the suggestion to apply the Surgeon General Warning on physicians that don’t use EMRs– that patients put their lives at risk when seeing a doctor that does not have an EMR. 

But panelist ePatient Dave spoke incisively during the conference about the accuracy of the information contained in the Electronic Medical Records (EMRs), noting that there are no mechanisms in place to monitor/ensure the quality of the data flowing into Electronic Health Records.  All other industries have mature data quality control systems, he argued, that filter, flag, and catch data quality problems.

While this may not be entirely accurate, it is true that other industries are a lot further down the road of managing both the quality and usability of their data.  While the move to some form of EMR seems like destiny given the Obama stimulus dollars, the issues around data quality and accuracy, control of entry, portability, interoperability, privacy, etc. remain to be sorted out–and resolving each of these issues will demand the brightest and best thinking. (See an example of interesting thinking and intense disagreement over the contours of EMR implementation at the The Health Care Blog.)

3.  Information Therapy — control in the wrong hands?: One Health 2.0 proponent stated that he objected to the Information Therapy approach because he didn’t want a computer programmer to determine his health care treatments. John Halamka,  Chief Information Officer of the CareGroup Health System, Chief Information Officer and Dean for Technology at Harvard Medical School (and more), reacted to this criticism by stating that it was the doctors themselves who were defining the clinical rules being programmed. As Halamka writes about in his blogs, the questions implicit here are important, however: Who controls what is considered the “right” clinical rules? How are disputes resolved? What roles should patients or geographic communities play?

4.  Paul Wallace made an interesting comparison in his presentation between the historic changes in wealth management to the emerging changes in health management. When wealth management went from a defined benefit to a defined contribution model, the growth of available tools to manage-your-own-portfolio was explosive. Despite this growth in access to products that would allow individual consumers to manage their own portfolios, only a small percentage of people became day traders. Another 25% became more active managers of their 401K. Most, however, continued to completely ignore their 401k. The same forces may be in play in consumer based-health management, he argued. A few people will be very active managers of their own health. An additional group may assume some middle level of management. The majority will continue to ignore the management of their health. Consequently, the solutions will be on the portfolio model—portfolios based on the diversity of patients and on their knowledge/comfort in managing their own health. 

This presentation points to the evolving nature of the physicians/patient relationship. Overall, doctors are being used less by patients as the only source of health information, and more as consultants who interpret the overwhelming quantities of information available to patients. Doctors are beginning to play the role of portfolio managers – similar to financial managers. (See Scott Shreve’s model which is something like a portfolio manager model).

Importantly, patients aren’t uniform: their knowledge and their access information exist along a continuum. Some patients still need to be “told” what to do to manage their health. Others show-up to office visits with a stack of articles printed from the Internet. So, empowered health communities on the web—as potent as these are—are not accessible or preferable for all patients, and the solution to the health care morass will have to be broader, more inclusive than this a complete shift to patient-directed care.

5.  Again on the doctor-as-consultant idea: Doctors only see patients for a very short time. Even when, or particularly when, a patient has a serious condition (e.g., lung or breast cancer), she may work with specialists who don’t remember her and have to look through her medical chart to remember her situation. The medical professionals who work with a particular patient on a day-to-day basis tend to be other team members, like the chemotherapy staff, who know their patients personally and support them in more personal ways. The idea is underscored here that “I should be the CEO of my body.”

Danny Sands,  assistant clinical professor of medicine at Harvard Medical School and senior medical informatics director for Cisco Systems, a member of the panel of doctors, adamantly opposed comments that doctors are only useful as specialists to deliver care. He responded by saying that the suggestion that MDs are best at episodic care cheapens the role MDs should play. They need to partner with the patient and be part of the “team.” (In an interview with Matthew Holt, the language is “knowledge symmetry.”)

6.  Problems with/questions about current models: Patients who are actively managing their health sometimes find that the traditional efforts of the managed care companies are not only ineffective but unsophisticated and even patronizing. On the other hand, as one panelist pointed out, many Health 2.0 companies use methods for interaction that can be considered intrusive or aggressive. Most healthy people, and even very unhealthy people, want to interact with the health care system as little as possible.While crowd source data is valuable because it is constantly churning and improving, who manages/ provides quality control for information captured from the “crowd data” on Health 2.0 wikis? The Medpedia approach? Who are the accepted sources? Is there such thing as volume transparency? Is it possible for the average person to wade through the information. 

7.  A few of the interesting vendors:

UpToDate: UpToDate provides online medical content management. There is a professional peer-review process to get data on topics. Interesting to me was that BOTH patients and doctors have access to the site. Patients get free access to consumer-level information. If patients want to get access to professional content, they pay a subscription fee. Subscriptions are the only source of revenue. Most of the doctors on this particular panel subscribed to and used UpToDate in their offices. The representative from American Well pointed out that the most powerful use of the relevant information from a tool like UpToDate would occur if the information were put in front of physicians during the patient visit. Quality of care could be increased dramatically.

Healia. Healia provides an on-line Question and Answer service for health care questions. They have recently added a group of 67,000 medical students that are answering medical questions for free that are posted on-line.

I look forward to continued active dialogue on these topics — especially as the components of health reform come into focus.  

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Measuring the Performance of Benefits Plans

April 14, 2009 · Leave a Comment

A recently recirculated article from Thomas Davenport reminded me of his very good book Competing on Analytics. Davenport’s hook in both is describing how businesses can improve their performance through collecting, analyzing, and acting on data. Rather than high-level financial analyses or reviews of operational measures, he advocates highly sophisticated analytics that “transform technology from a supporting tool to a strategic weapon.” As one example, he points to Amazon whose famous analytic models are employed to track consumer shopping and purchasing patterns and then smartly determine product placement and advertising.

I have been thinking about how best to apply his insights to the business of providing health and productivity benefits. Most decisions shaping current US healthcare policy and practice have been made based on very limited empirical information. In a 2006 survey from McKinsey, 6 in 10 CEOs claimed they never considered measuring the performance of benefit plans against  benefit objectives. It’s fair to say that decisions have most often been made on political expedience and lobbying, opportunistic vendors, and short-sighted financial goals. To make evidence-based decisions, a different model will have to be in place. Davenport provides some interesting ideas for those of us in the health and productivity field. These are my initial take-aways.

  • Both Employers and Plans need to become disciples of strong analytics. Despite the fact that health care costs are a very large expense for businesses, most businesses know surprisingly little about the performance of their benefit plans. Companies feel pressed into making benefit design decisions—decisions with significant financial implications–with very limited data. On the other side, the best performing health plans must acknowledge that they need to control their “destiny” and secure significant strategic analytic capabilities. This can be done by recruiting the best analysts, or by working with strong analytics partners. But it must be done.
  • ·These efforts must be championed at the C-suite level. An analytics strategy that doesn’t coherently permeate the whole operation isn’t compelling enough. On the Plan side, a visionary Informatics manager who cannot convince Sales to expand their use of analytics knowledge capital will not be able to create an analytics-rich corporate culture. Executive mandate and support can insure the substantial use of analytics approaches across multiple business functions and capabilities.
  • The “analytics” need to be not only good, but best. While descriptive statistics are helpful, they don’t go far enough. Companies that want to make the best benefits decisions will seek out predictive modeling and complex optimization techniques. These models measure the overall impact or “lift” of interventions and strategies. To do this type of work, companies will need to invest in
    • High Quality Data: Sufficient volumes of high-quality data
    • Quantitative Expertise: Hiring the right analytic expertise is time consuming and challenging. Contracting for these services requires selecting partners that understand the business objectives
    • A Capable Technology Environment: This means both hardware and software

Employers need to embrace the concepts presented by Davenport. The final arena for every corporation is dollars earned versus dollars spent. Managing the flow of health care dollars is critical to corporate financial health. These benefits offering deserve the same analytic attention as any other of the more traditional business operations. If you want to know if you are competing on analytics now, click here for Davenport’s list of questions to ask yourself (page 8).

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Designing Health Data: Apple Meets EHRs

March 16, 2009 · Leave a Comment

wikipedia-on-ipod4Here’s the premise for today’s blog: Technologists tend to overestimate the ability of users to efficiently navigate the tools they create. OK, now let me say that another way:  Technologists tend to overemphasize the power of their product, and under-emphasize the usability of their product. Wait–one last time (and this is one of my favorite quotes): “The customer is looking for a 1/4 inch hole, not a 1/4 inch drill.”

A few weeks ago I attended a conference in Boston called “The Transforming Healthcare Summit 2009:  Impact & Opportunity in the Obama Plan.”  Boston is a hotspot for interesting thinking about the intersection of health, new technology, and change.  There was a buzz in the room about the flow of capital to Healthcare IT–and EHRs in particular.  The locus of the presentations centered on technology and system interoperability. During the question/answer period, a woman at the back of the room stood and asked an intriguing question.  “What role does ‘design’ take in the growing amount of spending on healthcare IT and specifically, EHRs?”  She brought up Apple’s successes at dramatically improving usability through innovative interface design. (Think of the iPod and iPhone.)  She expressed her concerns about the potential for overspending on “technology” and underspending on the user interface design that improves both the quality and efficiency of the patient/provider interaction.

The sophistication of the technology permeating the health care industry is astonishing at every level.  The sophistication of the interactions between health care systems or stake-holders implied in a single episode of care is also astonishing. At each of these interactions, data is generated that could improve our understanding of what works and what doesn’t work. But health  information is not well-organized, and it is certainly not well-communicated.  I have stuck across my company’s website “Your data is only as good as the solution it provides.”  I mean this.  The need is there.  The data is there. The technology is there.  The money is there. The will is, arguably, there. So, what’s missing?  As we all focus on how to fix the troubled health care industry, I think the question asked by the conference participant is relevant.  What role does “design” — particularly the design of communication — take?

This type of design requires a deep dive of understanding into topics that cross traditional packages of expertise and training.  This includes comfort with the technology; knowledge of data (coding and data idiosyncracies); experience analyzing data to “tell stories”; as well as more traditional design skills on how to communicate information (a la Edward Tufte) both visually and with narrative text.  This is where design and business intelligence are joined at the hip. Designers tasked with communicating the key story lines mined from extremely complex datasets have to know all about the data as well as how the get those story lines through to the recipient.  They need to understand where the reader’s eyes are drawn on a particular report page, how to lead the reader to the most important information, and how much information can be loaded into a page before the reader hits overload and shuts down.

Strategist Richard Rumelt argues in a McKinsey Quarterly interview that

“the iPod came from knowledge and resources being adroitly combined. There were lots of people who knew the music industry and lots who knew about hardware and lots who knew about the Web. But to quickly and skillfully access those three pools of resource and knowledge was an impressive feat.”

So, to the conference attendee who asked about design: Thanks for asking one of the most interesting questions of the evening, and it is going to be a tough to break through the “design” barrier with health information.  I am really hoping that when we spend the last dollar of health care stimulus money that we are not staring at a tangle of computer systems all talking to each other, but saying nothing to doctors, patients, payers, and employers.

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