ࡱ> %` 4bjbj"x"x .x@@~6 t t t  8,Lx J>L"$ht   Rt R "t 5 >!6i" 0J?<D5Mt !\IfyTjJ d >HD; H  Draft Version: PLEASE DO NOT QUOTE Ambulatory Surgery Centers and General Hospital Financial Performance Kathleen Carey, Ph.D. VA Center for Health Quality, Outcomes and Economic Research Boston University School of Public Health James F. Burgess, Jr., Ph.D. VA Center for Organization, Leadership and Management Research Boston University School of Public Health Gary J. Young, J.D., Ph.D. Boston University School of Public Health VA Center for Organization, Leadership and Management Research I. INTRODUCTION Over the past three decades, the U.S. hospital industry has been experiencing growing competitive forces operating in an environment of wide-ranging organizational change. A key development during this period has been a dramatic shift in service provision from the inpatient to the outpatient setting, a transition reflecting both new technologies that have made more procedures feasible on an ambulatory basis, and efforts of public and private insurers to control the growth of hospital costs. Emphasis on cost containment realized through greater reliance on outpatient care also has provided a stimulus to the entry of a new healthcare organizational form, the freestanding ambulatory surgery center (ASC), a limited-service alternative for treating surgery patients not requiring an overnight stay. As ongoing changes in technology continue to favor more outpatient surgical procedures, ASCs, specialized providers of these services, are becoming increasingly important players in the competitive dynamic of the health care sector. Proponents of ASCs, specialty hospitals and other providers, argue that through increased focus and specialization of services, they can set a new competitive benchmark in the hospital industry by promoting cost efficiency, augmenting patient choices, and providing quality health care at competitive prices (Porter and Teisberg, 2007; Herzlinger, 2004). Opponents claim that these organizations engender unfair competition by carving out relatively profitable services, targeting patient referrals, and selecting lower severity patients (Voelker, 2003; Iglehart, 2005). The most powerful argument in support of limited service facilities is that they strengthen competition among health care providers and settings, promoting innovations that induce competitors to improve their own performance. This paper tests that argument through an analysis of the effects of ASC market entry on the financial performance of competitor hospitals, nearly all of whom also offer these ambulatory surgical services. If competition works as a positive force in promoting efficiency of hospital services, we would expect to find that hospitals located in markets where ASC competition has grown would be more successful at controlling cost growth over time, and concomitantly, would be able to maintain margins of profitability. Alternatively, a finding that profit margins declined significantly in markets newly penetrated by ASCs and/or that cost growth is no different in those markets would fail to support the argument that ASCs promote healthy competition in the hospital industry. II. BACKGROUND ASCs originated in 1970 when a group of anesthesiologists opened a surgical center in Phoenix, Arizona. Development of ASCs took off in the early 1980s, as technological advances coupled with growing efforts at cost control gave rise to surgery being increasingly performed on an outpatient basis. Growth accelerated during the 1990s; ASCs have grown in number from 1,450 in 1990 to almost 5,000 in 2007 (FASC, 2007). Most ASCs are single-specialty facilities; over one-half of ASCs specialize in ophthalmology, gastroenterology, or orthopedic surgery. While research on ASCs is limited, it has been demonstrated that they are meaningful competitors to general hospitals (Bian and Morrisey, 2007). Competition from ASCs has become a growing area of policy interest, because ASCs are largely owned by the surgeons who practice in them, and unlike physicians performing surgery in hospital outpatient departments, physician-owners of ASCs are permitted under federal law to refer Medicare and Medicaid patients to the ASCs in which they have an ownership interest (Guterman, 2006). Hospital executives argue that ASCs are adversely affecting their profitability by cream skimming the healthiest patients and the most lucrative procedures (Casalino, Devers and Brewster, 2003; Kher, 2006), and research has demonstrated that ASCs treat patients of lower complexity than hospital outpatient departments (Winter, 2003). Federal antitrust authorities generally view ASCs as a positive competitive force which has the potential to promote competition, increase efficiency, and ultimately benefit consumers of health care. Nevertheless, in response to attempts by some general hospitals to deny admitting privileges to physician-owners of ASCs and attempts by others to lockout ASCs from insurance contracts for outpatient surgery (Beeler, 2007), the Federal Trade Commission (FTC) has stated that it is poised to aggressively pursue anticompetitive conduct by ASCs (FTC and DOJ, 2004). In order to inform policy approaches to the controversy over potential financial harm to community hospitals emanating from ASCs, it is necessary to understand the extent of the impact, an effect that remains to be demonstrated systematically. One recent study did examine the impacts of single specialty hospitals on general hospitals financial performance, and failed to find a negative impact on full-service community hospital competitors, which experienced lower costs and higher profit margins associated with specialty hospital entry into local markets (Schneider, 2007). However, we are unaware of any studies that have provided scientific or other significant evidence on the competitive impact of ASCs on general hospital financial performance. This paper addresses that gap by examining changes in revenues, costs, and profit margins in general hospitals competing in local markets with ASCs. We compare the performance of general hospitals in markets characterized by ASC presence with those located in markets where there were no ASCs, over a recent time period during with there was considerable ASC entry. III. THEORETICAL FRAMEWORK We assume that general hospitals offer a set of services that include outpatient surgery, and that they compete with ASCs for outpatient surgical patients within the local markets which they serve. When an ASC enters a market, there are potential consequences for revenues, costs, and profits of a general hospital competing in that market. If the entering ASCs are mainly meeting growing demand for outpatient surgical care but not significantly affecting patient workload in the general hospital, there is a null effect on the competitor general hospital. However, ASCs may compete away some patients from the general hospital, reducing both revenue and cost in that hospital. In order to maintain profits, the general hospital may attempt to secure offsetting increases in revenue, and/or find ways to realize decreases in costs. The hospital may attempt to add to revenue flows though other channels, possibly by shifting patient mix toward more privately insured or self-paying patients, or by changing service mix. Alternatively, the general hospital might intensify cost containment efforts by undertaking efficiency improvements, cutting staff, moderating provision of uncompensated care, or otherwise reducing expenses. Another factor that is significant in competition between limited and full-service facilities is selection. The ASC may draw patients who have a low likelihood of requiring an overnight stay in the event of complications arising from surgery. If the ASC systematically treats the relatively low severity patients within the market, it follows that there will be an increase in the average severity of patients treated in the general hospital, raising the average cost per patient treated there. Under a prospective payment reimbursement mechanism including that of Medicare, this will have a negative effect on profits for the general hospital, which will be reimbursed at the same level for patients within specific diagnosis groups, regardless of severity level. The overall effect of ASC market entry on the financial performance of the general hospitals within markets will depend on the combined effects of these various factors. More formally, the profit level of a general hospital, , is equivalent to the difference between total revenue, R, accrued during a fiscal period and total cost, C, expended during the period:  = R  C (1) Revenue is modeled as a function of Q, the number of patients, P, the price received per patient, , and X, additional hospital and market level factors that affect revenue such as payer mix and competition from other hospitals in the market: R = f (Q (A), P, X) (2) The quantity Q of patients is a function of A, the level of ASC competition in the market. As in standard cost functions, total cost is determined by Q and by the prices of inputs, W. In this model of ASC competition, cost is also a function of the severity of patient mix, S, which may be affected by the level of ASC competition. At each level of Q, cost will be greater to the extent of the selection effect coming from ASC competition, since the average severity level of patients in the general hospital will be higher, and therefore incur greater costs. Total cost is also influenced by other hospital and market level factors Z, including ownership status and market competition from other hospitals. Cost is modeled as: C = g (Q (A), W, S (A), Z). (3) Our interest lies in the effect of ASC competition on . This is the partial derivative of  with respect to A: " = "R*"Q  "C*"Q  "C*"S "A "Q "A "Q "A "S "A = ("R/"Q  "C/"Q) * "Q  "C*"S (4)  EMBED Equation.3  "A "S "A We parameterize equation (4) as follows: " = (  )*   * (5) "A The term (  ) represents the change in the markup of patient revenue over cost, or the competitor hospital s responsiveness to loss of patients to ASCs. We assume that (  ) e" 0, depending on the extent to which the competitor hospital is successful in meeting the competitive response. If revenue losses are met by cost reductions,  = , and the hospital will be successful in maintaining average patient profitability. If revenue losses exceed cost reductions,  > , and the competitor will suffer profit losses. The second term, ( d" 0), is the competitive effect of ASC competition, or the marginal effect of ASC competition on the number of patients in general hospitals. The term  is the marginal effect of patient severity on cost ( > 0). Finally,  is the ASC selection effect. We assume that  e" 0, and that its magnitude depends on the presence and strength of the selection effect. A negative effect on the general hospital s profits exerted by ASC competition occurs in the event that "/"A < 0. A number of possible scenarios are illustrated in Figure 1. Figure 1. Combined Effects of ASC Entry on Changes in General Hospital Profits Selection Effect  = 0  > 0Effect of ASC Competition on Number of Patients  = 0  < 0 No effect(  ) = 0: No effect(  ) > 0: Negative effectNegative effect (selection)Negative effect (competition + selection) The model generates a number of testable hypotheses. If ASC entry meets a growing demand for outpatient surgery but does not draw patients away from the general hospital ( = 0), and there is no ASC affect on the hospital s average severity, ( = 0), then we would not expect to observe any effects on a competitor general hospital s revenues, costs, or profit margins associated with ASC entry. If ASCs draw patients away from competitors ( < 0), but there is no selection effect ( = 0), the effect on profits will depend on whether the average general hospital is able to offset losses in revenues. If they are successful ( = ), we would anticipate downward effects on both revenues, and costs, but not on profit margins. If unsuccessful, ( > ), we would expect to find decreases in revenues but smaller decreases in costs, and hence some decreases in profits associated with ASC entry. An outcome of no effects on revenues, but increases in cost and decreases in profit margins would be consistent with a scenario of selection but no competitive effect on number of patients ( > 0;  = 0). Finally, if both selection and competition are present ( > 0;  < 0), we would expect to find decreases in revenues, increases in cost, and decreases in profit margins associated with ASC entry. The next section develops an empirical model for testing these hypotheses. IV. EMPIRICAL MODEL 1. Context Our test of the effects of ASC market competition utilizes data on all acute care general hospitals in operation during the period 1997-2004 in three states in which there was considerable entry of ASCs, and for which we were able to obtain data on ASC location and opening dates: Texas, California and Arizona. The competitive market areas are the Hospital Referral Regions (HRRs), regional health care markets defined in the Dartmouth Atlas of Health Care. The 493 hospitals in this study belonged to 49 distinct HRRs. The unit of analysis is the hospital/year. 2. Variables We estimate three regression models. The dependent variables in the three estimating equations are net patient revenue (revenue), total operating expenses (cost), and profit margins [margin = (revenue cost)/revenue]. The key independent variable is the number of ASCs in operation for two or more years in the hospitals HRR in a given year. The main measures of quantity of output are number of admissions, number of outpatient visits, and hospital average length of stay. Because different payer types reimburse different amounts for the same procedures, we also include number of Medicare inpatient days and the number of Medicaid inpatient days. To capture the resource intensity of patient workload, we include the Medicare inpatient case-mix index, which correlates highly with a hospitals overall case-mix index, and which is standard in hospital cost function analyses (Gaynor and Anderson, 2005; Carey, 1997; Rosenman and Li, 2001). An outpatient case-mix index was unavailable, however we control for the portion of hospital outpatient visits that involved surgical procedures. Medicare Part A (hospital) adjusted average per capita cost (AAPCC) proxies for output prices in the county in which the hospital is located. To control for input prices, we use the wage index created by Medicare to adjust hospital reimbursements for higher cost of living in different geographic locations. While this measures the price of only a single input to production, it accounts for 54 percent of acute care hospitals total expenses in 2004. Variation in costs to hospitals for energy and food will also be partially reflected in wage rates, which must compensate workers for higher costs of living. Covariates include the number of staffed beds, indicator variables for whether the hospital operates under a for-profit or nonprofit ownership structure, and for whether the hospital is a member of a multi-hospital system. We also incorporate a number of market level variables. Also at the market level, we include a Herfindahl index, computed as the sum of squared market shares (measured in numbers of staffed beds), to control for the overall level of competition exerted by other general hospitals. Because there was entry and exit of general hospitals over the eight year study period, we include the number of general hospitals in the market in each year. We also measured the average hospital profit margin in the HRR (lagged one year), to account for the fact that ASCs may be inclined to enter relatively profitable markets. ASCs might also be more likely to enter HRRs that are high population growth areas or, since most ASCs are at least in part owned by physicians, that have a relatively large number of physicians per capita. While we did not have access to these measures at the level of the HRR, we include measures of population growth over the time period of the study, and per capita physicians in the county in which the hospital is located for each year. The models also include state specific year indicator variables. 3. Estimation The regression models are longitudinal panel data models with hospital fixed effects, allowing for changes to accrue over time following entry of ASCs that occur during different time periods and in different markets. Due to positive skewness in the distribution of revenues, costs, and output, these variables are transformed to natural log form. Our test of the effects of ASCs is based on an independent variable indicating the number of ASCs that have operated in the relevant market for at least two years, allowing time for competing hospitals to respond to changing market competition. In order to sharpen the focus on the effects of responsiveness of general hospitals to ASC entry, we balance the panel by excluding hospitals for which we did not have a full set of data for each of the eight years in the time period of study. The final sample includes 3,944 observations on 493 unique hospitals. A technical issue with natural experiments such as entry of ASCs is endogeneity bias due to the effects of selection of ASCs into particular markets. For example, if some unobserved factor is driving ASC market entry and also correlated with any of our dependent variables, we cannot definitively establish causality between competition from ASCs and general hospital performance. No method can completely identify causality from observational data, however the endogeneity issue is more of a problem in cross-sectional studies, and the longitudinal feature of our models alleviates this concern by controlling for unobservable hospital level factors. At the same time, fixed effects models only capture unobservable factors that are time invariant at the individual hospital level, and causality may be threatened by unobservable market factors such as the presence of large organizations of physician groups, that may in some way affect the financial performance of all general hospitals, regardless of whether they are in competition with ASCs. 4. Data Sources The primary source of data was the Centers for Medicare and Medicaid Services (CMS), from which we obtained information on revenues, costs, and ownership (Medicare Cost Reports), the area wage index, and the inpatient case-mix index. The American Hospital Association Annual Survey Database supplied information on the output variables, on hospital bed size and system membership, and on number of outpatient surgical procedures. County level variables came from the Area Resource File. Finally, we obtained information on the number and location of ASCs from the Texas Department of State Health Services, from the California Office of Statewide Health Planning & Development, and from the Arizona Department of Health Services. V. RESULTS Summary statistics of the variables used in the analyses are listed in Table 1 for the first and last year of data in the sample. ASC presence more than doubled over this period. The average number of ASCs operating in an HRR for two or more years grew from 14.7 in 1997 to 32.0 in 2004. Table 2 lists the full set of regression results. The level of ASC market penetration was negatively associated with both general hospital revenue and cost. The effect of ASCs on margins, however, was insignificantly different from zero. From these results, it appears that cost reductions in hospitals located in markets with relatively higher ASC penetration were sufficient to offset revenue losses. In general, the output variables performed as expected in the revenue and cost functions, with the exception of the Medicare and Medicaid inpatient days which were insignificantly different from zero in both equations. The price measure was not significant in the revenue function nor was the wage index significant in the cost function. While these variables are highly meaningful theoretically, if there was little real change in prices or wages within hospitals over time, then variation in revenues and cost due to these factors would be expected to be absorbed by fixed effects for individual hospitals. Neither the Herfindahl index of competition nor the number of hospitals in the market had an effect on either revenues or cost. For profit hospitals had relatively higher revenues and costs than not-for-profit hospitals or public hospitals (reference group). Population growth was unrelated to hospital revenues or costs. Per capita physicians, however, while unrelated to revenues, was positively associated with costs. In the profit margin function results, we also observe a negative association with case-mix. This likely reflects the fact that under Medicare and other prospective payment programs based on diagnosis-related groups during this period, hospitals were not reimbursed for the additional resource burden imposed by within group patient severity. For profit hospitals realized greater profit margins, as did hospitals located in HRRs with high average profit margins in the previous year. The coefficients on ASC penetration in the revenues and cost functions listed in Table 2 are changes in the natural logarithms of revenues and costs, and hence not in themselves revealing as to the magnitude of the ASC effects on revenues and costs. However, we can apply the results to estimate the changes in revenues and costs in actual dollars. At the mean values of revenue and cost for 2004, the final year of the sample, we find that one ASC is associated with a decrement of approximately $167,000 in revenue and of $116,000 in costs for the average general hospital competitor. These represent 0.127% and 0.085% of revenues and costs, respectively. The combined results suggest that general hospitals are indeed experiencing competition from ASCs. In the context of our theoretical model, the nature of that competition involves loss of some market share to ASCs by general hospitals located in markets with greater ASC penetration levels. As there was no significant difference in changes in profit margins in those hospitals, cost reductions appeared to largely offset revenue losses. We do not observe direct evidence of a significant selection effect emanating from the ASCs. VI. IMPLICATIONS FOR PUBLIC POLICY Recent controversy over hospital competition from limited service facilities has centered on single specialty hospitals (Barro et al., 2006; Mitchell, 2007; Nallamothu et al., 2007; Carey et al., 2008; Schneider et al., 2008). However, a recent report by the Government Accountability Office (GAO) remarks that based on surveys of community general hospitals, the most significant competitive challenge may come from ASCs (GAO, 2006). The results of our analyses support that view. We found evidence of downward pressure on both revenues and costs in general hospitals associated with the strength of ASC presence. However, single specialty hospital competition was not significantly associated with profit margins of general hospitals competing in the same markets. Understanding the role of ASCs in the competitive landscape of the U.S. hospital industry has important implications for public policy. ASCs are more loosely regulated than the hospital outpatient departments with whom they compete, generally under the assumptions that since they do not require the full set of services associated with overnight stays, they reduce costs and promote competition. ASCs are exempt in many states from certificate-of-need (CON) legislation, or laws designed to control cost growth by prohibiting hospitals to add beds or build new facilities without first obtaining state approval. However other states are reinvigorating CON laws in order to inhibit ASC entry. ASCs also have a different Medicare payment structure than hospital outpatient departments for the same services. CMS recently implemented a new payment system for ASCs that is based on the hospital outpatient prospective payment system, but under which ASCs receive only 65% of the hospital outpatient rate for the same procedures (AHA, 2007). However this regulatory adjustment was instituted despite the fact that knowledge of the relative cost structures of ASCs is limited (GAO, 2006). The results of our study suggest that ASCs are an important competitive force in the market for outpatient surgical care in the U.S. As policymakers continue to address overdue regulations of ASCs that will influence the future direction of the provision of surgical care, more research on this topic will be needed. VII. CONCLUSION This paper contributes to understanding of how growing competition from freestanding ambulatory surgery centers impacts general hospitals. Our findings produce evidence of the presence of a competitive effect. Moreover, in the states that we studied, our results suggest that general hospitals appeared to have been able to maintain profit levels in the face of ASC entry. However, support for the case that organization of surgical service around limited-service ambulatory surgery centers promotes healthy competition within the hospital industry, needs to take into account broader societal effects than what we have examined here. The effects of ASC competition on surgical outcomes and quality of care in general hospitals competing with ASCs is an important area for future inquiry. REFERENCES American Hospital Association News, July 16, 2007 Barro, J.R., Huckman, R.S. and Kessler, D.P. (2006). The effects of cardiac specialty hospitals on the cost and quality of medical care. Journal of Health Economics 25, 702-721 Beeler, C. Testimony before the Federal Trade Commission on Health Care Competition and Law. March 26, 2003:63-64. 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The uncertain future of specialty hospitals. New England Journal of Medicine, 352, 1405-1407 Kher, U. (2006). The hospital wars. Time Magazine, December 11, 64-68 Mitchell, J.M. (2007). Utilization changes following market entry by physician owned specialty hospitals. Medical Care Research and Review 64, 395-415 Nallamothu, B.K., Rogers, M.A.M, Chernew, M.E., Krumholz, H.M., Eagle, K.A. and Birkmeyer, J.D. (2007). Opening of cardiac hospitals and use of coronary revascularization in Medicare patients. Journal of the American Medical Association 297, 962-968 Porter, M.E. and Teisberg, E.O. (2006). Redefining Healthcare. Boston MA: Harvard Business School Press Rosenman, R. and Li, T. (2001). Estimation of hospital costs with a generalized Leontief function. Health Economics 10, 523-538 Schneider, J.E., Ohsfeldt, R.L., Morrisey, M.A., Li, P., Miller, T.R. and Zelner, B.A. (2007). Effects of specialty hospitals on the financial performance of general hospitals, 1997-2004. 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Ohsfeldt, R.L., Morrisey, M.A., Zelner, B.A., and Li, P. (2008). The economics of specialty hospitals. Medical Care Research and Review 65, 531-553. U.S. Government Accountability Office. (2006). Payment for ambulatory surgical centers should be based on the hospital outpatient payment system. GAO-07-86 Voelker, R. (2003). Specialty hospitals generate revenue and controversy. Journal of the American Medical Association, 289, 409-410 Winter, A. (2003). Comparing the mix of patients in various outpatient surgery settings. Health Affairs, 22, 68-75 Table 1. Means and Standard Deviations for 1997 and 2004 VariableMean (Standard Deviation) 2004 (n=493) (n=493)Net patient revenue (thousand $)77,356 (90,928)131,890 (155,430)Total operating cost (thousand $)81,497 (105,209)136,613 (159,697)Margin-4.37 (27.49)-7.27 (24.43)Number of ASCs 14.65 (15.46)32.01 (34.11)Admissions8,222 (7.433)9,807 (8,928)Outpatient visits101,769 (119,824)128,702 (165,471)Average length of stay5.305 (3.262)5.486 (4.970)Case-mix index1.371 (0.234)1.342 (0.257)Outpatient case-mix index0.043 ---0.046 --- Medicare inpatient days17,527 (15,870)21,129 (20,438)Medicaid inpatient days8.032 13,220)11,979 (16,152)Price317.44 (59.16)367.13 (36.06)Wage1.033 (0.204)1.033 (0.183)Number of beds193.9 (165.7)208.1 (183.3)% For-profit hospitals0.258 ---0.274 ---% Not-for-profit hospitals0.487 ---0.483 ---% Hospital system member 0.596 ---0.623 ---Number of specialty hospitals0.016 (0.126(0.124) (0.330)Herfindahl index0.109 (0.091)0.124 (0.101)Number of hospitals in market37.86 (34.53)38.01 (35.02)Average profit (market) lagged-0.058 (0.078)-0.052 (0.074)County population growth1.127 (0.105)1.128 (0.105)County physicians per capita0.0019 (0.0011)0.0020 (0.0011) Table 2. Panel Data Fixed Effects Estimates of General Hospital Patient Care Revenue, Costs, and Profit Margins (1997-1004) Independent VariableCoefficient (Standard Error)Dependent Variable Ln (Revenue) Ln (Cost) MarginNumber of ASCs -0.00127** (0.00057)-0.00085* (0.00044)0.00170 (0.05609)Ln (Admissions) 0.3156*** (0.0272)0.2743*** (0.0211)3.916 (2.682)Ln (Outpatient visits)0.0201* (0.0108) 0.0359*** (0.0084)-1.912* (1.068)Ln (Average length of stay)0.0372 (0.0241)0.0345* (0.0188)0.1590 (2.380)Case-mix index 0.1752*** (0.0551) 0.2610*** (0.0428)-11.74** (5.434)Outpatient case-mix index0.1335 (0.0906)0.2156*** (0.0704)-8.450 (8.931)Ln (Medicare inpatient days)0.0085 (0.0139) -0.0105 (0.0108)  2.987** (1.372)Ln (Medicaid inpatient days)0.0121 (0.0076) 0.0080 (0.0059) 0.2347 (0.7461)Price0.0002 (0.0003)0.0316 (0.0263)Wage-0.0776 (0.0731)0.8480 (9.275)Number of beds-0.0001 (0.0001)0.0000 (0.0001)-0.0006 (0.0085)For-profit dummy variable 0.1589*** (0.0402) 0.0886*** (0.0313) 8.767** (3.968)Not-for-profit dummy variable0.0419 (0.0326)0.0031 (0.0254)5.745* (3.216)System member dummy variable0.0084 (0.0190)0.0168 (0.0148)-1.823 (1.877)Herfindahl index-0.2532 (0.1844)-0.1177 (0.1434)-18.17 (18.19)Number of hospitals in market0.0038 (0.0049)0.0009 (0.0038)0.2990 (0.4865)Average profit (market) lagged 0.2279*** (0.0535)-0.0501 (0.0415) 42.65*** (5.281)County population growth0.3028 (0.7862)0.4929 (0.6102)-10.27 (77.59)County physicians per capita42.31 (31.70) 67.69*** (24.70) -3243 (3136)* p < 0.10 ** p < 0.05 ***p < 0.01     PAGE  PAGE 1 ?EFNOPWXabc $%&78?@ҭҭҭhBOhdCJ\h9"hdCJ\h9"hlZCJ\ hlZCJ\ hdCJ\hlZ5CJ\hd5CJ\hBOhv5CJ\hvhd5DWK $$Ifa$gdBOkdl$$Ifl40N "#`  t0644 layt$x$Ifa$gds x$IfgdZ$x$Ifa$gdt?FOPX_THHHH $$Ifa$gdBO x$Ifgdtkd$$Ifl40N "#   t0644 layt $IfgdlZ$ & Fx$If`a$gdlZXbcLA x$IfgdtkdX$$Ifl4\N "#  `@ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd> $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO%&8@JKSLA x$Ifgdtkd $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO@IJKRS\]^tuyz{  !)*+BCHIPQRXYabchiùùùùùùùùùh9"h CJ\ h CJ\h*hdCJ\hd5CJ\ hdCJ\h9"hdCJ\h9"hlZCJ\ hlZCJ\IS]^u{LA x$Ifgdtkd $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd$ $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO !LA x$Ifgdtkdh $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO!*+CIQRYLA x$Ifgdtkd $$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOYbcipxyLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOiopwxy !&'*+,12567PQVWZ[\abefgùh9"hq;CJ\ hq;CJ\h*hdCJ\hd5CJ\h9"hdCJ\h9"h CJ\ hdCJ\ h CJ\ILA x$IfgdtkdN$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO!'+,2LA x$Ifgdtkd4$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO267QW[\bLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBObfgLA5 $$Ifa$gdx[c x$Ifgdtkdx$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO@5 x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO $$Ifa$gdx[c ./=?MNOghuwHIM\giqsxǻ~hthgB*CJphhthgCJ\ hgCJ\hhgCJ\hg5CJ\hhg5CJ\hBOhg5CJ\ hg5\hghthq;CJ\h9"hq;CJ\h*hq;CJ\ hq;CJ\hq;5CJ\0LA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO/6>LA x$Ifgdtkd^$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBO>?FNOhnvLA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOvw}LA x$Ifgdtkd$$Ifl4\N "#  @ t0644 layt $$Ifa$gdBOL? 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