Price Transparency: An Interactive Timeline

“Price transparency.” Search the term on google news and almost all of the hits deal with health care. In the less than four months since Steven Brill published his Time expose on hospital prices (which I commented on), health care price transparency has vaulted to the center of national health care debate.

Today, Mr. Brill is on Capitol Hill testifying at a Senate Finance Committee hearing on price transparency. Sounds like he had some pretty harsh words on Obamacare.

Given the growing momentum on the topic, I’ve thrown together an interactive timeline of key events that have happened in the last few weeks. (Really wish WordPress would allow me to embed flash.) Enjoy!

http://www.timetoast.com/timelines/the-coming-wave-of-price-transparency

Colonoscopies: A Real Pain in the…

(Please excuse all of the terrible puns in this post. I couldn’t resist.)

Down in the Dumps?

Colonoscopies have gotten some pretty shitty news coverage lately.

In a cheekily titled New York Times piece, Elisabeth Rosenthal boldly blamed colonoscopies for causing the U.S. to the lead the world in health care expenditures. Tracking the confluence of specialist lobbies, lucrative up-billing by ambulatory surgical centers, and obscure market-specific price variation, Rosenthal highlights how colonoscopies have become one of the most expensive and widely used screening tests despite evidence that alternative treatment methods may be just as effective.

The price variation piece was hit home a week later by the New York Times’ editorial board.

And then there was the thoroughly disturbing revelation that 3 out of 20 endoscopes, which are used in colonoscopies, remain contaminated with “biological dirt” after current cleaning practices.

Given such painful coverage, it was a refreshing breath of air to read that Kaiser Permanente in California has actually been doing something about it for the last 20 years. Back in 1993, Kaiser changed its colon cancer screening policies to favor sigmoidoscopies, which are less invasive than colonoscopies. Screening rates jumped up to 45% but stalled (probably because having something stuck up your rear is unpleasant, no matter how far up you go).

But in 2006, Kaiser research found that a new version of a stool test had better accuracy than older ones. It offered it as an inexpensive, noninvasive mail-in stool test. Screening rates soared to nearly 85%, resulting in a corresponding jump in “screen-detection rate” (% of cancers detected through screening methods):

FOBT = fecal occult blood test; FIT = fecal immunochemical test. Values averaged across multiple time periods. Source: Moiel D and Thompson J. 2011. Early detection of colon cancer–the Kaiser Permanente Northwest 30-year history: How do we measure success? Is it the test, the number of tests, the stage, or the percentage of screen-detected patients? Perm J, 15(4):30-38.

The jury seems to be out on the relative effectiveness of the three screening methods: colonoscopy, sigmoidoscopy, and stool test. The CDC recommends any of the three without preference. The thing is, most prior research has compared the effectiveness of the different screening modalities without considering vastly different rates of uptake. You may have the most sensitive test, but if people aren’t willing to undergo it, its value as a screening tool at the population level greatly diminishes. As the Kaiser study concluded:

“The program realized that employing the most accurate screening method did not make a difference in screen-detection rate overall, if the availability of endoscopic resources and patient unwillingness to comply with the strategy did not support the program. [...] Using a good test (FOBT/FIT) that is able to reach more people, rather than the “perfect test” that reaches fewer people, transforms an ineffective program into a successful one when the strategy moves from individual testing to population-based screening.”

And that’s the thing: when clean clinical science meets messy clinical practice, oftentimes we’re not sure of the result.

Pragmatic Trials: Because Real Medicine Isn’t So Clean

Here’s how a typical randomized controlled trial might play out:

You define the research question as whether Intervention A will lower BP for hypertension patients. You recruit subjects and explicitly exclude anyone with a co-morbidity (say, diabetes or heart disease). You train a set of practitioners to deliver the intervention according to a specific protocol, and throw out results from any practitioners that don’t follow it. You require that subjects follow the intervention to the T, and throw out results from any patients that don’t comply. Finally, after running the trial, you produce rigorous, clean data that tells you, YES, the intervention works like a charm.

And then you take it out into the real world and it suddenly has no effect. Turns out patients and practitioners don’t comply 100% of the time in real life. Or have more problems than just high BP.

This example illustrates the contrast between randomized controlled trials and “pragmatic trials“. Randomized controlled trials, long considered the gold standard in clinical research, rely on careful participant selection and stringent adherence to protocols to determine “efficacy” in a best case scenario. Pragmatic trials attempt to mimic real-world scenarios to determine the “effectiveness” of an intervention in actual practice.

The concept of pragmatic trials have been around since 1967, but only took off in the last ten years. It’s part of a field known as comparative effectiveness research, which compares existing tests/treatments/services, often in real-world settings. Kaiser Permanente’s Division of Research has been doing this for years, and the health reform law devoted $3.5 billion through 2019 to fund the Patient-Centered Outcomes Research Institute (PCORI), which will fund and disseminate comparative effectiveness research. PCORI recently announced its 2nd round of research grants, totaling $88.6 million to 51 research projects across 21 states, and unveiled a plan to establish 8 “Clinical Data Research Networks (CDRNs)” and 18 “Patient-Powered Research Networks (PPRNs)”. They could’ve come up with catchier acronyms.

Articles per year catalogued in MEDLINE with the word “pragmatic” or “naturalistic” and “trial”. Source: Patsopoulos NA. 2011. A pragmatic view on pragmatic trials. Dialogues Clin Neurosci, 13(2):217-224.

Research Not Sufficient to Change Clinical Practice

Despite the hullabuloo, it may be too early to celebrate.

A recent NEJM study presents a great example of comparative effectiveness research at its best. It found that Enbrel, Amgen’s blockbuster joint disease drug, is no more effective than a cocktail of generic therapies in treating rheumatoid arthritis. Enbrel costs about $25,000 a year. The generic cocktail costs about $1,000.

Yet an accompanying editorial had some words of warning about how this study may be too late to influence ingrained physician practices:

“We have to consider, however, whether these findings have arrived too late to influence modern practice, in which arguably a TNF inhibitor [such as Enbrel] is the preferred next step when methotrexate alone is inadequate.”

Comparative effectiveness research was a focus of last October’s Health Affairs issue, and one article outlined a number of reasons that such research fails to change patient care, including:

• Less effective therapies may be better reimbursed under fee-for-service;
• Economic incentives encourage pharmaceutical and device manufacturers to use creative ways of influencing physicians’ decisions;
• Many results may be ambiguous and prone to accusations of methodological weakness, especially when they try to venture away from the gold-standard randomized controlled trial into the messy world of real life medicine;
• Physicians are only human and exhibit a number of psychological biases, including “confirmation bias“, “pro-intervention bias“, and “pro-technology bias”; and
• Use of decision support to help physicians change their practices is limited.

In fact, physician culture may trump even financial incentives and fear of lawsuits; a recent study showed that even physicians at Veterans Affairs hospitals, who do not get paid for ordering more tests and are rarely sued, order just as many unnecessary nuclear stress tests as physicians at other hospitals.

Simply conducting comparative effectiveness research and establishing recommended guidelines is necessary but insufficient. We need powerful ways to disseminate these guidelines, overcome historical prescribing inertia, and actually change treatment practices. We need more efforts like Dr. Jerry Avorn and colleagues’ “academic detailing” program, in which pharmacists and nurses are deployed to visit doctors one-on-one and inform them of the latest therapy recommendations without industry conflicts of interest. We need more systems like Kaiser and UCSF, who will not only research different treatment options but also implement them system-wide.

After all, spending thousands on a painful, infection-prone colonoscopy when a simple mail-in stool test will do can be a real pain in the…

Paging Dr. Watson: The Impact of Technology on Clinical Judgment

Last month, a provocatively-titled article in The Atlantic declared, “The Robot Will See You Now“. Starting with the story of IBM’s Watson going to medical school to learn to make diagnoses and treatment recommendations, it painted a future picture of medicine based on remote monitoring, clinical decision support, and above all, the cold, rigorous, seemingly-infallible power of Big Data.

“According to a growing number of observers, the next big thing to hit medical care will be new ways of accumulating, processing, and applying data.” Think: every primary care physician equipped with a Watson app to help them diagnose. Wearable sensors that track your blood pressure, heart readings, and numerous other indicators before you get to the doctor’s office. And as one venture capitalist predicts, computers and robots someday replacing 4 out of 5 physicians in the U.S.

Around the same time, I discovered a TED talk recorded in 2011 from Dr. Abraham Verghese, best-selling author and proponent of humanistic medicine, advocating for a very different kind of innovation:

“I’d like to introduce you to the most important innovation, I think, in medicine to come in the next 10 years,” Dr. Verghese declares, “and that is the power of the human hand.” Dr. Verghese goes on to describe the ritual of the physical exam–an age-old ritual of discovery and catharsis that has given way to something far less personal. He warns of a future “where the patient in the bed [becomes] an icon for the real patient who’s in the computer.”

“We seem to have forgotten — as though, with the explosion of knowledge, the whole human genome mapped out at our feet, we are lulled into inattention, forgetting that the ritual is cathartic to the physician, necessary for the patient — forgetting that the ritual has meaning and a singular message to convey to the patient.” -Dr. Abraham Verghese

So who’s right? Dr. Verghese’s message is simultaneously powerful and touching. But if we ascribe to his view, are we clinging to a romanticized notion of medicine at the cost of a less effective health care system? Are the two futures–one of “personalized” medicine and the other of medicine that is fundamentally personal–mutually incompatible? Or is there some middle ground we can aim for?

Déjà vu? The Unfulfilled Promise of EMRs

Turns out that somewhere 10,000 feet below the discussions of industry proponents and enamored health care executives, physicians have been debating a parallel of this question for quite some time. Not in response to the next robot-doctor, but to the replacement of good ol’ pen-and-paper notes with electronic medical records (EMRs).

According to a 2012 CDC report, the number of office-based physicians using EMRs has jumped from 18% in 2001 to 72% in 2012. EMRs were supposed to be the pill that saved us from an ailing, inefficient paper system. By digitizing all of our medical records, we could improve inter-provider communication, reduce errors, and finally solve the intractable problem of illegible physician handwriting. Indeed, much of the rapid adoption of EMRs in recent years has been driven by the Health Information Technology for Economic and Clinical Health (“HITECH”, har har) act of 2009, which provided incentives for physicians and hospitals to adopt EMRs. $27 billion of taxpayer money in incentives.

Unfortunately, a recent report by the RAND Corporation and subsequent reporting by the New York Times have highlighted some failures to achieve these promises. More and more people have begun seeing the whole thing as a scandal marred by industry influence, government complicity, and lack of evidence. Read a sample in this scathing account.

More directly relevant to our current discussion is the impact of EMRs on the end users (physicians) and the ultimate “beneficiaries” (patients). Driven like sharks to the frenzy of government money, EMR vendors rushed to spread their respective products, often without consulting the end user. As a result, physicians around the country began complaining about the burdens and limitations of EMRs, as Dr. Bob Watcher illustrates in a well-written post about the impact of EMRs on cognitive thinking:

“When I was on clinical service in July and read the notes written by our interns and residents, I often had no idea whether the patient was getting better or worse, whether our plan was or was not working, whether we need to rethink our whole approach or stay the course. In other words, I couldn’t figure out what was going on with the patient.” -Dr. Bob Wachter

The rigid, drop-down-menu style of EMRs may be impairing the ability of physicians to synthesize patient information. And that’s a scary thought.

Don’t Blame the Technology–Blame How We Use It

Interestingly, buried down below in the comments (credit goes to Dr. Leslie Kernisan for picking up on this) is a gem of a response from one Dr. Lawrence Weed–the same man who Dr. Wachter lauds in the opening of his post. “Our difficulty with Dr. Wachter’s analysis,” writes Dr. Weed, “is that he assumes the primary vehicle for clinical synthesis to be physician judgment. In reality, synthesis should begin before the exercise of judgment.”

In other words, why should old-fashioned physician thinking be the only way of synthesizing clinical information into a diagnosis? And why can’t technology like Watson be used to synthesize disordered clinical data, medical literature, insurance claims, and other data sources into meaningful clinical information that the physician can then use to make more informed clinical decisions?

Dr. Weed goes on to highlight an additional shortcoming of the current discourse around whether EMRs are good or bad: “Effective synthesis is tool-driven and process-driven.” (Emphasis mine.) And our debate over whether EMRs–or Watson–are “good” or “bad” for medicine ultimately addresses only half of the picture. Can we develop guidelines to ensure that the physician uses technology to inform rather than dictate the diagnosis? Can we establish processes that require the physician to continually elicit patient input into the treatment process?

The answers to those questions might be the key to determining the ultimate impact of technology on clinical reasoning and the wider field of medicine.

How Will It Help the Patient?

An extremely timely article published a few weeks ago in JAMA found 190 cases of missed primary care diagnoses in one year across two large health systems. Almost 80% of the errors were traced to “breakdowns in the physician-patient encounter”, with 56% of errors related to the medical history and 47% related to the physical examination. In an accompanying commentary, Dr. Newman-Toker estimates the error rate at about 0.1% of all primary care visits, which when extrapolated across the U.S. means at least 500,000 missed diagnostic opportunities each year.

(Update: This just in: diagnostic errors are the leading cause of successful malpractice claims, with 40% of diagnosis-related claims resulting in death.)

Just last week, a new survey by The Economist Intelligence Unit rank-ordered the activities in which “the need for retaining a role for human imagination or intuition [is] most critical.” The number one result is telling:

Source: Economist Intelligence Unit, 2013, “Smart Systems, Smarter Doctors: Humans and machines in healthcare”. http://ricoh.emailsrvc.net/track/dl/1394/Wave_2_Healthcare_final_WEB.pdf

These data point to an increasing urgency for solutions to improve the accuracy of our diagnostic capabilities , while simultaneously highlighting the tensions of emerging technologies such as Watson and their potential impact on clinical judgment. There is no simple answer to whether new technology will be good or bad for medicine. Rather, as our experience with EMRs shows, unlocking the promised benefits of technology will depend on our ability to foresee and mitigate a number of pitfalls:

• Will the end-user (physicians, nurses, and other care practitioners) be consulted in every step of the design process, so that the technology can be smoothly integrated into workflows instead of creating onerous burdens?
• Will the technology be designed to actually save money rather than driving ordering of unnecessary tests and services, as this recent Senators’ report accuses EMRs of doing?
• Will medical education continue to stress the importance of clinical judgment, even with the proliferation of new tools at our disposal? Or will physician and care practitioners become increasingly dependent on the judgment of Dr. Watson?

Given the limitations of relying solely on old-fashioned clinical judgment, we must not be afraid to embrace the promise of technology such as EMRs and Watson. But we should be vigilant against unintended consequences these technologies may have on cognitive processes and patient care–this means rigorous evaluations of the impact of new technology, something that has been conspicuously missing for EMRs. And as we continue to debate the benefits of new technology on the physician, we should all keep in mind some words of wisdom from former CMS Administrator Don Berwick: “How will it help the patient?“

Does Language Influence Our Propensity to Save?

Does my Chinese language subconsciously influence me to save more, avoid smoking, exercise more, and eat more healthily?

That seems to be the conclusion of economist Keith Chen of the Yale School of Management, in his recently published paper (and described in his much more viewer-friendly TED Talk).

Prof. Chen’s argument essentially runs as follows: certain languages, such as English and  Greek, oblige speakers to separate out present and future tense (“I will go to the store tomorrow”), while other languages, such as Chinese and German, prevent speakers from doing so (“我明天去商店”, or, “I go to the store tomorrow”). Could this linguistic separation of present and future in certain languages lead speakers of that language to discount the future, thus reducing their propensity to save and prepare for the future? Since this is certainly not a question that can be answered using a randomized controlled trial, Prof. Chen goes the big data route; pulling data from the largest data sets in the world and running regressions to parse out the effects of numerous possible confounding variables, so that he can compare the savings behavior of people born in the same country, living in the same country, of the same sex, age, income level, educational achievement, family structure, religion, etc. and differing only in the language they speak. What he found was a surprisingly rigorous correlation despite controlling for all of these other factors: “Futureless” language speakers are 30% more likely to report having saved in any given year, 20-24% less likely to smoke, 13-17% less likely to be obese by retirement, and 21% more likely to report having used a condom in their last sexual encounter.

Two Linguists Offer Their Criticisms

I listened to a recording of this TED talk while practicing my (apparently linguistically-driven) morning run yesterday, and slowly shifted from skepticism to mind-blown acceptance as Prof. Chen covered his statistical bases. But it’s easy to become a believer when you’re neither a professional linguist or economist. Upon arriving home, I did a quick search and sure enough, uncovered well-written criticisms from two linguistics professors:

Mark Liberman of the University of Pennsylvania highlights the dangers of running statistics on factors that may very well not be completely independent. He uses graphical depictions to show that as soon as you introduce the assumption that certain factors are correlated in their geographic diffusion (e.g. language and culture), it becomes quite easy to find highly statistically significant correlations between non-causally related phenomenon.

“If you torture the data long enough, it will confess.” -Economist Ronald Coase

Geoffrey K. Pullum of the University of Edinburgh has a slightly more piquant response (including taking a jab at Prof. Chen for being a “non-linguist”), challenging Prof. Chen’s categorization of languages into strong and weak “future time reference” languages. This underlied some of my initial skepticism as well (after all, I can easily say, “我明天会去商店”, or “I will go to the store tomorrow”). Perhaps most alarmingly, Osten Dahl–the same scholar whose work Prof. Chen relies upon to categorize his languages–shows up in the comments section to emphasize that he never created hard categorizations in the first place.

These posts touched off a series of additional conversations, which you can find outlined here. Not being an expert in either field, I’ll leave it to you if you want to continue down the rabbit hole of this very interesting debate. However, I did want to highlight one remark from Prof. Chen that I think we can all learn from.

Stepping Out of the Echo Chamber

Earlier in the week, I had listened to a TED Talk (maybe I’ve overdosing a bit here) by Margaret Heffernan, who recounted the story of Alice Stewart. Alice Stewart was an English physician and epidemiologist who in 1956 published a paper showing for the first time that children of women who received X-rays while pregnant were significantly more likely to die from childhood cancer. What’s most striking about this story is the fact that Alice had to fight entrenched interests for 25 years before the British and American medical authorities changed their practices, and how her working relationship with a statistician named George Kneale helped her persevere through the fight. As Ms. Heffernan explains, George saw it as his job to prove Dr. Stewart wrong. He crunched the numbers in different ways, explored possible confounding factors, and tried everything within his statistical power to poke holes in her conclusion.

“Because it was only by not being able to prove that she was wrong, that George could give Alice the confidence she needed to know that she was right.” -Margaret Heffernan

This brings me to a statement that Prof. Chen included in his response to Profs. Liberman and Pullum that jumped out at me:

“…all analyses I conduct are on publicly available data, and I’d love to talk more with readers interested in replicating, extending, or testing these results in ways I haven’t thought of.”

Too often we enclose ourselves in an echo chamber of like-minded thinkers, looking for the next killer argument to throw at “the other side”. Regardless of whether Prof. Chen’s hypothesis turns out to be valid or not, his openness to engaging in constructive conflict is something I think we should all strive to emulate.

Can Higher Wages Drive a Virtuous Cycle of Profit?

Suddenly faced with time for some free reading, I’ve decided to occasionally write a post on a topic outside of my usual focus. As such, I plan to structure these posts are shorter blurbs, offering more conjuncture than conclusion, and hoping to garner your thoughts and opinions. I hope these can lead to some interesting discussions.

Can Higher Wages Drive a Virtuous Cycle of Profit?

An article this week in The Atlantic makes the argument that companies like Costco, QuikTrip, and Trader Joe’s prospered through the recession because they viewed employees as assets and paid higher wages–in direct contrast to conventional business notions to cut costs (read: layoffs and lower wages) during a recession. It’s this philosophy, the author argues, that will allow companies to flourish in the future.

Perhaps. It’s certainly an enticingly paradoxical notion–that paying higher wages will actually lead to a virtuous cycle of more growth. I was drawn to the title precisely because of the beloved TJ’s located a block from my office, where staff seem constantly energetic, engaged, and all around happy to be there. But does it actually play out in practice? Three example companies make a very measly sample size (n=3), in a narrative that could easily confuse correlation for causation. Is there documented rigorous evidence that treating workers as assets (whatever that may mean in practice) actually leads to positive growth for companies?

It may turn out to hold true for the vast majority of companies, in which case we would be facing huge opportunities by changing companies’ ingrained sense of cost-cutting. I could also see it hold true only for certain types of companies–for example, ones that target a more socially conscious consumer willing to pay a premium for better service (TJ’s I’m looking at you!). “Treating workers as assets” is also a fairly vague term–does this mean higher wages, greater voice in sharing ideas, better benefit plans, or something else? I’m sure there’s already a growing management literature on this. The article quotes Dr. Zeynep Ton of MIT’s Sloan School of Management; that may be a good beginning place to look.

For Employee Health Benefits, “Cost Control” May be the Wrong Approach

This issue becomes most interesting for me when we look through the lens of health benefits. As the poorly portrayed CVS-demanding-workers’-weight story indicated, companies are becoming increasing interested in ways to manage their workers’ health through benefit plan design and wellness incentives. And the conventional wisdom is that when I write, “workers’ health”, I really mean “workers’ health costs”. Facing spiraling health care costs that parallel our nation’s terror over the future of Medicare, companies have been trying to find creative ways to rein in those costs, through euphemisms such as “consumer-driven health care” that make employees pay a greater share of health care costs to “get their skin in the game”.

The problem is, if the argument that better-treated employees contribute to increased productivity and a better bottom line, then offering employees skimpier health care benefits may paradoxically ruin productivity (greater absenteeism, less energy at the workplace, etc.) and hurt the bottom line. As employers increasingly recognize this, they may start looking beyond the health benefit price tag to see what plans, providers, and services can help increase worker productivity and well-being, even if they cost a little extra.

I have a hunch that research in this area is still a murky black box. How do we distinguish effective programs from trumpeted snake oils? What services actually translate into bottom line benefits? What metrics should we even look at to measure the “value” of a health benefit package?

What do you think?

My Post Featured in Health Wonk Review!

For a health care nerd, it’s a dream come true. Many thanks for Mr. David E. Williams for including my post on health care prices in this week’s edition of the Health Wonk Review, a biweekly compendium of health care blog posts.

Mr. Williams has assembled a collection of great articles that touch upon topics ranging from insurance exchanges to pharmaceutical regulation and why dictating payment models is like telling your restaurant manager how to price the menu. Check it out here.

Sorry Steven Brill: These Aren’t the Costs You’re Looking For

Steven Brill made headlines last week when he published a 26,000-word, 11-page Time article on why health care costs are so high–the longest article by a single author in the history of Time magazine. It’s a fascinating read, one that’s filled with real life stories, making it both more engaging and palatable than, say, a 26,000-word economics thesis on the same topic. But for those who don’t want to wade through all 11 pages, here’s a summary of Mr. Brill’s argument:

1. Health care costs are so high in the US because prices for health care are so high.
2. Prices for health care are high because by law, we have allowed them to be high. A lack of universal price controls allows “nonprofit” hospitals, pharmaceutical companies, and device makers to charge ridiculous prices and reap in huge profits.
3. His solutions:
   1. Tighten anti-trust laws so that hospitals can’t conglomerate and demand high prices from “helpless” insurance companies.
   2. Tax hospital profits at 75% and institute a tax surcharge on non-doctor hospital salaries that exceed $750,000.
   3. Outlaw the “chargemaster”, an internal price list that all hospitals keep which contain ridiculously high prices that seemingly have no basis, and are often only used as a starting point in negotiations.
   4. Institute medical malpractice reform to reduce defensive medicine (doctors prescribing too much for fear of being sued).

The article has already generated a multitude of responses, especially from the health care blogger community–ranging from ardent support (from “crooksandliars.com“) to scathing criticism (from Mitt Romney’s domestic policy director).

I’m certainly no health care expert, policy wonk, or Carnegie Mellon professor of economics. But given what I’ve heard through working with hospitals across the U.S. (many of whom pay us precisely because they’re worried they’ll go out of business in a few years), I thought I’d throw in my own two cents.

(I’ve tried to be as objective as possible and use data to support my assertions when I can. But given my job, it’s certainly possible that I’ve been slowly influenced to adopt an overly sympathetic view of hospitals…in which case I better watch myself.)

Real Stories, Real Hardships

First, I think the the most important thing to keep in mind as we engage in debate about the economics of the health care system, and whether the various root problems and solutions that Mr. Brill identifies are real, is that the seven lives Mr. Brill outlines in his article are very real. Emilia Gilbert, the 66-year-old school-bus driver who was put on a payment schedule of $20 a week for six years from one fall and ER trip. Alice D., who decided she can’t remarry because she can’t “risk the liability” of being stuck with over $170,000 in bills for her husband’s end-of-life cancer treatment. These seven stories represent the 48.6 million Americans who are uninsured (a number that will hopefully continue to drop as insurance expansion rolls out next year), people who are very much vulnerable to the excessive hospital prices that Mr. Brill outlines.

Brill’s Demonized Chargemaster is a Distraction

However, from a system perspective, I think the chargemaster that Mr. Brill repeatedly attacks is a distraction. The chargemaster is the internal list of prices that every hospital keeps for every procedure and supply item that the hospital uses. These are the prices that Mr. Brill incredulously highlights: $1200 for one hour of a nurse’s services; $1.50 for a single Tylenol tablet that you can buy a 100 of for $1.49 on Amazon.

They are indeed ridiculous, and often created without rhyme or reason. Thing is, they’re also rarely used:

• The latest data (from 2009) shows that on average, 40.9% of hospital cases in the U.S. are paid for by Medicare. Medicare, which–as Mr. Brill describes–could give a rat’s *** (my words) about chargemaster prices and instead pays each hospital a set amount, about 90% of the actual costs of treating that patient (see graph below).
• Another 17.2% are paid for by Medicaid, which vary on a state-by-state basis but are usually some percentage off of Medicare rates.
• 30.5% are paid for by HMOs, PPOs, or other private insurance. According to Mr. Brill, these private payers negotiate rates that are 30-50% higher than Medicare rates (rather than negotiating downward from chargemaster rates).

Here’s a handy graph showing how payments from Medicare, Medicaid, and commercial payers compare to the cost of treating a patient. Note that Medicare and Medicaid actually pay less than costs on average while commercial payers pay more–leading to the phenomenon of hospitals using profits from commercial payers to “cross subsidize” the costs of treating public payer patients. Source: Ginsburg PB. 2011. Reforming provider payment – The price side of the equation. N Engl J Med, 365:1268-1270.

• Excluding workers comp and some other miscellaneous categories, this leaves “just” 4.9% that are true self-pay cases, where the uninsured is charged the full chargemaster price. HOWEVER, many hospitals offer payment subsidies, discount prices, or simply write off patients’ charges as uncollected “bad debt”. A 2008 analysis of actual payments received by hospitals in California showed that the median uninsured patient paid 1% less than Medicare rates and 28% less than commercial rates.

These numbers suggest that the individual stories Mr. Brill documents may be limited to a very small subset of the population. Indeed, the average self-pay payment rate rate was higher than the median (20% higher than Medicare and 14% less than commercial), indicating a rightward skew–a small number of uninsured patients are truly getting hit hard. However, the concern about these ridiculous prices, and the dangers that a subset of the uninsured face when they can’t get discounts, can be solved by a simple solution–one that doesn’t require outlawing the chargemaster as Mr. Brill recommends, which would arguably make hospital prices even less transparent (the “Treatment for Heart Attack: $100,000″ bill, as Oren Cass posits). Rather, it’s a solution that Uwe Reinhardt suggested back in 2009: a national ceiling of 115% of Medicare rates for charges to the uninsured. Since hospitals are only collecting de facto payments of 1% less than Medicare rates from the median uninsured patient anyway, it’s not like it’s going to affect their bottom line. They would get to keep their (admittedly meaningless) chargemasters for negotiating purposes, patients could still see everything they’re being charged for (without having to pay the full amount), and those uninsured patients that are getting hit with true full prices today would be protected.

Are Hospitals Really That Profitable?

Apart from the chargemaster, Mr. Brill sees the primary culprit behind high health care costs as paradoxically profitable “nonprofit” hospitals that command high prices from “helpless” insurance companies and manipulate their “sympathetic nonprofit status” to reap in huge profits and dissuade lawmakers from doing anything about it. “That’s a 12.7% operating profit margin,” Mr. Brill writes of Stamford Hospital’s 2011 financials, “which would be the envy of shareholders of high-service business across other sectors of the economy.”

But is that really true? As of January 2013, the average operating margin of 6177 U.S. firms across most major sectors was 17.1%. The average for Medical Services was 10.1%–hardly enviable from a market perspective. In addition, as Mr. Brill himself notes, hospital inpatient care has an operating margin of only 2%. (Which does beg the question, why is hospital outpatient care so “wildly profitable”–and is this something that should be addressed? Perhaps more on this in a later post.)

I’m also somewhat dubious that the insurance companies Mr. Brill mentions are anything but helpless. Mr. Brill is right when he points out that hospital consolidation will increase their negotiating power against insurance companies. What he overlooks is the fact that insurance companies are consolidating too. Last July, WellPoint announced that it was buying Amerigroup. Six weeks later, Aetna announced it was buying Coventry. Which consolidation will “win out” on prices–hospitals or insurers–is unclear, but this 2011 study is enlightening: while consolidation of hospitals does appear to drive up prices, consolidation of insurers appears to have the opposite effect of driving down prices (by about 12% in the most consolidated markets), and that overall, “more concentrated health plan markets can counteract the price-increasing effects of concentrated hospital markets.”

On balance, excessively profitable hospitals may not be the major cause of excessive costs, as Mr. Brill believes. In fact, signs suggest that hospital profits are about to drop. Plans for the exchanges, which roll out next year, will likely pay hospitals lower than current commercial rates (10% lower, according to recent news from Texas; most providers fear more). Payment penalties and reforms from the Affordable Care Act, combined with movement by commercial payers toward paying for value, will only serve to further push down prices.

Barking Up the Wrong Tree

In 26,000 words, Steven Brill has painted a picture of soaring health care costs because profitable hospitals command high prices. Interestingly, Mr. Brill stops short of actually advocating for any type of price controls. The logical solutions–as Matthew Yglesias at Slate points out–would be to either (1) expand the price-setting Medicare program to cover the entire population, or (2) set health care prices nationally, as a number of European countries do. Aside from the fact that both solutions would be politically DOA, each one would either face substantial challenges or have unintended consequences.

However, given that full hospital prices only apply to less than 5% of cases, and that hospitals may not be as profitable as Mr. Brill suggests, trying to control hospital prices as a way to control health care costs may be barking up the wrong tree.

As Mitt Romney’s Domestic Policy Director points out (and as much as I hate to agree with Mitt’s anyone on anything), the true question may not be why health care prices are so high, but why the costs of providing that care are so high. As he writes:

“All of those enormous costs for treating a patient actually go to pay for things, not to line the pockets of scheming industrialists. But what? How much of a hospital’s expenditures are construction? Capital equipment? Doctors? Supplies? Management? Bureaucracy? And each of those things that it buys – an MRI machine, a pacemaker, a cancer injection – where does that money end up? How much of it goes to researchers? To the acquisition of start-ups that create new intellectual property? To TV advertisements? How much of a doctor’s income goes to the cost of her education? To her malpractice insurance?”

One more thing I would add: How much of the money we pour into health care is for services we don’t need? How much is going toward outcomes we don’t value? And most importantly, how can we get our health care system to start achieving ones that we do?