It’s time for some fun reading for the long weekend:
- Good news.
- Obamacare’s smoker penalty.
- Hospital Strike.
- Mourning the end of catastrophic-only plans?
- Bag of Shite.
Brad Wright has posted the latest edition of the Health Wonk Review at Wright on Health, which he describes as “a bit tongue-in-cheek, as I offer some interesting definitions of well-known words and make light of some of the more despair-inducing aspects of the world of health policy. Buckle up, because it’s going to be a bumpy ride!” Check it out.
Health care spending growth is slowing, and not just due to the recent recession. A paper by Ryu, Gibson, McKellar and Chernew in Health Affairs finds the following.
During and immediately after the recent recession, national health expenditures grew exceptionally slowly. During 2009–11 per capita national health spending grew about 3 percent annually, compared to an average of 5.9 percent annually during the previous ten years. Policy experts disagree about whether the slower health spending growth was temporary or represented a long-term shift. This study examined two factors that might account for the slowdown: job loss and benefit changes that shifted more costs to insured people. Based on an examination of data covering more than ten million enrollees with health care coverage from large firms in 2007–11, we found that these enrollees’ out-of-pocket costs increased as the benefit design of their employer-provided coverage became less generous in this period. We conclude that such benefit design changes accounted for about one-fifth of the observed decrease in the rate of growth. However, we also observed a slowdown in spending growth even when we held benefit generosity constant, which suggests that other factors, such as a reduction in the rate of introduction of new technology, were also at work. Our findings suggest cautious optimism that the slowdown in the growth of health spending may persist—a change that, if borne out, could have a major impact on US health spending projections and fiscal challenges facing the country.
Cutler and Sahni note that if this trend continues, US healthcare spending projections may be off by as much as $770 billion.
In order for Medicare to reimburse post-acute care in a skilled nursing facility (SNF), Medicare beneficiaries must have a 3-day hospital stay. Some hospital stays, however, are not counted as hospital stays; rather, they may be defined as “observation status” care that do not merit an inpatient admission. Patients may stay overnight at the hospital and receive similar care as if they were admitted, but hospitals may still classify the patient as under “observation status”. A New York Times article cites a paper by Feng, Wright and Mor that state that “…elderly hospital patients are increasingly likely to be held for observation and less likely to be admitted. Often kept in the hospital for 48 hours or even longer and treated as though they were inpatients, they don’t realize that they’re not.”
Recently, however, Senator Charles Schumer has proposed legislation that would address this issue. Schumer proposed a new U.S. Senate bill would change a Medicare provision preventing many seniors from getting coverage for skilled nursing therapy after hospital “observation stays.” Specifically, observation stays will be counted toward the 3-day mandatory inpatient stay for Medicare coverage of skilled nursing facility services after a hospital visit. The bill is called the Improving Access to Medicare Coverage Act of 2013 and is co-sponsorred by Sen. Sherrod Brown.
What is Mahalanobis distance?
Most people know what Euclidean distance is…it is the shortest distance between any two points. In other words, its what we typically think of when we think of distance – the distance we would measure with a ruler, and the one given by the Pythagorean formula.
Unlike Euclidean distance, Mahalanobis distance gauges the similarity of an unknown sample set to a known one. It differs from Euclidean distance in that it takes into account the correlations of the data set and is scale-invariant. In other words, it is a multivariate effect size.
Wikipedia defines Mahalanobis distance using the following intuition.
Consider the problem of estimating the probability that a test point in N-dimensional Euclidean space belongs to a set, where we are given sample points that definitely belong to that set. Our first step would be to find the average or center of mass of the sample points. Intuitively, the closer the point in question is to this center of mass, the more likely it is to belong to the set.
However, we also need to know if the set is spread out over a large range or a small range, so that we can decide whether a given distance from the center is noteworthy or not. The simplistic approach is to estimate the standard deviation of the distances of the sample points from the center of mass. If the distance between the test point and the center of mass is less than one standard deviation, then we might conclude that it is highly probable that the test point belongs to the set. The further away it is, the more likely that the test point should not be classified as belonging to the set.
This intuitive approach can be made quantitative by defining the normalized distance between the test point and the set to be . By plugging this into the normal distribution we can derive the probability of the test point belonging to the set.
The drawback of the above approach was that we assumed that the sample points are distributed about the center of mass in a spherical manner. Were the distribution to be decidedly non-spherical, for instance ellipsoidal, then we would expect the probability of the test point belonging to the set to depend not only on the distance from the center of mass, but also on the direction. In those directions where the ellipsoid has a short axis the test point must be closer, while in those where the axis is long the test point can be further away from the center.
Putting this on a mathematical basis, the ellipsoid that best represents the set’s probability distribution can be estimated by building the covariance matrix of the samples. The Mahalanobis distance is simply the distance of the test point from the center of mass divided by the width of the ellipsoid in the direction of the test point.
How does one calculate the Mahalanobis distance in practice? The Healthcare Economist has a simple example for you to examine here.
As the 18th Annual International Society for Pharmacoecomoics and Outcomes Research (ISPOR) begins this past weekend, today the Healthcare Economist examines drug prices around the world. Drug prices in the U.S. are much higher than any other developed country. This finding is robust whether the price index is created using the U.S. drug consumption basket or each countries own basket; whether the price index uses manufacturers or retail prices.
Every year, the Centers for Medicare and Medicaid Services (CMS) conducts a recovery audit. In a recent report, Medicare collected over $797 million in Medicare overpayments in 2011. Where do these overpayments come from?
Recovery Audit Contractors returned $488 million in improper payments to the Medicare Trust Fund in 2011. Although this may seem like a large amount of money, Medicare spending in 2010 was $524 billion. Thus, the recovered funds amount to less than two tenths of a percentage of total Medicare spending.
On The Health Care Blog (THCB), Dr. Vineet Arora argues that being a doctor is not as attractive as it once was. She writes:
After all, why go into this much debt and spend so much time in training if your prospects are not much better? More recently, the New York Times article points out job prospects for radiology trainees are thinning, meaning the well known “ROAD” (Radiology, Ophthalmology, Anesthesiology, and Dermatology) to success may soon become a road to nowhere if there are no jobs.
There in lies the question, why become a doctor? If the answer is to make money or to have an easy life, then you probably need to look for a new profession. With healthcare payment reform, doctors can expect lower salaries as bundled payment and cost cutting measures are instituted. Moreover, the demand for healthcare will go up as more patients have insurance, leading to higher patient volumes and the expectation to see more patients with the same amount of time.
On the one hand, these fiscal pressures are pushing U.S. physician salaries closer to those of other nations. On the other hand, the cost of medical education in most other countries is much lower. Instead, one of Dr. Arora’s colleagues argues that being a nurse practitioner may be a lower stress, less financially risky alternative.