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Entries in healthIT (15)

Thursday
Jul212011

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.

Tuesday
Jun282011

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.

Tuesday
May312011

Patient-Centered Computing and eHealth 

In early May, I had the opportunity to attend the Harvard Medical School CME course, Patient Centered Computing and eHealth: Transforming Healthcare Quality. The 2 1/2 day course is directed by  Blackford Middleton,MD, MPH, MSc Corporate Director Clinical Informatics Research and Development Partners HealthCare and co-directed by Patricia C.Dykes, DNSc, MA, RN Senior Nurse Scientist Nursing Research Program Director Center for Nursing Excellence Brigham and Women’s Hospital.  The outstanding faculty of experts included Brent James, Paul Tang, Patti Brennan, John Halamka, Fabienne Bourgeois, Josh Seidman, Victor Strecher, Judy Murphy, and many others.  The full list of the faculty and their affiliations is included on the site linked to above.   I served as the “official tweeter” for the course and want to share with my readers some of the highlights of this practical course designed for the physicians who are responsible for adopting EHRs and applying health IT in “meaningful” ways to improve healthcare quality.

The full transcript can be found at: http://hashtags.foxepractice.com/healthcare-hashtag-transcript.php?hashtag=PCeHealth11.  For smaller doses, you can read the daily summaries here:

Day 1 Summary

Day 2 Summary

Day 3 Summary

The course included workshops, panel discussions and plenary presentations. To give a taste of the topics covered and insights shared, I’m posting a few outtakes from the Twitter stream for #PCeHealth11 below:

 

dahern1 

 Brent James opening keynote sobering view of healthcare crisis but making case of HIT as one key factor for positive change

Clinicians are poor at “rate estimation” and need technology tools to support decision making - James 

bfm 

Brent James — more important to standardize care than anything else to control costs and improve quality. Great opening talk!

 

Sobko: 25% of Medicare recipients had a complication during care transition within 30 days post-discharge

janicemccallum 

Sobko on care transition: setting goals helps engage patients with care plans; also teach them when there is a red-flag.

bfm

 

Vic #Strecher #UMich to achieve behavior change don’t always need Health Coach, often eHeatlh tools sufficient, or combo 

janicemccallum 

Common theme for engaging #patients : establish a mission or goal to drive behavior change. Tools alone aren’t sufficient.

 

#MU incentives have to be aligned so that efficiency gains aren’t viewed as income reduction by some: @jhalamka.

 

#NHIN isn’t a “thing”; it’s a set of data usage agreements and standards: @jhalamka #HIE

 

Micky Tripathi: think of #HIE as a verb, the act of exchanging information. 

 

Common theme here: secure provider-patient communication saves time b/c it replaces phone calls that typically take more time.

 

Recap from @bfm for day 1: healthcare system is in crisis (Brent James) & has severely negative effect on US financial health.

 

Need to train physicians to be effective knowledge managers; simply too much to know everything. @bfm #KM #CDS #pcehealth11

bgaustin 

Paul Tang keynote: cannot change issues like obesity one person at a time. Change must be community-driven.

janicemccallum 

Jon Wald—biggest driver of usage of patient journals in study: marketing of the patient portal by the practice. #PHR

bgaustin 

“Any doctor who can be replaced by a computer deserves to be replaced.” -Dr Warner Slack

janicemccallum 

Who sponsors #PHRs? 50% health insurers; 25% providers. J. Wald, RTI.org

 

Not much focus on #patient-reported data yet in #EHRs; Wald calls it “patient-entered data” or P-E-D. #PHR

 

BI-like dashboards w/ trend data in #EHRs help provide early warning signs to physicians. #analytics

 

Too many facts to remember & the right information is often not available at point of need. #CDS #EBM #POC @bfm

 

Referral is weak link in continuum of care: Zuccotti’s team developed clinical referral management system. Patient role was key.

 

Jonathan Teich def of #CDS: makes the right thing to do the easy thing to do. #EBM

 

Teich refers to #AHRQ’s eRecommendations project: http://bit.ly/jMMS3G #CDS

 

Cool: @jjseidman describing new program #pophealth: http://projectpophealth.org/ Open-sourced qual measures prog. #CDS #MU

 

AF4Q works with #ONC #REC (regional ext. centers) to help them w/ #quality measures; also trying to harmonize the many meaures.

 

janicemccallum

Alt. future: If providers don’t respond to challenges they will be disrupted & insurers & payers will become coaches @bfm

 

#ARRA #HITECH: the $27B tail wagging the $2.5T dog (Paul Tang). #HCR

 

#EHR and #CDS adoption isn’t so much a function of fear of techology; rather physicians need to be convinced of added value. @bfm

 

#ACOs will shine light on importance of handoffs btwn providers & reduce missed communication. Luke Sato

bgaustin

Powerful keynote by Brent James: “Today’s problems are nearly always yesterday’s solutions.” #EBM

Monday
Jan242011

HIMSS11 Conference Planning

I could spell out what HIMSS stands for, but if you have to ask, you probably aren’t planning to attend this major gathering for the healthcare industry.  HIMSS (okay, it stands for Health Information Management Systems Society) is a membership organization that was established 50 years ago for IT professionals working in healthcare, but has grown to include adjacent segments with interests in health IT.  The annual conference attracts close to 30,000 attendees (about 28,000 last year in Atlanta, but I expect a higher number in Orlando this year) and requires advanced planning to arrange meetings and optimize one’s route to minimize miles walked per day. 

 

Last year, I was pleased to see so many “traditional” healthcare publishers with a presence in the exhibit hall.  My blog post last March mentioned many of them.   This year, I expect to see even more publishers in the exhibit hall, on the program, and sitting in education sessions.  Better yet, I expect to see more progress in creating point-of-care clinical decision support tools and care management tools that build on the best-of-breed authoritative content and data sources. 

 

Forging alliances between the healthcare publishers and EMR/EHR/Health IT vendors is an important part of what we do at Health Content Advisors.  We’re not always the final dealmaker, but we get involved in identifying content and technology partners in nearly all of our client projects.  So, whether you are on the publishing side or the IT content integration or data exchange side, we’re interested in learning what is new among your offerings.  Please contact me @ jmccallum@infocommercegroup.com if you’d like to set up a meeting at HIMSS11.

 

On the “social” side, I’m looking forward to meeting up with the healthcare folks I interact with on a near daily basis on Twitter and via this blog.  It was terrific to connect with many so many of my social media contacts last year in Atlanta and I look forward to catching up with even more people this year-with better advanced planning-in Orlando.  HIMSS will have an expanded social media center in Exhibit Hall E, Booth 7981 , where I know I’ll see familiar faces.  I still remember getting a Twitter message from Liza Sisler @lizasisler who recognized me from my online photo when I sat in one of the social media sessions last year (“is that you across the aisle from me?”).   Also, I plan to attend the new media bloggers tweetup at the MEDecision booth #2563 on Tuesday, February 22 from 4:30-6pm. 

 

For more information on the HIMSS11 conference, see the conference home page.  Along with all the activities I mention above, there is also an impressive line-up of keynoters, including the who’s who of federal healthcare officials.  I look forward to seeing you there!

Thursday
Apr162009

Google Health: PHRs Still Need Human Touch

Google has been very good at establishing a broad-based platform for search and search advertising.  However, they’ve always taken a “hands-off” approach when it comes to content.  Google doesn’t get involved in the dirty work of “data cleansing”, especially when it requires domain-specific knowledge and human intervention. Instead, Google focuses its resources where they can rely on existing metadata to fuel their engineering powerhouse. 

Therein lies the problem that came to light this week when the Boston Globe ran an article that detailed the experience of e-Patient Dave (Dave deBronkart) in transferring his medical record info from Boston’s Beth Israel  Deaconess Medical Center (BIDMC) hospital to Google Health, the highly anticipated personal health record (PHR) utility from Google.  Dave described in the Globe article and on the E-Patient.net blog some of the unacceptable outcomes that occurred when Google inferred information from content that was imported into his Google Health PHR from electronic records at BIDMC.   For instance, dates did not accompany most of the information, so Google Health issued alerts that assumed all of the conditions and meds listed in his record were occurring simultaneously. 

 

The article also highlights serious flaws in using medical billing codes to infer information about medical conditions.  E-Patient Dave delves more deeply into the medical coding issue on his blog and offers a good round-up of the various codes used by medical providers.  These billing codes are imperfect for their primary purpose; using them as the primary metadata to infer a patient’s medical history is a fatal flaw.

So, should we conclude that Google Health is a DOA as some have suggested?  Not necessarily.  But, I think it may be fair to say that Google Health isn’t ready for the average patient/consumer and won’t be until more progress is made in harmonizing the codes and terminology used by various stakeholders in the healthcare economy. 

One conclusion is clear:  given the current stage of development of PHRs, there are opportunities for content intermediaries in healthcare to solve some of the data inconsistency problems.  One new company,  Zweena Health, added its voice to the Google Health bashing to promote its own service that creates PHRs for individuals.  According to their site, they “do all the work” to convert information from providers into a usable information resource. 

Traditional healthcare publishers represent another group that is well-positioned to help solve the data translation and transfer problem for patient records.  Healthcare publishers like Elsevier, ThomsonReuters, and Wolters Kluwer have been combining content with technology to create clinical and workflow tools for years.  Their expertise in understanding content, technology and workflow of healthcare professionals should be included in efforts to develop electronic records for providers and patients.

Finally, medical librarians have expertise and hands-on experience in translating medical information for consumer audiences.  Perhaps it is time for Google to fund medical librarians to take on the work of creating taxonomies and harmonization schemes that would better serve multiple stakeholders.  I’ll forward this post to David Rothman and other medical librarians who blog to get their feedback.

One final thought.  Google likes to aim high and target projects that reach large numbers of people where Google can add value through low-touch high-tech projects that leverage their computing and coding resources.   In the case of digital health records, perhaps Google should take the approach that CMS has used and tackle a smaller piece of the puzzle first, starting with drug information.  Digital drug databases have evolved to a state where they are more reliable and CMS is advancing e-prescribing by providers through financial incentives and promotions.   This week’s announcement that Express Scripts is acquiring Wellpoint’s NextRx pharmacy benefits management (PBM) unit for $4.68 billion is another sign of progress in this arena.  The market apparently approves of the acquisition:  Express Scripts’ stock price has risen since the announcement and has been upgraded to a buy by UBS.

As we wrote last month on the subject of health IT, it is imperative that architects of the health IT software systems understand the content that will flow through their systems and how it will be used.   The same imperative applies to developers of PHR software and tools to an even greater extent, because of the need to translate or explain medical terminology for consumer audiences. 

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