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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?

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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 Your email address will not be published.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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