from THCB at http://bit.ly/2zxNb5W on December 26, 2017 at 03:50PM
By ANISH KOKA, MD
A recent kerfuffle ensued when a CDC analyst leaked details of a meeting that noted a list of banned words and phrases that included ‘evidence-based’ and ‘science-based’. This most recent assault on reason from the Trump administration was lapped up by partisans as yet another example of the dangers of having reality stars occupy the White House.
Unfortunately no one apparently told the director of the CDC, who took to twitter to respond:
I want to assure you there are no banned words at CDC. We will continue to talk about all our important public health programs.
— Dr Brenda Fitzgerald (@CDCDirector) December 17, 2017
Details are sparse. A meeting took place. Words were discussed. No Trump administration official has come forward to take ownership of the meeting.
Regardless, we should all be relieved that we can now get back to the business of implementing evidence based health care policy.
How has that been going anyway?
Ten years ago this month Atul Gawande wrote a widely read article in the New Yorker called The Checklist. In it he related a masterful riveting story of a 3 year old girl in Austria who slipped into an icy pond, and was underwater for 30 minutes. On arrival to the intensive care unit, she required massive support – a heart lung machine, treatment and monitoring of brain swelling. The end result in this case was nothing short of miraculous. Two years later, she was like any other than 5 year old. The point Gawande goes on to make is that the complexity of patients in the critical care setting is overwhelming. In these sickest of sick patients even one mistake could be the difference between life and death. Humans can’t do it – and the error rate that inevitably results is not one that society should bear.
The solution was the checklist. Derived from the airline industry to avoid errors, porting this innovation that allowed the flying of planes safely to medicine, would make medicine more manageable and therefore safer. Peter Pronovost, an intensivist at Johns Hopkins, started making use of a checklist when placing central lines to lower rates of infections related to the presence of these lines. Remarkable drops in the rates of infections were noted and the era of checklist mania was upon us. Dr. Gawande was sold, and as a young doctor, just finishing my training, I had no real reason to argue with him. But as the years passed and I flailed about, losing hair and sleep at the bedside of the sickest of sick patients in intensive care units, the whole concept started to seem absurd. Yes, patients were immensely complicated. Yes some patients died. But as I went over what we could have done differently – I began to realize that prognosis in most of these patient had little to do with the actions of the team in the ICU. The patient with a ruptured aneurysm in their brain related to an infection on a heart valve died for reasons that had nothing to do with better processes. One patient’s infection was controlled by antibiotics, and the strands of bacteria flipping around with every heart beat stayed put or regressed. The other patient treated in the same manner showered emboli, developed multiorgan failure as a result, and died. The initial presenting condition was paramount to prognosis. Beyond that, stochastic events – not expertise – seemed to guide patient outcome. This doesn’t mean no errors ever took place, but that it was a rare event that could directly link an error to a bad outcome.
So ten years later it comes as little surprise that checklists have failed in a variety of arenas. Just last week, the closely watched Gawande-inspired Better Birth Project to use checklists to improve maternal and fetal mortality in India was found to improve adherence to best practices, but was found to have no affect on mortality. Apparently checklists weren’t enough to wipe out the disadvantages inherent in communities that subsist on $2/day.
Checklists didn’t even succeed in solving simpler problems that seemed ideal for the process like the “wrong site, wrong procedure, wrong patient” medical error. There are few medical errors worse than surgery on the wrong breast, or even worse the wrong breast of the wrong person. But it happens. Making this a never event became a mission for all sorts of agencies and checklists proliferated in hospital surgical staging areas. As a boy growing up in India I had been accustomed to hearing the daily muslim call to prayer ringing out from the local mosque. Who knew that as an adult walking through the hospital I would get used to hearing the health system prayer as nurses dutifully put doctors in ‘time-out’ to call out items from checklists. (This was especially loud when the Joint Commission visited).
If I had only chosen to dig a little deeper than a New Yorker article I would have found that this whole endeavor was doomed from the start. As newsworthy as these events were, they were already almost never events. The seminal study on the topic found a rate of errors of 1 in 112,000 procedures. That means any one hospital would experience this event once every 10-15 years. That’s a rate of disastrous complications the aviation industry would be envious of. None-the-less, the pursuit of perfection in this arena brought us the universal protocol and its checklist from the aviation industry. And it may have made things worse.
According to the Joint Commission, the era of checklists and Universal Protocols resulted in a higher rate of never events.
To be fair, I don’t know this for sure. Perhaps the reporting improved, and the rate have been the same the whole time. No one really knows. But I think it would be reasonable to conclude that checklists didn’t result in these rare errors becoming never events.
The scale of the health policy evidence based blunders only get larger from here.
Remember The Cost Conundrum? Also written by Dr. Gawande in the New Yorker, this was another powerful tale that built on data from the Dartmouth Eliot Fisher group that had mapped Medicare spending by county. McAllen, Texas had the distinction of having the second highest per capita Medicare spending in the country. A trip from Gawande to this little town uncovered a profit driven enterprise of doctors and hospitals milking the system. The helpful solution was provided by a trip to the Mecca of healthcare in the United States that was low Medicare cost, but – the low cost, but high value Mayo Clinic. A visit to a surgeon’s clinic there told of an hour long discussion with a patient followed by a cardiologist materializing within 15minutes from another floor to help ready a patient for surgery the next day. How did they do this?
“..decades ago Mayo recognized that the first thing it needed to do was eliminate the financial barriers. It pooled all the money the doctors and the hospital system received and began paying everyone a salary, so that the doctors’ goal in patient care couldn’t be increasing their income. Mayo promoted leaders who focused first on what was best for patients, and then on how to make this financially possible.
No one there actually intends to do fewer expensive scans and procedures than is done elsewhere in the country. The aim is to raise quality and to help doctors and other staff members work as a team. But, almost by happenstance, the result has been lower costs.”
The answer to the health care cost problem lay in this elegant article. The plan as initially forwarded by Eliot Fisher from Dartmouth and now gracing the pages of the New Yorker was to create Accountable Care Organizations in the image of the Mayo Clinic. Convert McAllen, Tx to Rochester, MN and the nations problems would be solved.
I never stopped to think, of course, exactly how Mayo was operating in this manner. How could a surgeon at Mayo afford to spend a whole hour with a patient? How exactly does a cardiologist have time to run down in the middle of the day to discuss a complicated patient? If the cardiologist doesn’t bill the consultation, how is the cardiologist being paid?
These details were not provided, and these questions were never asked. The Cost Conundrum was required reading for the framers of the ACA, and so health care was reimagined and jiggered to make winners out of large health care systems. Cuts from CMS targeted private practice reimbursement. Regulations that required reporting of practices through an electronic health record were applied. The incentives quickly melted away to become penalties. Private practitioners faced a choice : accept the lump of coal or join a hospital. Most fled to hospitals, dotting the landscape with soup to nuts health care systems and realizing the dream Gawande had written about.
Except, Gawande and his adoring readers (that would include me) had been hoodwinked. The secret sauce for this high value care being provided to patients by the very best in the field wasn’t in the Medicare data that Eliot Fisher’s group in Dartmouth had put out. The drunk looking for keys under the lamp post doesn’t find his keys for a reason. The keys in this case was where no one was looking – payments from private insurers.
Just down the road from where I grew up at Carnegie Mellon University came a paper based on claims data from private insurers that showed a much more complex Savannah than the Eliot Fisher data had lead anyone to believe.
The dollars paid by private companies was multiple of what was paid by medicare. A knee MRI paid by private insurers was $1331, Medicare paid $353. Even more startling was how Rochester, MN ranked relative to its peers in per capita cost.
While Rochester, MN was a bargain when it came to Medicare spending per beneficiary, it was one of the most expensive markets when it came to private spending per beneficiary. The other large vertically integrated health systems (Grand Junction, CO – La Crosse, WI) that Gawande had highlighted? Also some of the most expensive on the private market.
Apparently, creating large integrated health system created a monopoly that could effectively name its price for the services it was rendering. Medicare gets to set its prices – the private insurers have to negotiate with providers. The fewer health systems in a county, the higher the prices negotiated. THIS is what was paying for one hour patient visits with a surgeons and made Cardiologists materialize out of thin air. The idea that any of these large health systems were low cost was a myth.
The New Yorker article was published June of 2009 and received widespread attention. Barack Obama subsequently held a health care town hall Grand Junction, Colorado a few months later to highlight that members of the community were getting “better results and wasting less money” as part of the push to pass the Affordable Care Act. The paper from Gaynor & colleagues arrived six years later in December 2015 to what would seem to be much less fanfare. Gawande wrote a brief mea culpa, acknowledging large health systems (like the one he had worked for his whole career) were not cheap, but they were still the path to providing high value care. It was just the cost side of the equation that had to be figured out. The New York times did a wonderful bit of reporting (by Margot Sanger Katz) in their Upshot blog as well. In today’s era were likes, clicks, and impressions declare victors, I would be willing to bet the non-narrative fitting paper and subsequent coverage lost by a mile.
I recall being profoundly disappointed on reading the Gawande mea culpa. It was reflective of the approach of most of the policy folks in charge at the time. Rationalization of one sort or the other were made – Coverage! Not Cost! – and the importance of staying on the path was reaffirmed.
This had been an exercise in a narrative in search of data. It turns out that empiricism in health policy isn’t quite like the science of sending rockets to Mars. Ideology rules – academics that worked for large health care systems produced data to support their world view. Even the paper from Gaynor had been produced with the help of claims data from private insurers who formed the Health Care Cost Institute in 2011. Everyone seemingly has a side of the story to tell. The mistake may be to reimagine the healthcare system based on any one of these views.
Designing health care policy would seem to be a thankless task. Some will no doubt conclude that we just need better data to design a more perfect system. I am not so sure. It may be that the lesson to learn from all this is to design as little as possible, and foster an environment that lets patients, not regulators, pick winners and losers in healthcare. The entrenched interests that control much of the flow of the $3 trillion dollars we spend annually are unlikely to let that happen. They have lots of studies that say so.
Evidence based health care policy awaits, saved from the Great White known as Donald Trump.
I can’t wait.