Here is a new post I’ve got up at the Health Care Cost Monitor, in which I try to convince folks that even Republicans should be in favor of federalizing Medicaid. I’d love your feedback, as I’m still developing this idea.
Not looking my best…but here is a blog post I wrote for the Hastings Center, in which I try to get to the root, so to speak, of an often overlooked issue: cutting dental coverage when trying to lower the cost of health care.
Here is a link to a Marketplace report that discusses the Obama administration’s efforts to keep states from trimming their Medicaid budgets by cutting doctor payments, to the point where patients have insurance but no doctors would be willing to care for them. I am quoted early on, the first broadcast in which I have been able to spout the phrase “dirty, naughty.”
Here is a blog post I wrote for the Hastings Center, laying out some hopeful thoughts about how we can use Medicaid crises, which are occurring in so many states right now, to figure out how to control health care costs.
Here is a link to an Op-Ed I wrote with two colleagues at Duke, in which we provide a novel explanation for why so many Americans hate Obamacare.
Check out my recent webcast interview with Duke University “Office Hours”:
George Loewenstein and I have an Op-Ed in the New York Times today. Check it out, and feel free to add your comments.
Is a test that costs $800,000 to add one year of life worthwhile? In one survey, most physicians said yes-evidence that controlling costs will require overcoming very powerful, and irrational, psychological forces.
Imagine for a moment that you are in charge of the U.S. health care system, and must decide whether to pay for a new cervical cancer screening test, let’s call it PapFinder. For every $800,000 spent on PapFinder, health care providers will add one year of life to the population of women receiving this test. Given this information, would you choose to add PapFinder to the standard diagnostic arsenal?
About a decade ago, I presented a national sample of U.S. physicians with a question like this, and almost of them stated that PapFinder (a hypothetical test, by the way) was too expensive, bringing benefits so rarely that they would not offer this test to their own patients. The desire to prevent and treat cancer, it seems, had limits.
Or did it? I presented a random sample of these physicians with a different choice. I asked them whether they would offer annual pap smears (well-established tests in routine clinical use) if they learned that the tests cost more than $800,000 to save one year of life – a figure that came directly from the medical literature. Given this information, physicians were nearly unanimous in saying they would offer their patients this test.
Same cost, same infrequent benefit, but very different attitudes. What’s going on here? And what do the results of this decade-old study tell us about the recent hubbub around mammography screening and, indeed, about the ongoing health care reform debates?
For starters, health care economists are nearly unanimous in holding that interventions that cost more than $800,000 per life year are not a wise use of resources. (Most endorse cost-effectiveness thresholds closer to $100,000.) That means that doctors’ attitudes toward PapFinder appeared quite rational: lots of money, little benefit … not a smart idea.
Why, then, did doctors remain enthusiastic about pap smears even after learning about the $800,000 figure? As a physician working in behavioral economics, I am quite familiar with the irrational forces influencing people’s attitudes towards health care interventions. In this case, a lot of such forces were at work.
For starters, physicians were influenced by loss aversion. People don’t like having things taken away from them. Doctors were used to providing annual pap smears to their patients, and they knew that their patients would be upset if they no longer offered such tests. We see parallels in current mammography debates, with many women in their 40s responding anxiously to the idea of no longer receiving annual mammograms.
Second was the belief that earlier detection of cancers is always better than later detection, a belief that has also influenced the mammography controversy. This idea is not supported in the medical literature.
In fact, medical science has discovered that some early cancers pose little threat to people’s lives, with the cancers growing so slowly that any intervention to thwart them would cause more harm than benefit. We’ve even learned that some cancers can regress over time. But these cold hard medical facts stand little chance against the hot passions of cancer psychology: doctors and lay people, understandably frightened by the thought of cancer, cannot believe that early detection could be anything but good.
Third was the limited human attention span. When we contemplate important decisions, it is difficult to consider all of the relevant factors, and thus we focus our attention on the most obvious ones. Deciding whether to live in Michigan or California, for instance, we think about the weather while ignoring other important differences between these two states – differences in daily commuting, for example, a factor that has been shown to have far more impact on people’s lives than climate.
Similarly, when people make decisions about cancer screening, they focus most of their attention on cancer – if the test detects cancer, they conclude it must therefore be worthwhile. People don’t pay as much attention to other aspects of the test. If it mistakenly characterizes a benign lesion as cancer, for example, it will cause undue anxiety or even lead to unnecessarily and potentially harmful treatments. But we don’t give such factors much weight when contemplating whether to utilize the tests.
Everyone who cares about this country should care about finding ways to reduce health care costs. The recent debates over mammograms reveal just how difficult it will be to achieve this goal, for controlling costs will require us to overcome very powerful psychological forces. The biggest impediment to successful reform of our health care system, thus, is not blue dog democrats or obstinate republicans. It is human nature.
To read the original post in the Hastings Center’s Health Care Cost Monitor, click HERE.
No sooner had the Obama administration committed a billion dollars to comparative effectiveness research than the critics began laying out their concerns: such research is a prelude to rationing, they said; it threatens to thwart doctors’ and patients’ abilities to make their own decisions. It will transfer too much power to government bureaucrats and treat medical practice like a cookbook.
Now that the Institute of Medicine has issued its priorities for comparative effectiveness research (CER), I will look at a common criticism: that it acts as if medical care is a “one size fits all” enterprise, and thereby forces policy makers to make blunt decisions that will unjustifiably harm people who don’t respond to medical interventions the way an “average” person would respond. This concern is legitimate, but an intelligent use of CER should allow us to avoid this fate.
If your life, like mine, has been touched by breast cancer, then you probably share my hope that researchers will find new treatments to reduce the harms of this awful illness. But if you also share my concern for the fiscal solvency of our nation, you might also be disturbed at the high price of some new cancer treatments.
Consider a drug like Avastin: a treatment that increases life expectancy of patients with some metastatic cancers by interrupting blood flow to the tumors. Avastin can cost more than $100,000 per patient, and in some cancers leads to an increase of only two months in median survival. Two months for $100,000—a steep price to pay.
With medical costs consuming an increasing portion of government budgets, and with U.S. businesses struggling to offer employees healthcare coverage, many experts contend that we cannot afford treatments that bring such modest benefits at such a startling price.
How might comparative effectiveness research inform such issues? CER strives to provide information to guide decision making. A comparative effectiveness study might evaluate the cost effectiveness of competing breast cancer treatments. Or it might not analyze cost at all, and focus instead on estimating the relative impact that alternative treatments have on people’s quality and quantity of life.
In neither of these cases would CER, on its own, show us whether to use these treatments. Like its name suggests, CER promises to provide decision makers with information on the relative effectiveness of common medical interventions, so that government payers, insurance companies, doctors and, yes, patients can spend their health care dollars more wisely.
To understand the “one size doesn’t fit all” criticism, let’s suppose that a new drug increases median survival in patients with metastatic breast cancer by two months. That doesn’t mean that it increases everyone’s survival by two months. It might have no effect on the majority of patients, harm a small minority, and bring huge benefits to another minority.
CER, by lumping all patients into one group, would ignore these important differences. And if policymakers, unimpressed by this two-month figure, decided not to pay for this drug, some patients will lose a chance at these huge benefits.
This criticism of CER, however, overlooks more nuanced ways decision makers can potentially use CER information. With the right data, CER can improve medical decision-making by splitting patients into relevant groups, rather than lumping them into a single group.
For example, if we know in advance that patients who meet certain criteria stand to gain much more than other patients, then CER is a tool to help identify this subgroup. A treatment that costs $600,000/life year across all patients may be much more cost effective in a specific subgroup of patients.
A treatment that brings no benefit to the majority of patients but a substantial benefit to a minority of patients could very well deserve to play an important role in the treatment of that subgroup of patients. CER can potentially identify such subgroups. Indeed, if our country starts emphasizing comparative effectiveness in making treatment coverage decisions, it will give researchers in academia and in industry an incentive to find out which patients stand to benefit the most from various healthcare interventions.
On the other hand, if we do not know in advance who will benefit from a specific treatment and who will be harmed – if we can’t, for instance, figure out who will gain years rather than months of survival from the drug – then the only rational way to decide whether to use such a treatment is to assume that each patient is roughly the same and has the same chance of benefit and harm as all other patients.
If only 5 percent of patients benefit from a certain treatment, and we don’t know who those patients are upfront, then we have to assume that any given patient receiving that treatment stands a 5 percent chance of benefiting. And then we have to decide, as a society, whether that 5 percent chance of benefit is worth the costs – both medical and financial – of that treatment.
It would be unwise to use CER to lump together the unlumpable: the long-term survivors from those destined to die soon regardless of treatment. But rather than dismiss CER for treating everyone as if they are average, we should fund the kind of research that will identify who stands to benefit the most from the health care available to them.
View the original post at The Hastings Center.
American presidents have been trying to reform our health care system since at least the Nixon era, but with only limited success. Past reform efforts have failed for many reasons. For starters, the U.S. health care system is complex, with the medical industry making up almost 1/6 of our economy. But perhaps the biggest obstacle to reform is a psychological one: thoughts of health-care reform too often trigger images of putting for bogey instead of putting for par.
I am referring to the psychological power of loss aversion, a phenomenon that behavioral economists have been studying for several decades now. Most of us, you see, seek to avoid losses with greater fervor than we seek to achieve equal gains. If given a 50-50 chance of either winning or losing $100, we decline. The $100 loss looms larger than the $100 gain. For similar reasons, most people express greater interest in surgical procedures that carry 90% survival rates than in ones that carry 10% mortality rates, even though these procedures are identical. Thinking about mortality triggers loss aversion. This week we even learned that loss aversion influences putting behavior among professional golfers. When putting to avoid a bogey, golfers are more aggressive than when putting for birdie, and consequently are more likely to make their putts. Few things are more motivating than the desire to avoid losses.
Which brings us back to health care reform. When President Clinton attempted an overhaul of our health care system in the 90′s, his administration correctly recognized the need to control health care costs. Without cost containment, they knew it would be impossible to expand health care insurance to the millions of people who lacked such coverage. So the Clinton administration looked for ways to increase the number of Americans enrolled in managed care plans, which at that time had achieved some success in controlling health care expenditures.
The problem with the Clinton approach was that it made Americans feel like they were losing their traditional health care. Managed care was infamous for saying no — for denying people health care services and for limiting their choice of doctors. By taking things away from people, managed care triggered loss aversion. Consequently, the American public never supported Clinton’s reform efforts.
The Obama administration is steeped with people knowledgeable about behavioral economics, who hope to keep the public from slipping into a state of loss aversion. Not surprisingly, then, the administration has enthusiastically embraced research out of Dartmouth University, demonstrating huge regional variations in medical expenditures that have not been accompanied by any variation in health care quality. According to this research, some cities in the US spend twice as much per capita on health care as other cities without experiencing any discernible improvement in health.
Obama’s people hope that Americans will perceive health care reform as a win-win opportunity, with lower health care costs through the elimination of waste and inefficiency, accompanied by more stable and secure health care coverage. But even if the administration succeeds in assuaging the fears of the general public, they face a much stiffer challenge with the health care industry. Any success they have in controlling health care costs will, after all, create losers. If we spend less money on health care in the US, then someone in the health care industry is going to take a financial hit. One person’s waste is another person’s income.
No surprise, then, that both the insurance industry and the AMA have begun pushing back against elements of the Obama plan. These groups stand to lose money under health care reform. Hospitals are likely to lose money too, as are drug companies, medical device companies, and other powerful parts of our vast health care industry. All of these groups will be motivated to fight health care reform.
The Obama administration has made a point of distinguishing its behavioral approach to economics from the more traditional approach embraced by the Bush administration. Ironically, though, it is the Bush administration that understood how to pass health care reform without triggering loss aversion. When George W. Bush decided to push for a Medicare drug plan, he recognized that the pharmaceutical industry would wield its powerful lobbying strength against his efforts if they feared a loss of income. So he crafted a plan that benefited the drug industry. Politicians on the left criticized these concessions to industry, but it is hard to imagine the drug plan passing without such concessions.
Obama should draw a lesson from his predecessor. If he causes the health care industry to perceive his health plan as a threat to their incomes, his plan will face stiff resistance. For health care reform to succeed, people in the health care industry need to keep making exorbitant sums of money for awhile. Over time, the government can gradually ratchet down health care costs. But initially, Obama needs to reduce the number of people who perceive health care reform as a loss.
The cost will be steep. But the alternative will be more costly. We cannot afford to make reform feel like a health care bogey.
Peter Ubel is author of Free Market Madness: Why Human Nature Is at Odds with Economics — and Why It Matters (Harvard Business Press, 2009), and Director of the Center for Behavioral and Decision Sciences in Medicine at the University of Michigan.
View original post and comments at Huffington Post