Provider Signing Bonuses: Mean vs. Median?

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Originally published by MGMA.

By Stephanie Tafoya

More physicians and nonphysician providers (NPP) are receiving signing bonuses as part of their compensation packages, according to MGMA data. And that financial sweetener might prompt more movement of providers between groups, which is something to consider whether you’re a provider seeking greener pastures or a practice manager who is hiring.

The most recent MGMA Physician Placement Starting Salary Survey: 2014 Report Based on 2013 Data shows a 10% increase in signing bonuses during the past five years with 60.3% of physician respondents who say they received a signing bonus of varying amounts. Amount differs substantially among physicians, who report a median signing bonus of $20,000 and NPPs, who received a median bonus of $5,000, according to the 2014 report. While the number of providers who receive these bonuses has increased, the median amounts reported have remained the same during the past three years, even though the means have shown slight changes.

And that leads me to my next point: Why use the median vs. the mean?

Meeting in the middle

The mean and median are both measures of central tendency in statistical research. Central tendency refers to a measurement of a middle or central value within a data distribution. The measured value, whether it is the mean or median, is located around the middle of a data set. The difference is that the median is the 50th percentile rank or middlemost point of data within a given data set while the mean is an average of all numbers in the set.
When it comes to compensation data, we frequently receive similar numbers from survey participants so the data points tend to cluster within a certain range. If there are outliers on the high or low end the middlemost number (median) doesn’t change much if at all, which makes it more reliable. Whereas the mean takes into account the high and low outliers — from particularly high- or lower-paying organizations — and can provide a number that isn’t necessarily representative of a dataset.

Which should you use?

We strongly encourage practice administrators use the median when they’re trying to determine a benchmark for physician compensation, bonuses or practice costs. As a single point of data, the median is not subject to distortion caused by outliers in the data and it is the best representation of the data set as a whole because it is calculated by finding the middle most value in the data set. In comparison, the mean is more vulnerable to outliers. When calculating the mean, you take the sum of all numbers and divide by the count. If outliers exist, the average is skewed one way or the other.

Whether you are transitioning to a new position or practice or preparing to hire a new provider, arming yourself with the most accurate benchmarking data can be key to successful negotiation and to ensure that your next contracts reflect your value.