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Science 2.0

October 9, 2008
by Joe Bormel
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Science 2.0?

Everyone working in healthcare informatics shares one deep and profound belief. The belief is that, with all of this data that we're systematically collecting (or going to be collecting when our projects are further along), we'll be able to arrive at truth. What works? What doesn't work? In short, applying the scientific method.

In concrete terms, if (or when) we're each diagnosed with breast cancer, or prostate cancer, heart disease, diabetes or a common cold, our doctors will be able to quickly and accurately diagnose us and prescribe the most effective treatment. Everyone working here shares an understanding that

there's a learning process, involving all prior patients and the healthcare system's experience with diagnosing and treating those prior patients. Patients and families also hope that we (society) will learn from our prior misfortunes, including deaths.

And yet, every single person who has had a few experiences with our healthcare delivery system has experienced

a system that clearly doesn't learn so well. Whether learning needs to come from observational research, or formal, multi-center trials with clever protocols, we're finding that our learning processes are unnecessarily inefficient.

A field of medicine has emerged to improve the speed and fidelity of this learning; it's called

translational medicine. It's focused on studying and then quickly taking action on translating what has been a 17 year process of taking medical discoveries and getting them into common practice, much faster. Going from lab bench to bedside. Now, in 2008, we have hundreds of commonly used tests and drugs. We have several orders of magnitude more genomics data coming on-line every year. Operationalizing learning is no longer just a good idea. The practice of medicine, whether that's evidence-based medicine, or simply experience-based, expertise-infused requires new methods.

It turns out, according to a healthcare informatics grand rounds presentation last week at Johns Hopkins, translational medicine has several barriers that are formidable:


Scientific publications

-- our current system is antiquated; repeating and/or combining studies for learning purposes is impossible in very objective terms. (hence the title "... where do they


come from")



amongst researchers across space and time is an extremely low reliability system.


Social, economic and management systems

need revision. That's an ecosystem with academic medical centers, biotech, pharma, and consumers.

The scientist / entrepreneur / executive who presented the grand rounds, Dr. Steve Bova, provided a glimpse of

what's required to solve the translational medicine problem. It includes governance and standards, but not what you might expect. It draws lessons from web 2.0 with mass collaboration tools, democratization of content, transparency and publication. And, there's a healthy dose of workflow automation. No surprise there!

Want to learn more?

If you've ever been involved in a clinical study, extensive chart review, or happen to have masters or PhD level training involving healthcare research, you'll find a lot of value in

Steve's Grand Rounds presentation here ( Bring lunch to your desk and attend virtually. It's free and requires no log in. You will need RealPlayer. (The initial introduction of Dr. Bova, not on the video, includes that Steve is an Assistant Professor of Pathology, Oncology, and Urology, holds a Joint Appointment In Health Science Informatics, and is boarded in Prostate Cancer and BioInformatics/Genomics.)

Despite the title, the talk is really about the big picture, Science 2.0. The title of the talk is just the entry point. The style is more of a first-person narrative with artifacts, rather than a primer on translational medicine per se. That said, it's absolutely relevant if you meet the audience criteria I described in the previous paragraph (

in italics).

Enjoy! And, of course, comment here on what you thought.



The Course Of Science (Humor) ...

[since we're talking about Science, here's a humorous picture, originally taped to the door of the biostats/computer lab at Harvard's School of Public Health, many years back.  Isn't humor grand? ]

Joe: Thank you for your thoughtful comments about the presentation I gave a few weeks ago. My main point is that what people call Translational biomedical research...moving ideas from bench to bedside and back again.... is only very weakly supported by our current publication system, and that we have no other system upon which to build such progress. I propose XioPub as a way likeminded people could work together to evolve publications to the next level. There is no time to waste...a large part of the current problem is what is not included in publications that should be included, and every publication that goes out prior to XioPub is a publication that is likely to have omitted critical data needed for translational research. If anyone is interested in helping to make XioPub a reality, please contact me at gbova2 at jhmi dot edu.

Thanks to reader feedback, I'd like to offer some clarifying notes:

Science 1.0: (What is scientific method?)

the systematic pursuit of knowledge about natural phenomena, involving the recognition and formulation of a problem, the collection of data through observation and experiment, and the formulation and testing of hypotheses.

What's wrong with how Science 1.0 is practiced today?  For a very clear answer, open the previously referenced video and jump to the section on XioPub.  It starts around 35 minutes and 30 seconds in, just after a discussion of BRISP.  For those of you who are time and technology challenged, ... okay, that's all of us! ... here's a bulleted list, adapted from the video:

  • Poor Usability and Functionality of Current Scientific Literature
  • Grazing
  • Repeating Experiments (inadequate detail to do so)
  • Evidence-Based Health Practice Support
  • False or Seriously Erroneous Publication Detection
  • Emergent Property Concept Developkment and Testing (Chaos Theory)
  • [lost data because of lack of specificity and access issues]
  • Unpublished Useful Data
  • Online Supplementary Data
  • Databases Without Context

Steve gives multiple examples from the literature and from personal communications that underscore how serious and ubiquitous the problem is.  He makes the case that Translational Medicine requires addressing these issues; it demands moving to Science 2.0.

Lastly, I've been asked to make the connection, why am I calling this Science 2.0.  The reason is that the societal changes that underlie Web2.0 and Health2.0 seem to apply to science.  (Thanks to Matthew Holt, his Healthcare Blog, and his Health 2.0 Conference for making it easy for me to learn this rapidly evolving perspectives.)  The slide below shows the definition of Web2.0.  The connection to Science 2.0 will be obvious to readers of this blog:

Thanks Steve.

I'm glad you summarized and pointed to the XioPub vision.

A note to all other readers:

If your vision is that your health system is or will become the best one on the planet, you'll need to understand what Steve is explaining.

I would strongly urge everyone working in the field of Translational Medicine to spend a lunch hour at their desks and virtually attend Steve's Grand Rounds presentation.  (Once again, click here to do that.)   Hint: If your institution is offering a single genetic test or therapy, you're already working in the field of translational medicine.

As I said in my introductory remarks, this presentation is foundational to everyone's vision of the art and science of medicine we want. If we want to continually improve healthcare, and delivering care in the kindest and most effective ways, enabled by information technology, we're going to need to understand and address the issues that Steve so eloquently elaborates.

Steve makes that clear when it comes to common cancers like prostate cancer, as well as common, pediatric surgical issues. Don't let the use of the word 'research' lead you to believe this is esoteric.

There's very much a management dimension to Steve's story as well.