What is the effect of a treatment on health outcomes? The real question is: can you be more specific? Researchers may measure the treatment effect a variety of ways. Sensible research questions include: What is the average effect of the treatment across all individuals? What is the average treatment effect only among those who received [...]
Read the rest of this entry »Will missing data affect physician P4P scores?
The answer is yes, but maybe not as much as you may thought. A paper by Ryan and Bao use data from a randomized controlled trial (RCT) called IMPACT (Improving Mood-Promoting Access to Collaborative Treatment) to determine if errors in physician quality profiling are due mostly to random variation or missing data. For this report, [...]
Read the rest of this entry »Mahalanobis Distance
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 [...]
Read the rest of this entry »What are we weighting for?
Weighting has a number of uses. For instance, one can use weighting to estimate population sample statistics. The Panel Study of Income Dynamics (PSID) for instance oversamples households with low income. To get nationally mean values, one must reweight the PSID values, either using survey weights or matching to a nationally representative sample such as [...]
Read the rest of this entry »Measuring Convergence
Is regional variation in healthcare spending converging or diverging over time? How would you know? How would you measure convergence? A paper by Panopoulou and Pantelidis (2013) answers just such a question. They define 3 types of convergence. These include beta convergence, sigma convergence, and stochastic convergence. I explain each one below.
Read the rest of this entry »What is the Negative Binomial Model?
Many research questions require healthcare economists to measure the effect of various patient, physician or market-level characteristics on specific health events. Oftentimes, these events are discrete in nature. For instance, doctor’s visits, ER visits, and hospitalizations are all discrete events. To properly estimate the effect of certain characteristics on a discrete event, count models are needed. The [...]
Read the rest of this entry »Quality Measure Reliability: Continuous and Binary Measures
How do you measure whether a quality measure is reliable? What does the term “reliable” even mean? In the world of quality measurement, reliability is the ability to confidently tell the difference between a high-performing individual (or physician or hospital) and a low-performing individual. One can think of reliability as a signal-to-noise measure; if the [...]
Read the rest of this entry »Attrition Bias
If you are evaluating the treatment effect of a policy or medical intervention, does it matter if some of your subjects leave the sample? In many cases, the answer is ‘yes’. The Problem As outlined in Grasdal (2001), the effect of the treatment is simply: Δ = E(Y|X, T=1) − E(Y|X, T=0) However, in some [...]
Read the rest of this entry »Add to Your Skills Toolkit: The Oaxaca Decomposition
Suppose you look at health care spending in two different regions and observe a significant difference. You may want to know what the cause of this difference is. Is it because one region has a mix of people who are sicker; or is because the reason treat patients with a given disease more intensively? One [...]
Read the rest of this entry »Biases
All economists are familiar with the problem of selection bias. In non-randomized samples, patients may choose to be in either the treatment or control group based on factors which are also related to the outcome of interest. Even if researchers can design a study that fully controls for selection bias, robust studies must also account [...]
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