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Friday, July 24, 2015

The Lean Transformation illustrated in 7:39

Nicely done. Concise. Five simple guiding principles to internalize and deploy. A quick animated recap of some of the detail I witnessed during the June Lean Healthcare Transformation Summit in Dallas. Props to LEI. I was touting Lean methodology from the first post of this blog in May 2010.


This was very nice, especially coming from John Lynn.

Well, yeah, I have some strong opinions on core issues (e.g., "interoperabbable," "organizational culture," "clinical methodology," etc). But if you spend much time reading my numerous accrued posts on this blog, you find that I devote most of my space to excerpting and citing evidence consisting of the works of learned, skilled others, spanning the overlapping gamut from technology to clinical science and pedagogy to process QI to policy. I feel like I'm in perpetual graduate school. I don't get paid to do this. I continue to do it because it's important. Now personally traversing the "shards" of the healthcare system renders that importance all the more vivid to me these days.

Speaking of "opinions," I have started a new little Twitter thing called "Your Daily Donald™." A bit of diversionary sport. The jokes just write themselves. Yesterday's Daily Donald.

Oh, and I updated my drought page. We have a raging out-of-control 7,000+ acre forest/brush fire going on this morning just east of Napa. Too close to home.


From Dr. Carter's always-excellent EHR Science:
EHR Data Accuracy is Essential for Decision Support and Data Exchange
by JEROME CARTER on JULY 20, 2015

Current EHR and HIT thinking places significant value on immediate and downstream use of EHR data. The expected benefits of interoperability, clinical decision support, and data analytics all depend on accurate EHR data. Yet, somehow, data quality has not gotten the attention that it should. While clinical researchers are increasingly focused on improving phenotyping algorithms for EHR data extractions(1), there is much less focus on how EHR data collection and validation practices can improve data quality.

Data validation can occur in a number of ways. Basic validation techniques (e.g., missing data, spelling checks, correct formatting) are easy to do, and are simply good software engineering. For clinical systems, the next level up is range-checking for standard data elements. At this level, unreasonable values, such as temperatures of 200o F or blood pressures of 1200/80, are prevented. The highest and hardest level of checking for EHR data is that of “truth” – that is, assuring that the information in the chart that makes it past the first two levels of validation is factually correct. Diagnosis accuracy – the correspondence between the coded diagnosis (ICD or SNOMED) and the remaining chart data–is an example of the challenges inherent in assuring accurate EHR data...
Indeed. Data quality and software QA have been an interest of mine since the 80's. See my first Oak Ridge tech paper "Laboratory Software Applications Development: Quality Assurance Considerations" (pdf). See also my recent post "Personalized Medicine" and "Omics" -- HIT and QA considerations.

See as well my 2013 post "(404)^n, the upshot of dirty data."


From The Neurological Blog:
I have noticed a common arc to many technologies. First they are known and discussed only by scientists and experts in the field. Then they are picked up technophiles who read nerdy magazines and websites. This is all while the research is preliminary and the technology just a distant hope for the future.

Then something happens that makes awareness of the potential technology go mainstream. This is often a movie depicting the technology, but can also be just an article in a more mainstream magazine or newspaper, an early demonstration of the potential for the technology, or a political controversy surrounding it. Then the hype begins.

The hype phase is driven by the researchers looking for more funding, the technophiles who have already been salivating over the technology for years, and a sensationalist media.

We then get into the dark phase of a technology’s arc – the exploitation phase. At this point the hype is running way ahead of the technology, and the public has this false sense that we are on the cusp of major applications.  This makes them vulnerable to charlatans who will claim that they have the technology, long before the tech actually exists.

As the hype and exploitation phase linger, the public is likely to move on to disillusionment. They have been waiting for years for the new technology, and nothing real has manifested. This often leads to the feeling that the whole thing was hype and will never manifest. Even the technophiles may be getting frustrated at this point.

Finally, we start to see real applications of the technology as it comes into its own. The application phase may be rapid – suddenly all the promises and hype of two decades before are not only met but exceeded. Of course, some technologies fizzle and never get to this phase, or may require fundamental advances in other areas to become viable, requiring many decades...
The core focus of this post is that of stem cells. But, it applies to other tech domains as well. Think about the "Gartner Hype Cycle." where are we today in terms of Health IT?

"Trough of Disillusionment" rings true to me a lot, at least with regard to the mainstream EHR and HIE spaces. The Policy ADHD folks on The Hill continue to lambast the "failure" of the Meaningful Use program. There are renewed calls to delay Stage 3, and also to yet again delay the ICD-10 coding conversion now slated for October 1st.

From Health Data Management:
Congress Considers Putting Brakes on Stage 3
Federal lawmakers are noticing some dark clouds surrounding the electronic health records meaningful use program to prod providers to adopt EHRs. With rising recent struggles in the program, lawmakers may be poised to intervene to push back the program’s third stage.

Problems with the current stage are all too apparent. As of mid-June 2015, 11 percent of eligible physicians have participated in Stage 2 of the electronic health records financial incentive program, and 42 percent of eligible hospitals have participated.

Now, there are rumblings in Congress about delaying Stage 3, which is supposed to start with an optional year in 2017 and with all participants moving to the third stage in 2018.

Sen. Lamar Alexander (R-Tenn.), chair of the Senate Health, Education, Labor & Pensions Committee, is broaching the subject of delaying Stage 3, and this month even mentioned the idea to Health and Human Services Secretary Sylvia Burwell. At a committee meeting, Alexander discussed his talk with Burwell and added: “There’s been some discussion about delaying Meaningful Use Stage 3, about whether it’s a good idea, whether it’s a bad idea, whether to delay part of all of it. My instinct is to say to Secretary Burwell, ‘Let’s not go backwards on electronic healthcare records.’ ”

Alexander also said it may be wise to slow down Stage 3, “not with the idea of backing up on it, but with the idea of saying, ‘Let’s get this right.’ ” At the same committee meeting, David Kibbe, MD, president and CEO of DirectTrust, a coalition of 150 organizations supporting the Direct secure messaging protocols, recommended “an immediate moratorium on Stage 3 until Stage 2 is fixed.”...
From The Health Care Blog:
Avoid ICD-10? Yes, You Can!
Jacob Reider, MD
...Technology should capture the diagnosis in a terminology that I understand – MY language (HLI, IMO or SNOMED-CT) and if additional data is required – I should always be prompted for it – in the most elegant manner possible.  The information that I capture can/should then be stored in the patient’s problem list if it’s not already there (and of course if it IS already there – it should be offered as an initial selection to avoid replicating work that was already done!) and then translated in the background into the administrative code.  This should be opaque to the user.  Accessible?  Yes – sure.  Just as I can “view source” in my browser to see the HTML.  But really – who wants to do that?  Not me (most of the time).  Not you.  Nor will I need to see the ICD-10 code 99% of the time.

Don’t burden your clinicians with ICD-10!  Avoid it.  Yes you can.  And you should.  Anything less is irresponsible.  Yes – some Who have been “educated” by high-priced consultants will ask for it.  But you shouldn’t give them a faster horse.  Give them what they need.
Well, we do live in interesting times. We only have a little more than two months now before the October 1st ICD-10 deadline and the new federal fiscal year. The contentious 60 day congressional review period of the proposed Iranian nuke deal falls right into that, plus there's that now-hardy perennial GOP federal shutdown threat, replete with poison pills like the umpieth "repeal ObamaCare" legislative amendments, etc.

Interesting indeed.

More to come...

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