Single Specialty Hospitals and Service Competition
Carey, Kathleen, Burgess, James F., Young, Gary J., Inquiry
Advocates for physician-owned hospitals specializing in cardiac, orthopedic, and surgical services claim that these facilities induce healthy competition, stimulating improved performance among acute care hospitals. This paper examines the effect of specialty hospital entry on one indicator of competition among hospitals: changes in service provision by general hospitals in local markets. Results suggest that general hospitals are stepping up their own offerings of services that are in direct competition with those of specialty hospitals. Entry of specialty hospitals is also associated with significantly higher growth in high-technology diagnostic imaging services in the general hospitals in those markets.
The Medicare Modernization Act (MMA) of 2003 imposed a congressional moratorium on referrals of Medicare and Medicaid patients by physician owners to new cardiac, orthopedic, and surgical hospitals. The moratorium ended in August 2006, but the controversy surrounding the development of physician-owned single specialty hospitals (SSHs) continues in full force. Opponents claim that SSHs engender unfair competition by targeting patient referrals, offering services leading to overutilization, cream-skimming patients, and limiting the ability of acute care general hospitals to cross-subsidize unprofitable services (Kahn 2006). Advocates maintain that by focusing on a limited range of services, SSHs offer better care and provide services more efficiently, promoting competition that stimulates higher quality of performance among their local general hospital competitors (Herzlinger 2005; Greenwald et al. 2006).
The SSH is a relatively new organizational model in the hospital industry, and of the approximately 100 currently in operation, most have opened in the last 15 years. Despite the moratorium, SSH growth has gained considerable momentum in very recent years, and currently dozens are under construction or in planning stages (U.S. GAO 2005; AHA 2008). Supporters on both sides of the debate generally agree that reimbursement inequities under the Medicare payment system has provided significant impetus for SSH development; shortly after the moratorium was lifted, the Centers for Medicare and Medicaid
Services (CMS) began refining reimbursement methods to level the playing field for competition (Hayes, Pettengill, and Stensland 2007). There are a number of other proposed regulatory approaches to SSH growth, some under policy discussion and others being tested and evaluated in various states.
Current policy concern and regulatory interest in SSHs are substantial, yet research that might inform policy on SSHs is limited. The two leading research efforts to date have been undertaken by the Medicare Payment Advisory Commission (MedPAC) and CMS, both in response to the MMA mandate. MedPAC found cardiac SSHs to be associated with increased rates of cardiac surgeries in local markets (MedPAC 2006), a conclusion reiterated in a recent study of coronary revascularization (Nallamothu et al. 2007). CMS investigated the quality of care at cardiac SSHs and concluded that it was as good as or better than competitors' care, although the evidence was drawn from a very small sample (Leavitt 2005; Greenwald et al. 2006). Both MedPAC and CMS found that SSHs treat lower severity patients, as have a small number of other researchers (Cram, Rosenthal, and Vaughan-Sarrazin 2005; Mitchell 2005). As for the relative efficiency of SSHs, the evidence is mixed (MedPAC 2006; Barro, Huckman, and Kessler 2006; Carey, Burgess, and Young 2008).
Understanding SSH impact on the performance of the hospital industry is only beginning, and whether SSHs are stimulating healthy competition is still an unsettled question. Prior to the emergence of managed care, hospitals competed for patients largely on quality by attempting to attract physicians, who preferred to refer their price-insensitive patients to facilities having a wide range of services and the latest and most sophisticated medical technology (Luft et al. 1985; Robinson and Luft 1985; Manheim, Bazzoli, and Sohn 1994). During the 1990s, pressure from growing managed care penetration shifted hospitals toward greater price competition (Bamezai et al. 1999; Gift, Arnould, and DeBrock 2002). More recent observations point to a resurgence of nonprice competition among hospitals, or what some have characterized as the "new medical arms race," triggered in part by the entry of new organizational forms for delivering patient care, including physician-owned specialty hospitals (Devers, Brewster, and Casalino 2003). Current trends in hospital competition also entail growth of within-hospital service lines organized around medical specialties, and hospitals increasingly are marketing themselves along branded service lines such as heart centers, rather than as generic organizations as in the past (Berenson, Bodenheimer, and Pham 2006).
Do SSHs stimulate hospital service competition within local markets? The small number of SSHs and the paucity of data available on their activities are a challenge to researchers in directly addressing the policy arguments relating to their competitive impact. To study this issue, our paper has focused on how general hospitals respond to the entry of SSHs into their markets. Specifically, we tested whether other hospitals have been observed to alter their service mix following market entry by SSHs. A number of different responses are possible. For example, hospitals in direct service competition with SSHs might add services in the same areas of specialization in order to avoid losing profitable patients to the new competition. Alternatively, to improve margins, they might add high-technology services or shut down unprofitable safety-net services. At the same time, hospitals that are not currently engaged in competition with SSHs because, for example, they do not offer cardiac or orthopedic surgery services but are located in markets where SSHs have entered, might decide to expand into those service lines in order to protect their patient base in the long run. Nevertheless, associative relationships, not causal relationships, are all that may be directly measured given the availability of data to study these effects.
In 2005, the Government Accountability Office (U.S. GAO 2006) conducted a survey of 401 general hospitals and failed to find a difference between SSH competitor and noncompetitor hospitals in service provision changes over a broad range of clinical services (U.S. GAO 2006). We conducted a statistical analysis of finer-grained changes in the clinical service offerings of competitor general hospitals. We used hospital-level administrative data that covered a time period when there was substantial SSH entry and, concurrently, extensive growth in the breadth of services offered by general hospitals. We examined the pattern of such service offerings by general hospitals to determine whether differences across markets were related to the presence of SSHs. In so doing, we address an underlying current of the SSH controversy: whether the entry of SSHs into local hospital markets stimulates changes in the competitive behavior of general hospitals in those markets.
Data and Methods
Our main source of data is the American Hospital Association Annual Survey Database (AHA) for the years 1997 through 2004, supplemented by the Area Resource File (ARF) and the CMS Medicare case-mix index. We study the 10 key states where SSHs have been growing in recent years: Arizona, California, Idaho, Indiana, Kansas, Louisiana, Ohio, Oklahoma, South Dakota, and Texas (U.S. GAO 2003). Geographically, SSHs are tightly concentrated; approximately 100 were in operation by the end of our study period (MedPAC 2005). From the state hospital associations and from Web searches, we identified the 90 SSHs that were open in the 10 states in 2004. Table 1 describes the distribution of identified SSHs across states.
We studied the effects of SSH competition by examining the relationship between changes in selected service offerings of general hospitals and the amount of SSH competition in those local hospital markets. The study comprised all general hospitals operating in the 10 states. The market area is the hospital referral region (HRR) as defined in the Dartmouth Atlas of Health Care. HRRs represent regional health care markets for tertiary medical care; nationally, each of the 306 HRRs contains at least one general hospital that performs major cardiovascular surgery. The hospitals in this study belonged to 108 distinct HRRs. Table 2 presents the distribution of SSH competition across HRRs, as well as the considerable entry of SSHs and the growth of competition between 1997 and 2004. In 1997, 309 of 1,249 hospitals were located in an HRR containing at least one SSH. By 2004, that number had grown to 575. There were only 10 hospitals in competition with cardiac SSHs in the 10 states in 1997, but by 2004, the number had jumped and 289 of 1,010 hospitals faced competition from cardiac SSHs.
The AHA data include 70 unique clinical services over the 1997-2004 period. We focused on the services--which we grouped into three categories--that are most relevant to competition between general hospitals and SSHs. One category had services that are growing and are in direct competition with SSHs: angioplasty, cardiac catheterization, outpatient surgery, and freestanding outpatient centers. A second category consisted of high-technology diagnostic imaging and other therapeutic services. This category enabled us to test whether hospitals facing increasing competition from SSHs are more likely to engage in nonprice competition, possibly contributing to the "new medical arms race." The final category, which we designated as "safety net," contained services heavily used by uninsured and underinsured patients. SSHs have been criticized for not offering emergency services (Iglehart 2005), and previous research has shown that general hospitals treat higher severity patients and patients with more comorbidities (Barro, Huckman, and Kessler 2006). At the same time, while emergency visits have increased by about one-third since 1990, the number of emergency departments has declined, increasing financial pressure on those that continue to operate (AHA 2005). Here we ask whether, over time, general hospitals in markets with SSHs increase their offerings of services that comprise the hospital safety net, or alternatively, whether they exit from low profitability safety-net services, possibly as a consequence of financial pressures brought about by SSHs drawing away patients from their more profitable services.
We estimated a set of logit regressions, where each dependent variable was a binary indicator of whether a specific service was offered; the unit of observation was a hospital/year. The logit regressions are longitudinal panel data models with hospital fixed effects, allowing for changes to accrue over time following the entry of SSHs during different time periods and in different markets. Our test of the effects of SSHs was based on an independent variable indicating the number of SSHs that have operated in the relevant market for at least two years, allowing time for competing hospitals to respond to changing market competition. We tested the sensitivity of the models with two alternative measures of SSH competition: a binary variable indicating the presence of any SSH in the market, and a measure of the share of SSH beds in the market. We also constructed additional measures of SSH competition for cardiac SSHs only and for orthopedic/surgical SSHs only. For purposes of this analysis, given the focus of many surgical SSHs on orthopedic cases, we followed the lead of MedPAC and treated orthopedic and surgical specialty hospitals jointly (MedPAC 2006).
Our analysis incorporated numerous covariates that account for time-varying hospital and location specific factors that potentially explain variations in hospital service offerings. Hospital service complexity was measured by the Medicare case-mix index, and an indicator variable was included for hospitals with fewer than 100 beds. Since the changes in hospital service offerings simply may be due to the fact that markets in which specialty hospitals enter are more competitive, we included a Herfindahl index of competition. We constructed this based on the share of an individual hospital's beds in the HRR. Also at the level of the HRR, we included measures for the shares of hospital beds based on type of ownership, whether the hospital is a teaching hospital, and whether the hospital is a member of a multihospital system. Finally, to control for area demand factors, we included county-level measures of per capita income and per capita physicians (obtained from the ARF).
Tables 3, 4, and 5 display regression results for the key independent variables, which relate to the level of competition resulting from the entry of SSHs and facing the hospitals in our sample. We explicitly break the results out by the type of SSH entering the market. Table 3 displays results for all SSHs as a group, Table 4 for cardiac hospitals alone, and Table 5 for the orthopedic/surgical hospitals alone.
Table 3 suggests that, on the whole, hospitals have responded to SSH entry with increased efforts to engage in direct competition with SSHs. Evidence is seen primarily in the cardiac services area: both angioplasty and cardiac catheterization exhibited a strong association with SSH competition across all three measures of competition. Outpatient surgery services were not related to SSH competition; however, hospital-owned freestanding outpatient centers did show an association with SSH competition when measured as a binary indicator and as SSH percentage of beds in the market.
The results for high-technology diagnostic services showed a very strong pattern of growth in markets with increasing SSH competition compared to markets without SSH competition: five of the seven services showed a positive and significant association with SSH growth. This result generally held across all three measures of competition.
Finally, the results for the safety-net services were mixed. While we found a statistical association for four of the six services of interest, the signs were not consistent, with trauma centers and burn units positively associated with SSH competition, but urgent care and emergency psychiatric services negatively associated. Only trauma centers (positive association) and crisis prevention (no association) showed consistent results across the three measures of competition.
Table 4 reports results for the logit regressions in which SSH competition was measured for cardiac SSHs only. As expected, given the results for all-SSH competition, effects on angioplasty and cardiac catheterization were generally positive and significant. Coefficients in limited dependent variable models are in themselves not easily interpreted. However, to better understand marginal effects, we used the coefficients to calculate marginal probabilities. For the association of angioplasty with the number of SSHs in the market for more than two years, the coefficient of 1.048 translates into a marginal probability of .028. The interpretation is that the entry of a cardiac SSH increases by 2.8 percentage points the probability that a general hospital located in the same market will add angioplasty within two years post-SSH entry. Cardiac SSH competition alone had a statistically significant association with four of the seven high-technology services. The effects were not without practical significance. For CT scan services, for example, the marginal probability that a general hospital will add the service following entry of a cardiac SSH was .371. However, little association existed between safety-net services and competition from cardiac SSHs.
Finally, Table 5 presents the effects on service offerings where competition was measured for orthopedic/surgical SSHs only. Outpatient surgery services offered within the hospital itself did not appear to be increasing, even where only SSHs with comparable services were included in the measure of competition. However, since 94.6% of general hospitals in the sample were performing outpatient surgery in 1997, there was little room for expansion in this area of service. Freestanding outpatient centers, however, did show an association for SSH competition measured as a binary variable and as a percentage of beds in the market. As with the measure of all SSH competition, the set of five high-technology services exhibited a highly significant association with orthopedic/surgical SSH competition (p < .01). While the practical implications for CT scan services were somewhat less than for cardiac SSH competition, the marginal probability of .207 represents a considerable predicted reaction. With the exception of the complex and costly trauma service, which showed a positive association, changes in safety-net services did not appear to be related to competition from orthopedic/surgical SSHs.
This paper examined the association between SSH market entry and changes in service offerings by general hospitals over a recent time period when there was significant SSH entry. We found some evidence that general hospitals are stepping up their own offerings of services that are in direct competition with those of SSHs. Cardiac surgery services, in particular, grew more in markets where SSHs were present. This result complements population-based studies cited previously, which found a greater volume of cardiac services in markets with cardiac SSHs (MedPAC 2006; Nallamothu et al. 2007). Our results add to the literature by showing that SSH entry is associated not only with more cardiac services being performed, but with more hospitals performing cardiac services since some that did not offer these services prior to the SSH entry added them. Competition from orthopedic and surgical SSHs also is associated with the growth of freestanding outpatient centers that are affiliated with general hospitals. This model may appeal to patients' preferences for the smaller-scale setting for outpatient surgery while simultaneously offering the support of a full-service general hospital in the event of unexpected complications from surgery.
Markets with greater SSH presence show significantly higher growth in high-technology services, compared to markets where SSHs are not present. It remains to be demonstrated whether the growth in services in these markets is improving quality by meeting growing demand and/or easing capacity constraints, as opposed to creating unnecessary service duplication. However, given recently reported strains in physician-hospital relations (Berenson, Ginsburg and May 2006; Goldsmith 2006), hospitals may be fueling the new medical arms race in an attempt to revitalize their appeal to physicians in markets where physicians have been separating from hospitals and establishing economic spheres of their own. Another possibility is that because of health plans' preferences for negotiating with general hospitals, SSH competitors are performing an increasing share of imaging services within their local markets. Some health plans have refused outright to reimburse physician-owners for expensive ancillary services, which they believe are increasingly prescribed by physicians when there is an ownership interest (Berenson, Bodenheimer, and Pham 2006).
Our results did not show an overall statistical effect of either growing or declining safety-net services among general hospitals. In the case of emergency department services, however, 94% of general hospitals offered them on average throughout the period. On inspection, we found that among the few hospitals that did not have emergency departments at the beginning of the study period, the majority that did add emergency services were located in SSH competitive markets; of those that did not add these services, most were in markets with no SSHs. A major criticism of SSHs is that most do not have emergency departments, leaving full-service hospitals to bear the financial brunt of this relatively unprofitable service. CMS recently issued guidance clarifying that the "Hospital Conditions of Participation in Medicare" requires SSHs to provide emergency service capability. A number of states also have proposed requirements for SSHs to provide 24-hour emergency department services (Jaklevic 2003). While our results do not directly address this important policy issue, they do suggest that in addition to bearing the burden of more complex patients--many of whom are admitted through emergency departments-more community hospitals in competition with SSHs may be adding emergency department services.
A technical point in studies of market entry is the potential for selection bias. For example, if some unobserved factor is driving both a new medical arms race and SSH entry, we cannot definitively establish causality between the competitive entry of SSHs and the growth in high-technology services. No method can completely identify causality from observational data; however, the selection issue is more of a problem in cross-sectional studies, and the longitudinal feature of our models mitigates 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 that may affect provision of services by all general hospitals, regardless of whether they compete with SSHs. What we do know is that SSHs are entering less regulated markets: virtually all SSH growth nationally since 1990 has been in states without certificate of need (CON) laws. Whether SSHs are selecting into markets within unregulated states for reasons that may affect results of this and other studies centered on market effects is an important topic for future research.
This paper has been concerned with whether the entry of specialty hospitals has affected service offerings by acute care general hospitals operating in the same local markets. The evidence generated here demonstrates a strong association between the opening of cardiac and high-technology services by general hospitals and SSH entry. While it is beyond the scope of this paper to assign causation between service provision and SSHs, future research that more precisely addressees the issue of why SSHs enter particular markets and/or which identifies hospitals that are in direct competition with SSHs would be useful. Accomplishing these important research tasks would be aided by more consistent availability of detailed patient-level data from these SSH entrants. Whether increased service competition is enhancing overall market efficiency also has yet to be demonstrated. Through competition, specialty hospitals may exert pressure on local general hospitals to improve their financial performance. This is another important area for continued research; in our future work, we intend to address the question of potential efficiency effects exerted by the growth of physician-owned specialty hospitals.
The authors grate/idly acknowledge comments received from Robert Ohsfeldt, the editor, and two anonymous reviewers; support from Jean M. Mitchell hi identifying specialty hospitals: and research assistance provided by Kyung Hye Kim and by (Tara J. Lewis.
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Kathleen Carey, Ph.D., is an economist at the VA Center for Health Quality, Outcomes and Economic Research in Bedford. Mass., and an associate professor in the Department of Health Policy and Management at Boston University School of Public Health (BUSPH). James F. Burgess, Jr., Ph.D., is a senior investigator at the VA Center for Organization. Leadership and Management Research. and an associate professor in the Department of Health Policy and Management at BUSPH. Gary Y. Young, J.D., Ph.D., is chair and professor in the Department o]Health Policy and Management at BUSPH, and associate director of the VA Center for Organization, Leadership and Management Research. This work was supported hi' a grant from the Agency for Healthcare Research and Quality (# R03 HL16541 01). Address correspondence to Prof Carey at VA Center for Health Quality. Outcomes and Economic Research, 200 Springs Road, Bed/oral, MA 01730. Email. firstname.lastname@example.org
Table 1. Distribution of single specialty hospitals (SSHs) across states in 2004 State All Cardiac Orthopedic SSHs SSHs /surgical SSHs Texas 29 5 24 Louisiana 13 2 10 Kansas 11 2 9 Oklahoma 8 l 7 South Dakota 8 1 7 Arizona 6 2 4 California 6 2 4 Ohio 4 1 3 Idaho 3 0 3 Indiana 3 2 1 All 10 states 90 18 72 Table 2. Distribution of single specialty hospitals across hospitals referral regions Number of general hospitals facing competition from SSHs All SSHs Cardiac SSHs Orthopedic/ Levels of competition surgical SSHs (measured by the number of SSHs in an HRR) 1997 2004 1997 2004 1997 2004 0 940 435 1,239 721 950 495 1 237 205 10 225 227 209 2 7 103 0 64 7 91 3 or more 65 267 0 0 65 215 Table 3. Relationships between service offerings and level of single specialty hospital competition: all SSHs Measure of SSH competition Number of SSHs in market for 2 or Presence of a SSH Service more years Direct competition Angioplasty .6853 *** (.1544) 1.5344 *** (.3617) Cardiac catheterization .6946 ** (.2945) 1.9755 *** (.3029) Outpatient surgery .0526 (.1237) -.3126 (.4827) Outpatient center .0647 (.0869) .6011 *** (.2143) High technology Computed tomography .9841 *** (.1230) 1.3949 ** (.5661) (CT) Magnetic resonance .7642 *** (.1008) 1.6051 *** (.1944) imaging (MRI) Diagnostic radioisotope .1169 (.1504) -.0268(.2730) Positron emission .7409 *** (.1345) 1.4368 *** (.2505) tomography (PET) Single photon emission .0688 (.0875) .3278 (.2046) computed tomography Ultrasound .2543 *** (.0600) .5858 ** (.2850) Extracorporeal shock wave .2598 *** (.0845) .6033 ** (.2665) lithotripter Safety net Emergency department .1705 (.2370) .6395 * (.3779) Trauma center .4691 *** (.1786) 1.0938 *** (.3200) Burn unit .6755 ** (.2895) .9555 (.6827) Urgent care center -.3387 ** (.1662) -.3795 ** (.1825) Emergency psychiatric -.1431 * (.0748) .3122 (.2578) Crisis prevention .0927 (.1581) -.0501 (.2941) Measure of SSH competition Percent of SSH beds in market Service Direct competition Angioplasty 1.2474 *** (.2406) Cardiac catheterization .9601 *** (.2935) Outpatient surgery .0007 (.1442) Outpatient center .2142 ** (.0985) High technology Computed tomography .9768 *** (.3337) (CT) Magnetic resonance .9539 *** (.1399) imaging (MRI) Diagnostic radioisotope .0089 (.0987) Positron emission .4877 ** (.2437) tomography (PET) Single photon emission .1364 (.1101) computed tomography Ultrasound .3091 *** (.0914) Extracorporeal shock wave .2134 (.1396) lithotripter Safety net Emergency department .3423 (.2303) Trauma center .4275 *** (.1495) Burn unit .0828 (.1352) Urgent care center -.0971 (.1087) Emergency psychiatric -.0293 (.1490) Crisis prevention .0249 (.1305) Noses: Covariates include Herfindahl index, case mix, per capita physicians, per capita income, small hospital indicator, and percentages of hospitals in the HRR that are nonprofit, public, teaching, and multihospital system members. Robust standard errors, which are in parentheses, are clustered at the HRR level. * p <.10; ** p <.05; *** p <.01. Table 4. Relationships between service offerings and level of single specialty hospital competition: cardiac SSHs Measure of SSH competition Number of SSHs in market for 2 or Service more years Presence of a SSH Direct competition Angioplasty 1.0477 *** (.3946) 1.7365 *** (.4452) Cardiac catheterization .8546 (.6777) 1.6761 *** (.4521) High technology Computed tomography (CT) 1.4848 *** (.3845) 2.0428 *** (.4301) Magnetic resonance imaging 1.4699 *** (.1997) 1.6760 *** (.2958) (MRI) Diagnostic radioisotope .1171 (.2469) .1330 (.3396) Positron emission 1.5337 *** (.3034) 1.1738 *** (.4262) tomography (PET) Single photon emission .2155 (.2905) .1721 (.2643) computed tomography Ultrasound .2907 * (.1558) .4378 (.3005) Extracorporeal shock wave .1656 (.2991) .2790 (.2635) lithotripter Safety net Emergency department .0502 (.5941) .9199 * (.4993) Trauma center .8181 (.5021) .8056 ** (.3158) Burn unit .7584 (.7472) 2.0228 * (1.0890) Urgent care center -.9299 *** (.3147) -.0166 (.1911) Emergency psychiatric -.2575 (.1895) -.3923 (.3466) Crisis prevention .5268 * (.2741) .1597 (.2955) Measure of SSH competition Percent of SSH Service beds in market Direct competition Angioplasty 1.4000 *** (.3865) Cardiac catheterization .6657 * (.3918) High technology Computed tomography (CT) 1.1458 ** (.4565) Magnetic resonance imaging .9584 *** (.2415) (MRI) Diagnostic radioisotope .0127 (.1123) Positron emission .1883 (.2312) tomography (PET) Single photon emission .1471 (.1941) computed tomography Ultrasound .2161 (.2097) Extracorporeal shock wave .0428 (.0974) lithotripter Safety net Emergency department .5129 * (.2981) Trauma center .3327 (.3067) Burn unit .0300 (.1085) Urgent care center .0756 (.0814) Emergency psychiatric -.1779 (.2123) Crisis prevention -.0134 (.1656) Notes: Covariates include Herfindahl index, case mix, per capita physicians, per capita income, small hospital indicator, and percentages of hospitals in the HRR that are nonprofit, public, teaching, and multihospital system members. Robust standard errors, which are in parentheses, are clustered at the HRR level. * p < .10; ** p < .05; *** p < .01. Table 5. Relationships between service offerings and level of single specialty hospital competition: orthopedic/surgical SSHs Measure of SSH competition Number of SSHs in market for Service 2 or more years Presence of a SSH Direct competition Outpatient surgery .0864 (.1434) -.2280 (.4868) Outpatient center .0965 (.1244) .4797 (**) (.2351) High technology Computed tomography (CT) 1.4846 (***) (.2419) 1.4975 (**) (.6731) Magnetic resonance .9541 (***) (.1328) 1.6206 (***) (.2073) imaging (MRI) Diagnostic radioisotope .1775 (.2180) .0679 (.2784) Positron emission .9215 (***) (.1784) 1.3345 (***) (.2264) tomography (PET) Single photon emission .0695 (.1044) .1948 (.1967) computed tomography Ultrasound .4028 (***) (.1050) .7146 (**) (.2829) Extracorporeal shock .4311 (***) (.1365) .6768 (**) (.2866) wave lithotripter Safety net Emergency department .2560 (.2987) .5590 (.4270) Trauma center .5995 (***) (.1961) 1.1051 (***) (.3442) Burn unit .8092 (**) (.3703) 1.4502 (*) (.7547) Urgent care center -.3404 (*) (.1948) -.4821 (**) (.2087) Emergency psychiatric -.1892 (.1168) .2308 (.2539) Crisis prevention .0402 (.2151) .0764 (.3266) Measure of SSH competition Percent of SSH Service beds in market Direct competition Outpatient surgery -.2173 (.1431) Outpatient center .3325 (**) (.1413) High technology Computed tomography (CT) 1.2321 (.8842) Magnetic resonance 1.3462 (***) (.2899) imaging (MRI) Diagnostic radioisotope .0032 (.1784) Positron emission .8767 (***) (.2330) tomography (PET) Single photon emission .1683 (.1473) computed tomography Ultrasound .4796 (***) (.1204) Extracorporeal shock .5175 (***) (.1583) wave lithotripter Safety net Emergency department .1957 (.3988) Trauma center .5975 (***) (.1702) Burn unit .4086 (.3667) Urgent care center -.3287 (***) (.1030) Emergency psychiatric .0957 (.2213) Crisis prevention .0589 (.2038) Notes: Covariates include Herfindahl index, case mix, per capita physicians, per capita income, small hospital indicator, and percentages of hospitals in the HRR that are nonprofit, public, teaching, and multihospital system members. Robust standard errors, which are in parentheses, are clustered at the HRR level. * p<.10; ** p<.05; *** p<.01.…
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Publication information: Article title: Single Specialty Hospitals and Service Competition. Contributors: Carey, Kathleen - Author, Burgess, James F. - Author, Young, Gary J. - Author. Journal title: Inquiry. Volume: 46. Issue: 2 Publication date: Summer 2009. Page number: 162+. © Not available. COPYRIGHT 2009 Gale Group.
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