By using tASA/OR FTE as the measure of productivity, Group P was only 88% as productive as Group A (Table 4). However, when the difference in concurrency is accounted for in the measurement of tASA/OR site, Group P was more productive (139% of Group A). Similarly, TU/OR FTE comparison shows that Group A billed for more hours than Group P, but, after correcting for concurrency, Group A and Group P had almost identical TU/OR site values (i.e., they worked similar numbers of actual hours).
Measurement of cases per OR site illustrates that Group P provided anesthesia for 78% more cases in the same amount of time as Group A. Furthermore, for each case, Group P’s surgical duration was only slightly more than one-half that of Group A (6.44 TU per case for Group P and 11.26 TU per case for Group A). The shorter surgical times account for a larger tASA per hour measurement (Group P is 136% more than Group A). This is probably not attributable to more difficult cases being performed in academic settings, because Group P’s base units per case are slightly larger than Group A’s, suggesting a similar complexity of surgical procedures.
In this report we illustrate the collection, calculation, and use of clinical productivity for comparison of two different anesthesiology groups. We found that “per OR site” measurements removed the confounding factors of different concurrencies. Additional measurements (e.g., tASA/h) allowed for a more informative comparison in OR management issues.
Our goal was to propose clinical productivity measurements that met two conditions: (a) use of raw data that would be available without requiring an individual anesthesiology group to invest heavily in personnel or other resources and (b) facilitation of meaningful and accurate comparisons between different anesthesiology groups.
To meet the first condition, we focused on billing—cases, charges and revenue, base units, and TUs—because this information should be available to each anesthesiology group. We then discarded charges and revenue because these reflect factors that are not dependent on the efforts of individual clinicians. We then chose numbers of cases, tASA, and TU as possible numerators of measurements. For denominators, we chose average daily FTEs and OR sites. To obtain those numbers, we developed a method of surveying one day a month to estimate the daily numbers.
By choosing these types of data to collect, we excluded all clinical services (specifically critical care and pain management) that are billed without using ASA units and other activities (such as preoperative evaluation and contract hospitals) for which patient-specific services are not billed. This was done because, although academic departments usually provide these services, many private practice groups do not. If included, the comparisons might otherwise not be accurate. In addition, on the basis of previous experience, we excluded obstetric anesthesia, which is difficult to compare with OR care because of a difference in the methods of billing TU and the highly variable approaches used to provide coverage of obstetric anesthesia (2). We also excluded from analysis FTEs who performed obstetric anesthesia billings and services that were not billed by using ASA units.
To further simplify data collection, we accepted two additional limitations. First, we chose to not include placement of central venous and arterial catheters because these activities are billed by using relative value units. To include these low-volume activities in the comparison, we would have had to convert ASA units to relative value units. Although methods for that conversion have been published (5), we considered the effort involved unjustified for the purpose of comparing different anesthesiology groups. Perhaps the effort would be justified if the purpose were to compare the productivity of anesthesiologists with that of other specialists. Second, we did not include on-call (night or weekend) FTEs in the estimate of daily FTEs because of the differences between groups in staffing after-hours cases. We therefore included all ASA units as if they were billed during the weekday schedule. This approach is further justified because the resultant increase in the TU/OR site measurement recognizes the effort of performing cases after hours, on weekends, or both.
The second condition for productivity measurements was to allow comparison between different anesthesiology groups. For comparisons between groups or for establishing benchmarks against which groups can compare their performance, measurements different from those used by groups to monitor the productivity of individual anesthesiologists may be useful. Two major factors that differ between anesthesiology groups—concurrency and duration of surgery—influence billed ASA units. Although Posner and Freund (6) have shown that tASAs increase as concurrency increases, the only industry-wide measure currently available (at the time of this study) is “total units per FTE,” a metric that does not correct for concurrency (3,4). To correct for the confounding effect of concurrency, we considered two options: either to correct “per OR FTE” measurements to a concurrency of 1:2 (one anesthesiologist to two OR sites) or to correct “per OR FTE” measurements to a concurrency of 1:1 (one anesthesiologist to one OR site). Arithmetically, the first correction simply equals twice the second correction. The second correction is the same as performing calculations “per OR site,” i.e., dividing the productivity data by the number of OR sites. We chose to use the “per OR site” calculation, because it seemed to be more useful for OR management evaluation.
In reviewing our results, we found that the current industry standard, “total units per FTE,” did not meet the second condition of allowing meaningful comparison between different groups. We found that a set of measurements based on “per OR site” and “per case” provided more precise comparisons between different groups.
In addition to data quantifying tASA units, data describing TU and cases performed allowed for additional measurements that provided information about the duration of surgery and the length of the workday. Base units per case were used to determine whether the productivity differences (in particular, the presence of shorter surgeries) were more likely related to faster or less complicated surgeries. Because the base units were actually larger in the private practice group, this measurement suggests that the larger number of cases per OR site and tASA per OR site for Group P, despite use of the same amount of anesthesia time (TU per OR site), is explained by faster surgeries rather than by less complicated surgeries. Because Group P provides anesthesia care for private practice surgeons, the finding that the private-practice surgeons are faster than faculty-supervised surgical residents is not surprising. However, the results illustrate how the duration of surgery is an important determinant of anesthesia productivity and billable charges. The tASA per hour of care measurement illustrates this difference. For every hour of anesthesia care, Group P’s bills were 36% more than those of Group A.
The next step after designing these measures is to test them in a larger number of groups with the purpose of determining whether the measures continue to provide meaningful comparisons. We have already begun this process, and, if it is successful, the next step will be to consider these productivity methodologies and metrics for use as an industry-wide standard for clinical productivity in anesthesiology. This would permit an industry-wide survey and reporting to allow anesthesiology groups and departments to benchmark their clinical activities.
1. Garson A Jr, Strifert KE, Beck JR, et al. The metrics process: Baylor’s development of a “report card” for faculty and departments. Acad Med 1999; 74: 861–70.
2. Abouleish AE, Zornow MH, Levy RL, et al. Measurement of individual clinical productivity in an academic anesthesiology department. Anesthesiology 2000; 93: 1509–16.
3. Medical Group Management Association. Table 48: physician work RVUs (PE excluded, HCFA RBRVS method). In: Physician Compensation and Production Survey: 1999 report based on 1998 data. Englewood, CO: Medical Group Management Association, 1999:97.
4. Medical Group Management Association. Table 21: standardized work RBRVS units (TC/PE excluded) for academic faculty to 100% billable clinical activity. In: Academic Practice Faculty Compensation and Production Survey: 1999 report based on 1998 data. Englewood, CO: Medical Group Management Association, 1999:74.
© 2001 International Anesthesia Research Society
6. Posner KL, Freund PR. Trends in quality of anesthesia care associated with changing staffing patterns, productivity, and concurrency of case supervision in a teaching hospital. Anesthesiology 1999; 91: 839–47.