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How do you measure whether a quality measure is reliable? 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 signal is stronger, it is easier to identify high-quality providers, but if the measure has a lot of noise, it will be difficult to distinguish a high quality provider from a low-quality provider.

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The framework above is most useful for determining the reliability of a continuous measure. Many quality measures, however, are binary in nature: Did the physician conduct an A1C test? Did the physician give the patient beta blockers after an acute myocardial infarction AMI? Did the patient die during the episode of care?

These variables take on a value of 1 if the answer is yes and 0 otherwise. Adams adapts the framework outlined above for the case of these binary variables.

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To do this, the author uses a beta-binomial model. The beta distribution is a very flexible distribution on the interval from 0 to 1. This distribution can have any mean in the interval and can be skewed left or right or even U-shaped.

It is the most common distribution for probabilities on the interval.

The beta distribution depends on two parameters: If these two parameters are known, one can estimate the variance terms in the equation above as:. The value of p is the rate of success of the quality measure i.

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Knowing this, we can calculate reliability for a binary quality score as follows:. To estimate p, one can simply use the observed pass rate from the data. You can follow any responses to this entry through the RSS 2.

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You can leave a responseor trackback from your own site. Your email address will not be published. Continuous and Binary Measures Written By: Today I review how to measure reliability for both continuous and binary quality measures.

The reliability statistic for a given measure is calculated as: If these two parameters are known, one can estimate the variance terms in the equation above as: Knowing this, we can calculate reliability for a binary quality score as follows: The Reliability of Provider Profiling: Leave a Reply Cancel reply Your email address will not be published.

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