• Where’s the best, deep health policy wonk blogging these days?

    There’s not a lot of old-school health policy blogging going on these days. But there’s not none!

    Over lunch, I was asked where (other than TIE) I turn for the best and deepest health policy wonk blogging. The answer came to me immediately, but my questioner had never heard of the blog or individual I spoke of. That should change!

    So, if you’re not reading David Anderson’s (frequent!) posts at Balloon Juice, you’re missing something good. My only regret is that he’s not writing on TIE. Sad.

    An RSS feed for David’s posts is here. He tweets via @bjdickmayhew. No his name is not really Richard Mayhew.


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  • AcademyHealth: Narrow networks can be a real problem for kids

    Narrow networks are a real concern in the ACA marketplaces, but much more for kids than many think. Go read why in my latest post over at the AcademyHealth blog!


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  • “Everyone seems to agree: Drug prices are too damn high.”

    So begins a post from Rachel Sachs, Darius Lakdawalla, and me at the Health Affairs Blog on the complicated interplay between value-based pricing and Medicaid’s best-price rule.

    What is the best-price rule? Does it really impede the adoption of value-based pricing? If so, what can be done about it?

    To keep federal spending in check, state Medicaid programs never pay full price for a drug. By statute, they receive rebates worth about one-quarter of a drug’s average manufacturer price. But if a manufacturer chooses to sell the drug to someone else for less than the rebated amount, Medicaid will only pay that “best price.” It’s a guarantee that Medicaid can buy the drug at the cheapest price that the manufacturer can afford to sell it.

    Now consider outcome-based pricing, in which manufacturers get paid less when their drugs perform poorly. A manufacturer, for example, might agree to pay a $75 rebate on a $100 drug that fails to work for a particular patient. If it did, however, $25 would now be the drug’s “best price.” Every Medicaid program would be legally entitled to that price, decimating the manufacturer’s revenue from Medicaid.

    That’s why the pharmaceutical industry complains that the best-price rule impedes outcome-based pricing. Its objection is accurate so far as it goes, but it ignores a technique that drug companies and insurers could use to contract around the best-price rule. Instead of granting a rebate if a drug fails to work for a particular patient, manufacturers can offer a rebate based on the performance of the drug across a patient population. To return to the earlier example, a drug manufacturer might sell a drug for $100 but offer a $75 rebate per patient for whom the drug doesn’t work, based on the drug’s performance across 1,000 patients. If the drug is 75 percent effective, the average price for the drugs sold to the 1,000 patients would be north of $80, high enough not to trigger the best-price rule. Indeed, the fact that drug companies have begun to enter into some of these contracts suggests that companies may already be doing some weighted average pricing.

    Even so, tremendous uncertainty remains. In a rule, the Centers for Medicare and Medicaid Services (CMS) has said that best price must be determined on a “unit basis.” Depending on what CMS understands the term to mean, the unit-basis rule may thwart efforts to contract around the best-price rule. At the same time, however, CMS has the authority to change its rule. The statute itself does not contain any unit-basis requirement, meaning that it could be amended to encourage outcome-based pricing arrangements.

    There’s more at the post, which builds off a paper, a draft of which is available here, that Rachel, Darius, and I will be publishing at the Journal of Health Politics, Policy and Law. Comments on the draft are welcome!


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  • Spend a dollar on drug treatment, and save more on crime reduction

    The following originally appeared on The Upshot (copyright 2017, The New York Times Company). It also appeared on page A15 of the April 25, 2017 print edition.

    The burden of substance abuse disorders can fall heavily on the families and friends of those who battle addictions. But society also pays a great deal through increased crime. Treatment programs can reduce those costs.

    For at least two decades, we’ve known substance use and crime go hand in hand. More than half of violent offenders and one-third of property offenders say they committed crimes while under the influence of alcohol or drugs.

    Researchers with the Centers for Disease Control and Prevention recently estimated that prescription opioid abuse, dependence and overdoses cost the public sector $23 billion a year, with a third of that attributable to crime. An additional $55 billion per year reflects private-sector costs attributable to productivity losses and health care expenses.

    About 80,000 Americans are incarcerated for opioid-related crimes alone. The total annual economic burden of all substance use disorders — not just those involving opioids — is in the hundreds of billions of dollars.

    In an editorial accompanying the C.D.C. researchers’ study, Harold Pollack, co-director of the University of Chicago Crime Lab, wrote that opioid-associated crime, like all crime, extracts an even larger toll when you consider its impact on families and communities.

    “The most important reason to support treatment is to improve the well-being and social function of people with addiction disorders,” Mr. Pollack said. But there are other social benefits. When the criminally active get help for this, “the economic value of crime reduction largely or totally offsets the costs of treatment,” he added.

    Relative to the costs of crime alone, treatment for substance use disorders is a good deal. Even though a typical burglary may result in a few thousand dollars of tangible losses, researchers have estimated that people are willing to pay 10 times that amount to avoid that loss and 100 times more to avoid armed robbery. This reflects the fact that crime exacts a large psychological toll — the threat or climate of it is far more costly than the crimes themselves.

    The most cost-effective treatment for opioid use disorders includes counseling along with a craving-relieving prescription drug, like methadone or buprenorphine, sometimes combined with other medications. According to an economic analysis by the New England Comparative Effectiveness Public Advisory Council, this kind of treatment actually saves society money. For instance, New England states could save $1.3 billion by expanding treatment of opioid-dependent persons by 25 percent.

    Though the war on drugs has not had a tangible impact on crime, treatment for substance use disorders has. A study by Emory University scholars found that a 10 percent increase in the treatment rate reduces the robbery and larceny theft rates by about 3 percent and the aggravated assault rate by 4 to 9 percent.

    For a dollar spent on treatment, up to three are saved in crime reduction. An earlier study found that interventions to address substance use disorders save more in reduced crime than they save in reduced health care spending.

    Several systematic reviews and meta-analyses of therapies for opioid addiction found that methadone therapy reduced criminal activities related to heroin use. One analysis of more than 8,000 heroin users found that their offending rates were lower while on methadone therapy than when not on it.

    For every 100 patients on methadone per year, there were 12 fewer robberies, 57 fewer break-and-enters and 56 fewer auto thefts. Another systematic review found that provision of heroin by doctors to patients addicted to it — permitted in Canada and some other countries — reduces crime.

    Findings such as these justify drug courts, which divert drug offenders from the traditional criminal justice system into treatment. But what about helping those with substance use disorders obtain treatment before they commit crimes and land in court? Given the crime-deterring value of treatment (among its other benefits), you’d think we’d make it easy for patients to get.

    We don’t. The need for treatment far exceeds its supply. Many treatment programs have waiting lists, and the vast majority of those with substance use or dependency problems go untreated.

    Stigma plays a role, which is why addiction treatment works best when it is integrated with and supported alongside ordinary medical care. A pervasive not-in-my-backyard attitude challenges the establishment of more programs. A recent study by economists from Texas A&M and Montana State Universities suggests this is shortsighted.

    The researchers found that the opening of an additional treatment facility in a county is associated with lower drug-related mortality in that county, as well as lower crime. The effect of crime reduction alone would save an estimated $4.2 million per facility per year, or almost four times its cost.

    “Addiction treatment may be the one area of health policy right now in which Democrats and Republicans want to work together to meet an important public health challenge,” Mr. Pollack said. “The economic and crime-reduction benefit of these services certainly provide good reason for this.”


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  • Healthcare Triage: Gaming the System – Orphan Drugs Part 3

    Even if the Orphan Drug Act were working properly, its enormous costs might outweigh its exiguous benefits. But it’s not working properly. Drug manufacturers are gaming the Act in at least three important ways. They’re the topic of this week’s Healthcare Triage.

    Sources can be found in the posts Nick has written on the subject! Special thanks to him!


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  • Healthcare Triage News: Exercise, Weight Loss, and Big Soda

    Exercise isn’t the key to weight loss. Still. But food companies want to convince you otherwise. This is Healthcare Triage News.

    Go read more about this here.


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  • They did not prove that diet soda causes Alzheimer’s Disease. THEY DID NOT!

    I know what the headlines say.

    Congratulations, media! You succeeded. You even managed to panic my wife. Here’s the abstract (highlighting mine):

    Background and Purpose—Sugar- and artificially-sweetened beverage intake have been linked to cardiometabolic risk factors, which increase the risk of cerebrovascular disease and dementia. We examined whether sugar- or artificially sweetened beverage consumption was associated with the prospective risks of incident stroke or dementia in the community-based Framingham Heart Study Offspring cohort.

    Methods—We studied 2888 participants aged >45 years for incident stroke (mean age 62 [SD, 9] years; 45% men) and 1484 participants aged >60 years for incident dementia (mean age 69 [SD, 6] years; 46% men). Beverage intake was quantified using a food-frequency questionnaire at cohort examinations 5 (1991–1995), 6 (1995–1998), and 7 (1998–2001). We quantified recent consumption at examination 7 and cumulative consumption by averaging across examinations. Surveillance for incident events commenced at examination 7 and continued for 10 years. We observed 97 cases of incident stroke (82 ischemic) and 81 cases of incident dementia (63 consistent with Alzheimer’s disease).

    This study used the Framingham Heart Study Offspring cohort, which began in 1971. The 10-year incidence of stroke and dementia began in 1998-2001. They excluded people with significant disease before the start of the monitoring period.

    Did the participants differ by race or ethnicity? I have no idea. I do know, however, that the authors write about the “absence of ethnic minorities, which limits the generalizability of our findings to populations of non-European decent.” Was that in the coverage you read?

    Did they differ by socioeconomic status? No idea. Did they abuse drugs? Work or retire? Live alone or with someone? Have a family history of disease? No idea.

    Did they acknowledge that different artificial sweeteners are different molecules with likely different effects or implications? No.

    Were there multiple comparisons, meaning some results might be due to chance? Yep. Did they rely on self-report, which might mean recall bias comes into play? Yep.

    Was this an observational study? Of course.

    Was all of that in the coverage you read?

    The study reported the hazard ratios for the Model 2 (which adjusted for demographics, diet, physical activity, and smoking, but still missed a lot, noted above). There was a Model 3, which also accounted for various cardiometabolic factors, but the results weren’t as dramatic. Anyway, in Model 2, compared to drinking no diet soda at all, those who drank at least one a day had HR 2.96 for ischemic stroke and HR 2.89 Alzheimer’s dementia.

    Reported in the small text under table 2 is that in Model 2, for this result, there were a total of 58 ischemic strokes in 2137 participants. So… it was rare. For Model 2, there were 47 diagnoses of Alzheimer’s Disease for 1087 participants. Again, pretty rare. (And that is if I’m reading it correctly. It says N/events, and I think they may have meant events/N).

    I have pored through the paper and the data supplement, and I can’t find the actual rates of disease reported for each group. I don’t know how they differed.

    This type of study, and any discussion of its meaning, would be full of caveats.

    It’s an observational study, and it cannot show causation. It’s a well-known and limited dataset, which almost entirely lacks minority participation. They could control for some things, but many other (and important) factors couldn’t be accounted for. There were multiple measurements, and the analysis did not adjust for them. There are other studies which show different findings. The overall rates of dementia and stroke were low in this study, and therefore the scary relative differences aren’t likely as scary in terms of absolute differences. Those absolute rates weren’t clearly reported. There’s also no evidence that changing your behavior with respect to drinking diet soda will change any of these outcomes at all.

    Was that in the coverage you read?


    P.S. If you do go look at the paper, make sure to note the y-axis labeling in Figure 2. Hint: It doesn’t go from 0-100.

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  • For Malpractice Reform, Focus on Medicine First (Not Law)

    The following originally appeared on The Upshot (copyright 2017, The New York Times Company).

    Congressional Republicans have recently revived efforts to overhaul malpractice laws, including capping certain kinds of suits at $250,000. A perennial argument of supporters of such measures is that many claims are frivolous, clogging the court system and driving up health care costs for everyone. But does the evidence support this?

    You don’t have to look too hard to find backing for the notion that some malpractice claims lack merit. A 2006 New England Journal of Medicine study reviewed a random sample of 1,452 claims from five malpractice insurers. Its authors found that 37 percent of these cases involved no errors, and 3 percent involved no verifiable injuries.

    It’s also undeniable that defending against malpractice suits gets costly. Other research shows that providers and hospitals spent $81,000 to $107,000 (in 2008 dollars) to defend cases that went to verdict, on average. Even defending claims that were dropped, withdrawn or dismissed cost $15,000 per claim.

    But it is not so clear that the best way to solve malpractice lawsuits is through changes focused on the legal system rather than the medical one.

    The same 2006 N.E.J.M. study also found that, in many ways, the malpractice system works reasonably well. Most claims without errors or injuries didn’t result in payments, and most claims with errors did.

    A study published last month in the American Journal of Health Economics explored the link between malpractice suits and metrics known as Patient Safety Indicators (P.S.I.). These indicators, developed and released by the Agency for Healthcare Research and Quality in 2003, are intended to quantify harmful events in the health care system. These events are thought to be preventable by changes at the level of the physician, the hospital or the system itself.

    The study’s researchers combined a number of data sets from Florida and Texas to see how the rates of 17 indicators were related to malpractice claims for hospitals. Their hypothesis was straightforward: Patient Safety Indicators are a reasonable measure of safety; poor safety makes medical errors more likely; and medical errors lead to malpractice claims.

    It turns out that hospitals differed quite broadly in P.S.I. rates. In Florida, among the larger hospitals, adverse events ranged from 55 to 390 per 10,000 discharges. The researchers also found a strong correlation between P.S.I. rates and the rates of malpractice claims.

    Bernard Black, one of the authors of the study and a professor at Northwestern’s school of law, said that even small changes in patient safety helped a lot: “Moving a hospital from roughly the 33rd percentile (worse than two-thirds of other hospitals) to the 67th percentile (better than two-thirds of other hospitals) reduces the rate of lawsuits by 16 percent. This level of improvement should be achievable.”

    This research is not the last word on this subject, of course. Patient Safety Indicators, while widely accepted as measures of safety and quality, are imperfect. This study includes only two states, with hospital-level data available only in Florida. The study wasn’t a randomized controlled trial, and causality isn’t assured.

    Causation is likely, though, because reverse causality doesn’t make much sense — it’s hard to see how higher malpractice rates would lead hospitals to pay less attention to safety.

    The study points to a significant link between measures of quality and safety and malpractice claims, suggesting that taking steps to improve patient safety should reduce the risk of lawsuits. Such measures would also probably improve outcomes for patients — a good in itself.

    Too often, efforts to fight undeniable problems in the malpractice system start from the assumption that there are too many cases, that they’re not “real,” and that we need to come up with solutions to limit them. But what the data suggest is that improving medical practices may be a more effective approach than passing new laws.


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  • AcademyHealth: Medicare Advantage risk selection

    One of the concerns about Medicare Advantage (MA) is that it doesn’t serve sick beneficiaries well, motivating some of them to switch to traditional Medicare (TM). My final blog post for AcademyHealth explores this topic.



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  • Oglala Lakota County, SD

    Here is a map of male life expectancy at birth by US county. Your eye is drawn to the striking red patch on the border of South Dakota and Nebraska. It has a history.

    Life expectancy at birth by country, Institute of Health Metrics and Evaluation, University of Washington.

    That’s Oglala Lakota County, which falls entirely within the Pine Ridge Reservation of the Oglala Lakota nation. This is the poorest county in America, with $8,768 per capita income. Male infants there have a life expectancy of 65.2 years, compared to 76.5 for the US as a whole. This is less than the (male and female) life expectancy in Laos and Yemen. Oglala Lakota County experienced 1945 deaths per 100,000 population in 2013 (compared to 927 / 100,000 for the US as a whole).

    The people of Oglala Lakota County are, clearly, exposed to severely adverse social determinants of health. But this epidemiological language is too impersonal: the social determinants include a history of oppression and murder. The Wounded Knee Massacre of Lakotas by the US 7th Cavalry occurred here in 1890.

    Frozen bodies in a mass grave at Wounded Knee. Photograph from 1891.

    Many communities have terrible histories. Oglala Lakota County is only the second worst country in the US for male life expectancy. The worst (3142 out of 3142) is McDowell County, West Virginia, where male infants are expected to live only 63.9 years. This is slightly worse than the life expectancy at birth in the Sudan. McDowell County was once a leading coal-producing county, but the industry has since collapsed. In 2015, the county had the highest rate of opioid deaths in the US (141 deaths per 100,000 people, roughly 10 times the rate for the US as a whole).

    In light of the 2016 election, there have been many scholarly and popular accounts of the health crises of rural US whites. These concerns are entirely appropriate. But we need to register the health needs of all communities, not just the ones that swing elections.


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