• The crisis in medical research. And how to fix it.

    Recent US government budgets have harmed the National Institutes of Health. But the problems in the medical research system are deeper than just the current budget. If you care about medical research, read this article in the Proceedings of the National Academy of Sciences by Bruce Alberts, Marc Kirschner, Shirley Tilghman, and Harold Varmus.

    Alberts and his colleagues describe a hypercompetitive culture in science that undermines the process of discovery.

    Competition… has always been a part of the scientific enterprise, and it can have positive effects. However, hypercompetition for the resources and positions that are required to conduct science suppresses the creativity, cooperation, risk-taking, and original thinking required to make fundamental discoveries… biomedical scientists are spending far too much of their time writing and revising grant applications and far too little thinking about science and conducting experiments.

    You probably expect that the next sentence will be, “So give us more money.” But that’s not where they go.

    We believe that the root cause of the wide-spread malaise is a longstanding assumption that the biomedical research system in the United States will expand indefinitely at a substantial rate. We are now faced with the stark realization that this is not the case.

    Assuming that science will expand forever, senior scientists have trained far more junior scientists than the system can support, leading to hypercompetition.

    The mismatch between supply and demand can be partly laid at the feet of the discipline’s Malthusian traditions. The great majority of biomedical research is conducted by aspiring trainees: by graduate students and postdoctoral fellows. As a result, most successful biomedical scientists train far more scientists than [there are] relevant positions in academia, government, and the private sector.

    The overproduction of new scientists is driven by “perverse incentives”:

    Salaries paid by grants are subject to indirect cost reimbursement, creating a strong incentive for universities to enlarge their faculties by seeking as much faculty salary support as possible on government grants. This has led to an enormous growth in “soft money” positions, with stagnation in the ranks of faculty who have institutional support. The government is also indirectly paying for the new buildings to house these scientists by allowing debt service on new construction to be included in its calculations of indirect cost recovery.

    Alberts et al. have detailed suggestions for reform. They write

    (i) to advocate for predictable budgets for US funding agencies and for an altered composition of the research workforce, both with the aim of making the research environment sustainable; (ii) to rebalance the research portfolio by recognizing the inertia that favors large projects and by improving the peer review system so that more imaginative, long-term proposals are being funded and scientific careers can have a more stable course; and (iii) to encourage changes in governmental policies that now have the unintended consequence of promoting excessive, unsustainable growth of the US biomedical research enterprise.

    I cannot overstate how distinguished these authors are, both as researchers and institutional leaders in science. Alberts made discoveries in how chromosomes replicate during cell division, is the former editor of Science, and former President of the National Academy of Sciences. Kirschner made discoveries in developmental biology and is a University Professor at Harvard, where he served as chair of the departments of systems biology and developmental biology. Tilghman made discoveries in gene regulation and is the former President of Princeton. Varmus won the Nobel Prize for discovering retroviral oncogenes. He is the former director of the NIH, former President of the Memorial Sloan-Kettering Cancer Center, and the current director of the National Cancer Institute.

    Get it? It’s as if the Pope and three leading cardinals held a press conference predicting the collapse of the Catholic church. These people know what they are talking about and we need to listen.


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  • Curious about the exchange litigation? Here’s a podcast!

    For those of you following the exchange litigation—and if you care about the ACA’s successful implementation, you should be—I participated yesterday in a telephone discussion/debate about Halbig v. Sebelius with Jonathan Adler, one of the lawsuit’s architects. The Federalist Society graciously hosted the phone call and has made it available as a podcast. I encourage you to listen in!

    You can play the audio after the jump:


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  • This is why we can’t get the public to accept changes to screening mammograms

    In 2013, the Swiss Medical Board was asked to review the use of screening mammography. Two of the participants have penned a piece in the NEJM that’s just amazing. Here’s a bit (emphasis mine):

    First, we noticed that the ongoing debate was based on a series of reanalyses of the same, predominantly outdated trials. The first trial started more than 50 years ago in New York City and the last trial in 1991 in the United Kingdom. None of these trials were initiated in the era of modern breast-cancer treatment, which has dramatically improved the prognosis of women with breast cancer. Could the modest benefit of mammography screening in terms of breast-cancer mortality that was shown in trials initiated between 1963 and 1991 still be detected in a trial conducted today?

    Second, we were struck by how nonobvious it was that the benefits of mammography screening outweighed the harms. The relative risk reduction of approximately 20% in breast-cancer mortality associated with mammography that is currently described by most expert panels came at the price of a considerable diagnostic cascade, with repeat mammography, subsequent biopsies, and overdiagnosis of breast cancers — cancers that would never have become clinically apparent. The recently published extended follow-up of the Canadian National Breast Screening Study is likely to provide reliable estimates of the extent of overdiagnosis. After 25 years of follow-up, it found that 106 of 484 screen-detected cancers (21.9%) were overdiagnosed. This means that 106 of the 44,925 healthy women in the screening group were diagnosed with and treated for breast cancer unnecessarily, which resulted in needless surgical interventions, radiotherapy, chemotherapy, or some combination of these therapies. In addition, a Cochrane review of 10 trials involving more than 600,000 women showed there was no evidence suggesting an effect of mammography screening on overall mortality. In the best case, the small reduction in breast-cancer deaths was attenuated by deaths from other causes. In the worst case, the reduction was canceled out by deaths caused by coexisting conditions or by the harms of screening and associated overtreatment. Did the available evidence, taken together, indicate that mammography screening indeed benefits women?

    There’s only so many times you can say the same thing. It does not appear that universal screening reduces mortality. But what’s even more stunning is how much women misunderstand this fact:


    The bottom half of this pic shows the actual effect of mammography. If we take 1000 women age 50 and watch them for 10 years, and don’t screen them, 5 will die of breast cancer, 44 will die of other causes, and 951 will be fine. If we do screen them, then 4 women die of breast cancer, 44 or 45 die of other causes, and 951 or 952 are fine. This is why the effects seem to be negligible.

    But if you ask women to estimate how well mammography works, then you’re in for a whole different ballgame. They think that without screening, of those 1000 women, 160 are going to die from breast cancer in the next 10 years. They way, way, way overestimate the danger. They also overestimate the effectiveness of mammography. They think that it will halve the rate of death, so that only 80 of the 1000 women will die from breast cancer.

    Therein lies the problem. If you think that breast cancer is going to kill 16% of all 50-year-old women in the next 10 years and that mammography makes a huge difference in the mortality rate, then you’re going to demand a universal screening program. Hell, I’d demand it if that were the case. Until we can change the perception of the public to more closely match reality, and make them realize that the harms may outweigh the benefits, we’re going to get nowhere in trying to make changes.


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  • Stand Up! – April 16, 2014

    I am a frequent guest on Stand Up! with Pete Dominick, which airs on Sirius/XM radio, channel 104 from 6-9AM Eastern. It immediately replays on the channel, so those on the West Coast can listen at the same times.

    Today we talked about the CPS and various ACA updates.

    You can play the audio right here, after the jump…


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  • Who should control ACOs, primary care doctors or hospitals?

    The ACA is reducing the number of uninsured. But now we have to face the deeper problem of limiting the growth in health care cost, while improving its quality.

    One of the principal idea for how to do this is the Accountable Care Organization (ACO). ACOs are groups of providers who contract with a payer (for example, Medicaid) to provide the care for a defined population for a capitated rate. The contract holds the providers in the ACO jointly accountable for achieving quality standards. The contract also targets a reduction in the rate of growth of health care costs, and it’s structured so that the ACO keeps a share of the savings if cost growth is under the target. Conversely, the ACO eats some of the excess cost if health care cost growth exceeds the targeted rate. In short, the ACO providers have a collective incentive to bend the cost curve down, while maintaining or improving the quality of care. The jury is still out on whether ACOs do reduce costs and improve quality. (For lots of TIE writing on ACOs, see here.)

    Farzad Mostashari, Darshak Sanghavi, and Mark McClellan raise an important question about ACOs: Who are the providers who should run them? Do we want a hospital-based ACO, or one that is run by a network of primary care providers (PCPs)?

    Many ACOs are founded by hospitals (including the US hospital that I work for). It’s easy to see why. Office-based physicians still largely work in small group practices and they have little experience in the organizational challenges of integrating diverse medical units and services. Starting an ACO requires capital and hospitals either have it already or know how to raise it.

    However, Mostashari and colleagues argue for a PCP-run ACO, because they believe that PCPs have far reaching influence over health care costs. They also think that PCPs have stronger incentives to control costs. Hospitals are likely to be ambivalent about cutting costs, because they may need to keep their beds filled.

    There may be an even more important reason to have PCPs run the ACOs. Americans hated managed care organizations (MCOs) when they tried to reduce costs. Patients perceived, often correctly, that the MCOs were making decisions without due consideration of a patient’s circumstances and against the wishes of her doctor. Moreover, the patient trusted her doctor and not the MCO.

    Compared to the MCOs or a hospital, a PCP-run ACO may do a better job of keeping decision-making about care in the hands of the patient and her team of providers. PCPs are the providers who are supposed to stay with patients, to know them, and to take the lead in managing their care. If the ACO incentives for better and more cost-effective care are designed correctly, the PCPs’ interests will be more closely aligned with the patients’ interests than under fee-for-service medicine. A PCP-run ACO may be the organization best suited to bending the cost curve, while keeping patients’ trust.


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  • How good is Gallup for evaluating the impact of health reform?

    Survey research in health policy is having its moment, assuming abstruse methodology is ever vogue enough to have a “moment”: yesterday’s news about the Census revising its widely-used Current Population Survey sparked one of the nerdier rounds of Obamacare controversy we’ve seen yet. Relevant to this moment is a new paper (gated) from Laura Skopec, Thomas Musco, and Benjamin Sommers.

    Setting aside sentiments about the CPS update, it’s always been the case the researchers will rely on more than one data source to triangulate the impact of the Affordable Care Act. To do that, you need to understand the data sources. Skopec et al focus on the Gallup-Healthways WBI survey, sizing it up against the Current Population Survey, the American Community Survey, the Medical Expenditure Panel Survey, the National Health Interview Survey, and the Behavioral Risk Factor Surveillance System. Gallup puts out periodic reports on the uninsured (among other things), but their data is also available for researchers to purchase.

    One unassailable perk of Gallup’s surveys is turnaround time: national-level data is available for analysis within a week of collection (state-level estimates are only made available twice a year, though). For reference, yesterday’s fracas about CPS revisions centered on data we’ll get in September. Data about calendar year 2013.

    Gallup has a robust sample size of 355,000. That’s not the ACS’s 3 million, but it is higher than CPS (200,000) and the most detailed health surveys (NHIS has a sample of 100,000, MEPS 35,000).

    From 2008 through 2011, Gallup exhibited a lower baseline rate of uninsured than CPS, ACS, and NHIS, but trends over time were relatively consistent. The chart below tracks reported rates of uninsurance among the surveys examined by the authors.


    It’s not all good news, though. One concern the authors cite is “frequent methodological and question changes [that] introduce a level of uncertainty not generally encountered in government surveys.” These changes are more opaque and more egregious than changes to government surveys—for example, Gallup halved their sample size starting in January 2013 to divert more resources to international polling. That kind of change is a huge blow to statistical power and precision.

    This criticism of Gallup isn’t naive to the CPS’s upcoming changes:

    While government surveys also change over time – in particular some government surveys are introducing question changes to better detect the coverage and access effects of the Affordable Care Act – these changes tend to be approached with caution and attention to minimizing breaks in trend. In addition to WBI’s unpredictability, the most concerning methodological limitation of the survey is its response rate of 11%. While this rate is similar to that of other telephone surveys, it is far below those of the government surveys (which range from 50% to 98%).

    The way that Gallup reports income is also likely to frustrate health services researchers: instead of reporting specific dollar amounts (treating income as a continuous variable), Gallup records one of ten discrete income ranges. Painting income in such broad strokes obscures the thresholds built into the ACA, making it incredibly difficult to draw inferences about key topics like Medicaid eligibility and subsidy generosity.

    One of the most troubling aspects of Gallup’s data is their Medicaid estimates: these come in at about half the enrollment in government surveys, a margin of four to five percentage points. It seems likely that some number of Medicaid beneficiaries are mistakenly reporting “other/non-group” coverage; Gallup has an unusually high proportion of respondents in that category. Given that, their data on enrollment in Medicaid and the private market should be used with caution.

    All in all, it’s a mixed bag: There are serious limitations for empirical research, but Gallup data seems adequate for the rough cuts of information that our impatient news cycle seems to demand:

    Gallup-Healthways WBI data seem particularly well-suited for real-time analyses of certain changes in health care trends that do not require distinguishing between different types of insurance coverage, such as whether the ACA had reduced the number of uninsured adults in the U.S., similar impacts of state expansions, and the impact of these changes on access to care.

    Adrianna (@onceuponA)

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  • Sorry, being a doctor is still a great gig

    Monday night, at the Seder we were attending, we all discussed things for which we were thankful. I acknowledged my thanks for my family and friends, and then said that I was very, very grateful to have a job which I found so utterly rewarding and fulfilling. Evidently, Daniela Drake disagrees with me:

    Simply put, being a doctor has become a miserable and humiliating undertaking. Indeed, many doctors feel that America has declared war on physicians—and both physicians and patients are the losers.

    I’m not going to quote her whole piece, but you should feel free to take a minute and go read it. I’ll wait…

    Regardless, she makes some valid points. Physicians are more likely to commit suicide than in many other professions. That is definitely true. But it’s been true for a long time, and her assertion seems to be that the misery of doctors is a recent thing. I don’t think there’s any evidence that suicide is high in the profession because it’s become “miserable”. I’ve discussed this before.

    But most of the piece is a litany of complaints on how “horrible” it is to be a doctor. We don’t get paid enough, so we gravitate to the high-paying specialties. As an academic general pediatrician, I cry BS. She claims physicians want out. I’ve heard that before. I’m still waiting. She declares that fixating on patient satisfaction is wrong. While I agree it’s not the panacea some think it is, it’s hard to argue that having a better patient-doctor relationship is a bad thing. She claims that patient demands are driving doctors to do things they don’t want to do. Evidence says that doctors overestimate that demand.

    For all the talk of a media that “blames” physicians, doctors are among the most respected professionals around.

    I’ve written about this again and again, and I don’t want to repeat myself more than I have to. I think physicians complain far more, and far more publicly, than their situations warrant. For all their complaints, they still do incredibly well financially. They have more professional freedom than most working people. And they’re beloved.

    Moreover, tons and tons of people want to be them. Applications remain at an all time high for medical school.

    These sentiments aren’t new. I’ve been around physicians for all my life, and for the entirety of it, I can remember many of them complaining. I can remember many of them complaining even while they made fortunes, lived fantastic lives, and had fulfilling careers. I remember many of them threatening to quit. None did.

    I imagine that a fairly large number of Americans work just to get a paycheck. They find their jobs to be dull and unfilfilling, should they be lucky enough to have them. Being a doctor is a great gig, and I don’t really know any who would give it up to punch a clock or go do something else. I know some who’d threaten to do so, and some who wish things were better, but the number of them who follow through and abandon the field is near zero. At some point, people are going to ignore the cries of “wolf”. Other than bankers, is there any profession doing so well overall that complains so much in the media?


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  • “We have hardly heard the last of voucherization”

    In the current issue of the Journal of Health Politics, Policy and Law (JHPPL) Jonathan Oberlander reviews the history and literature on Medicare voucher (aka, privatization, premium support, competitive bidding) proposals. He also critiques them, emphasizing ways “voucherization” is misunderstood, replete with limitations and political challenges. Though the voucher movement may be down, it’s not out.

    The substantive case for converting Medicare into a defined contribution system and relying on competition to control spending is thus less compelling than its advocates presume. As Uwe Reinhardt (2011) notes, ‘‘The hypothesis that managed competition among private health plans can better control overall spending per Medicare beneficiary than would traditional Medicare lacks empirical support. . . . That hypothesis remains purely a belief.’’ However, policy disputes are often not settled on the merits, and policy choices are often made on faith. A shift in political alignments or a federal budget bargain could bring premium support or its euphemistic equivalent back to the top of the agenda, opening up another Medicare reform debate. Voucher advocates do not speak of vouchers openly anymore, but we have hardly heard the last of voucherization. [Link added.]

    I agree with both Reinhardt and Oberlander. Competition, such as we have it in various commercial health insurance markets, hasn’t beaten traditional Medicare on cost control. Nevertheless, voucherization plans for Medicare will be back. I’m not so sure they’ve ever left. (See Paul Ryan.)

    Voucherization deserves to be considered and reconsidered, tweaked and reformed, if for no other reason it’s how Medicare Part D and the Affordable Care Act exchanges work. As Oberlander points out (citing me), even Medicare has vouchers today (there exists a choice of subsidized plans), just not ones based on as sound a competitive design as Part D or the ACA’s exchanges.

    Why have we adopted sound competitive designs for some Americans and not others? One answer is that competition has become better understood and accepted over time. Part D and the ACA exchanges are far more recent than the establishment of traditional Medicare or the predecessors to the Medicare Advantage program. Do the competitive designs of more recent programs reflect the rise of the economist?

    As Oberlander points out, many economists are rather fond of and advocate for the market designs of Part D and the ACA exchanges, myself included. There are reasons to prefer them over more administratively set prices, as exists for non-drug Medicare coverage today. The government has a hard time getting prices right or sticking to whatever it previously thought would be right. And there are advantages to some degree of choice (but not too much).

    Markets can do great things, maybe even in health care. But we usually fail to establish good ones. We can do better. And in another excellent paper in the same issue of JHPPLRussell Korobkin points the way. He

    proposes a new paradigm for rationalizing health care expenditures called ‘‘relative value health insurance,’’ a product that would enable consumers to purchase health insurance that covers cost-effective treatments but excludes cost-ineffective treatments.

    Korobkin’s idea is to establish a market in which plans differentiate themselves by the degree to which they cover technology of low or uncertain value. This idea, finally and explicitly, would bring technology management—the principal challenge to long-term health system efficiency— to the fore in a market. To be sure, traditional Medicare or single payer could also manage technology—without a market—but that would require a different arrangement. It could be done (see NICE), but it’s not the direction health policy appears to be heading (again, see Part D and the ACA).*

    I understand why some oppose voucherization. Indeed there are genuinely bad voucher schemes I would oppose. But there are also good ones. A few good examples exist today (not to say they cannot be improved). Building on and extending them in the right ways would be an improvement, in my view. Caveat: Still, engaging in reform is risky, and no health reform is perfect. Your mileage may vary.

    Oberlander’s and Korobkin’s papers are both worth your time. Read them, if you have access.

    * In light of this, I worry far more about implementation of bad voucher plans than about voucherization in general.


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  • ARGH! – Census edition

    From the NYT:

    The Census Bureau, the authoritative source of health insurance data for more than three decades, is changing its annual survey so thoroughly that it will be difficult to measure the effects of President Obama’s health care law in the next report, due this fall, census officials said.

    The changes are intended to improve the accuracy of the survey, being conducted this month in interviews with tens of thousands of households around the country. But the new questions are so different that the findings will not be comparable, the officials said.

    Many, including me, have been using CPS data for a long time to track the numbers of uninsured. Yes, the questions are imperfect. I’ve discussed that, too. This report was from 2005! But the standardization of them made it easier to track changes over time. 

    And NOW is the time to be able to track changes to the uninsured. Is the ACA working? You think we might want to know that?

    Altering the questions right now so that we can’t measure what’s going on is terrible. If they were so bad they needed altering, a few years ago would have been better. Or, a few years from now. But right now? It’s killing me.

    UPDATE : Yes, I know we’ll get data on 2013 with the “new” questions. But it’s actually helpful to have a trend to measure, not a pre-post 2013/2014. This still sucks.


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  • Health spending growth: known knowns and unknowns

    In her Brookings paper on health care spending growth Louise Sheiner’s makes (or suggests) several points that probably receive insufficient emphasis. In fact, one of the last points she implies should probably be the first thing anyone says on the subject, so I’ll make it explicit:

    Short-run analysis can be misleading about long-run spending growth. Or, to be even more clear, be very skeptical about predictions of health spending growth a few decades from now based on experience over the last decade alone. As has been found in long-term studies in the past, in the long run, it’s probably “the combination of technological innovation and a continued willingness-to-pay for that technology,” as Sheiner wrote, that will determine how much we spend on health care and how quickly.

    Still, much has been made about recent, short-run health spending trends. Earlier today, Tom Liu explored them, with an emphasis on the degree to which the ACA can be credited with the recent slowdown or blamed for the even more recent pickup in spending. More analysis can be found by Cutler and Sahni, Holahan and McMorrow, Levitt and colleagues, and Chandra, Holmes, and Skinner, among many others.

    To varying degrees, some of these studies emphasize the role of “the economy” (GDP), and Sheiner does as well. The Great Recession, which began at the end of 2008, looms large and surely had some effect on health spending. But wait, didn’t Tom write that the most recent slowdown in health spending began in 2003, predating the Great Recession by five years? Indeed he did, and he’s right!

    However, as large as the Great Recession looms, it was not the only recession (duh). There was also one in 2001. Could that have played a roll?

    That brings me to my second point: recessions matter, a lot. As Sheiner and others have shown, macroencomic effects are associated with health care spending with a lag on the order of five or six years. Some of the slowdown in the early-to-mid aughts can be associated with the 2001 recession. Likewise, some of the slowdown in the late aughts through the early part of this decade can be associated with the Great Recession. As the following chart from Sheiner shows, a model of health spending growth per capita based on five years of lagged GDP per capita predicts actual growth quite well, though certainly not perfectly (red line vs. blue line). Other work has demonstrated a tight connection between per capita GDP and health spending.

    health spending growth-sheiner

    For all that, there’s plenty of room for additional considerations, commentary, speculation, and shoulder shrugging: You’ll notice that actual health spending growth (blue line) is below the fitted (red line) in recent years. That opens up the possibility that some other factors are playing a roll. (It could be noise too. The fitted line can’t match the actual in every year.)

    Also, relating health spending growth to GDP doesn’t illuminate the mechanism(s), which can change over time. As the economy tanks, do health systems invest less? Does cost sharing go up? What’s the roll of prices vs. utilization, and how might those vary by payer (recognizing that Medicare and Medicaid control prices more tightly than private payers)? Even if one can answer all those questions, there’s no guarantee that the mechanisms at play over the last decade will be the same ones that dominate going forward.

    In the long-run, understanding the GDP-health spending connection isn’t as helpful as we’d like. Even long-run GDP projections are uncertain. Also, even if GDP (and lags thereof) predict a lot of health spending growth variation, small, systematic errors (that which they don’t predict) could compound into big ones over many years.

    In conclusion, in large part we don’t know precisely how the cost curve will bend, if at all. The evidence clearly shows we could bend it with a bad economy. Few would recommend that course.


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