Data Mine: The secret of staffing success

What is the secret of staffing success? When asked how they arrive at their staffing levels, executives more often than not obfuscate their answer, hiding the fact that their staffing levels are determined not by plan, but happenchance. If pressed, they may explain their strategy in terms such as, “It’s easy, just get the right number of staff doing the right things.”

Faced with ever-increasing pressure to be more productive and to maximize profits, medical group leaders constantly look to improve their practice’s financial performance. As they examine their organizations’ performance and benchmark themselves to others, executives often look to what the average staffing metrics are for similar-type practices to determine if they are under- or overstaffed. Unfortunately, benchmarking to averages often results in average results and not necessarily improved performance.

If comparison to the average of your peers doesn’t work, what is the secret? Is it saving money with fewer staff, or is it increasing costs by adding more staff with the hope that production increases to offset the added staff expense — or something else entirely?

Examining MGMA survey data provides some clues, as MGMA DataDive Cost and Revenue describes how better-performing practices generally have more staff than other practices. However, it’s important to “look behind the curtain” and examine the survey dataset to identify what happens at various staffing levels.

Figure 1 reveals an interesting phenomenon: Both hospital-owned groups and physician-owned groups display bell-shaped curves in their staffing, but physician-owned practices generally have more staff per full-time-equivalent (FTE) physician. More than 59% of hospital-owned multispecialty groups have four or fewer FTE employees per FTE physician, whereas only 4% of physician-owned groups staff at such a low ratio. Some of the difference can be attributed to centralizing selected administrative functions such as human resources, marketing or the transfer of imaging and laboratory services to a parent entity. However, this chart is also evidence that hospital-owned practices may understaff key areas.

Economists are usually more objective than providers and executives in their staffing analysis, typically examining staffing in the context of a production function, relating physical inputs as land, labor and capital to practice outputs such as the number of procedures. Since a practice’s capital investment and physical plant are constant in the short run, this model is useful to examine the effects that different amounts of labor, measured as staffing levels, have on practice production and profits to better understand how staffing optimizes practice output.

The impact of having higher or lower levels of staffing on productivity and on financial performance is shown in Figure 2. Production (median total procedures per FTE physician) is least at the lowest level of staffing and increases as FTE employees per FTE physician increases. This is most obvious comparing the output for practices with the lowest staffing level of 2.1 to 3.0 FTE employees per FTE physician with the median procedures for the practices with the most staffing (6.1 or greater FTE employees per FTE physician), which reported almost three times greater production. One can speculate that at the lowest level of staffing, practices starve themselves of support for their providers, while at greater staffing levels the providers are fully supported.

The chart also examines the financial implications of staffing level variation. As staffing and production increases, median total medical revenue per FTE physician increases, as does median total operating cost per FTE physician. The survey data show there is a substantial net benefit to greater staffing, as practices with the highest staffing levels generate more than three times the median total medical revenue after operating cost per FTE physician. 

Beyond the data, it’s also important to understand what actually happens in a practice. Figures 3, 4 and 5 display scatterplot information from the 141 multispecialty groups with primary and specialty care that participated in the survey, each showing a bi-variant view how total FTE support staff per FTE physician relates to three key financial metrics.

The patterns show a strong relationship between higher staffing levels and better financial performance. The graphs also display the statistical relationship, the “coefficient of determination” expressed as R-squared (R2) or the degree that variation in financial performance is explained by the linear regression line, with a higher value implying the metric on the vertical axis is more strongly related to staffing.

The scatterplot graphs display each individual group’s performance, providing the opportunity to examine the interrelationship of staffing to total medical revenue, total operating cost and the net total medical revenue after operating cost. For example, it is possible to isolate a practice that has just below 2.0 total FTE support staff per FTE physician. This practice is among the lowest for total operating cost per FTE physician; however, it is also lowest for total medical revenue per FTE physician and for the net of total medical revenue after operating cost. The same can be done for other practices, which shows the complex interrelationship of staffing to production and of productivity to practice revenue and operating cost.

The scatterplot graphs also display significant variance in revenue, costs and net profits for a specific staffing level. These medical groups have a median of 5.0 total FTE support staff per FTE physician, and the graphs show that the medical groups staffing at or near 5.0 total FTE support staff per FTE physician report total medical revenue per FTE physician as low as $250,000 or as high as $1,800,000 — a sevenfold difference. The same phenomena occur in total operating cost and net profit.

What could explain the sizeable variance in performance at the same level of staffing? It’s the second half of the secret of staffing success. It is not sufficient to only have more staff, it’s more important to have staff with the right skills doing the right things — and the data prove it.