Plotting Productivity with SHM-MGMA Data

Found under a pile of stuff on Troy Ahlstrom’s desk…

OK, so maybe paper airplanes, coloring, or back-office trash can basketball come to mind as your preferred use for an MGMA report.  But, hey, there’s a lot to be seen and understood in this panoply of inpatient practices.  In particular, there are analysis tools that might just help you get more information out of the darned thing!

The electronic versions of the MGMA report provide analysis and benchmarking tools that are worth one’s investigation. I’d like to highlight one of these tools today as I attempt to use the survey tools to answer the question, “How productive am I relative to my Hospitalist peers?”

Let’s take a look at the 2010 MGMA Physician Compensation and Production Survey “Physician Pay to Production Plotter” into which I’ve honed the sample to a representative data set for four physicians in a hospitalist practice.  (Also see the combined SHM-MGMA 2010 State of Hospital Medicine Report which provides this information at a significant discount for SHM members.)

I’ve selected a representative section of hospitalist practice based on size of practice, but one can also hone into certain geographic areas, medical revenue or setting of practice based on population.  Data for various physicians for work RVUs and compensation is then entered for comparison.  This generates a scatter plot, best fit line for mean with standard deviations above and below the mean, and all of the physician data points that makes up the sample.  (As a disclaimer, let me mention that the example physician data is fictitious.)

In this case, I’d highlight Doc 1 as a highly productive physician who is well compensated for her productivity.  Meanwhile Doc 4 also appears to be within the norm for compensation for his lower productivity level.  Both physicians are operating near the compensation/productivity mean which likely represents a “zone of efficiency” for workload and compensation among hospitalists.  Doc 2 is doing well on compensation, but exhibits lower productivity for that compensation.  It’s possible that this represents local market phenomena or that the physician is relatively underutilized.  Maybe this physician performs a good deal of leadership or management work for a practice, such that his/her wRVU productivity is lowered relative to compensation.  Meanwhile, Doc 3 is likely in a range of high productivity relative to compensation which might mean that the physician is relatively overburdened or undercompensated relative to his peers.  It might also represent a local market effect where hospitalists are potentially paid less because the market is saturated with these providers.

Obviously, one can plot themselves versus the MGMA data as a self-analysis.  But beware, as one needs to consider what aspects of a compensation plan differ from the reported measures to MGMA as well as local market pressures and practice expectations.  This is still a scatter plot of individuals, and each individual has a practice compensation structure directed at its own hospitalist market.

More fun with SHM-MGMA data next week… Trendlines and marginal returns for everyone!

(Graphics used with permission from the Medical Group Management Association, 104 Inverness Terrace East, Englewood, Colorado 80112.  877.ASK.MGMA.  www.mgma.com.  Copyright 2010.)

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