Entries in healthIT (13)


Event Planning for 2012

At this eventful time of year, I thought I would hold off from sending a long post and instead focus on conference and event schedules. Don’t worry, the year-end review/look ahead post will be forthcoming after the 1st of the year.

There are so many good events to choose from, especially in the healthcare and health IT spaces, that it’s difficult to decide where to devote time-constrained resources. The Events page that we added to the Health Content Advisors site earlier this year lists all major events that I or my colleagues will be attending. At this point, only past 2011 events are listed, but we’ll update the list over the holiday period.

Somehow, I chose a fantastic mix of live events to attend last year and I hope to make a repeat appearance at all of these events in 2012. I’m making plans for #HIMSS12, February 20-24 in Las Vegas now and hope to add the SIIA IIS conference, January 24-25 in New York to the list for 2012.

When we update the Events page, we’ll add links to blog posts, pictures and videos from the events. As a preview, here’s a short video interview I did with at the Health2.0 conference in San Francisco:

Also, please check out my previous post on Using Game Dynamics that includes a link to a video of my session at Data Content11 that focused on using game dynamics in market research and provides examples from healthcare research, including PatientsLikeMe.   

That’s it for now. Happy holidays and best wishes for a 2012 that exceeds your expectations!





Stay Tuned for Health 2.0 Coverage

This blog took a hiatus in August, but will be back in force for the remainder of September. I’ll be attending the annual Health 2.0 conference in San Francisco next week and look forward to some related events starting on Friday, September 23 (HealthCamp SF Bay), the Rock Health BootCamp on Saturday, and the pre-conference Patients 2.0 meeting on Sunday.

Health Content Advisors is a media sponsor of Health 2.0 this year, so watch for daily updates to this blog, along with my Twitter feed @janicemccallum that will post more frequent updates from the meetings.  Follow the conference hashtag #health2con for updates from the entire group of attendees.

On the topic of conferences, the InfoCommerce annual event, Data Content11, is coming up soon (November 2-4) in Philadelphia. As always, some healthcare companies will be represented on the program, but the focus is on the broader issue of how to build successful data publishing businesses. This year’s conference program theme is: Cloud, Crowd, and Curation.  Join us for B2B data publishing’s best networking event and to learn from our Models of Excellence companies how to create and sustain high value data businesses.

For those who want to know more about Data Content11, please contact me at  Or, drop me a line if you want to meet up in San Francisco.


Will Health IT Mergers Help Drive Productivity in Healthcare?

Healthcare insiders –and even casual observers—know that the health IT sector is overcrowded with too many vendors that have overlapping functionality. This fragmented and crowded health IT market confuses buyers and leads to costly and inefficient implementations of technology that is intended to improve efficiencies.  A recent blog post by John Lynn (@techguy) provides a useful illustration of how the fragmentation affects provider networks and alliances.  Personally, I wouldn’t want to be the CIO who had to deal with multiple IT vendors within a single institution, never mind dealing with the entire mosaic of vendors by function and across institutions in a formal or informal network of providers.

So, it is easy to predict consolidation between competing players that serve the same functions.  Just last week there were two acquisitions within the medical transcription sector that illustrate this trend: Nuance Communications acquired WebMedx and MedQuist acquired M*Modal.

IT won’t deliver true workflow efficiencies—and accompanying productivity gains—unless vendors  take a systems view of processes and focus on improving the workflow instead of simply digitizing existing paper-based processes.  I’m not saying anything new here. Anyone who has read Clayton Christensen’s Innovator’s Prescription or has lived through a disappointing EMR implementation project understands the problem.  We need a rationalization of vendors and solutions across the entire system. Vertical consolidation within each subsector reduces the confounding number of options for buyers, but doesn’t necessarily solve the larger problem of improving productivity (and by productivity I mean better outcomes and improved efficiency).

In a tangentially related event last week, the Society for Participatory Medicine (#S4PM) held a tweetchat that included some discussion of doctor-patient communication when the doctor is facing a computer screen. Unfortunately, existing EHR/EMR systems haven’t been optimized for the doctor-patient encounter. Voice input, touch screens, direct-from-device input, and even Kinect-style input all represent technologies that could vastly improve the data collection process during, before and after patient visits. Although it’s a small step, I am hopeful that the recent acquisitions in the medical transcription segment allow the consolidated companies more leeway to formulate a wider range of productivity-enhancing voice-data solutions and are representative of future merger activity to come.


Health IT 100: Leaders in Healthcare Social Media

Just a quick note to thank everyone who voted for me in the HIT100 poll. I was delighted to be ranked #8 among an elite group of health IT specialists and industry leaders.

For more detail and information on the follow-on poll to name the top 5 health IT social media influencers, see Keith Boone’s post.

A special thanks to Michael Planchart (@theEHRguy) who conceived of the poll. The results are very helpful in steering people to the highest quality disseminators of health IT information.  I’m truly honored to be in the company of everyone who is on the list.


Google Health Post-Mortem

Last Friday, June 24, Google announced that it will shut down Google Health, which had become a much-hyped platform within the health IT community for storing one’s personal health and wellness data. Outside of the health IT community, Google Health made little impact.  I have read at least a dozen other articles that dissect the technical reasons and health IT insider viewpoints on why Google Health failed.  I’d like to discuss the reasons why Google Health never gained traction within Google.

I’ve followed Google from the very early days when they burst on the scene as a new search engine when nobody thought we needed a new search engine.  Google transformed search by using an algorithmic approach to identify the most relevant results.  Among the three key factors that differentiated Google from the pack were 1) algorithms that ranked pages based on popularity (Page Rank) and 2) scale: the larger the collection of sites that were crawled, the better the results (at the time circa 2000).  Since its introduction, Google’s algorithms have changed many times, but the fundamental fact that Google prefers to depend on programmable solutions that don’t require human intervention remains constant.  And, Google continues to chase large-scale opportunities where it can become an essential layer of the infrastructure.

Factor 3) is the business model. Remember the early 2000s when we all wondered how Google would make money?  After Yahoo acquired Overture in 2003, the revenue model was decided.  Keyword-driven advertising became the preferred method to monetize traffic on the popular search engine sites and scale matters in this model.    

With these three key factors in mind: algorithms not people, scale, and an advertising-driven revenue model, let’s consider why Google Health was destined for failure.

Google has done an excellent job of staying ahead in the “scale” category.  Google loves large repositories of data that it can monetize via advertising.  Google Books is an example. Once the legal hurdles have been worked out, Google Books will run without much human intervention –and has the bonus of providing an e-commerce revenue stream along with an advertising revenue stream.

Where Google got into some early trouble with Google Books was they wanted to side-step the hard work involved in working out agreements with publishers, so they did a deal with AAP and the Writers Guild that required authors and publishers to opt-out and take action if they wanted to set their own pricing terms.  When it came to orphan works, Google would be the presumptive copyright owner if the rightful owner couldn’t be located. So far, Google Books fits with the scale and business model elements. But, Google Books required a heavy initial investment in scanning books.  That certainly requires significant human effort, but Google was able to hire inexpensive labor and only older books needed to be scanned.  Newer books are available in electronic form, so once the initial investment is completed, the humans that place the books on the scanners will no longer be necessary. 

With Google Health I have to agree with Kent Bottles who wrote that Google found the degree of complexity in healthcare too great because it required too much specialized conversion programming and relationship-building with multiple stakeholders.  This variability that cannot be easily managed algorithmically is beyond Google’s chosen core competencies.

With respect to revenue models, Google said they would never put ads around PHR data in Google Health.  I think I still have a copy of the initial terms and conditions that stated that Google planned to monetize Google Health through data-mining aggregated patient data and then presumably selling the results to interested parties, with Pharma undoubtedly at the top of the list. In order for the mined data to be useful, scale and consistency of content types and formats would be necessary.  The revenue models could include keyword and display ads or content sales.

So, in effect, Google Health fell short on all three factors: scale, ability to use an algorithmic approach to content management and search, and revenue model.  Yes, health represents over 17% of our economy, so scale was still a possibility, but rate of adoption was slow—and was named as the primary reason for discontinuing the service.  Google will continue to reap benefits of health care searches via its advertising programs on its existing online and mobile search engines, but a Google Health product that was defined as a personal health data repository just doesn’t represent a big enough opportunity for Google. 

Like most of the healthcare publishing and health IT community, I was excited when I first heard that Google was establishing a health group.  Note, I first wrote about Google Health in 2006 when Google Health was envisioned as part of the Google Co-op program that had a crowdsourced model that encouraged publishers and subject matter experts to tag healthcare information.  Google Health took several turns during its short lifetime and who knows, it could come back in five or ten years once the healthcare industry grows up to resemble the financial services industry where the majority of customers log on to their computers to manage their accounts.  But, even then, its business model will have to measure up to Google’s broad business objectives for it to have any chance of succeeding.