Data Mine: The big picture on productivity

One of the most complex problems facing a healthcare executive is to design a compensation plan that fairly compensates providers and, at the same time, rewards the professionals who work harder, use fewer resources or who are noted for providing a better patient experience. Building a successful compensation plan is not an easy process and has the added peril of creating real or perceived inequities among the practice’s providers.

A first step for many healthcare executives in assessing how different types of incentives impact physician productivity and compensation is to examine the survey data published in the MGMA DataDive Provider Compensation.

Examining the median values for total compensation and the number of work RVUs (wRVUs) for physicians compensated with 100% salary (essentially having no productivity incentive) or physicians whose compensation is partially or fully based on production is revealing. For example, the 2019 MGMA DataDive Provider Compensation reports that physicians in family practice without OB who are compensated with 100% salary have median compensation of $225,309 with 4,012 median wRVUs, while their peers who are compensated either by 100% production, equal share or 50% more production plus quality metrics reported median compensation of $256,892 and, more important, produced a median of 5,138 wRVUs. Having a productivity incentive increases the number of wRVUs performed and the doctor’s compensation.

However, there is a very complex relationship between incentives and compensation levels; only examining median information provides a very limited view. To examine the big picture, it is necessary to take multiple views of the data. Within MGMA DataDive, the Pro Report Builder includes two reports that, when combined, provide this view:

1. The Pay to Production Plotter displays the actual distribution of the database on two axes, showing each provider’s compensation and wRVU production.
2. The Quartile Report provides descriptive statistics for key metrics for each quartile of wRVU production.

Filtering these reports by the type of compensation plan is extremely revealing for any executive who needs to better understand how productivity incentives impact compensation and production.

Figures 1 and 3 show the Pay to Production Plotter reports for physicians in two different specialties (family medicine without OB and noninvasive cardiology) who are compensated with 100% salary. Some doctors — those on the right side of the vertical line marking median wRVU production — report a substantial number of wRVUs; however, there are an equal number of doctors on the left side of the median reporting less than median wRVU production and, in many cases, substantially less production — yet they are well compensated.

The scatterplot graphs also display the statistical relationship, the “coefficient of determination” expressed as “R-squared,” or the degree that variation in compensation is explained by the linear regression line, with a higher value implying that total compensation is more strongly related to increases in wRVU production. The relatively low R-squared values — especially for noninvasive cardiology — confirm that doctors who are salaried have little incentive to produce.

Figures 2 and 4 display data for doctors who have a productivity-based compensation plan, showing that they not only have higher median wRVU production (15% greater for family practice without OB and 14% for noninvasive cardiology) but also have substantially higher compensation (23% greater for family practice without OB and 28% for noninvasive cardiology). The relationship of wRVU production to compensation is visually different from the earlier graphs, with the doctors’ compensation and wRVUs clustering much closer to the regression line, which is confirmed with a higher R-squared than the earlier graphs.

The Pay to Production Plotter provides an excellent view, but an executive may want additional information. A parallel view is available in the Quartile Report, providing key metrics that help fill in the information gaps in the scatterplot graph. Figure 5 shows for each quartile in wRVU production, the median compensation and the median wRVU production. Examining the information for doctors with 100% salary, not only are the quartile ranges much lower than the doctors with productivity-based compensation system, but the median total compensation and median wRVUs are lower within each quartile.

Essentially, the Quartile Report provides the quantifiable information that confirms the qualitative views of the Pay to Production Plotter. An advantage of viewing data by wRVU quartile is the ability to use the information to project how compensation could change as production increases.

One of the principles of evidence-based management is that good decisions are based on good data. The interrelationship of provider production and their compensation is extremely complex, and a healthcare executive wanting to better understand the dynamic requires substantial information from within the practice as well as external benchmarks. Fortunately, with the right tools and data reports it is possible to view the big picture and to understand and manage even the most complex problem.

Dig deeper

MGMA DataDive is the premier data benchmarking tool in healthcare. Access the industry’s largest benchmarking datasets in topics such as compensation, operations and cost and revenue. For more information on how MGMA DataDive can help your organization, contact sales@mgma.com or call 877.275.6462, ext. 1801.