For non-laboratory-based, tenure-track faculty, total annual revenue recoveries are substantially less than for their laboratory-based counterparts (Table 2). This reflects both the larger proportion of unfunded faculty and the lower award totals for non-laboratory-based investigators. The difference is greatest for professors (column L), who recover one seventh of the revenues of their laboratory-based counterparts during a six-year period. Of note, assistant professors (nonlaboratory, column J) recover more at all time points than do professors (nonlaboratory). Also, funding increases progressively for assistant professors (nonlaboratory) and averages one third of the levels for their laboratory-based counterparts.
For faculty in the research track (most commonly, PhD faculty in the nontenure track in either basic science or clinical departments), revenues are substantially lower at all time points (columns F and H). This is attributable primarily to the small fraction with any funding (fewer than 10% have any revenue in the first three years after hire). The limited funding of research-track faculty is a particularly important observation when constructing recruitment packages at the University of Arizona College of Medicine.
Facilities and administrative revenues
At the University of Arizona, the full F&A revenue rate is 51.5%. That is, for every $1.00 of revenue acquired to cover the direct expenses for the faculty and staff conducting the research (salary and fringe benefits, supplies, equipment, meetings, other), up to $0.515 is acquired to cover the overhead expenses to the institution of conducting the research. For many research awards, the F&A revenue rate is lower. Of recovered F&A revenues at the University of Arizona, 64% of these are retained on the main campus, and 36% are returned to the individual colleges, through two separate mechanisms (30% formulaically to the college and 6% for equipment and new programs). During the period from 1998 to 2004, the 30% returned to the college of medicine was split equally with the departments. In this report, positive central cash flows to the dean’s office from F&A revenues are modeled as 21%, representing the sum of the 15% retained by the dean’s office and the 6% for equipment and new programs.
Temporal trends for F&A revenue recovery parallel but exaggerate the differences for total revenue recoveries, when faculty are grouped by rank (Table 3). Annual F&A revenue return by laboratory-based assistant professors (column B) increases steadily during the six-year period. F&A revenue recovery represents of 20.1 ± 3.0% of total revenues during the first 6 years. This corresponds to an average F&A revenue rate of 25.2% (e.g., direct revenues multiplied by 25.2% gives the F&A revenue). In contrast to the F&A revenues for assistant professors, F&A revenues for laboratory-based professors fluctuate around a mean in each of the six years (column C). For professors, F&A revenue recovery represents 29.2 ± 4.2% of total revenues and corresponds to an average F&A revenue rate of 41.2% (e.g., direct revenues multiplied by 41.2% gives the F&A revenue). On a per-faculty basis, professors recover twofold more F&A revenue per year ($106,369/year) during a six-year period than do assistant professors ($54,107/year). This has direct and important implications for calculation of npv[+].
On an annual basis, non-laboratory-based assistant professors (column F) recover F&A revenues at one fifth the level ($11,853/year) of laboratory-based assistant professors. For non-laboratory-based professors (column G), the value of $3,756/year is 28-fold lower than for laboratory-based professors.
For faculty in the research track, F&A revenue recovery is low for assistant professors (column D) and negligible for associate professors (column E).
Central cash flows from clinical activities by tenure-track faculty
The cash flow returned to the dean’s office from clinical activities was determined. This is a 4% assessment on clinical collections (dean’s tax, or academic enrichment fund) generated through the faculty practice plan (University Physicians, Incorporated). Forty eight of 61 faculty tenure-track faculty were appointed in clinical departments, and of these, 37 were MDs conducting clinical work generating academic enrichment fund revenues (one MD was appointed at the VA). Of these 37 MDs, 20 were assistant professors, in laboratory (n = 6) and nonlaboratory (n = 14) categories.
Central clinical cash flows were lower for faculty with laboratory research programs than for faculty with nonlaboratory research programs. The average academic enrichment fund revenues for laboratory-based assistant professors increased progressively and, by year seven, approached levels for assistant professors with non-laboratory-based programs (Figure 1). For non-laboratory-based professors, average annual revenues during the first five years ($10,088) were similar to those for nonlaboratory assistant professors ($9,868). For laboratory-based professors, average annual revenues were $4,152 during the first six years, but too few faculty with clinical earnings were available to plot trends.
Incremental central cash flows from tuition
Only incremental cash flows directly attributable to the newly recruited faculty are applicable to the analysis. Accordingly, the net increase in tuition resulting from an increase in medical school class size, and adjusted for offsetting financial aid from central sources, was determined for the period from 1998 to 2004. Tuition for masters and PhD students was retained by the university and was not included. The average medical school class size increased from 100 to 110 during the project period, whereas the tuition and fees increased from $7,932 to $11,579 during the same time frame. After adjusting for simultaneous changes in financial assistance, and making the very liberal assumption that 100% of the net incremental tuition revenues were ascribed solely to the newly recruited tenure-track faculty, the average cash flow per newly recruited faculty was $4,552/year. Under the more realistic assumption that the incremental tuition revenues were distributed across the tenure-track and suffix-track faculty, the average cash flow per newly recruited faculty was $1,605/year. Regardless of which value is used, the contribution to positive central cash flow is a small fraction of the total positive cash flow.
Central cash flows from gifts and philanthropy
Positive cash flows (or their equivalent) to the dean’s office from gifts and other development activities were estimated. Analysis of gift revenue is less straightforward than that for either sponsored research funding or academic enrichment fund revenues. Gifts made to individual faculty members rather than for discretionary use by central administration, on behalf of the faculty member, do not necessarily contribute to central cash flows. Nonetheless, we assume, for purposes of this analysis, that all development funds are used to offset expenditures which would be required from central sources. Although this overestimates central cash flows, the magnitude does not substantially affect the overall analysis, as will be apparent from the data below.
A second complexity is that only a minority of faculty receive gifts. Of the 61 tenure-track faculty, only 10 obtained gift revenue, giving a sample size insufficient to project the expected magnitude for future recruits. We therefore opted to analyze gift revenue for all newly recruited faculty and to extrapolate the results to the tenure-track faculty.
Of the 311 individuals recruited between 1998 and 2004, and exclusive of center directors or department heads, 20 (6.4%) received a gift of some kind. The average amount of the gift when all faculty were included never exceeded $2,500 in any given year, with an average of $1,552 annually for the six-year period. Between 3.0% and 5.9% of faculty received gifts (average 4.1%) in any given year. For those receiving gifts, the annual average was $39,098, with a range between $20,492 and $54,989.
Gifts for center directors and department heads ranged between $135,000 and $337,000 per year.
Historical revenues from other sources, including royalties and patents
Patent and royalty income was analyzed during FY1998 through FY2004 on the basis of a five-tier income-sharing distribution policy of the university. Distribution to central administration is not realized until the third-tier distribution, where lifetime net royalty income is greater than $50,000. Central college of medicine administration receives 5% of net patent income at tiers three (>$50,000), four (>$500,000), and five (with >$1,000,000). As with gift revenue, only a small number of college of medicine faculty received patent or royalty revenue. During the evaluation period of FY1998 to FY2004, patent/royalty income did not exceed tier three income levels for any faculty member, with average income to central administration of only $3,400 per year for the entire college of medicine. This revenue stream contributes insignificantly to central positive cash flows.
Projection of total central revenues using historical predictions
Data from all revenue sources can be added to obtain an estimate for total incremental central revenues over time. Table 4A shows projections for a 10-year period, by faculty rank, based on the sum of F&A revenue, academic enrichment fund, incremental tuition, gifts and endowments, and patents and royalties. Values for years 7 to 10 were generated by linear regression, from values in years 1 to 6. Although this may be an overestimation, in the latter years, for assistant professors with a laboratory research program, this assumption can be modified in subsequent analysis. According to the data in Table 4A for annual positive cash flow, npv[+] can be projected for a new faculty recruit, at any time point after hire (Table 4A, npv[+] rows).
Prediction of future sponsored research funding for newly recruited faculty
By far, the largest source of central revenues for newly recruited tenure-track faculty is F&A revenue. In the analysis shown above, projections were based on historical results. The limitations of this approach, when the outcome is so heavily dependent on changing funding probabilities, is intuitively obvious. To address this limitation, we used a modification of our previously published work13 to estimate future sponsored research funding levels for newly recruited faculty, in the face of changing likelihood for funding. A probability-based simulation model for sponsored research funding was constructed, using historical data from the University of Arizona College of Medicine. Inputs into the simulation model, therefore, included probabilities of obtaining funding (1) at various time points after hire, (2) by faculty rank, (3) with direct and F&A revenues within defined ranges, and (4) with durations of support within defined ranges.
Total F&A revenue return to the dean’s office and departments/centers, by year and rank of faculty recruit, was projected for a six-year period. We varied probabilities for obtaining funding at various time points after hire, to reflect the impact of changing funding probabilities for awards with substantial F&A revenue recovery (e.g., those from the NIH, Department of Defense, Centers for Disease Control, and Veterans Affairs). These are most relevant for an npv model focused on positive central cash flows.
Probabilities for sponsored research funding for the first six years after hire were modeled for both assistant professors and professors, on the basis of the data accumulated and described above. Too few data were available to permit modeling for associate professors. One thousand simulations were performed for total revenue and F&A revenue for six years by newly recruited, laboratory-based, tenure-track assistant professors and professors (Figure 2 and 3, solid bars). The data are illustrated in histogram form, demonstrating the range of outcomes and the frequency of their occurrence.
We modeled the current funding climate at the NIH and other sources providing full F&A revenue recovery. The probabilities for funding, derived from the baseline data, were lowered by one third for all new awards (Figure 2 and 3, open bars), reflecting the drop in success rates when comparing 1998–2004 with 2006.10 The impact was substantially greater for assistant professors than for professors. Aggregate total revenues and F&A revenues for assistant professors decreased by 37% and 44%, respectively, during a six-year period. For professors, aggregate total revenues and facilities and administrative revenues decreased by 30% and 29%, respectively. The impact of these projections on the npv is considered further below.
Central cash flow generation by all college of medicine faculty
The analyses above were conducted for recently recruited faculty to the University of Arizona College of Medicine. It was of substantial interest and importance to compare these data with results for faculty who were members of the college of medicine for longer periods of time. Central cash flows generated by all faculty in the college of medicine were determined during the period from 1998 to 2004, for comparison with central cash flows by newly recruited faculty. A total of 932 faculty members generated revenue from some source during the period from 1998 to 2004. For purposes of comparison, we analyzed the demographics of faculty generating the most F&A and academic enrichment fund revenues during the project period (Table 5). Seven categories were compared (described in the legend to Table 5), for faculty with 1 to 6, 7 to 10, 11 to 15, and more than 15 years on faculty. The group with one to six years on faculty represent, at most, one sixth of the faculty (from all tracks) in the top categories, while constituting one third of the total faculty generating positive central cash flows over the same period. Thus, newly recruited faculty are underrepresented among the top earners. In contrast, faculty with more than of 15 years experience are overrepresented among the top earners. Although not necessarily surprising, this result provides further support for the importance of faculty retention, if financial return is to be maximized.
We constructed a detailed prediction model for central positive cash flows from faculty recruits at the University of Arizona College of Medicine. The predictions can be used to help configure and scale recruitment packages. The model can also be used to justify expenditures for faculty retention. Most important, this approach imposes fiscal discipline in a situation where large amounts of money are in play and where precise analysis of return on investment has not been typical. The effort and expense associated with this analysis is minimal in the context of the magnitude of the cash flows.
There will be a natural and entirely reasonable inclination to argue that averages do not apply when trying to recruit a specific faculty member. Nonetheless, predictions based on past experience are likely to be more accurate than the projections of department heads and/or center directors, who have an appropriate vested interest in consummating the recruitment. The same logic applies to assembling a retention package for a faculty member who has demonstrated steady increases in productivity, even if not yet at full potential, and faculty members who are on a flat or even declining trajectory.
In comparison with most other valuation tools, the npv explicitly accounts for the time value of money, by discounting future cash flows back to dollars at time zero. This permits the direct comparison of projects irrespective of magnitude or duration, and it allows individual projects to be added together.11,12 Moreover, because the npv for any project is equivalent to the sum of the npv for positive cash flows (indicated here as npv[+]) and the npv for negative cash flows (indicated here as npv[−]), the two parameters can be assessed separately. With aggressive assumptions regarding positive cash flows in years 7 to 10, the npv[+] for laboratory-based assistant professors increases from $118,600 at year 6 to $255,400 at year 10 (Table 4A). Contrast this with the npv[−] for negative cash flows associated with recruitment packages. Typically, the largest outlay is in the first year of recruitment, with progressively smaller commitments in ensuing years. For purposes of illustration, assume that the total recruitment package from central sources for an assistant professor (laboratory) is $500,000, distributed during four years (year one: $200,000; year two: $150,000; year three: $100,000; and year four: $50,000). The npv[−] (3% discount rate) for such a recruitment package is −$485,600. Hence, the project npv at year 10 is −$230,200 (i.e., $255,400–$485,600). Shown in Table 4B are the project cash flows annually, leading to the cumulative npv of −$230,200 at year 10. This cumulative npv would be even more negative if one uses the data in the open bars from Figure 2B, showing projected F&A revenue return with lowered probabilities for sponsored research funding. Using those data, the npv[+] for assistant professor–laboratory drops from $118,600 to $86,600 at year six (not shown). Because the modeling does not project beyond year 6, it is not valid to project npv[+] at year 10. Nonetheless, the consequences are obvious.
What are the options to deal with projects that have large negative npv over prolonged periods? Most obviously, and most important, faculty retention provides the best strategy for fostering positive npv projects, while simultaneously allowing the faculty member to contribute to the overall mission of the college. Although decreasing the magnitude of the recruitment package is another obvious approach, this is not likely to be a successful strategy for competing in the recruiting “marketplace.” Extending the negative cash flows for the recruitment package over a longer period of time provides a better match between the timing of positive and negative cash flows, raising total npv, albeit marginally. A more substantive solution is to create a better correspondence between the entities making financial commitments in the recruitment package and the ultimate distribution of positive cash flows back to those entities. In the example illustrated above, central administration was portrayed as contributing the majority ($500,000) of the recruitment package, yet recognized only 21% of F&A revenue recovered. Increasing the percentage of F&A revenue recovered by central college of medicine administration to 50% would lead to a marginally positive project npv by year 10. An attractive strategy is generation of incremental positive cash flows from incentives and development activities. For example, if an endowment providing an incremental positive cash flow of $26,200 per year to central sources were available to apply to the assistant professor recruit, the project npv at year 10 would be 0 (bottom rows of Table 4B).
It is of interest that the actual and predicted distribution of funding success for newly recruited assistant professors at the University of Arizona College of Medicine mirrors results, both qualitatively and quantitatively, for newly recruited assistant professors at Yale University School of Medicine.12 Moreover, all tenure-track assistant professors at the University of Arizona College of Medicine who ultimately obtained substantial funding had done so by year four (not shown), again mirroring results from the previous study. The similarities of these results could have been anticipated by comparing individual investigator success rates at research-intensive institutions.16
A substantial difference in the timing of academic enrichment fund revenue was observed when laboratory-based and non-laboratory-based assistant professors were compared (Figure 1). The progressive increase in central academic enrichment fund collections for laboratory-based assistant professors has a number of potential explanations. Many faculty recruited as laboratory-based investigators have minimal clinical responsibilities in the first several years of their appointment. Others, for a variety of reasons, progressively decrease their research time and increase their effort on clinical activities. For the faculty in our data set, the former explanation seems more likely. In all cases, the increase in academic enrichment fund revenues was also accompanied by an increase in F&A revenue recovery—often of much greater magnitude. Once again, this analysis supports the critical importance of faculty retention to permit all investigators and, in this case, clinical investigators, with laboratory research programs, to establish their clinical and investigative presence.
Our historical analysis includes the five-year period during which funding for the NIH doubled. Although the current downturn in NIH and other federal funding sources for research is now being fully appreciated, the decline in support began in the last two years of our historical analysis period. There are two interrelated strategies for dealing with such future uncertainty. First, prediction models can be developed and applied to future revenue streams, with appropriate modifications in probabilities. This is the approach applied herein. Second, analysis can be updated on a frequent basis, and averages can be calculated using a moving window approach. We have previously suggested that a three-year moving window is an appropriate period over which to follow support from sponsored research funding.16
One of the most striking results was the underrepresentation of newly recruited faculty in the top revenue-generating categories during the last six years. This has two immediate and complementary explanations. First, the faculty size within the University of Arizona College of Medicine was reasonably constant for more than 15 years, reflecting both a net balance between recruitment and retention, and the intention to keep faculty size relatively stable. Second, there was a lag period before newly recruited faculty with research programs generated substantial academic enrichment fund, F&A revenue, or gifts. Several obvious conclusions follow. Faculty retention is necessary to realize these substantial revenue streams, which are typically recognized after recruitment packages have expired. Second, in the absence of recruitment of faculty with extensive grant support, the most substantial revenue streams will be from established faculty. In our situation, the established faculty in both the clinical and research arena are subsidizing the recruitment of new faculty.
Determination of npv[+] requires that the project period be defined. Six- and 10-year periods have been used here, reflecting the typical duration from initial appointment to a decision regarding promotion (six years), and the usual period of time for promotion to professor with tenure. It could be argued that investments from central sources of the magnitude discussed above are ill advised, given the substantial mobility of academic faculty. This is particularly true with the recognition that AHC pay a minimum of $0.15 to $0.20 on the dollar to support the research mission.17 Although there is no single answer to this dilemma, it is important to look beyond the faculty recruits and, certainly, beyond the financial analysis, for the justification. Most important, the newly recruited faculty contribute towards the mission of the college of medicine and to advances in the clinical, educational, and investigative arenas. Direct revenues and F&A revenues support jobs, both in the university and community. Tax revenues flow back to the government. Nonetheless, a balance between positive and negative npv projects is necessary for sustainability.
In the process of negotiation and construction of recruitment packages for department heads and center directors, we routinely calculate projected npv, using the tools described herein. This has allowed us to more appropriately distribute resources with regard to magnitude, timing, and expectations. It has permitted more effective negotiation with central university administration for additional support, by illustrating the distribution of benefit in return for risk. A major advantage of the npv approach has been the ability to directly compare projects with vastly different scales and scopes, creating a uniformity that is reassuring in negotiations. Finally, we have applied this strategy in conjunction with a comprehensive model for management of research space, (A. Libecap et al. A comprehensive space management model for facilitating programmatic research. Acad Med. In press.) to optimize allocation of faculty positions and research space for newly recruited department heads and center directors. In combination, the goal is to systematically maximize the allocation of resources towards faculty recruitment.
The authors would like to acknowledge David Coleman, MD, Boston, Massachusetts, and Anne Wright, PhD, Tucson, Arizona, for helpful comments on the manuscript.
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