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ResearchArticle5.pdf
A Longitudinal Analysis of the Distinction between For-Profit and Not-for-Profit Hospitals in America
Author(s): Sharyn J. Potter
Source: Journal of Health and Social Behavior , Mar., 2001, Vol. 42, No. 1 (Mar., 2001), pp. 17-44
Published by: American Sociological Association
Stable URL: https://www.jstor.org/stable/3090225
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A Longitudinal Analysis of the Distinction between For-profit
and Not-for-profit Hospitals in America*
SHARYN J. POTTER
University of New Hampshire
Journal of Health and Social Behavior 2001, Vol 42 (March): 17-44
Have changes in the hospital industry forced not-for-profit hospitals to become more like for-profit hospitals in measures of efficiency and community service? As a result, are not-for-profit hospitals moving away from their community ser- vice missions? In recent years researchers have asserted that the once-salient distinctions between not-for-profit and for-profit hospitals are quickly eroding and that this convergence threatens the community service that not-for-profit hospitals have historically provided. Neo-institutionalists explain that regulato- ry changes often force differing organization types to pursue similar strategies (Fligstein 1991, 1985; DiMaggio and Powell 1983). Guided by this theory, the present research analyzes if regulatory changes and the implementation of sim- ilar strategies result in not-for-profit andfor-profit hospitals having similar effi- ciency and community service outcomes.
Researchers have vigorously debated the Association 1992b). These teaching programs implications of the fading distinction between provide a substantial amount of care for the for-profit and not-for-profit hospitals. Policy poor (Reuter and Gaskin 1998). analysts, social scientists, and advocates for Some argue that the for-profit hospitals have the poor fear that the remnants of the safety infused a "corporate ethos" in the healthcare network for the poor, uninsured, and underin- system. This "ethos" is evident in the market- sured provided by some not-for-profit hospi- ing plans, information systems, and manage- tals will erode if not-for-profit hospitals ment techniques now found in not-for-profit become indistinguishable from their for-profit hospitals (Light 1986). Numerous communi- counterparts (Burns 1990; Stevens 1989; Starr ties support not-for-profit hospitals with tax- 1982). Not-for-profit hospitals historically payer dollars, income and property-tax exclu- have offered services that were not traditional- sions, and tax-free financing and contributions ly viewed as revenue producing, including (Kane 1993; Fox and Shaffer 1991). Therefore, burn units, neo-natal intensive care, units and many have been concerned that not-for-profit emergency departments (Altman and hospitals will jettison community service in an Shactman 1997; American Hospital attempt to reduce operating costs (Gentry and Association 1992a). Additionally, not-for-prof- Penrod 1998; Morrisey, Wedig, and Hassan it hospitals have accounted for the majority of 1996). Nonetheless, "two decades of research teaching programs (American Hospital has failed to provide definitive empirical evi-
dence on the differences between for-profit
* The author would like to thank the following indi- and nonprofit health care facilities" viduals for their comments and suggestions: (Blumenthal and Weissman 2000:158). E. Kathleen Adams, Edmund R. Becker, Cliff Brown, The existing research analyzing the question Timothy J. Dowd, Blair Gifford, Karen Hegtvedt, of convergence in the hospital industry has two Alex Hicks, Richard Levinson, Rick Rubinson and methodological shortcomings. First, most of Mike Schwartz. I am also grateful to the reviewers the empirical research examines cross-section- and John Mirowsky for their helpful comments and th e rical res rexamines cros-ection insights. Address correspondence to the author at al data or data representing a limited time the Department of Sociology, University of New frame (Kane 1993; Chang andrTuckman 1988). Hampshire, Horton Social Science Center, Durham, In other words, the researchers attempted to NH 03824; e-mail: sharyn.pottergunh.edu. develop a historical argument, but their assess-
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18 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
ments lacked longitudinal data that allowed for care needs. Since 1913, the federal govern- trend analyses. Second, most of these studies ment has differentiated between not-for-profit ignore environmental pressures that may pro- and for-profit hospitals by exempting not-for- mote convergence (Arrington and Haddock profit hospitals from most revenue and proper- 1990; Chang and Tuckman 1988; Herzlinger ty taxes. In exchange for their tax exemption, and Krasker 1987). Typically, they examined not-for-profit hospitals were required to pro- the hospital's internal structure while overlook- vide free or below-cost medical services. In ing environmental factors such as policy, 1969 an Internal Revenue Service ruling
demand, and supply. Researchers who did con- superseded prior regulations and required sider the environment typically examined only merely that not-for-profit hospitals provide one facet (see Norton and Staiger 1994; services that benefit the community in Hultman 1991). exchange for their tax exemption (Fox and
My research addresses these limitations. Schaffer 1991). Therefore, not-for-profit hos- First, I analyze the claims of a narrowing dis- pitals "have historically had an aura of com- tinction between not-for-profit and for-profit
hospitals over a fifteen-year period with the muniy servic ro s utilization of a latent growth curve model that (Gray 1991 :61)
enables me to capture the development of cer- Not-for-profit hospitals are prohibited from tain trends. Additionally, the present research distributing their profits. Instead, profits must uses data from every short-term general hospi- be reinvested in the hospital (Gray 1991; Light tal in the 48 contiguous states. Therefore, the 1986). Alternatively, for-profit hospitals can results capture national trends rather than just distribute their profits to their owners or share- regional trends. Finally, various environmental holders. Consequently, stockholders demand factors, including the role of the larger regula- that for-profit hospitals should behave in a tory environment and internal factors includ- manner that results in profitable financial ing hospital ownership type are investigated. statements (Homer, Bradham, and Rushefsky
1984). Therefore, potential stockholders do not base their purchasing decisions on how well
ARE NOT-FOR-PROFIT AND FOR-PROFIT the hospitals are meeting community needs HOSPITALS CONVERGING? (Rushing 1976). In fact, some for-profit hospi-
tals avoid high-cost, low-profit services like If, as researchers postulated, the distinction outpatient departments, emergency-rooms,
between for-profit and not-for-profit hospitals and teaching programs in an effort to increase is narrowing, what reasons are given to explain hospital profits and stockholder returns this declining distinction? First, some argue (Ginzberg 1988). that the fading differences in the hospitals Public hospitals are an important compo- legal charter is an important factor in explain- nent in the not-for-profit/for-profit hospital ing the possible convergence between hospital debate. Their presence in a community influ- types. Others explain that the changes in the ences the strategies of the other hospitals, both
regulatory environment may promote a declin- for-profit and not-for-profit. Research indi- ing distinction between hospital types. Some cates that public hospitals often care for hypothesize that the hospital's external envi- . r ronment drives similarities across all hospital patients that other hospitals consider undesir- types. Finally, there are mediating processes able. A disproportionate number of their that need to be analyzed in an effort to under- patients are poor, uninsured or Medicaid recip- stand their effects in the possible convergence ients (Brown 1983). between hospital types. My analysis considers Most research on hospitals neglected to look all four of these explanations. at the hospital's legal charter until 1976, when
Rushing (1976) argued that an organization's profit orientation influences organizational
The Hospital s Legal Charter outcomes. However, in recent years some have argued that hospitals' legal charters no longer
Throughout the twentieth century hospitals provide insights into hospitals' operating in the for-profit, not-for-profit, and public strategies (Kane 1993; Fox and Schaffer 1991; health care sectors have met different health Marmor, Schlesinger, and Smithey 1987).
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 19
The Hospital Regulatory Environment patients (American Hospital Association 1994). Furthermore, private insurers soon
The neo-institutionalists hypothesize that began using the Prospective Payment System new legislation introduced to an organization reimbursement rates for their own enrollees population increases the likelihood that iso- (Reinhardt 1998). DiMaggio and Powell morphism (declining differences between (1983) indicate that increased regulatory con- organizational types) will occur. This enables straints force different types of organizations them to demonstrate that changes in the regu- to adopt strategies that result in similar out- latory environment influences organizational comes. In fact, many researchers pointed out responses to local demand and supply condi- that the scaled back Medicare payments forced tions. Therefore, neo-institutionalists postulate not-for-profit hospitals to behave like busi- that organization leaders consider current pol- nesses (Sorrentino 1989; Coddington, Palm- icy as they develop strategies for managing quist, and Trollinger 1985; Waldholdtz 1982). local demand and supply. Furthermore, the Therefore, the widespread adoption of cost- neo-institutionalists argue that the personnel of saving strategies following the passage of the separate organizations adopt similar strategies Prospective Payment System legislation could to comply with regulatory changes (Dowd and be attributed to a declining distinction between Dobbin 1998; Fligstein 1991, 1985; Baron, hospital types. Dobbin, and Jennings 1986).
Significant federal policy. The passage of the Medicare Prospective Payment System leg- The External Environment islation in 1983 initiated the implementation of highly innovative federal health-care cost con- Some argue that the environments in which tainment policy (Reinhardt 1998; Altman and organizations operate are more definitive than Young 1993; Hultman 1991; Rogers, Draper what the institutions call themselves on their and Kahn 1990; McCarthy 1988). The legal charters (Marmor, Schlesinger and Prospective Payment System legislation, Smithey 1987). That is, the hypothetical con- whose purpose is to regulate Medicare reim- vergence between for-profit and not-for-profit bursement marked the beginning of the use of hospitals may actually result from both types price controls at the national level in the hospi- of hospitals facing similar environmental fac- tal industry (Flood and Fennel 1995). tors. For instance, in highly competitive mar-
Until the passage of the Prospective Payment kets, Shortell and colleagues (1986) find that System legislation, hospitals had been using both for-profit and not-for-profit hospitals their own discretion in pricing their services. offer a larger number of alternative hospital The Prospective Payment System legislation services including geriatric care, health pro- eliminated such discretion by authorizing the motion and outpatient diagnostic services. government to establish uniform prices for all Alternately, when physicians are plentiful in a hospital services for Medicare patients, whether given area, hospitals compete for physicians' the treatment was provided at a for-profit or not- patients by increasing amenities for physicians for-profit hospital.' Therefore, the Prospective (e.g., acquiring sophisticated equipment) and Payment System legislation forced both hospital may duplicate services in an effort to attract types to incur costs lower than the reimburse- referrals (Menke 1997; Hadley and Swartz ment amount to make a profit or else suffer the 1989). Finally, research indicates that commu- consequences of a loss (Altman and Young nity wealth can create similarities in different 1993). Additionally, the "reasonable costs" for hospital types in the same communities (see which hospitals were able to bill Medicare prior Becker and Sloan 1985; Becker and Steinwald to the passage of Prospective Payment System 1981; Sloan and Becker 1981). Therefore, I allowed them to offset costly services via analyze those environmental factors that previ- Medicare reimbursement. The Prospective ous research has found to be significant deter- Payment System legislation forced some hospi- minants of hospital strategies. tals to discontinue some of their more costly services (Kauer, Silvers, and Teplensky 1995).
Since Medicare accounts for approximately Mediating Factors 40 percent of all hospital discharges, most hos- pitals were not in a position to refuse Medicare Many studies have analyzed internal factors
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20 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
to determine whether the distinction between staff is also widely accepted as a proxy for hos- hospital types is narrowing (see Arrington and pital efficiency (Arrington and Haddock 1990). Haddock 1990; Herzlinger and Krasker 1987). Hospitals spend approximately 80 percent of I argue that the internal hospital characteristics their costs on labor (Anderson and Kohn 1996) act as mediators in that they are influenced by and can realize more cost savings by eliminat- the hospital type and ultimately influence hos- ing staff positions than by any other mechanism pital outcomes. Thus, for-profit and not-for- (Barrett 1995). Therefore, it is difficult for hos- profit hospitals that share the same internal pitals to earn profits when they have a large hos- characteristics may have similar community pital staff. For-profit hospitals have fewer per- service and efficiency outcomes. Therefore, I sonnel than their not-for-profit counterparts analyze three groups of mediating factors that (Woolhandler and Himmelstein 1997; Sorren- previous research has found to be significant; tino 1989; Light 1986; Watt et al. 1986). How- hospital facility characteristics, hospital prac- ever, as hospitals face an increasingly cost-con- tice characteristics and hospital payor mix. science environment, researchers hypothesize
that both hospital types will use staff reduction as a means of reducing costs.
EFFICIENCY AND COMMUNITY SERVICE AS INDICATORS OF
CONVERGENCE Community-Service Outcomes
In previous studies, researchers have used Compared to other hospital departments, similarities in hospital outcomes to demon- emergency departments are rarely successful strate a convergence between for-profit and profit centers, and hospitals with teaching not-for-profit hospitals (see Herzlinger and commitments generally care for disproportion- Krasker 1987), but they have not simultane- ate numbers of uninsured patients and patients ously analyzed efficiency and community-ser- with serious conditions (Blumenthal and vice outcomes. The present research addresses Weissman 2000; Reuter 1999). Therefore, both this gap by analyzing both efficiency and com- endeavors are seen as community service by munity-service outcomes. hospitals and their communities.
Emergency room utilization. Many see the emergency room as the cornerstone of a hospi-
Efficiency Outcomes tal's provision of community care: Emergency departments employ a specialized medical
Two of the most visible hospital efficiency staff capable of dealing with any medical prob- strategies are reducing costs and reducing the lem 24 hours a day, 7 days a week (Albrecht, size of the hospital staff. Slobodkin, and Rydman 1996). In the past few
Hospital Expenses. Total hospital expenses years, hospitals have seen an increase in are the annual costs incurred to operate the patient demand for emergency-room services hospital. Examples include payroll, adminis- (Williams 1996; General Accounting Office tration, cafeteria, supplies, operating-room, 1993). More than half of the emergency and hospital lab expenses (Morey et al. 1995). department visits made in 1992 were for Hospitals can implement various strategies in nonurgent care (Baker, Stevens, and Brook order to reduce costs. Examples include dis- 1995). The competitive healthcare market has continuing unprofitable services, reducing the forced many community clinics to close, there- average length of stay, and substituting lower- by increasing the number of people seeking skilled hospital personnel. Two prior studies nonurgent care in hospital emergency rooms examined the relationship between hospital (Gordon 2000). In addition to the demand for costs and hospital performance. The first illus- nonurgent care, a high proportion of emer- trated a strong relationship between hospitals gency-department patients are uninsured acci- with low costs and an increased risk of negli- dent and trauma victims. These patients fre- gent injury (Burstin et al. 1993). In the second quently require extensive and costly inpatient study, Hartz and colleagues (1989) found a services, for which hospitals are often unable relationship between a hospital's financial sta- to collect payment (Arrington and Haddock bility and a lower mortality rate. 1990; Committee on Implications of For-prof-
Size of hospital stafT The size of the hospital it Enterprise in Health Care 1986).
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOsPITALs 21
Hospital teaching commitment. The avail- H2: Over the pastfifteen years, all things being ability of training opportunities for medical equal, there has been a convergence in the students, residents, physicians, and other med- nation 's short-term general hospitals as ical professionals is used to proxy a hospital's measured by community service outcomes.
provision of community service. Research has In recent years, however, many researchers shown that hospital training programs are cost- have argued that the cost-containment focus of ly to provide for several reasons (Duffy, the Prospective Payment System legislation
Ruseski, and Cavanaugh 2000; Kuttner 1999; has forced not-for-profit hospitals, like their Reuter 1999; GAO 1989; Morey et al. 1995; for-profit counterparts, to focus on cost-saving Grannemann, Brown, and Pauly 1986; Sloan, strategies in an effort to become more efficient Feldman, and Steinwald 1983). Hospitals with (Altman and Young 1993; Sorrentino 1989).
teaching programs treat a more costly mix of Particular concerns are that these hospitals will patients, maintain larger reserve margins, have cut back on unprofitable services including larger staffs, and offer more extensive treat- emergency rooms and teaching programs. ment options than do nonteaching hospitals Recently scholars have raised concern that not- (Thorpe 1988a; 1988b). These hospitals are for-profit hospitals have begun to discontinue typically not reimbursed the full cost of such these types of services in an effort to reduce care. Furthermore, the cost of attracting and their expenses (Morrisey, Wedig, and Hassan retaining high-quality physicians (Morey et al. 1996). Therefore, I hypothesize that the impact 1995; Custer and Wilke 1991) and maintaining of ownership type decreases as organizations the latest in medical technology (Friedman and adopt similar outcomes to meet regulatory Jorgensen 1994) accounts for higher costs at changes: teaching hospitals. Researchers find that these higher costs often act as a deterrent in hospi- H3: Changes in the regulatory environment
tahs' efforts to attract managed care patients have made hospital ownership less signifi- (Reuter 1999; Reuter and Gaskin 1998). cant in explaining the variation in efficien- cy outcomes in recent years compared with
previous years;
HYPOTHESES H4: Changes in the regulatory environment In recent years some have argued that have made hospital ownership less signifi-
changes in the health care arena have forced cant in explaining the variation in commu- not-for-profit hospitals to become indistin- nity service outcomes in recent years com- guishable from their for-profit counterparts. pared with previous years. Much of the health care literature suggests that when hospitals concentrate on efficiency they do so at the expense of community care. If METHODS indeed this is true, we should expect not-for-
profit hospitals to cut their costs by reducing Models expenses and cutting hospital staffing ratios. We should also expect not-for-profit hospitals Ordinary least squares regression. The data to reduce their provision of community service analysis occurred in two steps. First, for each by, for example, scaling back or closing their cross sectional data set I performed an ordi- emergency departments or reducing the num- nary least squares (OLS) regression with the ber of available teaching opportunities. In two efficiency and two community service other words, knowing the hospital's legal char- outcomes. Each cross-sectional data set differ- ter will not provide insight into the hospital's entiated between the three major hospital efficiency and community service operations. types, for-profit, not-for-profit, and public Therefore, I hypothesize that, hospitals. The OLS regression identified sig-
Therefore, I hypothesize that, nificant environmental and internal character- H1: Over the pastfifteen years, all things being istics that were included in the second step of
equal, there has been a convergence in the my analysis that utilized latent growth curve nation s short-term general hospitals as models (see Wright, Gronfein, and Owens measured by efficiency outcomes, 2000).
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22 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
Latent growth curve model. Using structural YU = aio + adt + ai2 (t2 / 00) + eit, equation models with AMOS 4, 1 examined the relationship between hospital outcomes and where hospital type over time (Arbuckle and Wothke
1997). In particular, I used a latent growth t = Year - 1980 curve model to model changes in the effect of hospital type (e.g., not-for-profit, public) on I analyzed five different models for each the efficiency and community service out- efficiency and community service outcome. comes over the research time frame The first model (see Figure 1) estimated the (1980-1994). The analysis used a merged data association between hospital type and hospital set that combined the four cross sectional data outcome at the baseline of the study, 1980. sets used in the OLS regression analysis. The Additionally, this model estimated the change hospitals that were included in this consolidat- in the association between hospital type and ed data were merged using a unique identifica- the hospital outcome over the fifteen year tion number. As a result of consolidating the research period. Model 2 builds upon model 1 cross sectional data sets, the new data set has a by including the environmental variables to fourth hospital type, those hospitals that estimate the total effect and the change in total change ownership during the study time frame effect with time. The model includes two types (e.g., from not-for-profit in 1980 to for-profit Of environmental variables, population charac- in 1990). teristics and market characteristics. Population In the model the intercept represents the c haracteristics include the unemployment rate,
research baseline period, and it is constant for the per capita income, and the proportion of each hospital across time (Duncan, Duncan, the population that is age 65 and over. Market and Li 1998). The slope term illustrates the characteristics include the proportion of the shape of the hospital's growth and is deter- population that is HMO members, the mined by repeated measures (Duncan et al. Herfindahl index, and the number of hospitals 1998). To complement the linear slope factor, in the state involved in mergers and consolida- each model includes an added growth factor to tions (e.g.with values from 1980, the study account for nonlinear growth. The present baseline).2 models utilize a quadratic growth term to cap- In models 3-5 (see table 2), I include vari- ture differences between the four groups of ables that are affected by hospital type and in hospital types (e.g., for-profit, not-for-profit, turn influenced the hospital efficiency and public, and hospitals that change ownership community service outcomes. In model 3, hos- type): "The added growth factor approach pro- pital facility characteristic variables, including vides a test of the difference in the growth rate hospital size and the ratio of full-time licensed between the [four] groups without having to practical nurses to full-time registered nurses, resort to the use of Lagrange Multiplier or are added to model 2. In model 4, hospital other model modification tests" (Duncan et al. practice characteristics including the surgical 1999:59; Muthen and Curran 1997). operations per adjusted inpatient day, the ratio Additionally, the inclusion of the quadratic of technology services and the average length growth factor improves the root mean square of stay-are added to model 2. Finally, model error of approximation (RMSEA) goodness of 5 combines model 2 and two variables repre- fit index for each of the latent growth curve senting hospital payor mix, Medicare and models in the analysis. Medicaid inpatient days as a proportion of
Each hospital in the analysis implicitly has adjusted inpatient days. its own intercept, linear coefficient, and qua- dratic coefficient, measured from the average one among the consistently for-profit hospi- Sample tals. Those implicit coefficients are taken as latent factors, indicated by the observed The analysis utilizes two types of secondary scores. The fixed factor loadings shown in data: (1) data from the American Hospital Figure 1 correspond to to, t', and t2 respective- Association and (2) data from the Area ly. The loadings on the latent quadratic coeffi- Resource Files. The American Hospital cient are divided by 100 to make the results Association and Area Resource File data sets readable. are two of the most commonly utilized sources
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 23
FIGURE 1. The Latent Growth Curve Model
0, 0, 0, 0,
1 ~~ ~~1 11 0 0 0 0
1980 1985 1990 1994 Expenses Expenses Expenses Expenses per an d Ser Adjusteinal And pe r Adjusted per Adjusted 11Te Admission Admission Admission thissuho
dn al al ps a96
\ Not-For-Profit Public Hospitalsa /
Note: heireerece, caeoyisfrpoit slospetals.
of hoptladdmgahcifrain(e ht fe eea eia n ugclsrie
1981). The American ~~~~HospitalsAscainptet hti es hntit as uhhs
defne aut-crehospitals astoehospiaspitals aritingisedfometlhahan
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24 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
specialty hospitals (American Hospital were found. Finally, in the analysis utilizing Association 1992b). These acute-care hospitals the latent growth curve model, the missing are used in the analysis. Table 1 presents a cases were handled using a maximum likeli- breakdown by type of all U.S. hospitals in each hood estimation procedure with the AMOS 4 of the years covered by this research. program (Katula, Blissmer, and McAuley
The Area Resource File data, compiled by 1999; Arbuckle and Wothke 1997). The maxi- the Bureau of Health Professions, provide mum likelihood estimation procedure allows demographic data for each of the 3,248 coun- missing data to be accounted for in the analy- ties in the contiguous United States. Linking sis by calculating reliable standard errors internal hospital data from the American (Katula, Blissmer, and Mcauley 1999; Muthen, Hospital Association with demographic data Kaplan, and Hollis 1987). from the Area Resource File enables me to analyze the claims of a declining distinction between hospital types in light of data about Measures the hospitals' local environments. The means and standard deviations for the variables used Hospital expenses. Total expenses per in the analysis are presented in the appendix. adjusted admission is the first proxy for hospi-
The merge of the American Hospital tal efficiency. For purposes of standardization, Association and the Area Resource File data I divided the total hospital expense by the files created four separate files of internal and adjusted admissions (an aggregate figure environmental hospital information for every reflecting inpatient and outpatient days). short-term for-profit, not-for-profit, and public Size of hospital staff The number of full- general hospital at four points in time: 1980, time equivalent employees per adjusted daily 1985, 1990, 1994. The variables were speci- census is used as the second proxy for hospital fied identically for each year in the study to efficiency. Full-time equivalents employees ensure an accurate comparison of the relation- include all full and part time hospital personnel ships between the dependent variables and the with the exception of medical residents and independent variables for each of the years in other trainees. The number of full-time equiv- the study. alents employees is standardized using the
Missing data. Since the American Hospital adjusted census, that is, the average number of Association compiles self-reported hospital inpatients and outpatients receiving care dur- data on a voluntary basis from U.S. hospitals, ing a given twelve-month reporting period hospital officials have the option of not pro- (American Hospital Association 1994). viding the requested information. In the OLS Emergency room utilization. The ratio of regression models, those hospitals that did not emergency room visits per adjusted inpatient provide the appropriate data were left out of days is the first community service variable. In the analysis. However, the means and standard order to standardize emergency-room utiliza- deviations of the cases that were not included tion, the number of emergency-room visits was in the analysis were compared with the cases divided by adjusted inpatient days-an aggre- that were retained in the analysis, and no sig- gate figure reflecting both hospital inpatient nificant differences between the two groups and outpatient days.
TABLE 1. Number and Percent of U.S. Hospitals by Type and Year
Entire 1980 1985 1990 1994 Research Period
# % # % # % # % # %
Public Hospital 1,531 30% 1,433 28% 1,333 28% 1,193 27% 1,415 24% Not-for-profit 3,030 59% 3,063 60% 2,909 60% 2,706 62% 3,194 53% Hospital
For-profit hospital 556 11% 620 12% 590 12% 489 11% 697 12% Hospitals Changing 654 11% Ownership Type (e.g., from not-for- profit in 1980 to for-profit in 1990)
Total 5,117 100% 5,116 100% 4,832 100% 4,388 100% 5,960 100%
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 25
Hospital teaching commitment. The extent RESULTS of a hospital's teaching commitment is the sec-
ond proxy for community service. Research The Hospital 's Legal Charter
that focuses on hospitals' teaching status usu-
ally differentiates three levels of teaching corm- What effect does the hospital's legal charter mitment. Therefore, this study uses a weighted have on hospitals' efficiency and community ratio of the three levels of hospital teaching service outcomes? The hospital type intercept
status.3 coefficients in model 1 of Table 2 indicate that,
TABLE 2. Latent Growth Curve Model Regression Weights-Expenses per Adjusted Admission
Model 1 Model 2 Model 3 Model 4 Model 5
Intercept-Not-for-profit Hospital -.028 .021 -.065*** -.085*** .007
(.02) (.02) (.01) (.01) (.01) Intercept-Public Hospital -.258*** .122*** -.076*** -.106*** -.071***
(.02) (.02) (.02) (.01) (.02) Intercept-Hospitals Changing Ownership Type -.212*** .049* -.069*** -.091*** -.053**
(.02) (.03) (.02) (.02) (.02)
Yearly Slope-Not-for-profit Hospital -.014*** -.015*** -.015*** -.014*** -.016***
(.00) (.00) (.00) (.00) (.00) Yearly Slope-Public Hospital -.011*** .006*** -.012*** -.011*** -.013***
(.00) (.00) (.00) (.00) (.00) Yearly Slope-Hospitals Changing Ownership Type -.002 .563*** -.002 -.002 -.003
(.00) (.03) (.00) (.00) (.00) Quadratic Growth-Not-for-profit Hospital .119*** .138*** .122*** .122*** .122***
(.02) (.02) (.02) (.02) (.02) Quadratic Growth-Public Hospital .136*** -.003 .138*** .138*** .138***
(.02) (.00) (.02) (.02) (.02) Quadratic Growth-Hospitals Changing .047 .287*** .049* .048* .049* Ownership Type (.03) (.05) (.03) (.03) (.03)
Intercept-Unemployment Rate -.039* .004** .007*** .002
(.02) (.00) (.00) (.00)
Intercept-Proportion of Population Age 65 and Over -.033 -.156 -.381*** .310*
(.02) (.12) (.10) (.12)
Intercept-Number of Hospital Mergers in the State .004*** .004*** .004*** .003***
(.00) (.00) (.00) (.00) Intercept-Per Capita Income -.299*** .392*** .425*** .545***
(.02) (.03) (.02) (.03) Intercept-Proportion of Population HMO Members -.012*** .382*** .251*** .280***
(.00) (.05) (.04) (.05) Intercept-Hefindahl Index -.544*** -.186*** -.160*** -.298***
(.13) (.02) (.01) (.02) Intercept-Number of Hospital Beds (size) .001***
(.00) Intercept-Ratio of Full Time LPNs to Full Time RNs -.256***
(.03)
Intercept-Surgical Operations per Adjusted Inpatient Day -.424*** (.11)
Intercept-Average Length of Stay .022*** (.00)
Intercept-Ratio of Technology Services .547*** (.01)
Intercept-Medicare Inpatient Days as a Proportion -.364*** of Adjusted Inpatient Days (.04)
Intercept-Medicaid Inpatient Days as a Proportion .645*** of Adjusted Inpatient Days (.06) RMSEA .03 .04 .10 .09 .09 CFI 1.00 1.00 .99 .99 .99 N 5,960 5,960 5,960 5,960 5,960
*~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* p <.05 ** p< .01 *** p< .001
Note: The reference category is for-profit hospitals. Standardized errors are in parenthesis.
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26 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
in 1980, not-for-profit (b = -.028) and public tors and hospital practice characteristics. The (b = -.258, p < .001) hospitals had lower for-profit hospitals are the omitted category expenses than their for-profit counterparts, the and have a value of zero for each time period. reference category. The slope coefficients for From Figure 2, we see that hospital type is a the hospital type indicate that, over time, not- more important predictor of hospital expenses for-profit (b = -.014, p < .001), and public in 1980 than in 1994 when we compare the hospitals (b = -.011, p < .00 1) have signifi- three hospital types against for-profit hospi- cantly lower expenses than their for-profit tals. This finding supports my first hypothesis; counterparts. Furthermore, the significant over the past fifteen years, all things being coefficients indicate that not-for-profit and equal, there has been a convergence in the public hospitals are reducing their expenses at nation's short-term general hospitals as mea- a more rapid growth rate than their for-profit sured by efficiency outcomes. counterparts. This illustrates the not-for-profit Table 3 presents the results of the five latent and public hospitals' focus on efficiency. growth curve models for the second efficiency
In model 2 in Table 2, I add baseline hospi- outcome, full-time equivalents employees per tal environmental factors to model 1. In model adjusted census. Once again, all five models 3, hospital facility characteristics are added to have relatively good fit indicators as indicated model 2. In model 4, hospital practice charac- by the root mean square error of approxima- teristics are added to model 2, and in model 5 tion and comparative fit index (Duncan et al. hospital payor mix indicators are added to 1999; Bentler 1990; Browne and Cudeck model 2. Hospital type remains a significant 1989). The not-for-profit hospital positive predictor of expenses per adjusted admission slope coefficients in models 1-5 (b = .017, b = with the inclusion of both environmental vari- .015, b = .007, b = .022, b = .0 14) indicate that ables and mediating factors. Based on the root over the research time frame, not-for-profit mean square error of approximation, and the hospitals had higher ratios of full-time equiva- comparative fit index, we find that all five lents employees per adjusted census than for- models have relatively good fit indexes profit hospitals. Furthermore the non-signifi- (Duncan et al. 1999; Bentler 1990; Browne cant slope coefficients in all five models indi- and Cudeck 1989). cate that over time not-for-profit and public
In Figure 2, I graphed the predicted values hospitals are experiencing parallel growth for the expenses per adjusted admission by rates in their staffing ratios. hospital type, adjusting for environmental fac- In Figure 3, I graphed the predicted values
FIGURE 2. The Predicted Values of Expenses Per Adjusted Admission by Hospital Type, Adjusting for Environmental and Hospital Practice Characteristics
0.05
160 0.001- C* CO 1 1982 1984 1986 1988 1990 1 -0.05
A -0.10
< L -0.15 CDE 0 0
-0.20
= F -0.25
-0.30 * not-for-profit - - public changed
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 27
FIGURE 3. The Predicted Values of Full-time Equivalent Employees per Adjusted Census by Hospital Type, Adjusting for Environmental and Hospital Payor Mix
L? s 0.50 0.40
0.30
8 W . 0.20
?co'5 010
= _ O.1d9 1982 1984 1986 1988 1990 1992 1
* not-for-prof ft * public A changed
for the full-time equivalent employees per adjusting for environmental factors and hospi- adjusted census by hospital type, adjusting for tal practice characteristics. The for-profit hos- environmental factors and hospital payor char- pitals are the omitted category and have a acteristics. From Figure 3, we see that over the value of zero for each time period. While not- research time frame, not-for-profit and for- for-profit hospitals provided a higher ratio of profit hospitals have similar ratios of full-time emergency-room care than their for-profit equivalent employees per adjusted census. counterparts in 1980, this difference narrows Again, we see that ownership is a more signif- by 1994. From Figure 4, we see that the ratio icant predictor of hospital efficiency outcomes of emergency room visits per adjusted inpa- in 1980 compared to 1994, providing evidence tient days for not-for-profit and for-profit hos- of the convergence between not-for-profit hos- pitals have begun to converge. While not-for- pitals and their for-profit counterparts. profit hospitals are still providing more emer- Therefore, these findings also support my first gency care, ownership is a more significant hypothesis regarding the claims of conver- predictor of this community service outcome gence among short-term general hospitals. in 1980 compared to 1994.
In Table 4 the results of the five latent The hospital ownership regression coeffi- growth curve models for the first community cients from the latent growth curve models for service outcome, ratio of emergency-room vis- the second community-service outcome, the its per adjusted inpatient day, are presented. hospital's teaching commitment, are shown in Analyzing the intercept coefficients in model 1 Table 5. These five models also have good fit of Table 4, we see that in 1980 not-for-profit indicators, as indicated by the root mean (b = .01) and public (b = .042, p < .001) hospi- square error of approximation and comparative tals had a higher ratio of emergency-room vis- fit index (Duncan et al. 1999; Bentler 1990; its per adjusted inpatient day than their for- Browne and Cudeck 1989). The not-for-profit profit counterparts. The difference is signifi- intercept coefficients in models 1 through 5 cant in models 3-5 for not-for-profit hospitals, (b = .124,p < .001, b = .143,p < .001; b =.045, and the difference is significant for public hos- p < .001; b = .070,p < .001; b = .137,p < .001) pitals in all five models. All five models have indicate that, in 1980, the not-for-profit hospi- relatively good fit indicators, as indicated by tals had a higher teaching commitment than the root mean square error of approximation their for-profit hospital counterparts. and comparative fit index (Duncan et. al. 1999; Analyzing the slope coefficients for the not- Bentler 1990; Browne and Cudeck 1989). for-profit hospitals in models 1 through 5, (b =
In Figure 4, I graphed the predicted values .003, p < .05; b = .003, p < .05; b = .003, p < for the ratio of emergency room visits by .01; b = .003,p < .01; b =.003,p < .05) we see adjusted inpatient days by hospital type, that, over the research time frame, the not-for-
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28 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
TABLE 3. Latent Growth Curve Model Regression Weights-Full Time Equivalent Employees per Adjusted Census
Model 1 Model 2 Model 3 Model 4 Model 5
Intercept-Not-for-profit Hospital -.016 .068 -.016 .122** .150** (.05) (.05) (.05) (.05) (.05)
Intercept-Public Hospital .041 .314*** .265*** .426*** .414*** (.06) (.06) (.06) (.05) (.06)
Intercept-Hospitals Changing Ownership Type .029 .247*** .207** .302*** .303*** (.07) (.07) (.06) (.06) (.06)
Yearly Slope-Not-for-profit Hospital .017 .015 .007 .022 .014 (.02) (.02) (.02) (.02) (.02)
Yearly Slope-Public Hospital .021 .019 .022 .041* .019 (.02) (.02) (.02) (.02) (.02)
Yearly Slope-Hospitals Changing Ownership Type .020 .018 .019 .036 .019 (.02) (.02) (.02) (.02) (.02)
Quadratic Growth-Not-for-profit Hospital -.214 -.199 -.197 -.202 -.195 (.11) (.11) (.11) (.11) (.11)
Quadratic Growth-Public Hospital -.276* -.261* -.258* -.263* -.254* (.12) (.12) (.12) (.12) (.12)
Quadratic Growth-Hospitals Changing -.299* -.285* -.287* -.292* -.283* Ownership Type (.14) (.14) (.14) (.14) (.14)
Intercept-Unemployment Rate -.002 -.004 -.006 .008 (.01) (.01) (.01) (.01)
Intercept-Proportion of Population Age 65 and Over -3.687*** -3.249*** -1.097** -7.358*** (.43) (.42) (.38) (.41)
Intercept-Number of Hospital Mergers in the State .001 .001 .001 -.003* (.00) (.00) (.00) (.00)
Intercept-Per Capita Income .632*** .379*** .433*** .926*** (.09) (.09) (.08) (.09)
Intercept-Proportion of Population HMO Members .850*** .948*** .701 *** .704*** (.18) (.18) (.15) (.17)
Intercept-Hefindahl Index -.237*** -.100 -.134** -.155** (.05) (.05) (.05) (.05)
Intercept-Number of Hospital Beds (size) .001*** (.00)
Intercept- Ratio of Full Time LPNs to Full Time RNs -.499*** (.09)
Intercept-Surgical Operations per Adjusted Inpatient Day 2.911 * (.43)
Intercept-Average Length of Stay -.058*** (.00)
Intercept-Ratio of Technology Services .464*** (.05)
Intercept-Medicare Inpatient Days as a Proportion 2.592*** of Adjusted Inpatient Days (.11)
Intercept-Medicaid Inpatient Days as a Proportion 1.345*** of Adjusted Inpatient Days (.19) RMSEA .06 .04 .09 .06 .09 CFI 1.00 1.00 .99 1.00 .99 N 5,960 5,960 5,960 5,960 5,960
* <.05 **p <.01 ***p <.001 Note: The reference category is for-profit hospitals. Standardized errors are in parenthesis.
profit hospitals are continuing to provide sub- dent that not-for-profit hospitals are not aban- stantially more teaching service than their for- doning their community-service mission as profit counterparts. they pursue efficiency strategies. Therefore,
Finally, Figure 5, the graph of the predicted these findings do not support my second values of the ratio of the hospital's teaching hypothesis. commitment by hospital type, adjusting for environmental and mediating factors illus- trates the absence of a convergence between The Hospital Regulatory Environment not-for-profit and for-profit hospitals over the research period. From these results it is evi- Do changes in the regulatory environment
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 29
FIGURE 4. The Predicted Values of the Ratio of Emergency Room Visits by Hospital Type, Adjusting
for Environmental and Hospital Practice Characteristics
*.I 0.12 E 0>
CL csX0.10
008
*u 0.02
> 0.00
1980 1982 1984 1986 1988 1990 1992 1994
* not-for-profit * public * changed
affect hospital efficiency and community ser- incurring these extra costs, they were increas-
vice outcomes? In model 1 of Table 2, the neg- ing their bottom line.
ative coefficients for not-for-profit (b = -.028) From the predicted values of expenses per
and public hospitals (b = -.258) from the latent adjusted admission by hospital type graphed in growth curve model indicate that in 1980 the Figure 2, we see that following the 1983 pas- for-profit hospitals, the reference category, sage of the Prospective Payment System legis- were benefiting more from the reimburse- lation the expenses per adjusted admission for
each hospital type converged with for-profit ments than their counterparts; that is, the for- hospitals. That is the various hospital types profit hospitals were incurring higher expens implemented similar strategies in an attempt to es. Prior to the passage of the Prospective reduce their expenses in order to work under
Payment System legislation, the administrators the newly imposed price controls. These find-
at for-profit hospitals knew that they would be ings support my third hypothesis: Changes in
reimbursed for these higher expenses. By the regulatory environment have made hospital
FIGURE 5. The Predicted Values of the Ratio of the Hospital's Teaching Commitment by Hospital Type, Adjusting for Environmental and Hospital Practice Characteristics
C I- 0.12
M2 E0.10
_o 0.08
C0.O .6
0.04
0.02
0.00 I I l I l
8 1980 1982 1984 1986 1988 1990 1992 1994
- not-for-proft * public A changed
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30 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
TABLE 4. Latent Growth Curve Model Regression Weights-Ratio of Emergency Room Visits per Adjusted Inpatient Day
Model 1 Model 2 Model 3 Model 4 Model 5
Intercept-Not-for-profit Hospital .010 .015 .035*** .047*** .020* (.01) (.01) (.01) (.01) (.01)
Intercept-Public Hospital .042*** .058*** .074*** .083*** .065*** (.01) (.01) (.01) (.01) (.01)
Intercept-Hospitals Changing Ownership Type .021 .036** .052*** .055*** .040*** (.01) (.01) (.01) (.01) (.01)
Yearly Slope-Not-for-profit Hospital .000 -.001 .001 .001 .000 (.00) (.00) (.00) (.00) (.00)
Yearly Slope-Public Hospital .005 .005 .004 .004 .005 (.00) (.00) (.00) (.00) (.00)
Yearly Slope-Hospitals Changing Ownership Type .012*** .012*** .011** .012*** .012*** (.00) (.00) (.00) (.00) (.00)
Quadratic Growth-Not-for-profit Hospital -.029 -.027 -.027 -.027 -.027 (.02) (.02) (.02) (.02) (.02)
Quadratic Growth-Public Hospital -.040 -.040 -.040 -.040 -.040 (.02) (.02) (.02) (.02) (.02)
Quadratic Growth-Hospitals Changing -.074** -.073** -.071* -.073** -.072** Ownership Type (.03) (.03) (.03) (.03) (.03)
Intercept-Unemployment Rate .008*** .009*** .008*** .009*** (.00) (.00) (.00) (.00)
Intercept-Proportion of Population Age 65 and Over -.933*** -1.056*** -.905*** -1.193*** (.08) (.08) (.08) (.08)
Intercept-Number of Hospital Mergers in the State .000 .000 .001 .000 (.00) (.00) (.00) (.00)
Intercept-Per Capita Income .008 .028 .034 .020 (.02) (.02) (.02) (.02)
Intercept-Proportion of Population HMO Members .177*** .149*** .182*** .173*** (.04) (.03) (.03) (.04)
Intercept-Hefindahl Index .025* -.012 -.017 .028** (.01) (.01) (.01) (.01)
Intercept-Number of Hospital Beds (size) .000*** (.00)
Intercept-Ratio of Full Time LPNs to Full Time RNs -.069*** (.02)
Intercept-Surgical Operations per Adjusted Inpatient Day .182* (.08)
Intercept-Average Length of Stay -.009*** (.00)
Intercept-Ratio of Technology Services -.127*** (.01)
Intercept-Medicare Inpatient Days as a Proportion .127*** of Adjusted Inpatient Days (.02)
Intercept-Medicaid Inpatient Days as a Proportion -.030 of Adjusted Inpatient Days (.04) RMSEA .01 .03 .09 .06 .09 CFI 1.00 1.00 .98 1.00 .99 N 5,960 5,960 5,960 5,960 5,960
*p <.05 **p< .01 *** <.001 Note: The reference category is for-profit hospitals. Standardized errors are in parenthesis.
ownership less significant in explaining the full-time equivalents employees per adjusted variation in efficiency outcomes. census. These findings also support my third
Figure 3, the graph of the predicted values hypothesis regarding regulatory change and of the full-time equivalent employees per convergence, as the hospitals exhibit similar adjusted census, indicates that following the growth rates in the wake of the Prospective 1983 passage of the Prospective Payment Payment System legislation. System legislation hospitals adopted similar When we examine the effect of regulatory strategies that resulted in not-for-profit and change on hospital community service out- for-profit hospitals having similar ratios of comes we find mixed results. Figure 4 is the
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 31
graph of the predicted values of the ratio of community service outcomes in recent years emergency room visits per adjusted inpatient compared with previous years.
day (the graph of model 3 in Table 4). In 1985,
following the 1983 implementation of the Prospective Payment System legislation, we The External Environment and Mediating see that the not-for-profit hospitals' ratio of Factors (Internal Hospital Characteristics) emergency room services began to decline. By 1994 the not-for-profit hospitals were provid- What effects do the external environment ing slightly more emergency room care than and hospital internal characteristics have on
their for-profit counterparts. These findings hospital efficiency and community service
support my fourth hypothesis: Changes in the outcomes? Figure 6 illustrates that much of the regulatory environment have made hospital differences in expenses per adjusted admission ownership less significant in explaining the between not-for-profit and for-profit hospitals variation in community service outcomes in are attributable to baseline differences in the recent years compared with previous years. demographics of the service population and
When we analyze the effect of regulatory differences in the hospital payor mix. By con- change on the not-for-profit hospitals' teach-
ing commitment we see different results. From .troln 'for these actors, ft d ifens Figure 5, the graph of the predicted values of between not-for-profit and for-profit hospitals Fiur . th grap of th prdce vlue of in this efficiency measure decreased over the the hospitals' teaching commitment (the graph intch of model 4 in Table 5), we can see that since period. 1980 not-for-profit hospitals have had a larger In Figure 7, we compare the effects of con- teaching commitment than their for-profit trolling for baseline differences in the hospi-
counterparts. Furthermore, the not-for-profit tal'sexternal environmentcand hospitalepractice hospitals did not reduce their teaching com- characteristics including the number of surgi- mitments following the passage of the cal operations per adjusted inpatient day, the Prospective Payment System legislation. average length of stay and the ratio of technol- Therefore, these findings do not support my ogy services on the hospitals' community fourth hypothesis: Changes in the regulatory service outcome. Figure 7 indicates that differ- environment have made hospital ownership ences in the for-profit and not-for-profit hospi- less significant in explaining the variation in tals' provision of emergency care increased
FIGURE 6. Not-for-profit Hospitals Compared to For-profit Hospitals
0.04
T X 0.02 -
< 0.00 -\|||I|/
] as 1 980 1982 1984 1986 1988 1990 2 1994 ? -0.02- ~0
-0.04
X 0 -0-06
Mb S -0.08
* not-for-profit without adjustments
U not-for-profit adjusting for baseline demographics and hospital payor ray
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32 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR TABLE 5. Latent Growth Curve Model Regression Weights-Ratio of Hospital's Teaching
Commitment
Model 1 Model 2 Model 3 Model 4 Model 5
Intercept-Not-for-profit Hospital .124*** .143*** .045*** .070*** .137*** (.01) (.01) (.01) (.01) (.01)
Intercept-Public Hospital .063*** .139*** .092*** .104*** .123*** (.01) (.01) (.01) (.01) (.01)
Intercept-Hospitals Changing Ownership Type .048*** .000*** .058*** .063*** .094*** (.01) (.01) (.01) (.01) (.01)
Yearly Slope-Not-for-profit Hospital .003* .003* .003** .003** .003* (.00) (.00) (.00) (.00) (.00)
Yearly Slope-Public Hospital .002 .002 .002 .002 .002 (.00) (.00) (.00) (.00) (.00)
Yearly Slope-Hospitals Changing Ownership Type .000 .000 .001 .001 .000 (.00) (.00) (.00) (.00) (.00)
Quadratic Growth-Not-for-profit Hospital -.015* -.016* -.015 -.015 -.016* (.01) (.01) (.01) (.01) (.01)
Quadratic Growth-Public Hospital -.014 -.014 -.013 -.014 -.014 (.01) (.01) (.01) (.01) (.01)
Quadratic Growth-Hospitals Changing -.006 -.006 -.007 -.007 -.007 Ownership Type (.01) (.01) (.01) (.01) (.01)
Intercept-Unemployment Rate -.001 -.003*** -.001 -.003* (.00) (.00) (.00) (.00)
Intercept-Proportion of Population Age 65 and Over -.509*** -.066 -.099 -.190* (.10) (.07) (.08) (.09)
Intercept-Number of Hospital Mergers in the State .000 .001* .000 .000 (.00) (.00) (.00) (.00)
Intercept-Per Capita Income .110*** -.038* .014 .114*** (.02) (.02) (.02) (.02)
Intercept-Proportion of Population HMO Members -.126** -.025 -.155*** -. 136*** (.04) (.03) (.03) (.04)
Intercept-Hefindahl Index -.151 -.015 -.039*** -.146*** (.01) (.01) (.01) (.01)
Intercept-Number of Hospital Beds (size) .001 *** (.00)
Intercept-Ratio of Full Time LPNs to Full Time RNs -.086*** (.02)
Intercept-Surgical Operations per Adjusted Inpatient Day -.720*** (.08)
Intercept-Average Length of Stay .001** (.00)
Intercept-Ratio of Technology Services .507*** (.01)
Intercept-Medicare Inpatient Days as a Proportion -.167*** of Adjusted Inpatient Days (.03)
Intercept-Medicaid Inpatient Days as a Proportion .385*** of Adjusted Inpatient Days (.04) RMSEA .03 .02 .09 .06 .09 CFI 1.00 1.00 .99 1.00 .99 N 5,960 5,960 5,960 5,960 5,960
* p< .05 ** p< .01 *** p <.001 Note: The reference category is for-profit hospitals. Standardized errors are in parenthesis.
when I controlled for hospital baseline demo- that hospitals in areas with lower concentration graphics and hospital practice characteristics. (generally areas with large numbers of hospi-
Table 6 provides the OLS regression coeffi- tals) have higher expenses than those hospitals cients for both efficiency outcomes, the in areas with higher hospital concentration (see expenses per adjusted admission, and the full- Menke 1997). The positive and significant time equivalent employees per adjusted cen- coefficients for the unemployment rate (equa- sus. A negative coefficient on the Herfindahl tions 1-4, b = 23, p < .001; b = 21, p < .001; Index for all four study years (equations 1-4, b = 41,p < .001; b = 63,p < .001) indicate that b = -384, p < .001; b = -397 p < .001; b = hospitals in areas with high unemployment are -561; p < .001; b = -522; p < .001) indicates more likely to incur the higher expenses per
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 33
FIGURE 7. Not-for-profit Hospitals Compared to For-profit Hospitals
0.06
0.04-
0.02 -
0 *-
C) C a
0.00 -
CD (~1982 1984 1986 198899
-*- not-for-pofit hos ptds without austmens
-U not-for-pofit hos piths alus tin for to; hine cbtu~ ics hos pith
ltice dwra~tis tac
adjusted admission for treating patients with- p < .001; b = .l128, p < .001; b = .O64, p < .001; out insurance. b = .056, p < .00 1). Finally, my results indicate
In Table 7, the OLS regression coefficients that the higher the hospitals teaching commit- for the community service outcome, the ratio ment, the higher the proportion of Medicaid of emergency-room visits per adjusted inpa- patients (b = .294, p < .001; b = .069, p < .05; tient day are provided. In equations 1-4, we b = .150, p< .001; b= .084, p< .01). see that an increase in the proportion of the population aged 65 and over has a negative effect on emergency-room utilization (b = DISCUSSION
-.35,p< .01;b= -1.21,p< .001,b=-1.11; p < .001; b = -1.70, p < .00 1). Equations 14 The External Environment and Mediating indicate a positive relationship between the Factors UInternal Hospital Characteristics) unemployment rate and the ratio of emer- gency-room visits per adjusted inpatient day. My research demonstrates the importance of In other words, an increase in the unemploy- controlling for the external hospital environ- ment rate increases emergency room utiliza- ment and mediating factors. Without control- tion (b =.Ol, p < .001; b = .Ol, p < .001; b = ling for these factors we lose sight of how they .02, p < .001; b =.01, p < .00 1). influence the community service and efficien-
In equations 14 in Table 6 we see that hos- cy outcomes. For example, when we analyze pitals with higher ratios of licensed practical efficiency outcomes we see that the variation nurses to registered nurses had lower expenses between not-for-profit and for-profit hospitals per adjusted admission (b =-8 18, p <.001; b= decreases over the research period when we -1 l29,p <.001; b=-lO87,p <.001; b=-322, control for the environmental and mediating p < .001). Hospitals with longer lengths of stay factors. Alternatively, when looking at commu- have higher expenses per adjusted admission nity service outcomes we see that when con- (b = 85.l7,p < .001; b = i3.38,p < .001; b = trolling for these factors the difference 74.25, p < .001; b = 75.55, p < .001). Finally, a between not-for-profit and for-profit hospitals' higher ratio of technology services available at provision of community service is more pro- the hospital results in higher total expenses per nounced-not-for-profit hospitals are providing adjusted admission (b = 1,009, p < .001; b = more community service than their for profit
1,326,p <.001; b= 1,185,p <.001; b =1,116, counterparts. p <. .01). Additionally, the results of controlling for
In Table 7, equations 5-8 we see that hospi- the external environment and mediating fac- tals with a high ratio of technology services tors are consistent with prior research and thus have a higher teaching commitment (b = .142, substantiate my models. For instance, my
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34 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 35
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38 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
results indicate an increase in per capita The 1983 Prospective Payment System leg- income is also associated with higher expenses islation marked the first time in the history of per adjusted admission. This finding is consis- the hospital industry that hospitals were forced tent with previous findings that for-profit hos- to accept price controls. Prior to the passage of pitals choose to locate in affluent areas this legislation, not-for-profit hospitals had lit- (Norton and Staiger 1994) and that hospital tle incentive to look for more efficient ways to offerings are often a reflection of the wealth in provide patient care. Medicare and other third the hospital community (Sloan and Becker party insurance payors were reimbursing hos- 1981). Consistent with previous studies, my pitals for virtually all the costs incurred for an results indicate that people aged 65 and over episode of patient care. Therefore, one could seek emergency-room care at a lower rate than conclude that passage of the Prospective other sectors of the population (Tyrance, Payment System legislation prompted the not- Himmelstein, and Woolhandler 1996). for-profit hospitals to pursue efficiency strate- Alternatively, my findings show that emer- gies. My research supports these assertions as gency department utilization increases when we see not-for-profit and for-profit hospitals there is an increase in the unemployment rate converging in terms of their efficiency out- in the hospital community. For most people, comes following the passage of the health insurance is coupled with their employ- Prospective Payment System legislation. These ment (Altman, Reinhardt, and Shields 1998). findings are consistent with recent work by Previous research has established that emer- neo-institutionalists who suggest that efficien- gency rooms are sources of care for people cy is shaped by the regulatory environment; without regular health care access (Albrecht et that is, organizations do not entertain certain al. 1996). efficiency solutions until policy change occurs
My research substantiates prior studies that (see Scott 1995). indicate substituting lower paid licensed prac- Alternately, using the latent growth curve tical nurses for higher paid registered nurses model results, an assessment of the conver- enables hospitals to decrease their labor costs gence in hospital types for the community-ser- (Woolhandler and Himmelstein 1997). vice outcomes provides mixed evidence for the Additionally, the results corroborate prior claims that hospitals are reducing community research, as my findings indicate that it is care in an effort to reduce their expenses. In expensive for hospitals to acquire and maintain fact, over the fifteen-year period in this analy- the latest technology (Steiner et al. 1997; sis, not-for-profit hospitals continued to pro- Newhouse 1993). However, teaching hospitals vide substantially more community service as want to offer the latest in medical technology measured by the not-for-profit hospitals' to train new physicians (Friedman and teaching commitment compared to their for- Jorgensen 1994). Finally, my research supports profit counterparts, and they continue to pro- prior research that indicates the higher the hos- vide slightly more emergency care. These find- pitals' teaching commitment the higher the ings are not consistent with neo-institutional proportion of Medicaid patients (Morey et al. theory and leave many questions unanswered. 1995; Thorpe 1988a, 1988b). Why would convergence between these two
hospital types occur in terms of efficiency but not in terms of community service? Some may
The Hospital Regulatory Environment hypothesize that community service is tightly coupled with a hospital's legal charter. In fact,
Neo-institutionalists assert that isomor- the mission statements of many not-for-profit phism occurs when regulatory changes force hospitals specifically mention the hospital's different types of organizations to pursue sim- responsibility to its community. The findings ilar strategies (Fligstein 1991, 1985). The pre- suggest that not-for-profit hospitals can simul- sent research analyzes if the regulatory taneously pursue both efficiency and commu- changes generate similar strategies that result nity service strategies. in similar organizational outcomes. If indeed neo-institutionalists' predictions are accurate, the hospitals' legal charters would be a less The Hospital a Legal Charter significant predictor of hospital outcomes fol- lowing legislative change in the industry. Prior research indicates that when hospitals
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 39
behave in a manner that does not coincide with their legal charters there are many policy implications. Furthermore, researchers empha- size that hospital efficiency and community service are inversely related and assert that hospital efficiency comes at the price of com-
munity care (Kane 1993). As explained earlier, all not-for-profit hospitals receive the same property and revenue tax exemptions, regard- less of their location. Critics question whether it is cost effective for communities and all lev- els of government to continue to support hos- pitals through tax exemptions, which are esti-
mated to be in the billions of dollars (Kane 1993; Fox and Schaffer 1991). Many critics insist that not-for-profit hospitals should not be eligible for tax exemptions if indeed a con- vergence is occurring in the hospital industry. Others argue that we should not discontinue the exemption; instead we should hold hospi- tals accountable for their actions and penalize hospitals that are not acting responsibly.
The present research empirically analyzes the hypotheses of convergence between not- for-profit and for-profit hospitals in the con- text of both internal and environmental factors. The research covers a fifteen-year period. Its scope thus enables me to more accurately assess the presence or absence of convergence in the hospital industry. Prior research was lim- ited in both time frame and environmental fac- tors. My findings clearly demonstrate that not- for-profit and for-profit hospitals are converg- ing in terms of efficiency outcomes. However, I find mixed evidence that not-for-profit hos- pitals are abandoning their community-service missions as they become more efficient. In fact, I find evidence that not-for-profit hospi- tals are simultaneously pursuing efficiency and community service. We should find comfort that, to date, not-for-profit hospitals are giving back to their communities. However, further research is necessary to find incentives to ensure not-for-profit hospitals do not slip off the so-called "community service path" as they face increasing cost-containment pressures from their environments.
Finally, we have begun to see an increase in
the sale of not-for-profit hospitals to for-profit
entities (Shactman and Altman 1998; Claxton et al. 1997). As not-for-profit hospitals become more efficient, as evident in this research, they also become more attractive to for-profit own- ers. Additionally, as this research indicates,
for-profit hospitals are more likely to provide
less community service. Policies must be in
place to ensure that communities receive bene- fits as their "more attractive" not-for-profit
hospitals are purchased by for-profit organiza- tions and the community service mission is replaced by a profit motive.
NOTES
1. Small variations in Medicare capital pay- ments per case accounted for hospital out- liers including geographic locations, case
mix, larger teaching hospital, and whether the hospital is the sole community facility (Kauer, Silvers, and Teplensky 1995).
2. I use a Herfindahl Index calculated by uti- lizing inpatient days. This enables me to
capture the hospital's actual market share
rather than Hospital A's available beds as a share of all beds in Hospital A's market (Zwanziger, Melnick, and Eyre 1994). In this analysis, the Herfindahl Index ranges from .02 to 1. Hospitals in areas with low market concentration (a large number of hospitals) have a Herfindahl Index approaching .02; those that have no local competitors have a Herfindahl Index of 1.
3. This study uses a weighted ratio of the three levels of hospital teaching status. Membership in the Council of Teaching Hospitals signifies the highest level of teaching commitment, medical-school affiliation represents the second-highest commitment to medical training, and the presence of an internship or residency pro- gram represents the lowest level of teaching commitment. Hospitals may offer all three, two, one or none of the specified teaching opportunities.
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40 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
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THE DISTINCTION BETWEEN FOR-PROFIT AND NOT-FOR-PROFIT HOSPITALS 41
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44 JOURNAL OF HEALTH AND SOCIAL BEHAVIOR
Patients." Journal of Health and Social Behavior 41:68-90.
Zwanziger, Jack, Glenn A. Melnick and Lisa
Simonson. 1996. "Differentiation and Specialization in the California Hospital Industry." Medical Care 34:361-372.
Sharyn J. Potter is Assistant Professor of Sociology at the University of New Hampshire. Her research focuses on the hospital industry, health care policy and social inequalities in health care. She is currently working on several research projects. One study analyzes the role of for-profit hospitals in rural areas. Another longitudinal study examines the careers of women hospital administrators.
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- Contents
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- Issue Table of Contents
- Journal of Health and Social Behavior, Vol. 42, No. 1 (Mar., 2001), pp. i-vi+1-113
- Volume Information [pp. 111-113]
- Front Matter [pp. i-iv]
- Message from the New Editor [pp. v-vi]
- Social Structure, Medicine, and Health Care
- The Profession of Medicine and the Public: Examining Americans' Changing Confidence in Physician Authority from the Beginning of the 'Health Care Crisis' to the Era of Health Care Reform [pp. 1-16]
- A Longitudinal Analysis of the Distinction between For-Profit and Not-for-Profit Hospitals in America [pp. 17-44]
- Economic Change and Health Benefits: Structural Trends in Employer-Based Health Insurance [pp. 45-63]
- Mental Health and Mental Illness
- Modeling Processes in Recovery from Mental Illness: Relationships between Symptoms, Life Satisfaction, and Self-Concept [pp. 64-79]
- Status, Role, and Resource Explanations for Age Patterns in Psychological Distress [pp. 80-96]
- Self-Efficacy and Smoking Behavior
- Changes in Self-Efficacy and Readiness for Smoking Cessation among Women with High School or Less Education [pp. 97-110]
- Back Matter
