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1. Do For-Profit and Not-for-Profit Nursing Homes Behave Differently?.......................................................... 1
Bibliography...................................................................................................................................................... 15
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Aaronson, William E; Zinn, Jacqueline S; Rosko, Michael D
The Gerontologist 34. 6 (Dec 1994): 775-86.
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The purpose of this study was to examine behavioral differences between for-profit (FP) and not-for-
profit (NFP) nursing homes. Previous studies have failed to establish consistent behavioral differences. This
study uses a simultaneous equation model to control for potential endogeneity among system variables, with
model parameters estimated using 3SLS. The study provides evidence that NFPs provide significantly higher
quality of care to Medicaid beneficiaries and to self-pay residents than do FPs, as evidenced by better staffing
and better outcomes among nursing homes with residents at higher risk for adverse outcomes. [PUBLICATION
ABSTRACT]
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Headnote The purpose of this study was to examine behavioral differences between for-profit (FP) and
not-for-profit (NFP) nursing homes. Previous studies have failed to establish consistent behavioral differences.
This study uses a simultaneous equation model to control for potential endogeneity among system variables,
with model parameters estimated using 3SLS. The study provides evidence that NFPs provide significantly
higher quality of care to Medicaid beneficiaries and to self-pay residents than do FPs, as evidenced by better
staffing and better outcomes among nursing homes with residents at higher risk for adverse outcomes. Key
Words: Ownership, Care staffing, Quality, Adverse outcomes, Case mix, Payer mix O'Brien, Saxberg, and
Smith (1983) asked the question, "For-profit or not-for-profit, does it matter?" Several studies have assessed
differences between for-profit (FP) and not-for-profit (NFP) nursing homes in terms of access, cost, efficiency,
and quality. While these studies have focused on the influence of ownership on nursing home behavior,
consistent behavioral differences between FP and NFP nursing homes have not been established (Davis,
1991). The lack of consistent results may in part be related to the use of analytical techniques which do not
control for potential endogeneity among case and payer mix, payment rates, and facility characteristics (Lee,
Birnbaum, &Bishop, 1983). This study investigates behavioral differences between FP and NFP nursing homes
in Pennsylvania by using a simultaneous equation model to control for the effects of endogeneity. In assessing
differences between FP and NFP nursing homes, it is useful to identify the comparative effectiveness of each
ownership type. Organizations are effective to the extent that they identify and meet the needs of multiple
constituents (Zammuto, 1982), including customers, potential customers, regulators, and payers. Nursing
homes perform a social function that exposes them to public scrutiny. The use of nursing home services is
considered by many to be undesirable, but possibly inevitable. Thus, access to and quality of nursing home
care are important public policy issues. Second, nursing homes are the recipients of public money through the
Medicare and Medicaid programs. Thus, government has a stake in the cost-effective operation of nursing
homes. Third, NFP nursing homes are publicly subsidized through tax exemptions, including tax-exempt capital
financing. Thus, NFPs have added responsibilities to provide substantive community benefits related to their
tax-exempt status (American Association of Homes for the Aging, 1993). Empirical Studies of Nursing Home
Ownership O'Brien et al. (1983) reviewed several studies of differences in FP and NFP status that focused on
the influence of ownership on nursing home behavior. The predominant finding of the studies reviewed was that
NFP homes had higher quality, but lower efficiency (higher costs). Fottler, Smith, and James (1981) had
concluded that quality and profitability were antithetical concepts and that administrators who were required to
maximize profits faced a dilemma when state regulatory agencies imposed minimum quality standards. O'Brien
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et al. (1983) also noted that NFP facilities may (1) purposefully operate at a deficit over a long period of time; (2)
have a restricted constituency; and (3) enjoy a measure of support from the sponsoring organization. Thus,
higher costs necessary to support higher quality are acceptable to NFPs, and also beneficial in attracting self-
pay patients. Since many NFP nursing homes have religious affiliations, they may focus on specialized market
niches defined by the denominational constituency. Religious affiliation may also project an image of high
quality and compassionate care, which in turn would provide a competitive advantage in the self-pay market.
While Cohen and Dubay (1990) did not find theoretical justification to hypothesize higher self-pay use rates in
NFPs, they speculated that higher quality offered by NFPs may be associated with greater private demand in
NFPs. Ullman (1987), in a study of the behavior of nursing home administrators, proposed that administrators of
FP nursing homes have an incentive to maximize facility profits subject to a minimum quality constraint.
However, NFP nursing home administrators may pursue objectives that enhance personal prestige by
increasing the quantity and quality of services in the facility. Thus, staffing may appear in the maximand of the
objective function of NFP facilities. By contrast, staffing may be viewed as a cost to be controlled in profit-
maximizing FP facilities. While a number of studies have suggested that NFP status may be associated with
better staffing and higher quality of service (Davis, 1991; Greene &Monahan, 1981), Zinn, Aaronson, and Rosko
(1993), who used a standardization model to adjust for casemix related risk of adverse outcomes, found that FP
ownership status was not associated with adverse outcomes such as pressure sores, restraint, or urethral
catheterization rates. However, they did not use a simultaneous equation model to account for the endogenous
effects of staffing, Medicaid use, payment rates, and case mix. Nyman and Bricker (1989) found that FPs were
more efficient, but also found evidence that NFPs did not provide the level of quality necessary to explain the
efficiency differences. Nursing Home Service Quality Defining and measuring the quality of nursing home
services has been difficult for regulators, consumers, and researchers (Kane &Kane, 1988). While service
quality is an elusive concept in nursing homes, it is clear that important constituencies have found quality to be
unacceptably low. The Institute of Medicine (1986) identified inadequate supervision of care by physicians and
professional nurses as a primary reason for poor quality, and called for increased standards for nurse staffing.
Obviously, nurse staffing alone does not assure high quality. The report went further and stated that the most
valid proxy measures for quality included care outcomes. The Institute's report served as the model for the
enactment of the Nursing Home Reform amendments of the Omnibus Budget Reconciliation Act of 1987. This
act was intended to improve the quality of care in nursing homes and specifically identified outcome measures
as important criteria of quality. Donabedian (1966) identified three dimensions of health services quality:
structure, process, and outcome. With the exception of Zinn et al. (1993), most studies of nursing home quality
have used structural variables as proxy measures of quality (Davis, 1991; Creene &Monahan,1981). This study
builds on the model developed by Zinn et al. (1993) in that outcome variables are identified as proxy measures
of quality. These measures include pressure sores and restraint usage. Pressure sores are an importantproblem in nursing homes. The prevalence of pressure sores has been estimated to range from 2.6% to 24%
and is associated with increased risks for mortality (Brandeis, 1990). Pressure sores are one of the most
common, preventable, and treatable conditions associated with immobility in the elderly (Kane, Ouslander,
&Abrass, 1989). If NFP status is associated with higher levels of staffing and if NFP objectives include a quality
objective, then NFP ownership should be associated with lower rates of pressure sores. Restraint use is also a
problem in nursing homes. An Institute of Medicine (1986) study found that there is excessive use of restraints
in nursing homes. On average, 41% of all nursing home residents were placed in restraints in 1989, compared
to 25% in 1977 (Tinetti, Liu, &Ginter, 1992). Coughlin, McBride, and Liu (1990) found that persons who were
confused or functionally incapacitated were more likely to become permanent admissions to nursing homes.
Restraints may be used to control aggression (common among persons with dementias) or to prevent injuries
(falls in debilitated individuals). However, immobility resulting from restraint use may increase the risk for
pressure sores, depression, mental and physical deterioration (Evans &Strumpf, 1989), and may increase risk
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for mortality as well (Miles &Irvine, 1992). Behavioral Models of Nursing Home Behavior We developed
conceptual models of behavioral differences between FPs and NFPs. The empirical literature suggests that FPs
and NFPs differ in payer mix, cost, and staffing. Scanlon (1980) presented a theoretical model of the nursing
home market, on which our conceptual model was built. The mathematical conceptualizations of the FP and
NFP models are presented in Appendix A. The assumption that FPs were profit maximizers was used as the
basis for the conceptual model of FP behavior. The model suggests that profits will be maximized when the
marginal costs and marginal revenues of Medicaid patient days and self-pay patient days are equal. However,
the Medicaid payment rate is subject to a rate ceiling. Consequently, if Medicaid costs are high, the Medicaid
price will exceed the ceiling and the nursing home will not provide services to Medicaid patients. Profit-
maximizing nursing homes are subject to market forces in the self-pay market (Nyman, 1989; Scanlon, 1980;
Zinn, Aaronson, &Rosko, 1992), suggesting that they must offer a product that is competitively priced and
provides a level of quality acceptable to the market. Given the constraints on profitability identified in the
conceptual model, one strategy would be to maintain Medicaid resident costs at or below the Medicaid payment
rate ceiling. Since the ceiling is not known in advance, nursing homes must base decisions on estimates of final
retrospective reimbursement rates in order to achieve maximum profits. Setting costs too low may adversely
affect quality and, as a consequence, reduce self-pay demand. Setting costs too high may violate the rate
ceiling and reduce profitability. Alternatively, considering the nature of firms and limits on rationality (March
&Simon, 1958; Thompson, 1967) less than rational nursing home decision makers may shift the excess cost of
care onto self-pay residents through higher payment rates. However, this strategy is risky since it may diminish
the quantity of care demanded by self-pay residents who are price sensitive (Nyman, 1989; Scanlon, 1980) and
increase reliance on Medicaid payments. Given the need to remain within the rate ceiling, equation 8 (see
Appendix A) suggests further that profit-maximizing nursing homes must keep the marginal cost of care for
Medicaid residents low. Heavy care residents generate greater marginal cost and, thus, are more likely to be
discriminated against by FPs with high rates of Medicaid use. The existence of excess Medicaid demand allows
FPs to practice this type of discrimination (Nyman, 1990). While FP behavior is assumed to be profitmaximizing,
there is little agreement as to the prime motives for NFP behavior. The conceptual model of NFP behavior
presented in Appendix A is based on Scanlon's model of NFP behavior, which assumes that NFPs maximize
services, subject to profit constraints. Scanlon's model implies that revenue from private residents will be used
to subsidize Medicaid residents when a favorable shift in private demand occurs, allowing for an increase in
capacity. Thus, service expansion has two purposes: to increase selfpay participation, and to increase the
home's ability to cross-subsidize Medicaid patients. Consequently, there is limited incentive to "game" (setting
costs at a level that will maximize profits from Medicaid without jeopardizing private demand) the Medicaid rates
and, thus, a greater likelihood that NFP nursing homes will be reimbursed at the rate ceiling, since costs are
more likely to exceed the ceiling. By definition, scale is fixed in the short run and may be difficult to increaseeven over a long period of time due to bed supply regulations (certificate of need). In order to increase capacity,
nursing homes may add unregulated residential services, such as independent living or personal care units, to
accommodate the anticipated shift in private demand. Cohen, Tell, Greenberg, and Wallack (1987) found that
continuing care retirement communities were attractive to persons with moderate to high incomes who were
interested in protecting their assets. However, independent living capacity may allow nursing homes greater
latitude in subsidizing Medicaid residents, since they provide increased access to the self-pay market. As
inferred from Scanlon's (1980) model, we expected NFPs with independent living capacity to continue to serve
Medicaid residents. Methods Sources of Data The individual nursing home serves as the unit of analysis in this
study. Nursing home data for 1987 were obtained from three sources: (1) the Medicare and Medicaid
Automated Certification System (MMACS) data files; (2) the Pennsylvania Department of Health Long-Term
Care Facilities Questionnaire; and (3) Health Profiles of Pennsylvania Counties published by the State Health
Data Center. Nursing homes are required to submit responses to the certification survey questionnaire as part
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of recertification for Medicare and Medicaid (MMACS). The survey is completed on one day and provides
information on staffing, services, and resident characteristics. The resident characteristic data were used to
calculate a nursing home specific case mix index, known as the long-term care index. The calculation of this
index is presented in Appendix B. Pennsylvania required, in addition to the certification survey questionnaire,
the completion of a comprehensive questionnaire on annual use, employment, and payment characteristics.
The three sources of data were merged into one data base and provided information on utilization, prices,
facility characteristics, resident characteristics aggregated to the facility level, and county demographics and
economic conditions. Definitions and descriptive statistics by ownership type for the variables used in the
analysis are presented in Table 1. The merged data base consisted of 449 free-standing, nongovernmental
Pennsylvania nursing homes with complete information of which 269 (59.9%) were FP and 180 (40.1%) were
NFP. Model Estimation - Statistical Analysis Previous studies have observed that there is considerable
endogeneity among payer mix, case mix, occupancy, nurse staffing, and payment rate variables (Cohen
&Dubay, 1990; Lee et al., 1983). Thus, a simultaneous equation system was constructed to identify the
behavioral effects associated with ownership on case mix, patient outcomes, Medicaid use, and payment rates.
In the payer mix models, payment rates and case mix on the right side of the equation were considered to be
endogenous. In the payment rate models, Medicaid use and case mix were considered to be endogenous,
while payment rate and case mix were viewed as endogenous in the staffing model. In the adverse outcomes
models, we assumed payer mix and case mix as right-hand variables to be jointly determined with the
dependent variable. In the case mix models, we also assumed that staffing and Medicare use were
endogenous. A summary of the regression equations is shown in Table 2. The simultaneous equation model
was first estimated using two-stage least squares. This technique was selected since all reduced form
equations were either exactly identified or overidentified, and the system is nonrecursive (Kennedy, 1985).
However, examination of the error variance-covariance matrix of the structural equations suggests that
correlation between the error terms between equations exceeded one-third in at least four cases. While the
more robust two-stage least squares (2SLS) may be desirable, Kennedy (1985) recommends the use of three-
stage least squares (3SLS) to estimate models under these circumstances, in order to increase the efficiency of
the estimators. Accordingly, the model was estimated using 3SLS. Only the third-stage estimations for the
Medicare use, case mix, nurse staffing and occupancy models are reported. However, it should be noted that,
while a few of the coefficients in the 3SLS differed in magnitude and significance, there were no differences in
coefficients used to test hypotheses. The order condition was applied in examining the non-zero coefficients for
each of the equations. An examination of the results for nonzero coefficients showed that all equations were
exactly identified or overidentified.
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Hypotheses Payer Mix and Payment Rate Models. - The first model that we specified had Medicaid use as the
dependent variable. Based on previously reported empirical research, Medicaid use was hypothesized to be
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higher among FPs than among NFPs. However, based on the conceptual model, we hypothesized that
Medicaid use in FPs would be associated with higher self-pay payment rates. Higher self-pay payment rates act
in two ways. First, they reduce the quantity of self-pay patient days in a price-sensitive market (Nyman, 1989).
second, higher self-pay payment rates result in more rapid asset "spend-down" and Medicaid conversion. Thus,
we included an FP Self-pay interaction term in order to test this hypothesis. The self-pay payment rate is also
likely to be adjusted as Medicaid use goes up; thus, it is endogenous as a right-hand variable. Medicaid use
was also hypothesized to be associated with lower levels of functional severity and higher discharge rates in
FPs since less heavy care is likely to be associated with lower costs, and higher discharge rates prevent asset
spend-down followed by Medicaid eligibility. However, these case mix measures are likely to be influenced by
the Medicaid use rate as well. Since independent living capacity may attract self-pay residents to the nursing
home, it was anticipated that lower Medicaid use rates would be associated with independent living capacity.
However, we had hypothesized that NFPs with independent living capacity (ILC) were likely to have higher
Medicaid use rates than FPs who developed independent living to maximize self-pay and profits. An ILC FP
interaction term was included to test this hypothesis. Medicaid demand variables were included as controls.
Next, we developed a model to explain the Medicaid payment rate. The payment rate is influenced by nursing
home decisions regarding cost and use, but is subject to a rate ceiling. The conceptual models suggest that FPs
have a greater incentive to "game" the Medicaid payment rates, since hitting the rate correctly maximizes
profits. Thus, we concluded that NFP payment rates were more likely to be at or close to the rate ceiling. Thus,
the Medicaid payment rate was hypothesized to be negatively associated with FP status, and positively
associated with case mix and staffing variables. Market cost variables were included as controls. The self-pay
payment rate was hypothesized to be positively associated with FP status and was also expected to be
associated with higher Medicaid use among FPs. Case Mix Models. -There is considerable variability among
nursing homes in terms of case mix. Case mix affects staffing needs, facility costs, and patient outcomes. Thus,
it was important that we specify case mix as a dependent variable. Case mix is a complex construct; thus, all of
its dimensions cannot be measured directly. We selected two proxy measures of case mix: the long-term care
index and the discharge rate. The long-term care index is an aggregate measure of functional severity which
was calculated for each facility (see Appendix B). The discharge rate is a proxy for the extent to which the
nursing home specializes in short-term rehabilitative or post-acute care (Cohen &Dubay, 1990). Higher
discharge rates were expected to be associated with FP status (Cohen &Dubay, 1990). Facility and market
characteristics expected to be associated with bed turnover or the level of functional severity were included as
controls. The association between the long-term care index and ownership is indeterminant based either on
theory or empirical evidence (Cohen &Dubay, 1990). However, functional severity is likely to be higher among
older residents (age 85 and older) and among residents who are restrained more frequently (Evans &Strumpf,
1989). The discharge rate was expected to be positively associated with FP status, the Medicare use rate, andthe proportion of RNs in the facility, all suggestive of short-term rehabilitative care (Cohen &Dubay, 1990). Care
Staffing Model. - Care staffing is a structural measure of quality (Cohen &Dubay, 1990). Both the empirical
research and the conceptual model suggest that care staffing is higher among NFPs than FPs. However, care
staffing is also jointly determined with case mix and payment rate variables. Thus, case mix and payment rates
were included on the right side of the equation as endogenous variables. Bed size and market supply variables
were included as controls. The log of beds was used because the incremental changes in regulation determined
minimum staffing according to number of residents, unit size, and number of nursing units. Regulation-driven
staffing needs were expected to grow at a decreasing rate with numbers of residents due to the dual
requirements of minimum nursing hours per resident day and minimum staffing levels per nursing unit and per
facility. Adverse Outcomes Models. - Two models were specified, one each for the pressure sore rate and for
the restraint use rate, to assess the impact and interaction of facility and risk characteristics on adverse
outcomes. Pressure sore rates were expected to be positively associated with personal risk factors, including
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functional severity, percent age 85 and older, restraint use, and Medicaid payment status. Restraints applied
properly and monitored appropriately do not materially increase the risk for pressure sores. However, when the
restraints are applied incorrectly or when protocols for monitoring are not followed, the risk of pressure sores is
increased even in individuals under no additional risk. As suggested by prior research, NFPs may have a quality
objective. Thus, we hypothesized that when controlling for risk factors, the pressure sore rate will be positively
associated with FP status. FP Risk factor interaction terms were included in the equation to test this
hypothesis. Staffing, size, and market variables indicating excess Medicaid demand (Nyman, 1990) were
included as controls. Restraint use was also assumed to be associated with personal risk factors, such as the
number of confused residents (self/other protection), functional severity (safety), and Medicaid payment status.
Again, FP interaction terms were included to test the hypothesis that FPs were more likely to have greater
restraint use among residents at risk than NFPs. Size, staffing and county-level Medicaid proportion variables
were included as controls. Results The results of the simultaneous-equation model estimation can be found in
Tables 3 and 4. The system-weighted R-square across all models was .4335. Only coefficients achieving a
significance level of p
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The Medicaid payment rate model results are presented in Table 3B, and the self-pay payment rate model
results are presented in Table 3C. The self-pay payment rate was positively associated with FP ownership, but
the Medicaid payment rate was not associated with ownership. The self-pay payment rate was positively
associated with the Medicaid use rate. However, the coefficient of the FP Medicaid use rate interaction term
was not significant, contrary to our expectations. Case Mix. -Tables 3D and 3E present the results of the case
mix model estimations. The long-term care index was not associated with ownership status, a result consistent
with our expectation. Surprisingly, functional severity is negatively associated with two of the risk factors for
functional severity, percent of residents 85 and older, and the Medicaid use rate. The FP interaction terms with
proportion of residents 85 and older and the Medicaid use rate suggest that FPs with a greater proportion of
these high-risk residents have higher levels of functional severity than do NFPs. The long-term care index was
found to be positively associated with a third risk factor, restraint use. The FP Restrained residents interaction
term coefficient suggests that FPs with higher restraint use rates have lower rates of functional severity than do
NFPs with high restraint usage. As expected, higher discharge rates (Table 3E) are positively associated with
FP ownership. However, the coefficient on the FP interaction with Medicare use is negative, suggesting that
FPs with higher Medicare use rates have lower discharge rates than NFPs with high Medicare use rates. This
may be due to the greater use of hospitals as sources of admission by FPs (thus, higher Medicare use rates
and lower discharge rates) or greater propensity to admit permanent nursing home residents to hospitals for
brief stays, resulting in eligibility for Medicare benefits upon a hospital discharge. Care Staffing. - The estimated
coefficients for the care staff per bed model are presented in Table 4A. As hypothesized, NFP nursing homes
have higher levels of care staffing than FPs. Although direct care staffing was positively associated with
payment rates, as expected, the measure was negatively associated with the case mix measures. While this
finding requires additional investigation, the association may be due to variation in care needs associated with
the measures. For example, nursing homes with high discharge rates may provide a considerable amount of
rehabilitation. Nurses and rehabilitation staff may provide services more efficiently and patients may be
expected to perform more self-care. Patients who are confused but functionally less debilitated may require
more staff-intensive supervision than persons with high levels of functional severity, explaining the negative sign
of the long-term care index coefficient. Adverse Outcomes. - The results of the adverse outcomes models are
presented in Tables 4B and 4C. Consistent with previous observations (Zinn et al., 1993), the pressure sore
rate is negatively associated with FP status (Table 4B). As expected, the pressure sore rate is positively
associated with functional severity. However, the pressure sore rate is negatively associated with the three
remaining risk factors, Medicaid payment status, restraint use, and proportion of residents 85 and older. The
coefficients of the interaction terms provide evidence that the pressure sore rate is associated with the personal
risk factors in FPs, not NFPs. That is, each of the FP Risk factor interaction coefficients is positive andsignificant. These findings suggest that when FPs have residents at risk for pressure sores, their pressure sore
rates are higher than among NFPs with equal risk profiles, supporting our hypothesis that when case mix and
personal risk are controlled, adverse outcomes are higher among FPs. The negative coefficient on the FP
binary variable may be a result of FPs having lower patient risk profiles for pressure sores. The restraint use
rate was not observed to be associated with FP status (Table 4C). The restraint use rate is positively associated
with the three factors expected to place residents at higher risk for restraint use: the Medicaid use rate, the
number of confused residents, and the long-term care index. The FP interaction terms for confused residents
and the long-term care index suggest that FPs with residents at risk for restraint use due to these factors are
more likely to use restraints than NFPs, supporting our hypothesis that greater restraint use is likely in FPs once
personal risk factors are controlled. However, the FP Medicaid use rate interaction term suggests that FPs
with heavy Medicaid utilization are less likely to restrain residents than are NFPs with high rates of Medicaid
utilization. Results in Table 3D suggest that FPs with high restraint use rates in turn have lower rates of
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functional severity. Thus, FPs with heavy Medicaid use may be more adept at behavior control and restraint use
than NFPs. Discussion This study has examined behavioral differences between FP and NFP nursing homes,
using a simultaneous equation model. The model estimations were used to test hypotheses that were based on
a conceptual model of behavioral differences between FPs and NFPs, and previously reported empirical
research. Thus, compared to previous studies, we have used a more systematic approach to assessing
differences between FPs and NFPs. We found that FPs differed significantly from NFPs in areas of cost and
quality, but not access. Several studies (Nyman, 1989,1990; Scanlon, 1980) have found that the nursing home
market is characterized by chronic excess Medicaid demand. Since the market for nursing homes can be
partitioned into public and private markets, and since public markets are characterized by excess demand
(Bishop &Dubay, 1991; Nyman, 1990; Scanlon, 1980), greater access to the public market may be considered a
positive social contribution. Previous research had suggested that FPs have higher Medicaid proportions,
suggesting greater access to Medicaid eligibles. This study found that there is no difference in Medicaid
proportions according to ownership. However, lower Medicaid use rates are associated with independent living
capacity. While NFPs are more likely to have independent living units, FPs are more likely to use independent
living to increase self-pay market share. Cohen et al. (1987) proposed continuing care retirement communities
as a viable private sector alternative to increased government funding of long-term care. The association of low
rates of discharge, lower self-pay payment rates, and continuing care retirement community status with NFP
ownership suggest that NFPs are better able to conserve personal funds and prevent asset spend-down to
Medicaid eligibility levels. The ability to do so may be related to care subsidies for self-pay patients, allowing
reduction of self-pay payment rates. FPs are likely to have higher self-pay payment rates. Higher self-pay
payment rates among FPs may be related to case-mix, the discharge rate in particular, or they may be a
response to a high Medicaid share, low Medicaid payment rates, and the need to cost shift to protect profits.
Contrary to our expectation, FPs were not found to have lower Medicaid payment rates. However, FPs with
higher Medicaid use rates have lower Medicaid payment rates, suggesting lower costs than their NFP
counterparts with high Medicaid use rates. The association of NFP ownership with higher levels of staffing
would suggest that costs are higher in NFPs as a result of better staffing. Thus, NFPs with higher Medicaid use
rates are more likely to have Medicaid payment rates at or near the rate ceiling, a finding consistent with our
hypothesis. While access by publicly supported residents is an important criterion of social contribution, the
issue is complicated by the trade-off between quality and access. Nyman (1990) found that quality suffers due
to excess Medicaid demand. That is, as demand by Medicaid eligibles for nursing home admission increases
relative to supply, nursing homes are no longer subjected to the rigors of competition. He argued that it was not
the low Medicaid payment rates that resulted in lower than expected quality, but the lack of market discipline,
which allows nursing homes to overlook issues of service quality. In this study, adverse outcomes were
observed to be positively associated with market control variables representing excess Medicaid demand; thus,this study provides additional support for Nyman's conclusion. Access to Medicaid eligibles has been
problematic, not just in terms of admission and quality of stays, but also in terms of appropriateness. Payment
systems based on two levels of care, skilled and intermediate, have been identified as a cause for nursing home
discrimination against heavy care residents at admission (Rosko, Broyles, &Aaronson, 1987). Medicaid heavy
care residents may be more subject to discrimination at admission due to the dual disincentives of Medicaid
status and heavy care needs. Within the context of a payment system based on two levels of care, association
of heavy care resident loads with high Medicaid use would suggest greater social contribution. While a study by
Buchanan (1992) found that Pennsylvania adjusts payment level for heavy care case mixes, the same study
indicated that heavy care residents in Pennsylvania are hard to place. In this study, we found that FPs with
higher levels of Medicaid use had a higher functional severity index. Association between functional severity
and Medicaid use in FPs may suggest that FPs are less likely to discriminate against heavy care Medicaid
eligibles at admission. However, high rates of functional severity associated with high Medicaid use in FPs may
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also suggest poor quality care. This study provides evidence that NFP status is associated with better care
outcomes, a dimension of quality considered to be the best proxy measure of service quality (Donabedian,
1966; Institute of Medicine, 1986). The adverse outcomes models clearly indicate that FPs with high-risk
residents have higher rates of adverse outcomes than NFPs. NFPs are more likely to house permanent
residents, as evidenced by significantly lower discharge rates. Thus, NFPs also house a significantly higher
proportion of the oldest patients, those 85 and older. These patients should be at greater risk for such adverse
outcomes as pressure sores, functional severity, and dementias with consequent restraint use, but were
observed to experience lower rates of adverse outcomes in NFPs. The cause of higher rates of adverse
outcomes in FPs may be either lower levels of staffing resulting in less resident supervision, or poorer process
quality. For example, pressure sore rates may be higher in FPs due to inadequately observed care protocols,
improper application of restraints, or insufficient staff relative to care needs. Nyman (1988) observed that quality
in nursing homes is not associated with cost and that quality can be improved through policies providing quality
incentives. He stated that nonprofits may be more motivated to provide better care, explaining better outcomes
among NFPs. The one exception to the observed differences in outcome by ownership was the restraint use
rate. While FPs are more likely to use restraints with increasing functional severity (safety risks) and with
increasing numbers of confused residents (self/other protection) than NFPs, it appears that FPs with high
Medicaid use rates are less likely to use restraints. NFPs with high rates of Medicaid use provide quality of care
that is not better and may be worse than their FP counterparts when it comes to excessive use of restraints.
Thus, the study provides evidence that NFPs produce significantly higher quality of care to Medicaid
beneficiaries and to self-pay residents than do FPs. In consideration of the differences in self-pay payment
rates, NFPs provide better value and are less likely to shift excess Medicaid costs onto self-pay residents. This
may be due to the extensive availability of independent living units among NFPs, or to operating subsidies from
charitable sponsors or endowments. The broader range of residential services may allow NFPs to take
advantage of private demand for residential services and to assist potential nursing home residents in managing
the financial risk of nursing home entry by providing an element of insurance (Cohen et al., 1987). This allows
NFPs to better serve the Medicaid residents that are admitted. There are a few study limitations that may affect
generalizability. First, while there are a number of possible models, we chose to emphasize the relationships
among certain variables we considered to be endogenous and/or which help to identify nursing home
organizational effectiveness. Other models are possible and may change the perceived relationships. second,
we focused on one state, Pennsylvania. While this limited the confounding effects of environmental
characteristics (i.e., differences in Medicaid payment method), the state-specific industry and its environment
may have sufficient distinctiveness to limit applicability across geopolitical lines. For example, FP nursing
homes represent 59.9% of the free-standing, nongovernmental nursing homes in Pennsylvania, compared to
75% nationwide. The higher proportion of NFPs may distort market behavior when compared to markets inwhich FPs clearly predominate. References References American Association of Homes for the Aging. (1993).
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166-206. Evans, L., &Strumpf, N. (1989). Tying down the elderly: A review of the literature on physical
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Greene, V., &Monahan, D. (1981). Structural and operational factors affecting quality of patient care in nursing
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Economics, 8, 209-231. Nyman, ). (1990). The future of nursing home policy: Should policy be based on an
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Nyman, J., &Bricker, D. (1989). Profit incentives and technical efficiency in the production of nursing home care.
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profit: Does it matter? The Cerontologist, 23, 341-348. Rosko, M., Broyles, R., &Aaronson, W. (1987).
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in action. New York: McCraw-Hill. Tinetti, M., Liu, W., &Cinter, S. F. (1992). Mechanical restraint use and fall-
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S. (1987). Ownership, regulation, quality assessment and performance in the long-term health care industry.
The Cerontologist, 27, 233-239. Zammuto, R. (1982). Assessing organizational effectiveness: Systems change,
adaptation and strategy. Albany, NY: State University of New York Press. Zinn, J., Aaronson, W., &Rosko, M.
(1992). The basis for competition in the nursing home industry: A managerial perspective. Journal of Health
Administration Education, 10, 595-610. Zinn, J., Aaronson, W., &Rosko, M. (1993). Variations in the outcomes
of care provided in Pennsylvania nursing homes: Facility and environmental correlates. Medical Care, 31, 475-
487. Received July 30, 1993 Accepted June 7, 1994 AuthorAffiliation William E. Aaronson, PhD,1 Jacqueline S.
Zinn, PhD,1 and Michael D. Rosko, PhD2 AuthorAffiliation 1 Department of Health Administration, Temple
University, Speakman Hall (006-00), Philadelphia, PA 19122. Address correspondence to Dr. Aaronson at this
address. 2 Department of Health and Medical Services Administration, Widener University, Chester,Pennsylvania.
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Studies; Nursing homes; Mortality; Efficiency; Quality standards; Regulatory agencies; Costs; Risk;
Customer services; Competitive advantage; Health services; Profitability
Health Facilities, Proprietary -- economics, Health Facilities, Proprietary -- standards, Homes for the
Aged -- economics, Homes for the Aged -- standards, Humans, Least-Squares Analysis, Medicaid,; Medicare,
Models, Organizational, Nursing Homes -- economics, Nursing Homes -- standards, Outcome Assessment
(Health Care), United States, Health Facilities, Proprietary -- organization &; administration (major), Homes for
the Aged -- organization & administration (major), Nursing Homes -- organization & administration (major),
Ownership -- economics (major), Quality of Health; Care (major)
The Gerontologist
34
6
775-86
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1994
Dec 1994
1994
Oxford University Press, UK
Oxford
United Kingdom
Medical Sciences, Gerontology And Geriatrics
00169013
GRNTA3
Scholarly Journals
English
Feature
Tables; References; Equations
7843607
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Citation style: APA 6th - American Psychological Association, 6th Edition
Aaronson, W. E., Zinn, J. S., & Rosko, M. D. (1994). Do for-profit and not-for-profit nursing homes behave
differently? The Gerontologist, 34(6), 775-86. Retrieved from
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