Determinants of First Practice Location Choice by New PhysiciansChiu-Fang Chou1,2, Dr.PH and Anthony T. Lo Sasso2, Ph.D.,

Midwest Center for Health Workforce Studies1, Division of Health Policy and Administration2

University of Illinois at Chicago, Chicago, Illinois

Introduction

Materials and Methods

This study is aimed at understanding how new physicians choose their initial practice locations. There is considerable disagreement on the role of malpractice premiums on physicians’ practice decisions. New physicians’ practice location decisions can have a lasting impact on the future healthcare workforce because relocation can be particularly costly for physicians.

The objectives of this study are threefold: (1) The impact of malpractice premiums and laws affecting premiums; (2) Policies aimed at encouraging physicians to practice in underserved areas(3) The ethnic and racial backgrounds of physicians.

Statistical analysis involved fixed effects models to examine the factors affecting the choice of initial practice location by new physicians. Data are from a unique survey of exiting medical residents acquired by the HRSA-funded New York Workforce Center at SUNY Albany. These data are matched to data on malpractice premiums from Medical Liability Monitor. Additional location information is from the Area Resource File (ARF).

The sample consists of 9,137 physicians who just finished their residency training in New York and California in 1998-2003 and who are beginning their careers in patient care. The dependent variable is the choice of location among the 357 metropolitan statistical areas (MSAs) and non-metropolitan areas within each state in the United States. Where appropriate, independent variables have been weighted by area population. Other local market characteristics include the number of hospital beds, per capita income, and the local unemployment rate.

Results

Conclusions The results suggest that malpractice premiums may be an important factor for some risky subspecialties. New surgeons were less likely to practice in areas with increasing malpractice premiums. OB/GYNs were less sensitive to malpractice premiums than were surgeons. PCPs appeared to be drawn to areas with higher malpractice premiums, suggesting a potential substitution effect.

Symmetric results were observed for the impact of state damage award caps. New surgeons and OBs were more likely to practice in areas with caps. New PCPs were less likely to practice in areas with caps.

The results suggest that health professional shortage areas may not be an important factor. Only OB/GYNs and PCPs without debt (18% and 36%of the respective samples) were more likely to practice in areas with HPSAs. Suggesting the program as structured does not appear to draw physicians.

Racial/ Ethnicity matching plays an important role on location choices for new physicians. he estimates are relevant for policy given the amount of interest in increasing the presence of minority physicians in predominantly minority communities. Educational debts is also found to be a factor influencing location choice of new physicians.

Limitation of this study:This study used the new physicians who finished their residency training in New York and California states, which are urban state. Malpractice data is limited because it does not have detailed information on the number of physicians that each company represents in the state; so it is rough average premium rather than a weighted average premium.

This map displays MSAs chosen by new physicians. The most frequently chosen option for all three specialty groups in the sample located in New York City. The second and third most common location was Nassau-Suffolk, NY (Long Island) and Los Angeles-Long Beach, CA.

Implications for Policy

AcknowledgementsWe gratefully acknowledge the contributions of Edward K.Mensah, Ph.D., Judith A. Cooksey, MD,

MPH, Surrey M. Walton, PhD, Lorens A. Helmchen, Ph.D., and Janelle Yi-Ju Lee, Dr. PH. Data for this study was provided by Gaetano Forte from the Center for Health Workforce Studies of the State University of New York at Albany and Robert Kaestner, Ph.D.

Funding for this project was provided by the National Center for Health Workforce Analysis of the Bureau of Health Professions of the Health Resources and Services Administration, and the University of Illinois at Chicago.

Hypothesis are the following:

Hypothesis 1: New physicians will be more likely to practice in a place with lower malpractice premium rate.

Hypothesis 2: New physicians will be more likely to practice in a place with a malpractice damage award cap.

Hypothesis 3: New physicians with higher educational debt will be more likely to practice in a health professional shortage area.

Hypothesis 4: New physicians will be more likely to locate in areas with higher proportion of the population of their race.

The determinants of first practice location choices for physicians vary by specialty. Policy makers who create programs regarding the physician workforce need to consider the different needs of physicians in different specialties.

Increasing malpractice premiums do appear to deter some specialists from locating in certain area; although malpractice damage award caps may be an effective tool for state policy makers to attract some traditionally high malpractice premium specialists.

Policy makers need to reevaluate the existing programs regarding HPSAs and to study the impacts of these program on physicians’ distribution or promote these programs to new physicians.

Table 4 Racial/Ethnicity matching: Racial/Ethnicity matching plays an important role on location choices for new physicians. That is, minority doctors appear to prefer to practice in areas that have more population of their own race and ethnicity. For example, in the Hispanic community, the results indicate that 1 % increase in the proportion of the population that is Hispanic makes a Hispanic OB/GYN 13.7% increase in the probability of locating in an area. The estimate is statistically significant for OB/GYNs (p<.05), PCPs (p<.01) and surgeons (p<.1).

Fellowship/others

NY/CA Resident Exit Data

Primary Care

ARF

MLMFIPS County Code

Location Characteristics

Personal Characteristics

Malpractice premiums

Not Accepted Jobs/Others Accepted Jobs

Missing Zip/City Practice Location

9,137 (90.64%)

22,504

12,695 (56.41%)9,809 (43.59%)

2,615 (20.60%) 10,080 (79.4%)

943 (9.36%)

9,137

BLSMSA Code

Cap

Figure 1 displays population weighted averages of malpractice premiums over time. Premiums grew quite slowly between 1998 and 2000, but they increased rapidly after 2000, with OB/GYN premiums increasing roughly 50% by 2003 and surgeon and PCP premiums increasing over 70% by 2003. In 2003 OB/GYN premiums were still nearly 1.5 times greater than premiums faced by surgeons and nearly 5 times greater than premiums faced by PCPs.

Figure1: Weighted mean of annual malpractice premiums by specialty and year

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

1998 1999 2000 2001 2002 2003

Year

OB/GYN premiums

Surgeon premiums

PCP premiums

Table 1 presents the characteristics of locations chosen by new physicians trained from NY and CA during 1998-2003. Malpractice premiums average nearly $65,000 annually for OB/GYNs and roughly half that figure for surgeons. PCPs by contrast faced premiums of roughly $12,000 per year.

Beyond the striking difference in malpractice premiums, location differences between the three specialist types were not particularly apparent. Surgeons appeared somewhat more likely to locate in states with malpractice damage award caps.

OB/GYNs Surgeons PCPs

N 633 7% 937 10% 3230 37%

Variable Mean Std Dev Mean Std Dev Mean Std Dev

Personal Characteristics

Age 32.17 3.78 33.39 3.16 32.68 4.96

US citizen 0.96 0.97 0.84

Race and Ethnicity

White 0.56 0.66 0.46

Black 0.12 0.04 0.07

Asian 0.21 0.20 0.33

Hispanic 0.04 0.04 0.08

Other 0.05 0.04 0.04

Gender (Male) 0.30 0.83 0.52

Educational Debt

$0 0.18 0.23 0.36

<$100,000 0.42 0.43 0.34

$100,00–$125,000 0.30 0.26 0.23

>$125,000 0.07 0.06 0.06

Location Characteristics

Malpractice premiums 64,685.13 27,138.06 32,734.26 17,501.79 11,999.00 5,799.00

State with malpractice damage cap 0.31 0.46 0.36 0.48 0.33 0.47

Physician hourly wage 68.09 11.60 72.34 11.73 57.79 11.66

Health professional shortage area 0.13 0.10 0.12 0.10 0.14 0.12

Proportion of population by race

White 0.59 0.20 0.63 0.20 0.62 0.21

Black 0.16 0.11 0.14 0.10 0.14 0.11

Asian 0.07 0.06 0.06 0.07 0.07 0.06

Hispanics 0.18 0.13 0.17 0.13 0.18 0.14

Other 0.01 0.002 0.01 0.002 0.01 0.002

Same-specialty physician per 100,000 population 15.08 5.31 20.93 37.74 34.50 23.93

Resident physicians per 100,000 population 58.46 40.18 45.88 39.45 48.21 39.55

Hospital beds per 100,000 population 375.91 117.85 367.68 122.53 369.85 117.87

Table 1: Summary Statistics of Characteristics of Location chosen by Physicians

Table 2 shows the regression results. Malpractice premiums: Increases in malpractice premiums have a negative and significant effect (p<.05) on the probability of choosing to locate in a given area for surgeons. No significant effect on the probability of choosing to locate in a given area for OB/GYNs, a statistically significant positive effect for PCPs. The magnitude of the result indicates that a one standard deviation increase in malpractice premiums for surgeons (approximately $17,500) would make a surgeon 0.1percentage point less likely to move to a given location, or roughly 8%.

Malpractice damage caps: Statically significant (p<.01) for surgeons and no statistically significant effect for OBs. The magnitude of the result indicates that surgeons are 0.28 of a percentage point more likely to locate in an area with a cap – suggesting a 23.9% (for surgeons) increase in the probability of locating in an area.

OB/GYNs Surgeons PCPs

Malpractice premiums ($1000s)

0.000095 0.000011 -0.000003 -0.000052 0.000119 0.000118

(0.000019)*** (0.000035) (0.000012) (0.000024)** (0.000019)*** (0.000031)***

Damage award cap -0.00117 0.001432 -0.000658 0.002796 -0.001000 -0.000119

(0.000671)* (0.001857) (0.000310)** (0.000957)*** (0.000116)*** (0.000303)

Health Professional Shortage 0.01482 0.002408 0.003137 0.001041 0.001813 0.000126

Area (0.00223)*** (0.003428) (0.001071)*** (0.001289) (0.000243)*** (0.000320)

Physician hourly wage 0.00030 0.000049 0.000109 0.000042 0.000061 -0.000042

(0.00004)*** (0.000087) (0.000019)*** (0.000047) (0.000007)*** (0.000018)**

Same-specialty physicians per -0.000264 0.000092 0.000014 0.000012 0.000090 0.000055

100,000 population (0.000176) (0.000281) (0.000008)* (0.000008) (0.000007)*** (0.000007)***

Resident physicians per 0.000023 0.000109 0.000011 0.000234 0.000004 0.000071

100,000 Population (0.000024) (0.000067) (0.000014) (0.000074)*** (0.000004) (0.000013)***

Hospital beds per 100,000 0.000011 0.000008 0.000008 0.000007 0.000007 0.000006

Population (0.000003)*** (0.000020) (0.000001)*** (0.000006) (0.000000)*** (0.000002)***

State Loan Repayment 0.003601 --- 0.001358 --- 0.001102 ---

Program (0.000595)*** (0.000296)*** (0.000110)***

Constant -0.025456 -0.047313 -0.014833 0.000076 -0.009456 -0.028974

(0.005402)*** (0.058552) (0.003053)*** (0.013512) (0.001031)*** (0.005206)***

MSA fixed effects No Yes No Yes No Yes

Observations 77859 77859 199581 199581 904960 904960

Number of physicians 633 633 937 937 3232 3232

R2 0.05 0.10 0.02 0.04 0.03 0.07

Table 2: Physician Fixed Effects Linear Probability Model Selected Results for Location Choice, with and without Fixed Location Effects

OB/GYNs Surgeons PCPs

Proportion of black population -0.000432 -0.000112 0.000154

(0.000433) (0.000269) (0.000089)*

Proportion of Asian population -0.001059 -0.000465 -0.000547

(0.000499)** (0.000167)*** (0.000076)***

Proportion of Hispanic population 0.000314 0.000124 0.000418

(0.000356) (0.000195) (0.000064)***

Proportion of other population 0.001154 0.001628 0.000727

(0.002702) (0.001285) (0.000457)

Proportion of black population* Black physicians 0.000264 0.000065 0.000175

(0.000074)*** (0.000069) (0.000023)***

Proportion of Asian population* Asian physicians 0.000381 0.000239 0.000134

(0.000122)*** (0.000080)*** (0.000030)***

Proportion of Hispanic population* Hispanic 0.000368 0.000130 0.000127

physicians (0.000143)** (0.000076)* (0.000018)***

Proportion of other population* Other race -0.000302 -0.000188 0.000263

physicians (0.000102)*** (0.000056)*** (0.000169)

MSA Fixed Effects Yes Yes Yes

Observations 77859 199581 904960

Number of physicians 633 937 3232

R2 0.10 0.04 0.07

Table 4: Physician Fixed Effects Linear Probability Model Results for Location Choice, Selected Coefficients for Race/Ethnicity Interaction Terms

Table 3 Health professional shortage areas: OB/GYNs and surgeons are generally unresponsive to shortage areas regardless of debt level. However, PCPs with no debt are significantly more likely to locate in areas with higher HPSA values. The magnitude of the result for PCPs without educational debt suggests that they are 14% more likely to locate in an area that is entirely a HPSA.

OB/GYNs Surgeons PCPs

Health professional shortage area 0.006543 -0.000482 0.002874

(0.004020) (0.001917) (0.000519)***

Educational debt greater than 0 but less than -0.006532 0.000875 -0.003712

$100,000 *HPSA (0.003539)* (0.002085) (0.000605)***

Educational debt between $100,000 and -0.002288 0.004056 -0.004967

$125,000 *HPSA (0.004587) (0.002690) (0.000618)***

Educational debt $125,000 or more*HPSA -0.007823 -0.000760 -0.004656

(0.008715) (0.002382) (0.000660)***

MSA Fixed Effects Yes Yes Yes

Observations 77859 199581 904960

Number of physicians 633 937 3232

R2 0.10 0.04 0.07

Table 3: Physician Fixed Effects Linear Probability Model Results for Location Choice, Selected Coefficients for HPSA-Physician Debt Interaction Terms

Contact Information: Chiu-Fang Chou, e-mail address cchou4@uic.edu or cchou4@gmail.com