For example, the practice I am part of has dedicated nocturnists who don’t work day shifts. So when thinking about how hard we’re working, we tend to sum each “day” doctor’s wRVUs for the year and divide by the number of day doctors. Calculated this way, our day doctors appear to be more productive than SHM data might indicate, but when including our nocturnists’ production and FTEs in the analysis, the overall workload per FTE in the practice is similar to the data.
Productivity Per FTE
While I think productivity per FTE per year is the best metric to use when comparing a practice to external survey data or comparing one practice to another, it is confounded by two sticky problems: inconsistent definitions of what constitutes an FTE, and the lack of an agreed-upon method of accounting for the contribution of nonphysician providers.
The most common definitions of what constitutes an FTE are based on the number of hours or shifts worked. One practice might define an FTE as 2,000 hours of work annually; another might use 180 annual shifts. Unless each shift has a clearly defined duration, it will be very difficult to reach conclusions. Although each practice might make sound decisions about how they define an FTE, they’re ultimately making arbitrary choices that aren’t consistent from one practice to the next. Controlling for this issue is very difficult.
Even trickier is how to compare the contributions of physician assistants (PAs) and nurse practitioners (NPs) from one practice to the next. In the above example, Dr. Plant’s practice has eight physician FTEs and four NPPs, and Dr. Krause’s group has eight MDs and no NPPs. How much more productive should we expect Dr. Plant’s practice to be? (NPPs make many valuable contributions, in addition to increasing productivity, but these are outside the scope of this article.)
Though survey data offer some clues, there is no established standard for increased productivity expected of PAs and NPs. One approach I use is to compare an NPP’s total compensation (salary and benefits) with that of the average physician FTE. If the cost of each NPP is 60% of an MD, then one could say that each NPP represents 0.6 “physician FTE equivalents” and could be expected to increase the productivity of the practice proportionately. So Dr. Plant’s group might be expected to have the productivity of 10.2 physician FTEs (4 NPPs X 0.6 = 2.2 “physician FTE equivalents,” added to the eight physician FTEs). (Note: While I think converting NPP FTEs into “physician equivalents” is useful in analyzing the effect of workloads on budgets, there are clearly many other very important issues when trying to quantify the contribution of NPPs to a practice.)
There are dozens of additional issues, such as the effect on productivity resulting from inefficient hospital systems (e.g., a clunky electronic health record, typed admit notes aren’t available for a few days compared with records available within two to four hours of dictation), activities such as attending Rapid Response Team activations, and differences in the social complexity of the patient population. None of these would show up in wRVU reports, so they are missing from the analysis I’ve described above.
I think it is impossible to control for all of the differences between practices that influence the definition of appropriate workload. This is the main reason SHM probably will never have a firm position on exactly what is the right or optimal number.
Although 15 patients a day is a reasonable starting point (I prefer to see fewer patients daily, but work more days/shifts annually), things get complicated in a hurry, and there will always be significant variation. TH