1. Determinants of First Practice Location Choice by New Physicians Chiu-Fang Chou 1,2, Dr.PH and Anthony T. Lo Sasso 2, Ph.D., Midwest Center for Health Workforce Studies 1, Division of Health Policy and Administration 2 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 Acknowledgement s We 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 MLM FIPS County Code Location Characteristics Personal Characteristics Malpractice premiums Not Accepted Jobs/OthersAccepted 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 BLS MSA 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. 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/GYNsSurgeonsPCPs N6337%93710%323037% VariableMeanStd DevMeanStd DevMeanStd Dev Personal Characteristics Age32.173.7833.393.1632.684.96 US citizen0.960.970.84 Race and Ethnicity White0.560.660.46 Black0.120.040.07 Asian0.210.200.33 Hispanic0.04 0.08 Other0.050.04 Gender (Male)0.300.830.52 Educational Debt $00.180.230.36 <$100,0000.420.430.34 $100,00–$125,0000.300.260.23 >$125,0000.070.06 Location Characteristics Malpractice premiums64,685.1327,138.0632,734.2617,501.7911,999.005,799.00 State with malpractice damage cap0.310.460.360.480.330.47 Physician hourly wage68.0911.6072.3411.7357.7911.66 Health professional shortage area0.130.10 0.120.100.140.12 Proportion of population by race White0.590.200.630.200.620.21 Black0.160.110.140.100.140.11 Asian0.070.06 0.07 0.06 Hispanics0.180.130.170.130.180.14 Other0.010.0020.010.0020.010.002 Same-specialty physician per 100,000 population15.085.3120.9337.7434.5023.93 Resident physicians per 100,000 population58.4640.1845.8839.4548.2139.55 Hospital beds per 100,000 population375.91117.85367.68122.53369.85117.87 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/GYNsSurgeonsPCPs Malpractice premiums ($1000s) 0.0000950.000011-0.000003-0.0000520.0001190.000118 (0.000019)***(0.000035)(0.000012)(0.000024)**(0.000019)***(0.000031)*** Damage award cap-0.001170.001432-0.0006580.002796-0.001000-0.000119 (0.000671)*(0.001857)(0.000310)**(0.000957)***(0.000116)***(0.000303) Health Professional Shortage0.014820.0024080.0031370.0010410.0018130.000126 Area(0.00223)***(0.003428)(0.001071)***(0.001289)(0.000243)***(0.000320) Physician hourly wage0.000300.0000490.0001090.0000420.000061-0.000042 (0.00004)***(0.000087)(0.000019)***(0.000047)(0.000007)***(0.000018)** Same-specialty physicians per-0.0002640.0000920.0000140.0000120.0000900.000055 100,000 population(0.000176)(0.000281)(0.000008)*(0.000008)(0.000007)*** Resident physicians per0.0000230.0001090.0000110.0002340.0000040.000071 100,000 Population(0.000024)(0.000067)(0.000014)(0.000074)***(0.000004)(0.000013)*** Hospital beds per 100,0000.0000110.000008 0.000007 0.000006 Population(0.000003)***(0.000020)(0.000001)***(0.000006)(0.000000)***(0.000002)*** State Loan Repayment0.003601---0.001358---0.001102--- Program(0.000595)***(0.000296)***(0.000110)*** Constant-0.025456-0.047313-0.0148330.000076-0.009456-0.028974 (0.005402)***(0.058552)(0.003053)***(0.013512)(0.001031)***(0.005206)*** MSA fixed effectsNoYesNoYesNoYes Observations77859 199581 904960 Number of physicians633 937 3232 R2R2 0.050.100.020.040.030.07 Table 2: Physician Fixed Effects Linear Probability Model Selected Results for Location Choice, with and without Fixed Location Effects OB/GYNsSurgeonsPCPs Proportion of black population-0.000432-0.0001120.000154 (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 population0.0003140.0001240.000418 (0.000356)(0.000195)(0.000064)*** Proportion of other population0.0011540.0016280.000727 (0.002702)(0.001285)(0.000457) Proportion of black population* Black physicians0.0002640.0000650.000175 (0.000074)***(0.000069)(0.000023)*** Proportion of Asian population* Asian physicians0.0003810.0002390.000134 (0.000122)***(0.000080)***(0.000030)*** Proportion of Hispanic population* Hispanic0.0003680.0001300.000127 physicians(0.000143)**(0.000076)*(0.000018)*** Proportion of other population* Other race-0.000302-0.0001880.000263 physicians(0.000102)***(0.000056)***(0.000169) MSA Fixed EffectsYes Observations77859199581904960 Number of physicians6339373232 R2R2 0.100.040.07 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/GYNsSurgeonsPCPs Health professional shortage area0.006543-0.0004820.002874 (0.004020)(0.001917)(0.000519)*** Educational debt greater than 0 but less than-0.0065320.000875-0.003712 $100,000 *HPSA(0.003539)*(0.002085)(0.000605)*** Educational debt between $100,000 and-0.0022880.004056-0.004967 $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 EffectsYes Observations77859199581904960 Number of physicians6339373232 R2R2 0.100.040.07 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.comcchou4@uic.educchou4@gmail.com