Health Practitioner Bonuses and Their Impact on the Availability and Utilization of Primary Care Services. 1. Effects of Earnings on Specialty Choice by Physicians


While the estimated effect of earnings on specialty choice is present and significant, the magnitude of this income effect and its relative importance as compared to other factors in deciding a specialty is contentious. Recent data from the residency match program in the US reveals that among 16,875 US Medical school senior applicants in 2012 about 35.5 percent were matched to primary care specialties such as internal medicine, family practice and pediatrics.15 In 2010 the proportion matched to primary care (internal medicine, family practice and pediatrics) was 34.1 percent of 16,427 US Medical school senior applicants.16 Between 1995 and 2006, the total number of physician residents in the US in primary care training programs increased by 6 percent, from 38,753 to 40,982 (Exhibit 1). Physician residents in specialty care increased by about 8 percent during the same period.

Exhibit 1. Number of Physicians in Residency Programs17

Type of Resident Number of Resident Physicians Percentage Change
1995 2006
Primary Care Residents 38,753 40,982 5.75
Specialty Care Residents 59,282 63,897 7.78
All Physician Residents 97,416 104,526 7.30

Nicholson and Propper (2011) argue that the rate of return to medical training and specialization is the key driver of choosing medical occupation and the choice of specialty within the area of medicine. The gap in median income between primary care physicians and specialists is well-publicized. For instance, using cross-sectional earnings data from 2008 Vaughn et al. (2010) report that the average primary care physician could expect to earn $2.5 million over his lifetime, net of income taxes, living expenses and education costs, versus $5.2 million for a cardiologist. Berenson et al. (2007) report that, according to the Medical Group Management Association (MGMA), between 2000 and 2004 median physician income for all primary care increased by 9.9 percent while average incomes of all non-primary care specialists increased by 15.8 percent. Arguably, given the income gap, raising the payment rate for primary care services relative to other services would impact the number of primary care physicians and raise the amount of primary care services they provide. Moreover, if the reimbursement rates vary by geographic region, this strategy can also affect the geographic distribution of services of primary care services.

In a related study, Bodenheimer (2007) attempts to explain this disparity in incomes. The author notes that the Resource-Based Relative Value Scale, which was initially designed to reduce the inequality between fees for office visits and for procedures, has failed to reduce the primary care–specialty income gap. He finds that this failure is due to four factors: (1) the volume of diagnostic and imaging procedures has increased more rapidly than the volume of office visits; (2) the process of updating the relative values units (RVUs)18 associated with covered procedures is heavily influenced by the recommendations of the Relative Value Scale Update Committee (RUC), a majority of whose membership are specialists; (3) Medicare’s formula for controlling physician payments penalizes primary care physicians; and (4) private insurers tend to pay for procedures at higher rates than office visits relative to Medicare. They conclude that the program was designed with the correct motives but ultimately was weak and cannot achieve its purpose as currently formulated. Furthermore, incentives that favor specialists remain in the private market.

Nicholson (2002) also provides econometric evidence that the disparity in the expected earnings between primary care and other specialties has a significant influence on medical students’ decisions to choose primary care or another specialty. He observes that there is a persistent excess supply of residents to most specialties with relatively high lifetime earnings and a persistent excess demand for residents in primary care with relatively low lifetime earnings. His main contribution is to examine how differences in expected earnings affect the number of students who desire to enter a specialty rather than the number who actually enter the specialty. The study finds that the income elasticity ranges from 1.03 in family practice/pediatrics to 2.20 in radiology.19 In other words, a 1 percent increase in the lifetime earnings of primary care providers, such as family practitioners, will increase the number of students ranking family practice as the most preferred choice by 1 percent which can be translated into an increase of equal magnitude in the supply of family practitioners.

However, there are studies that report comparatively less impact of expected earnings on the decision to choose primary care. Bazzoli (1985) found that medical students are more likely to choose primary care when the expected earnings are relatively large, but the effect is quite small. More specifically, a $10,000 (about 20 percent of the mean earnings in 1981) increase in the expected earnings in primary care relative to the non-primary care yields a 1.4 percentage point increase in the probability of choosing primary care.

Gagne and Leger (2005) have studied the specialty choice decision of Canadian physicians who practiced between 1989 and 1998. They find that a 9.1 percent reduction in relative fee-per-consultation for a general practitioner in Quebec and Saskatchewan, for example, would lead to a 0.4 percent reduction in the proportion of medical students entering general practice. The largest response is observed in Manitoba where the proportion of medical students entering general practice is estimated to decrease by 2.29 percent as a result of a 9.1 percent reduction in relative fee-per-consultation. The implied responsiveness of specialty choice to changes in earnings from this study and from other studies discussed in this section is summarized in Exhibit 2.

Vaughn et al. (2010) bolster this point by noting that programs designed to affect the number of medical students choosing primary care have largely failed because of the programs’ inability to affect relative incomes. By estimating career wealth accumulation across specialists, primary care physicians, physician assistants, business school graduates, and college graduates, the authors try to elucidate the true difference between payment of physicians and non-physicians, and between specialists and generalists within the physician group. They note that this result is to be expected as programs have done little and continue to do little to affect the disparity in expected lifetime earnings between primary care physicians and specialists. The authors also find that for a primary care physician’s lifetime earnings to equal those of a cardiologist the primary care physician would have to receive a bonus of $1.1 million upon completion of medical school.

Sivey and Scott (2012) use an econometric approach to address the question of the effect of lifetime earnings on training specialty choice based on a sample of Australian postgraduate doctors. Using a generalized multinomial logit model the authors find a statistically significant positive impact of earnings on the probability of choosing general practice training versus specialty training. Subsequently, they use the same model to simulate the effect of a $50,000 increase in annual earnings of general practitioners (GPs) on the probability of junior doctors choosing GP training. Specifically, the simulation result suggests that $50,000 additional earnings for GPs (a 27.8 percent increase over their current salary of $180,000) would lead to a 26.3 percent increase in the propensity of junior doctors to choose GP training. Therefore, the implied earnings elasticity of the propensity to choose GP training is 0.95, which is consistent with previous findings (Nicholson 2002).

Exhibit 2. Summary of Responsiveness of Specialty Choice to Changes in Earnings (Earnings Elasticity)



Earnings Elasticity

Nicholson (2002) Elasticity of ranking Family Practice/ Pediatrics as the 1st specialty choice with respect to lifetime earnings (among US medical school residents) 1.03
Nicholson (2002) Elasticity of ranking Radiology as the 1st specialty choice with respect to lifetime earnings (among US medical school residents) 2.20
Gagne and Leger (2005) Elasticity of proportion of medical students (in 8 Canadian provinces) entering General Practice with respect to relative-fee-per-consultation 0.044 to 0.25
Sivey and Scott (2012) Elasticity of probability of junior doctors (in Australia) choosing General Practice with respect to annual earnings 0.95
Hogan and Bouchery (2010) Elasticity of percentage of male US medical school Internal Medicine graduates choosing Cardiology subspecialty with respect to annual compensation 2.50

Note: earnings elasticity gives the percentage change in the outcome measure of interest (e.g., proportion of students ranking family practice or radiology as the 1st choice) due to 1 percent change in earnings.

In an unpublished piece, Hogan and Bouchery (2010) estimate a multinomial logit model of the choices of internal medicine residents to remain in internal medicine and practice primary care, or to obtain a fellowship for further training in one of nine subspecialties of internal medicine and ultimately practice in that subspecialty.20 The authors find that a 1 percent increase in earnings from one of the career paths, holding earnings in other specialties constant, increases  entrants of male U.S medical graduates into that the examined specialty (Cardiology) by about 2.5 percent, but increases female entrants by about only 0.3 percent. They also find that increases in the length of additional training required for a subspecialty have a negative effect on the number of US medical graduates pursing that subspecialty and reduces the probability that US medical graduates pursue the specialty, but increases the probability that international medical school graduates pursue that subspecialty.21

Expected lifetime earnings are not the only factor that influences decision making during specialty choice. Medical students assign a low level of prestige to a primary care career compared to other specialties. Students surveyed associate primary care with low income expectation, low class rank and high educational debt (Henderson, 1996). Students often enter medical school with a positive perception of primary care, but by the time they reach their fourth year they are increasingly likely to disagree with the assertions that primary practice is prestigious, adequately compensated, and allows more control over working hours (Lynch, 1998). It appears that students’ positive perceptions concerning primary care may change as they experience the more realistic professional demands on primary care physicians that can develop during medical school and as they observe their peers and role models, both within primary care and outside.

15 Source: NRMP Results and Data-2012 Main Residency Match (

16 US Medical school seniors who are matched into internal medicine can subspecialize, later on, in non-primary care specialty such as cardiology, endocrinology, oncology etc.

17 Steinwald B. Primary Care Professionals: Recent Supply Trends, Projections, and Valuation of Services. Statement in Testimony before the Senate Committee on Health, Education, Labor, and Pensions. Washington (DC): GAO; 2008. Available from:

18 RVU is a key component of the formula used under Medicare Physician Fee Schedule (PFS) to calculate payment rates for an individual service. There are three different RVUs: work RVU, practice expense (PE) RVU and malpractice (MP) RVU. Work RVU reflects the relative time and intensity associated with Medicare PFS service; PE RVU reflects the costs of maintaining a practice; and MP RVU reflects the cost of malpractice insurance. Source:

19 Earlier studies of J.W. Hay (“Physicians’ specialty choice and specialty income”, Econometrics of Health Care, edited by G. Duru and J. Paelinck, Netherland Klwer Academic, 1991) and J. Hurley (“Physician choices of specialty, location and mode”, Journal of Human Resources, No. 26, 1991, pp. 47-71) did not account for uncertainty in entry to a specialty. However, they find that medical students are substantially responsive to expected income. These studies report income elasticities that range from 1 to 3.

20 Paul F. Hogan and Ellen Bouchery, “ A Model of Subspecialty Choice for Internal medicine Residents,” prepared by The Lewin Group for the American College of Cardiology. 2010.

21 After simulating the impact of decreasing cardiology training requirements from three years to two, the study finds that one-year decrease in training requirements would increase the percentage of male, U.S. medical school graduates choosing cardiology from 17.1 percent to 18.2 percent.

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