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Saturday, May 12, 2012

My first guest cross-post: "Personalized Prevention"

One nice upshot of surfing A-list healthcare blogs such as THCB is the lead generation resulting in hooking up with many of the thought leaders in medical care.

to wit, I have made contact with Dr. Joseph C. Kvedar, Founder and Director of the Center for Connected Health in Boston. We've reciprocally placed blogroll links in our respective blogs, and he's agreed to a cross-post comprising an aggregation three recent posts of his that I find of particular interest and relevance to the Big Picture of my REC/HIE work.


Personalized Prevention, Part I
FEBRUARY 22, 2012
For a few years now, I’ve been thinking about the potential intersections of genetics/genomics/proteomics and connected health. In fact, my colleague Kamal Jethwani and my daughter Julie coauthored a piece for the journal Personalized Medicine on the topic in 2010. A summary and the reference is linked. (I should also note that the figure I reproduced below is from that article with permission from the publisher.)

To learn more, I initially checked in with some local geneticists but their focus was on identifying genetic mutations in various cancers in order to predict therapeutic response. This fascinating area was recently discussed in the NEJM in a piece called Preparing for Precision Medicine. However, that is not exactly what I’ve been dreaming about. I was thinking more about the potential to identify folks with propensity towards chronic illnesses like obesity, diabetes and hypertension using genetic techniques. Then, getting these individuals on connected health programs in an effort to change the course of their personal health history, before they wound up with these often avoidable, costly conditions.

A couple of months ago I had an email and subsequent visit by George Church, the world-famous geneticist and founder of the Personal Genome Project. This conversation was pivotal for me as George is interested in collaborating with researchers who can track and map phenotype in such a way that we can match to genotype. Our team is meeting with him again this week and I’m looking forward to an exciting collaboration to emerge.

The intersection of connected health and genetics is interesting and complex terrain, and I am going to break up the discussion into several posts. Today I just want to introduce the concept of Personalized Prevention and get your reaction to it. Subsequently, there will be posts on some of the lifestyle diseases that have a genetic component and how we might use connected health to address those conditions. As a start, I want to make sure we are all on the same page as to the meaning of a couple of terms.

A person’s genotype is the manifestation of the DNA in their cells, i.e. genetic information. An individual’s phenotype is the expression of those genes in terms of proteins, cell behavior and ultimately human traits and behaviors. Some time ago, the visionaries in the world of genetics coined the term personalized medicine to refer to the idea that if we know your genotype, we can be precisely predictive of your risk of getting certain diseases, as well as your response to certain therapeutics.

The $1000 genome is nearing reality. As a society, we’ve not yet begun to appreciate what this means. There are all sorts of implications but the most mind-bending is the idea that we will eventually be able to create diagnoses that are unique to you and therapeutic responses that are equally unique.

Consider that we are constantly bombarded with messaging about health care that goes like this: “40% of patients had a positive response as compared to placebo.” This sounds like a triumph at the population level, but what if you are one of the 60% that would not respond and we could predict that? One of my professors was prescient on this matter back in the ‘70s and said, “Patients don’t really care what their percent likelihood of an outcome is. For them, the outcome is 100% success or failure and they’d like to be able to predict it on that  binary level.” Until very recently we’ve only been able to offer patients a sense of risk, but the time is coming where we will be able to be much more confident in our choices for them.

Connected health does this too. It is the ‘phenotypic map’ that corresponds to the detailed ‘genotypic map’ the geneticists come up with. Consider if we have a population of workers and we want to incent them to be more active. Connected health can provide, at a minimum, a very precise measurement of the outcome. It enables folks who are investing in the program to see — both at a population and individual level — whether the program is resulting in increased activity.

Healthrageous has had success with this in the employer/health plan market. They are giving customers precise data on how their populations respond to various incentives and programs to increase activity and lower blood pressure. The company will be moving next into diabetes. Healthrageous can measure a program’s success quite precisely, reporting % engagement, % that stick with the program through the end and % achieving clinically significant results. In all cases, they are creating new industry norms, but equally exciting is the precision of their reporting.

The illustration below lays out the concept of Personalized Prevention graphically.  Individuals who are at risk to develop a chronic illness can be identified, then offered connected health programs as a tool to prevent progression. Likewise, individuals who are not responding to connected health programs can be identified as candidates for genetic testing to uncover the reasons why not.

I think the best example of how this might work is for people who are overweight or obese. There is now good evidence that people who gain weight reset their satiety thermostat, i.e., when they lose weight even to a previously low weight, their body sends their brain a signal that they are chronically hungry, as if trying to get them back to their overweight state. Tara Parker-Pope covered this wonderfully in a recent NY Times Magazine article called The Fat Trap.

I’ll write more on this next time, but to me it makes great sense to try to identify folks at risk for weight gain and educate them about activity using smart pedometers. The feedback loops that connected health provides allow for an intense education into how one can easily increase activity. It seems that, knowing there is a risk of weight gain, and knowing that this extra weight would be incredibly hard to take it off, an individual might be motivated to sign up for an activity monitoring program. Finding the right motivational triggers is, in part, how we create Personalized Prevention.

So what do you think? Does the concept of Personalized Prevention make sense?
Personalized Prevention, Part II – 

The Psychology of Engagement
MARCH 13, 2012

My colleague Meghan Searl collaborated with me on the psychology framework discussed herein.

 I don’t spend much time on Facebook.  Its not that I’m antisocial, but on a given day if I get through my email inbox by 10 PM, I feel good about myself. That leaves little time for social networking.  I haven’t played Angry Birds or Farmville for the same reason. I just have other priorities.  I grew up in a family of plain-spoken, simple Vermonters.  My dad was a kind and gentle man, but when he raised his voice we all took notice. And, because of his ‘kinder-gentler’ side and plain-spoken character, my brother and I took him quite seriously and felt it was wise to comply with his wishes. Also, my folks both had a deep sense of the value of good health and strove to achieve a healthy lifestyle.

I believe this combination of circumstances and history is what is behind my individual connected health psychology. I am responsive to authority – a compliant fellow who sometimes forgets, but when reminded complies.

In Personalized Prevention, Part I, I talked about the power of genetic data combined with the phenotypic mapping that connected health tools give us to micro-segment the population to a level where we have a completely unique, individual genotypic and phenotypic profile. The example I used was obesity, suggesting that with these two technologies colliding, we’ll have the opportunity to identify individuals at risk for weight gain early in life and put them on connected health programs to keep them trim. Many readers pushed back and the essence of the push back was, “micro-segmentation alone is not the answer.  Even providing individuals with data on their caloric expenditure in the context of their risk for weight gain will not solve this problem.”

Folks, I couldn’t agree more. The medium of blogging is best suited to ‘bite-sized’ writing and the first bite in this series was about the micro-segmentation piece. Today I want to spend time on the psychology of engagement, as I believe it is critical to the success of connected health and can also be highly individualized.

The first point to re-emphasize is that connected health data alone do not solve any problems, except perhaps for the very small group of highly motivated fitness buffs and quantified selfers (maybe 10% of the population). There was a time when companies in this space boasted that they could ‘get biometric data into the PHR or EMR.’ Work done at the Center for Connected Health and by others has demonstrated that this is nearly meaningless.  We’ve relearned the old adage that data is not information.

Of course, it’s all about what you do with the connected health data. Objective data inputs are a critical component of the solution – self-reported data is also nearly useless – but the success of connected health programs is all about the psychology of how we engage program participants in these data in order to motivate them to improve their health.

Most companies who have focused on engagement have not bothered to include the objective data stream because of the cost of sensors and the complexity of integration. Most have also touted one engagement strategy or another as the key to success. The options these days seem to be:  gamification, social networking, coaching, reminders, incentives and punishments.

Lets go back to me as an example. If my employer rolled out a wellness program and the engagement tool was social networking, I am afraid I would not be successful in it. Likewise for competitions/games. But set me up with a reminder system and an automated coach with an authoritarian tone and I will improve my health behavior.

Purveyors of wellness programs tout their success, e.g., ‘40% engagement after 6 weeks.’    My question is what about the 60% who didn’t engage? It seems to me we understand the tools and triggers to get closer to 100%, but we must admit that one size does not fit all and do some behavioral segmentation at the outset to tailor programs to what individual buttons need to be pushed.

Healthrageous comes the closest to offering this type of approach (I say this with as much objectivity as possible, as a co-founder and share holder). Their vision is to know so much about you that they can anticipate the engagement experience that gets you involved in a way that you feel they know you intimately.  This will come about through a machine learning environment and as more and more participants take advantage of their programs, they’ll do better and better at this.  In the meantime, I think we can start with a simple set of questions designed to paint a profile of each individual that is akin to the one I wrote describing me at the beginning of this post. We’re working on that at the Center. I am excited to share our learning as we go forward.

Personalized Prevention, Part III: 
Applying the Model to Obesity
APRIL 2, 2012
Weight loss (or gain) = calories in minus calories out.  Simple, right?  Well actually, not as any person who has gained a few pounds and can’t shed them will attest. It seems as we grow older, our metabolism slows. There is also good evidence that once we put on weight, our body re-adjusts to ‘defend’ (that’s a word scientists use) that new weight. Stated another way, if you gain 10 pounds, then lose 10, your body goes into a state where various hunger hormones are secreted more often than they’d be in the case of someone who never gained the 10 lbs. Tara Parker-Pope covered this wonderfully in a recent NY Times Magazine article called The Fat Trap.

But actually that’s only true for some of us. Those of you who were around to witness the amazing performance of Robert DeNiro in Raging Bull (1980) know he gained 50 lbs to play the character of Jake LaMotta in his later life.  After the film, DeNiro lost the weight promptly and easily. He can be seen as slim and trim playing a priest in True Confessions  (1981) not long after. Even if you look at modern-day pictures of DeNiro (e.g. in Little Fockers 2010), he is no where near as heavy as he was when he played the senior LaMotta 30 years before.

Ok, now are you convinced that it is more complicated than simple calories in vs. calories out?

In Personalized Prevention, Part I, I reviewed the concept of connected health as phenotypic mapping and started a discussion of how one type of data might inform our use of the other. In Part II, I discussed the psychology of engagement as applied to connected health interventions.  In this post, I want to use obesity as an illustration of how it might practically work.  I am not going to cover the public health story on obesity (how we live in a time of calorie excess and a dearth of opportunities to be active). I know some of you will have that top of mind and may wonder why its not mentioned. Yes, we’re all growing a bit more overweight as time goes on due to this trend. In general, we’d all benefit from eating more plants, more colorful foods, less animal-based food, less processed food and finding ways to be more active. Today, I want to talk though about how the genetics of obesity may be able to help us create segments of the population that may respond differently to connected health interventions. Also, response to connected health interventions may be a trigger to prompt genetic testing.

Although I am not an expert on genetics, I have studied up on the genetics of obesity as I am giving at talk at BioIT, May 25, at the BIO meeting in Boston. We are a long way off from having exact obesity genotypes the way we now do for certain cancers and the like.  But the genetics argue that we can distinguish at least 5 genotypes:
  • Thrifty genotype: low metabolic rate and insufficient thermogenesis
  • Hyperphagic genotype: poor regulation of appetite and satiety and propensity to overfeed
  • Sedens genotype: propensity to be physically inactive
  • Low lipid oxidation genotype: propensity to be a low lipid oxidizer
  • Adipogenesis genotype: ability to expand complement of adipocytes and high lipid storage capacity
Imagine a world where we knew this information before or shortly after birth. Could you envision someone with either the thrifty genotype or the sedens genotype being targeted for an exercise program involving activity monitoring and customized motivational tools as were discussed in Parts I and II? If we got to these folks when they were young, do you think we’d have the ability to reorient their lifestyle choices for the better?

One example worthy of consideration is the partnership we have with the Boston Public Schools to encourage activity in children from some of our underserved schools. I blogged on this some time ago. The 2011 program was such a success that we’ve expanded it this year, and we are just launching the spring 2012 program. The children who took part last year shared numerous stories about how wearing a smart pedometer, getting weekly feedback and participating in a classroom competition on activity helped them become more aware of how active they are, encouraged them to be more active and even bring the culture of activity into their homes.

When people are on a connected health program, we can determine at an individual and at a population level who is active and who is not responding to the program. Imagine that we could take those data and compare them with genetic data to elicit finer and finer comparisons.

I am wildly enthusiastic about personalized connected health, about the opportunities to combine genetic and phenotypic data to gain insights about individuals and about personalized prevention.

Much more to come. Among other places, we're gonna have to go Back Down in The Weeds', e.g.,
...With the ongoing revolution in genomics and proteomics, the myriad resemblances and differences among individual human beings are becoming far more sharply defined at the molecular level. These advances are already making it possible to reconceive existing diagnostic entities, classifications and therapeutic understanding. But to fulfill their potential, these advances require more complete, organized, documented clinical observations in patient care, plus better linkages among these observations and existing knowledge. Were that to occur, there is reason to believe that we would learn how seemingly distinct disease conditions may actually be interrelated, how medical interventions that seem narrowly targeted at a specific gene or molecular pathway may actually disrupt multiple body systems, of how an individual’s phenotype may actually be more important than genotype for some diagnostic and therapeutic purposes, and how drugs and other powerful interventions sometimes may be more disruptive and less effective therapeutically than simple improvements in health behaviors. These possibilities are reinforced by evidence that common disease conditions appear linked to many rare genetic variants among individuals rather than to a few common variants across populations. [ Lawrence Weed, MD, and Lincoln Weed JD, Medicine in Denial, pg 191.]

"If you want every blood pressure below 130/80, hire a computer to dose the drinking water with antihypertensives. The quality measures will be perfect, and every hospital will be No. 1 in the U.S. News & World Report rankings." - Danielle Ofri, MD, PhD
apropos of "Personalized Care," both "preventive" and post-presentation

 In the wake of reading yet another post on TCHB, this one, "Slow Medicine," by the above-quoted Dr. Ofri, I was compelling to buy and download the new book cited therein, Dr. Victoria Sweet's  "God's Hotel. A doctor, a hospital, and a pilgrimage to the heart of medicine."

I got it Friday night after work. I finished it today. Every page. Every word, all the way to the final end note on page 372. "A PageTurner," is long by now a cliche, to be sure. But it was certainly the case for me. My huge pile of ironing, and the sweeping and mopping of the floors will just have to wait.
As I watched Mrs. Muller get into her car, I thought about the money that Laguna Honda’s Slow Medicine had saved the health-care system. I was beginning to think of it as just that— as Slow Medicine, in the same way that there was Fast Food and there was Slow Food.
I was thinking about it especially because we were in the middle of yet another budget crisis, and administration was sending us memos about cost containment. We should pay attention to the costs of what we did, administration advised. Perhaps we could avoid prescribing the newest medicine if an older, cheaper one would do; shelve expensive tests if they had no clinical repercussions; order vans instead of ambulances; or reconsider routine lab tests. Administration presented its suggestions as if doctors had to be convinced to watch out for costs, and some doctors do take such suggestions as evidence for a capitalist invasion of the health-care enterprise. Yet the real problem, Mrs. Muller showed me, was that administration’s thinking did not go far enough; it did not cast a wide enough net and did not snare the real culprits.
In her case, what saved money were an accurate diagnosis and the leisurely reevaluation of the patient. It wasn’t much— a simple physical examination and an old-fashioned X-ray— but it did take time, quite a bit of time, actually. A thorough exam takes me almost two hours, and my daily visits, while not lengthy, were not rushed, but they were what allowed me to see that Mrs. Muller A thorough exam takes me almost two hours, and my daily visits, while not lengthy, were not rushed, but they were what allowed me to see that Mrs. Muller was not demented, psychotic, or diabetic.
Economists assume that this kind of care is expensive, but it is still cheaper than an MRI or even a routine lab panel, not counting the cost of keeping Mrs. Muller in the hospital for the rest of her life. I worked it out. At $ 120,000 per year for the average six years a patient lives at Laguna Honda, less the cost of Mrs. Muller’s resurgery (and not counting the cost for the care her retarded daughter would have required), an accurate diagnosis of Mrs. Muller saved the health-care system about $ 400,000.
The case of Mrs. Muller got me to thinking. If doctors were going to be held accountable for costs, why shouldn’t we get some kind of credit for savings? To use for patients, for the kind of care that economists cut out as extravagances?
What was happening was the opposite: No expense was spared for medications, tests, and procedures, but to make up for that, staff, food, and accoutrements were cut to the bone. The calculus being that the medications, lab tests, and procedures were necessities, but that staff with enough time to do their jobs were an expendable luxury.
Doctors in particular. I was amazed at how expensive economists thought doctors were. They instituted many economic maneuvers— de-skilling medicine onto nurses and physician assistants; computerizing medical decision-making; substituting algorithms for thinking— because they assumed that doctors were such expensive commodities. And yet doctors were not expensive, at least, not the doctors I knew. We cost no more than the nurses, the middle managers, and the information technicians, alas. Adding up all the time I spent with Mrs. Muller, the cost of her accurate diagnosis was about the same as Adding up all the time I spent with Mrs. Muller, the cost of her accurate diagnosis was about the same as  one MRI scan, wholesale.
Economists did the same thing with the other remedies of premodern medicine— good food, quiet surroundings, and the little things— treating them as expensive luxuries and cutting them out of their calculations. At Laguna Honda, for instance, while most patients were on fifteen or even twenty daily medications, many of which they didn’t need, the budget for a patient’s daily meals had been pared down to seven dollars, which could supply only the basics.
I began to wonder: Had economists ever applied their standard of evidence-based medicine to their own economic assumptions? Under what conditions, with which patients and which diseases was it cost-effective to trade good food, clean surroundings, and doctor time for medications, tests, and procedures? Especially ones that patients didn’t need?
Although Mrs. Muller was an impressive example of Laguna Honda’s Slow Medicine, she wasn’t the only one. Almost every patient I admitted had incorrect or outmoded diagnoses and was taking medications for them, too. Medications that required regular blood tests; caused side effects that necessitated still more medications; and put the patient at risk for adverse reactions. Typically my patients came in taking fifteen to twenty-five medications, of which they ended up needing, usually, only six or seven.
And medications, even the cheapest, were expensive. Adding in the cost of side effects, lab tests, adverse reactions, and the time pharmacists, doctors, and nurses needed to prepare, order, and administer them, each medication cost something like six or seven dollars a day. So Laguna Honda’s Slow to the extent that it led to discontinuing ten or twelve unnecessary medications, was more efficient than efficient health care by at least seventy dollars per day.
I thought about what I could buy for my patients with seventy dollars a day. Good food. Not just tasty food, but excellent, organic, and varied food. Good wine. Hildegardian medicinal ales for the anorexic and digestives for the dyspeptic. Acupuncture. Massage. We’d be rich with seventy dollars per day to spend on each of our patients.
Over the next months, as I studied Hildegard’s medicine, my thinking evolved. Suddenly it occurred to me: Why not have a ward at the hospital where Laguna Honda’s Way of Slow Medicine could be tested for efficiency? Against the efficient health care of the economists? It would be easy to run a two-year experiment. All I would need would be a ward and an administrative dispensation from the forms and regulations raining down, along with a computer program to track the costs and savings incurred. I was pretty sure we’d end up in the black, and I knew just how I’d spend those savings.
I had a name for the ward, the ecomedicine unit, or ECU. Ecomedicine because it would be an oikos— a self-sufficient system at the level of the body, the ward, and the world. The patient’s body would be an oikos because it would be envisioned not in isolation but as part of its environment. The ward would be an oikos because it would be in balance as a self-sufficient minihospital, with its own ecology within the larger ecology of the hospital and the world. The well-being of the staff would be taken into account as well as the well-being of whatever and whoever came and left the ecomedicine unit: the plants and animals we ate, the stuff we used and threw away.
The ECU would be ecologic in a fractal sense, with ecosystems from smallest to biggest, lowest to highest. [God's Hotel, pp. 125-128].
From Daniell Ofri's TCHB review:
Dr. Victoria Sweet, a general internist, came to Laguna Honda for a two-month stint more than 20 years ago and ended up staying. Laguna Honda was home to the patients who had nowhere else to go, who were too sick, too poor, too disenfranchised to make it on their own. The vast open wards housed more than a thousand patients, some for years. Laguna Honda was off the grid, and this, Sweet discovered, was to the benefit of the patients.
Unencumbered by HMOs and insurance companies, the doctors and nurses practiced a very old-fashioned type of medicine, “slow medicine,” as Sweet terms it. There was ample time for doctors and nurses to get to know their patients, and ample time for patients to convalesce. Many a written-off patient recovered within the comforting, unhurried arms of Laguna Honda.
Sweet realizes that the inefficiencies of this old-fashioned hospital – from the doctors who had time to fully research their patients’ complicated histories, to the nurse who knitted a handmade blanket for every charge on her ward, to the chicken that wandered regularly through the AIDS ward, bringing a spark of life to even the most demented patients – were actually its secret weapon. The inefficiencies were actually quite efficient, if your metric was healing patients.

Dunno. I've by now drunk -- if at times warily and irascibly -- a railroad tank car's worth of the HIT/QI Kool Aid, but this book cannot but give you pause, if you care about more than hitting this quarter's ONC Milestones, or about actually facilitating "patient centered care."

See, btw, "The Provider Will See You Now."

"God's Hotel" reads at once like a historical novel and PBS Frontline documentary screenplay. Riveting. While working as a physician at Laguna Honda, Dr. Sweet earned a Doctorate in history, having to become fluent in German, French, and Latin along the way in order to study the ancient literature of premodern western medicine (see Hildegard von Bingen) at their medieval archival sources for her dissertation.

Buy it. Not kidding. (I get nothing for touting this, or any other work I cite.) I kept thinking, "Yo, MiraMax, y'all busy these days? I got a story for you..."

Tangentially, from the BMJ, 2003

Advice to young doctors from members of the BMJ's editorial board
  • Learn to cope with uncertainty
  • Challenge what you are taught, especially if it seems inconsistent or incoherent
  • Regard your knowledge with humility
  • Be yourself at all times
  • Enjoy yourself
  • Try to practise medicine with the same ethics and principles you believed in when you started medical school
  • Never be afraid to admit your ignorance
  • Medicine is not only clinical work but is also concerned with relationships, team work, systems, communication skills, research, publishing, and critical appraisal
  • Treat your patients with the same care and respect as if they were your loved friends or family
  • Cure is not what everyone is expecting from you: your patients and their families may be just seeking support, a friendly hand, a caring soul
  • Outside the family there are no closer ties than between doctors and patients
  • Don't believe what you read in medical journals and newspapers
  • Aim at knowing how to learn, how to get useful medical information, and how to critically assess information
  • The first 10 times you do anything—present a patient, put in an intravenous catheter, sew up a laceration—will be difficult, so get through the first 10 times as quickly as possible
  • Although you should not be afraid to say “I don't know” when appropriate, also do not be afraid to be wrong
  • Cherish every rotation during your training, even if you do not intend to pursue that specialty, because you are getting to do things and share experiences that are special
  • When you have a bad day because you are tired, stressed, overworked, and underappreciated, never forget that things are much worse for the person on the cold end of the stethoscope. Your day may be lousy, but you don't have pancreatic cancer
Advice from Dave Sackett, the father of evidence based medicine
  • The most powerful therapeutic tool you'll ever have is your own personality
  • Half of what you'll learn in medical school will be shown to be either dead wrong or out of date within five years of your graduation; the trouble is that nobody can tell you which half—so the most important thing to learn is how to learn on your own
  • Remember that your teachers are as full of bullshit as your parents
  • You are in for more fun than you can possibly imagine
 "...In particular, avoid the trap of thinking you need to know everything. Even if you knew everything at 6 o'clock this morning (which of course you never could), you won't by midday—because a thousand new studies will have been published. “Medicine,” says John Fox, head of the Advanced Computing Laboratory, “is an inhuman activity.” We need the help of machines. Ask travel agents the time of planes from Shanghai to Hong Kong, and they will not quote from their heads. They will use information tools. Doctors must learn to do the same."
Interesting. pretty Weedy. How will we reconcile the romantic Slow Medicine of Hildegard with the caffeinated (and CPT-encounter-billable) Clinical Digitiverse of HIT x.0?


I call mine my "cognitive crack pipe." I have the b/w Kindle itself (got it with AMEX points from my paid-in-advance, not-covered jawbone graft surgery job last year) and an iPad that my daughter gave me -- also very convenient for reading.

I can't keep up. In addition to all of my blog reading and my periodicals (e.g., Atlantic Monthly, The New Yorker, Rolling Stone), and my endless laws/regs reading for work, I've started and finished five books in the last ten days, four of them regarding health care, and one fun new Grisham novel.

Then there are my current works-in-progress (the last one an interesting take on a core aspect of economic history):

I get tired, but I never tire of reading.

Most men give flowers and chocolates. I give reading assignments.



Headline link to the ONC blog on the HITRC this morning.

I have to admit that I bristled just a bit when I saw that. I posted a comment asking about efforts to position RECs "for continued success." It has yet to pass "moderation." It may well not.



More shortly...

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