Managerial Ownership in Nursing Homes: Staffing, Quality, and Financial Performance

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1 The Gerontologist cite as: Gerontologist, 2017, Vol. 00, No. 00, 1 11 doi: /geront/gnx104 Advance Access publication June 20, 2017 Research Article Managerial Ownership in Nursing Homes: Staffing, Quality, and Financial Performance Sean Shenghsiu Huang PhD*,1 and John R. Bowblis PhD 2 1 Department of Health Systems Administration, Georgetown University, Washington, DC. 2 Department of Economics in the Farmer School of Business and Scripps Gerontology Center, Miami University, Oxford, Ohio. *Address correspondence to: Sean Huang, PhD, Department of Health Systems Administration, Georgetown University, 3700 Reservoir R., NW., St. Mary s Hall, Washington, DC sean.huang@georgetown.edu Received April 5, 2017; Editorial Decision Date May 18, 2017 Decision Editor: Rachel Pruchno, PhD Abstract Purpose of the Study: Ownership of nursing homes (NHs) has primarily focused broadly on differences between forprofit (FP), nonprofit (NFP), and government-operated facilities. Yet, among FPs, the understanding of detailed ownership structures at individual NHs is rather limited. Particularly, NH administrators may hold significant equity interests in their facilities, leading to heterogeneous financial incentives and NH outcomes. Through the principal-agent theory, this article studies how managerial ownership of individual facilities affects NH outcomes. Design and Methods: We use a unique panel dataset of Ohio NHs ( ) to empirically examine the relationship between managerial equity ownership and NH staffing, quality, and financial performance. We identify facility administrators as owner-managers if they have more than 5% of the equity stakes or are relatives of the owners. The statistical analysis is based on the pooled ordinary least squares and NH-fixed effect models. Results: We find that owner-managed NHs are associated with higher nursing staff levels compared to other FP NHs. Surprisingly, despite higher staffing levels, owner-managed NHs are not associated with better quality and we find no statistically significant difference in financial performance between owner-managed and nonowner-managed FP NHs. Our results do not support the principal-agent model and we offer alternative explanations for future research. Implications: Our findings provide empirical evidence that NH ownership structures are more nuanced than simply broadly categorizing facilities as FP or NFP, and our results do not fully align with the standard principal-agent model. The role of managerial ownership should be considered in future NH research and policy discussions. Keywords: Nursing home, Quality of care, Long-term care, Staffing, Managerial ownership, Organizational structures Since the early 1990s there has been significant expansion of for-profits (FPs) into the health care sector. Among nursing homes (NHs), which deliver long-term care to functionally and cognitively impaired individuals, FPs are the most common provider and operate nearly 70% of all NHs in the United States (Centers for Medicare and Medicaid Services, 2015). Because nonprofits (NFPs) are restricted from sharing any profits with employees and stakeholders (Hansmann, 1980), NFPs and FPs are thought to have different objectives. Although FPs are motivated by profits, the objectives of NFPs are less clear. This has led to an abundant literature that studies the complex relationship between FP and NFP ownership of NHs for a number of outcomes, and generally finds that FP NHs provide lower quality but are more profitable than NFP NHs (Grabowski, Feng, Hirth, Rahman, & Mor, 2013; Hirth, Grabowski, Feng, Rahman, & Mor, 2014; Weech-Maldonado et al., 2012). What is less studied is how ownership structure among FPs may vary across facilities to affect NH outcomes, as The Author Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please journals.permissions@oup.com. 1

2 2 The Gerontologist, 2017, Vol. 00, No. 00 the simple for-profit status may not reflect the increasingly complexity of ownership structures (Stevenson, Bramson, & Grabowski, 2013). In larger FP chains, key administrative NH personal are salaried employees, but in smaller facilities these administrators may have ownership interests in the facility. These administrators, which often are required to be licensed and hold advanced degrees in their field, include traditional business managers, Medical Directors and Directors of Nursing. Since these key administrators must manage resource availability against resident and staff needs (Siegel, Young, Zysberg, & Santillan, 2015), the characteristics of these administrators, such as the management styles and tenure, have been shown to be important predictors of NH outcomes (Castle & Decker, 2011; Donoghue & Castle, 2009; Krause, 2012; Lerner & Trinkoff, 2014). Castle and Banaszak-Holl (1997) also show that the characteristics of the top management team in NHs can affect the adoption of innovations. Administrators with significant equity stakes (i.e., owner-managers) may have different incentives than nonowner managers as outlined in the classic principal-agent problem (Hölmstrom, 1979). Because owner-managers are able to share more NH profits through their equity stake, the stronger financial incentive may distort ownermanagers behaviors to pursue profits at the cost of quality. Meanwhile, these owners-managers may have stronger control interests and thus have more flexibility than salaried managers in making operation decisions. This means that owner-managers may be better able to address dayto-day issues to improve operational efficiency and quality. It is therefore theoretically ambiguous how the combination of stronger financial and control interests can affect NH outcomes. To our knowledge, there are no studies that examine how managerial ownership of individual facilities may affect NH quality and financial performance. In this article, we bridge this gap in the literature by utilizing a unique dataset that is collected in Ohio. This dataset contains detailed ownership information that allows us to identify if a NH administrator has a significant equity stake in the individual NH they operate. Using this unique ownership information for Ohio NHs between 2005 and 2010, we examine the relationship between managerial ownership and various NHs outcomes, including staffing, quality, and financial performance. Based on the classical principal-agent theory, we hypothesize that among FP NHs, those administrated by managers holding significant equity stakes will have different outcomes compared to NHs operated by managers without equity stakes. The Principal-Agent Problem and Managerial Ownership The classic principal-agent problem revolved around a conflict of interest between owners (principal) and managers (agents). Owners want managers to take particular actions which maximize the firms value. Although managers will internalize some of the business interests of owners, each action also has private costs and benefits (e.g., effort, reputation, and career risk). Therefore, managers will weigh the costs and benefits to the business against their own private costs and benefits. When the private costs and benefits are not aligned with the business cost and benefits, managers may behave in a manner that is counter to ownership s interest. One way to mitigate the principal-agent problem is through optimal contracting that attempts to better align the interests of managers and owners. For example, publically-traded companies often implement various mechanisms that align executive compensation with shareholder wealth, such as salary revisions and bonuses for reaching specific goals (Jensen & Murphy, 1990). Although writing complete contracts seems reasonable, these contracts are nearly infeasible given the multiple dimensions in which to gauge performance and the inability to foresee all potential situations where manager and owner interests are misaligned (Holmstrom & Milgrom, 1991). For these reasons, owners have often turned to the second best alternative equity ownership. Because owner-managers directly share a portion of the profits, a proportion of the manager s private benefits are directly aligned with the owners and the principal-agent problem can be lessened (Core et al., 2003; Murphy, 1999). As expected, some empirical evidence suggests that the principal-agent problem is found to be weaker and that firm performance is better the greater the ownership stake of the manager (Ang, Cole, & Lin, 2000; Fahlenbrach & Stulz, 2009; Mehran, 1995). However, the use of managerial ownership in NHs raises concerns when serving this vulnerable population. These concerns are similar in spirit to those found in the physician ownership literature, where patients only have limited information about their medical conditions and equity ownership intensifies the financial incentives of providers (Hollingsworth, 2010; Mitchell & Sass, 1995; Stensland & Winter, 2006; Strope et al., 2009). In the case of NHs, many residents are physically and cognitively impaired, and quality is not directly observable to consumers. Since NH residents incur high switching costs to move to another facility, NHs are not fully rewarded by providing high quality and are not fully penalized by providing lower quality. This creates a situation in which NHs can take advantage of residents by promising to provide high quality but underperform on promises (Hirth, 1999). This inability to fully observe quality heightens the complexity and importance of understanding the policy implications of managerial ownership in NHs. How owner-managers differ from managers without significant ownership stakes will depend on how managerial ownership affects the principal-agent problem and the tradeoff between profitability and quality. Following the optimal contracting hypothesis in the situations where consumers do not fully observe service quality, we would

3 The Gerontologist, 2017, Vol. 00, No expect that owner-managers have incentives that are more aligned with owners. Furthermore, owner-managed NHs would have lower quality and better financial performance than nonowner-managers. Method: Data and Empirical Strategy To examine the effect of owner-managers on NH outcomes, we merged data from three sources. We obtained the Ohio Medicaid Cost Reports for years from the Ohio Department of Job and Family Services. The Ohio Medicaid Cost Reports are facility-level datasets collected annually for every NH that receives Medicaid reimbursement in the state of Ohio, including information on ownership and financial performance. These data are unique because they contain a list of all NH administrators who are directly responsible for the operation of the facility and provide information whether key administrators, or their relatives, owned at least 5% equity in the facility. Next, the Ohio Medicaid Cost Reports were merged with data from the Online Survey, Certification and Reporting (OSCAR) System. The OSCAR database is the most comprehensive source of facility-level information (e.g., operational characteristics, staffing, and quality) on NHs that is collected as part of the annual recertification process required for all NHs that receive Medicare and/or Medicaid reimbursement. Finally, we utilized the zip code of each NH to identify the urban/rural setting of the facility via rural urban commuting area (RUCA) codes. These datasets are merged to create a panel dataset from 2005 through 2010 with the unit of observation of a NH year. This analytic sample starts with all free-standing NHs which are operated by a FP or NFP organization. After eliminating another 264 NH-year observations for data reliability issues, which are discussed later, the resulting sample contains 4,979 NH-year observations from 784 FP and 192 unique NFP facilities. Empirical Model Our empirical model estimates how a comprehensive set of NH outcomes, such as staffing, quality, and financial performance are different based on whether NH administrators have significant equity ownership (i.e., owner-managers). The basic analytic approach is to compare NHs with owner-managers to NHs without owner-managers (i.e., nonowner-managers). One concern with this comparison is that owner-managers are more likely to be part of organizations that only own a single facility whereas many FP NHs are owned by corporate chains. In our sample, 23.9% of independent (non-chain) FP NHs have owner-managers, whereas only 5.1% of chain-affiliated FP NHs are operated by owner-managers. In addition, managers work at chain-affiliated NHs may follow guidelines established at the corporate headquarters, and thus have less autonomy compared to managers of the independent NHs. Therefore, we make two sets of comparisons by estimating two models: (a) utilizing a sample of all FP NHs and (b) utilizing a sample which is restricted to only independent FP NHs. We also estimate a third model which compares owner-managed and nonowner-managed FP NHs to NFP NHs. In our dataset, the unit of analysis is a NH-year. Because we observe the same NH over multiple years, we are able to estimate regressions models using panel (e.g., crosssectional time-series) estimation techniques. Utilizing the panel nature of the data and estimating panel fixed effects regressions (i.e., NH-fixed effect), we are able to account for time-invariant factors that are unobservable and specific to each NH, such as organizational culture, floor plan, market environment, and regulations. Treating Y i,t as an outcome for NH i in year t, we estimate the following facility-level regression model: Y it, = µ OwnerManager i,t + γ Firm i,t + δ i + τ t + it, where OwnerManager i,t represents if the NH is operated by an owner-manager, Firm i,t is a vector of time-varying NH characteristics, δ i is a NH fixed-effect, τ t is a set of time indicator variables, and ϵ i,t is an error term. The standard errors are clustered at the NH level. Although the fixed effect panel regression usually is viewed as a more rigorous method, it relies on the changes in the owner-manager variable over time to provide statistical identification. These switches may be infrequent. In our sample, there are 784 unique FP NHs and a total of 119 switches among FPs to or from being operated by an owner-manager over the 6 years of data, suggesting there is an adequate number of switches to utilize the fixed effects regression. Even with an adequate number of switches, if these switches are nonrandom it could lead to some bias in our estimates. Although we expect switching to occur if the owner-equity model becomes more or less attractive, it is not clear if switching will bias our estimates in one particular direction. Furthermore, NHs that had switches in the owner-manager variables were found to have characteristics similar to NHs that did not undergo switches. Therefore, we are not overly concerned with the potential bias from switching, but we report results using both pooled ordinary least squares (OLS) and fixed effects when analyzing FP NHs for completeness. Because there are fewer switches from NFPs to owner-managed NHs, we only use pooled OLS when comparing FPs to NFPs. Defining Owner-Managers The Ohio Medicaid Cost Reports contain a list of all administrators who are directly in charge of the operation of each NH. For each administrator, the data also reports whether a key administrator or their relatives has at least of 5% equity ownership in the facility. For the purpose of this article, we defined a NH to have an owner-manager if any of the administrators have at least 5% equity ownership in the facility or they are relatives of the owners. Our

4 4 The Gerontologist, 2017, Vol. 00, No. 00 definition is consistent with the finance literature (Mehran, 1995) and regulations required for financial reporting by the Security Exchange Commission (SEC; U.S. Securities and Exchange Commission, 2012). In our data, there are a total of 4,047 FP NH-year observations, of which 632 are operated by owner-managers (15.62%). There are also an additional 932 NH-year observations in which the facility is owned by a NFP. Dependent Variables In the analysis we examine a number of outcomes. First, most direct care in NHs are provided by licensed nurses and certified nurse aides (CNAs). Although only registered nurses (RNs) and licensed practical nurses (LPNs) are technically licensed as nurses, licensed nurses and unlicensed CNAs provide nursing services to residents and all three are commonly referred as nursing staff (Centers for Medicare and Medicaid Services, 2017). RNs are the highest qualified and generally supervise other nurses and coordinate medical care. In contrast, CNAs have the lowest qualifications and provide most of the direct care to residents. Using OSCAR data, for each type of nursing staff we measure the direct care staffing level using a ratio that adjusts for the number of residents in the facility. We use the number of hours per resident day (HPRD) as the main measurement, which approximates the average number of hours each staff type can theoretically have contact each resident. Given the potential for coding errors for staffing levels in OSCAR, we utilize a cleaning method common to the literature to exclude observations with questionable staffing ratios (Bowblis, 2011). In addition to staffing, we examine various quality outcomes which are shown to be related to staffing and affected by the characteristics of NH administrators (Bowblis, 2011; Castle & Decker, 2011; Castle & Ferguson, 2010; Krause, 2012; Lin, 2014). First, we examine the number of regulatory deficiencies received by the facility in their most recent recertification inspection. This inspection requires that state health personal evaluate the NH and issue deficiency citations if the facility fails to meet a specific regulatory standard. The second set of quality measures are the proportion of residents with certain medical conditions or treated with certain care practices. In terms of medical conditions, we examine the proportion of residents with a bedsore or a contracture. In terms of care practices, we examine the proportion of residents that are physically restrained, catheterized, or are utilizing certain medications (e.g., antipsychotic or psychoactive medications). In the case of bedsores, catheters, physical restraints, and contractures, we are able to examine these proportions for the number of residents that acquired the condition at the facility. For all quality measures, higher numbers indicate worse quality. The final set of outcome measures is financial performance. Financial performance is measured as profit margin and adjusted profit margin. Profit margin is defined as net income divided by total revenues. Because owner-managers have significantly higher salaries than nonowner-managers (Huang, Hirth, & Smith, 2016), we also examined adjusted profit margin which is calculated as net income plus administrator compensation divided by total revenues. The purpose of using adjusted profit margin is to account for any bias in profitability due to systematic difference in compensation between owner-managers and nonowner-managers. For both measures, higher values imply the facility is more profitable. It should be noted that sometimes facilities report erroneous values in the Ohio Medicaid Cost Reports. To account for potential outliers that may be coding errors, we trim the data by excluding observations in the top and bottom 1% of profit margin from the analysis (We also used the top and bottom 2.5% as alternative thresholds and the results are qualitatively consistent. Therefore, we use the top and bottom 1% as our main thresholds to include as many observations as plausible.). Control Variables In the regressions are a host of control variables that may affect the dependent variables. Many of these variables are constructed from the OSCAR and include measures on facility characteristics, patient payer and case-mixes, and the urban/rural settings (Table 1). Nursing facility characteristics include size (number of beds), chain affiliation, being part of a continuing care retirement communities (CCRC), occupancy rate, and the payer-mix. We include payer-mix in the model to account for the varying generosity of reimbursement by Medicare, Medicaid, and private payers, as having a greater reliance on Medicaid has been found to be associated with lower staffing and potentially worse quality (Cohen & Spector, 1996). Patient case-mix includes the Acuindex (Cowles 2015), percentages of residents that have dementia, psychiatric illness, are depressed, have a developmental disability, bedbound, and chairfast. We also include if the facility has a dementia special care unit. Finally, to control for differences in geographic setting, we categorize NHs into urban areas, micropolitan cities, small rural towns, and isolated small rural towns according to Categorization A provided by the WWAMI Rural Health Research Center. Results Descriptive Statistics The summary statistics that describe the facility characteristics of NHs in the sample are reported in Table 1. The results are reported for the overall sample, FPs with manager-owners, FPs without manager-owners, and all NFPs. Compared to FPs without owner-managers, the ownermanaged FPs tend to be smaller (84.1 vs beds), less likely to be part of a chain (14.2% vs. 49.3%) and have a payer-mix that is more reliant of Medicaid. Additionally, owner-managers are less likely to operate a facility with a

5 The Gerontologist, 2017, Vol. 00, No Table 1. Summary Statistics Nursing Home (NH) Characteristics All NHs For-Profit Nonprofit Owner-manager Nonowner-manager dementia special care unit (16.5% vs. 19.4%), and seem to be in more urban geographic locations. The descriptive statistics of the outcome measures are reported in Table 2. NHs operated by owner-managers have direct care nursing staff levels that are higher than FP NHs administrated by nonowner-mangers, but lower than NFP NHs. Although NHs operated by owner-managers also have fewer deficiencies than other FPs, there does not seem to be a discernable pattern among the other quality measures. For financial performance, NHs administrated by owner-managers have lower profit margins than other FPs, but both financial indicators are higher than those of NFPs. Regression Results For each outcome measure, we report five different regression specifications which also controls for a number of other variables reported in Table 1. First, we restrict the analysis to all FP NHs, effectively comparing owner-managers to nonowner-managers. As noted earlier we report results utilizing pooled-ols (column 1) and fixed effects panel regression (column 2). Because the majority of NHs operated by owner-managers do not belong to multi-facilities chains, we then limit the sample to FP NHs that are not affiliated to chains, and estimate the model using pooled OLS and fixed effects panel regression (columns 3 and 4). Finally, to determine if owner-managed NHs differed from NFPs, utilizing pooled OLS, column 5 reports the effect for owner-managers and nonowner-managers relative to the reference group of NFPs. (1) (2) (3) (4) Facility characteristics Number of beds (46.56) (38.29) (43.52) (58.53) Chain-affiliation (0.493) (0.350) (0.500) (0.465) Continuing care retirement community (0.329) (0.229) (0.236) (0.491) Payer-mix: Medicaid (%) (15.94) (15.56) (14.86) (17.52) Payer-mix: Medicare (%) (8.502) (7.164) (8.711) (8.304) Occupancy rate (%) (11.30) (13.17) (11.15) (9.766) Acuindex (1.151) (1.242) (1.135) (1.139) Case-mix: Dementia (%) (16.77) (16.55) (16.79) (15.64) Case-mix: Psychiatric illness (%) (18.21) (19.52) (18.27) (15.13) Case-mix: Depression (%) (20.14) (21.51) (19.99) (19.70) Case-mix: Developmental disability (%) (4.176) (4.330) (4.326) (2.943) Presence of a dementia special care unit (0.414) (0.371) (0.395) (0.477) Urban/rural setting Urban (0.456) (0.452) (0.464) (0.418) Micropolitan city (0.393) (0.412) (0.399) (0.349) Small rural town (0.265) (0.223) (0.274) (0.255) Isolated small rural town (0.165) (0.131) (0.180) (0.117) Observations (NH-year) 4, , Table 3 reports the regression results of the relationship between managerial ownership and staffing levels, health deficiencies, and the use of psychoactive medications. In all regressions (panels A C) that compare only FPs, RN and CNA staffing levels are statistically higher among NHs operated by owner-managers. Among RNs, the magnitudes of the effects range from to HPRD, with the effect being larger in the sample of only independent FPs. Although the magnitude may seem small, these represent 11.9% to 15.4% higher RN staffing levels (sample mean = 0.31). Owner-managed NHs also employ more CNAs (0.09 to 0.19 HPRD). Relative to the average staffing level these effects translate into 4.0 to 8.1% higher CNA staffing levels (sample mean = 2.31). We also find these effects to be slightly larger when they are estimated from the sample that only includes independent NHs (column 3 and 4). Interestingly, there is no difference in LPN staffing levels. Comparing owner-managed NHs to NFPs (column 5), owner-managers have lower staffing levels, but the result is only statistically significant for CNAs. In contrast, nonowners-managed NHs have statistically lower RN, LPN, and CNA staffing levels when compared to NFPs. Panel D in Table 3 reports the results for the number of regulatory deficiencies. Among FP NHs, there is no statistically significant difference between NHs with and without owner-managers for any of these quality measures. However, we do find statistically significant differences between FP and NFP NHs (column 5). Compared to NFPs, owner-managed NHs receive 0.92 additional deficiency

6 6 The Gerontologist, 2017, Vol. 00, No. 00 Table 2. Summary Statistics Staffing, Quality, and Financial Outcomes All NHs For-Profit Nonprofit Owner-Manager Nonowner-Manager and FP NHs ran by nonowner-managers receive 1.11 additional deficiencies in their annual recertification inspection. Panels E and F in Table 3 show the results of the use of antipsychotic and psychoactive medication. FPs (regardless of manager s ownership) utilize more antipsychotic medications. This indicates that FPs have worse quality than NFPs. However, we find no statistical difference among owner-managers and nonowner-managers. Table 4 reports results for health outcomes and care practices for the overall proportion of residents and the proportion of residents that acquired the following conditions at the NH. These include bedsores, contractures, physical restraints, and indwelling catheters. For all quality measures, there is no consistent pattern suggesting that NHs with owner-managers provide different quality than NHs without owner-managers, except potentially in one case. Both contracture measures are positive and statistically significant in the OLS regressions, but the effect becomes smaller and statistically insignificant in fixed effects regressions. This may be due to differences in the facilities that are not observable in the data. Given our preference for the results of fixed effects models which can handle time-invariant unobservables, we find no evidence that NHs operated by owner-managers have different quality than other FPs. In contrast, the comparison between FP and NFP NHs provides mixed results and depends on the measure (1) (2) (3) (4) Staffing level (hours per resident day) Registered nurses (RNs) (0.174) (0.170) (0.164) (0.200) Licensed practical nurses (LPNs) (0.279) (0.287) (0.271) (0.297) Certified nurses aides (CNAs) (0.524) (0.536) (0.470) (0.584) Number of regulatory deficiencies (4.700) (4.505) (4.850) (4.055) Quality measures (all residents) Physical Restraint (%) (6.038) (6.745) (6.155) (4.743) Bedsore (%) (3.938) (4.123) (3.979) (3.621) Indwelling catheter (%) (5.412) (7.412) (4.625) (6.370) Contractures (%) (23.18) (25.09) (22.49) (22.37) Antipsychotic medications (%) (14.72) (15.54) (15.45) (8.085) Psychoactive medications (%) (11.31) (11.21) (11.58) (10.16) Conditions acquired in nursing home (NH) Physical restraint (%) (5.455) (5.475) (5.661) (4.423) Bedsore (%) (2.690) (3.140) (2.618) (2.604) Indwelling catheter (%) (3.829) (5.126) (3.026) (5.177) Contractures (%) (16.50) (19.48) (15.90) (16.04) Financial performance Profit margin (%) (9.883) (9.075) (9.066) (12.70) Adjusted profit margin a (%) (9.753) (8.832) (8.967) (12.54) Observations (NH-year) 4, , Note: a Adjusted Profit Margin defines profit as net income plus administrator s compensation to account for higher compensation for the owner-managers. Adjusted Profit Margin = (Net Income + Administrator s Compensation)/ (Net Revenues). examined (column 5). For example, NHs operated by nonowners-managers are found to have a greater percentage of residents with bedsores than NFPs, but the results are not statistically significant for the facility-acquired bedsore measure. Owner-managed NHs have worse quality in terms of contractures when compared to the NFPs whereas nonowner-managed NHs have better quality. However, for the facility-acquired contractures, we find no difference between owner-managed NHs and NFPs. In terms of care practices, all FPs have more residents that are physically restrained. For indwelling catheters, the total measure finds no statistical difference between FPs and NFPs, but the facility-acquired measure suggests better quality among nonowner-managed NHs when compared to the NFPs. The final outcome we examined is financial performance as measured by profit margin and adjusted profit margin which adds back administrator compensation into net income (Table 5). From the societal perspective, one main concern is that managerial ownership provides administrators stronger incentives to pursue profitability at the costs of patient s welfare. Among FPs, there is no statistically significant difference in financial performance by owner-managed and nonowner-managed NHs. When comparing FPs to NFPs, we found that NHs operated by owner-managers have statistically significant higher profit and adjusted profit margins (column 5). For completeness, we also use

7 The Gerontologist, 2017, Vol. 00, No Table 3. Managerial Ownership and Staffing, Deficiencies, and Use of Psychoactive Medications All for-profits Independent for-profits All for-profits and nonprofits OLS FE OLS FE OLS (1) (2) (3) (4) (5) Panel A: Registered nurse (HPRD) Owner-manager *** (0.0117) ** (0.0171) *** (0.0131) ** (0.0212) (0.0180) Nonowner-manager *** (0.0147) Panel B: Licensed practical nurse (HPRD) Owner-manager (0.0201) (0.0229) (0.0226) (0.0267) (0.0269) Nonowner-manager * (0.0209) Panel C: Certificated nurse aide (HPRD) Owner-manager *** (0.0386) * (0.0548) *** (0.0420) (0.0665) ** (0.0620) Nonowner-manager *** (0.0456) Panel D: Number of regulatory deficiencies Owner-manager (0.2842) (0.4288) (0.3070) (0.4777) *** (0.3417) Nonowner-manager *** (0.2613) Panel E: Antipsychotic medications (%) Owner-manager (0.8675) (0.7424) (0.9487) (0.8318) *** (0.9812) Nonowner-manager *** (0.6713) Panel F: Psychoactive medications (%) Owner manager (0.6592) (0.8589) (0.7059) (0.9844) (0.8488) Nonowner-manager (0.6474) Number of observations 4,047 4,047 2,272 2,272 4,979 Notes: HRPD = hours per resident day; NH = nursing home; OLS = ordinary least squares. FE means the NH-fixed effect model. The standard error is clustered at the NHs level. All regressions control for NH beds, chain-affiliation (except for the regressions in columns 3 and 4), being part of Continuing Care Retirement Community, payer-mix, patient case-mix, and urban/rural indicators. ***, **, and * represent significance at 1%, 5%, and 10% levels. total revenues, total costs, and return on assets as the alternative financial outcomes. Similar to the main financial performance analysis, we do not find statistically significant difference between owner-managed and nonowner-managed NHs (For brevity, we do not present these additional analyses. The results are available upon request.). Discussion The NH industry is highly regulated because the population that NHs serve is vulnerable and is often not fully informed about the quality of the services. Although the government has made many attempts to increase this knowledge, through annual inspections of facilities and public reporting of quality, some NHs may still exploit residents to increase profits. For these reasons, there has been much focus on how ownership and chain-affiliation affect NH outcomes, yet none of these studies examine the role of managerial ownership at the individual facility level. Under the standard principal-agent problem framework, providing a manager with equity ownership should better align the manager with the owner s objectives. In the case of FP NHs, it creates stronger incentives to provide a level of quality that maximizes profits but not necessarily residents welfare. Therefore, we would expect that NHs operated by owner-managers to have lower staffing levels, potentially similar or lower quality, but higher financial performance. Our results indicate otherwise. We find that NHs operated by owners-managers have higher staffing levels. Although nursing staff are the primary input in NH care, our results find no difference in most quality measures between owner-managed and nonowner-managed NHs, though quality in these two types of FP NHs is generally lower than the quality provided in NFPs. Furthermore, we find no statistically significant difference in financial performance across FP NHs. To reconcile the counter-intuitive findings, we discuss management entrenchment and managerial control as two potential explanations. Traditionally, entrenchment implies that greater equity ownership in a company weakens the oversight of managers (Chang & Mayers, 1992; Lasfer, 2006) and increases the manager s influence over corporate policies (Lemmon & Lins, 2003). As owners-managers increase their equity holdings in a firm, they are afforded more freedom to engage in the pursuit of private benefits at the expense of other owners when exercising their control power (Bebchuk & Fried, 2003; Morck et al., 1998; Short & Keasey, 1999). Consequently, this results in potentially larger compensation packages and managerial inefficiencies (Barclay & Holderness, 1989; Holderness & Sheehan,

8 8 The Gerontologist, 2017, Vol. 00, No. 00 Table 4. Managerial Ownership and Facility-Acquired Quality Measures All for-profits Independent for-profits All for-profits and nonprofits OLS FE OLS FE OLS (1) (2) (3) (4) (5) Panel A: Bedsore (%) Owner-manager (0.2394) (0.3983) (0.2712) (0.5242) (0.2895) Nonowner-manager ** (0.2123) Panel B: Acquired in NH: Bedsore (%) Owner-manager (0.1765) (0.2735) (0.1976) (0.3267) (0.2151) Nonowner-manager (0.1422) Panel C: Contractures (%) Owner-manager *** (1.8472) (1.9647) *** (1.9854) (2.4658) ** (2.2495) Nonowner-manager *** (1.5497) Panel D. Acquired in NH: Contractures (%) Owner-manager ** (1.3676) (1.7836) ** (1.5195) (2.0948) (1.6779) Nonowner-manager ** (1.0771) Panel E: Physical restraint (%) Owner-manager (0.4877) (0.6952) (0.5419) (0.8845) *** (0.5751) Nonowner-manager *** (0.3736) Panel F: Acquired in NH: Physical restraint (%) Owner-manager (0.4055) (0.4807) (0.4511) (0.5378) ** (0.4963) Nonowner-manager *** (0.3372) Panel G: Indwelling catheter (%) Owner-manager (0.4772) (0.4556) (0.4726) (0.5727) (0.5485) Nonowner-manager (0.3265) Panel H: Acquired in NH: Indwelling catheter (%) Owner-manager * (0.3328) (0.4240) (0.3023) (0.5323) (0.3507) Nonowner-manager *** (0.1830) Number of observations 4,047 4,047 2,272 2,272 4,979 Notes: OLS = ordinary least squares; NH = nursing home. FE means the NH-fixed effect model. The standard error is clustered at the NHs level. Note (3) All regressions control for NH beds, chain-affiliation (except the regressions in columns 3 and 4), being part of Continuing Care Retirement Community, payer-mix, patient case-mix, and urban/rural indicators. ***, **, and * represent significance at 1%, 5%, and 10% levels. Table 5. Managerial Ownership and Financial Performance All for-profits Independent for-profits OLS FE OLS FE OLS (1) (2) (3) (4) (5) All for-profits and nonprofits Panel A: Profit margin (%) Owner-manager (0.6175) (0.6161) (0.6811) (0.7054) *** (0.9331) Nonowner-manager *** (0.7171) Panel B: Adjusted profit margin (%) Owner-manager (0.6105) (0.6079) (0.6784) (0.7208) *** (0.9207) Nonowner-manager *** (0.7059) Number of observations 4,047 4,047 2,272 2,272 4,979 Notes: OLS = ordinary least squares. FE means the nursing home-fixed effect model. The standard error is clustered at the nursing homes level. All regressions control for NH beds, chain-affiliation (except the regressions in columns 3 and 4), being part of Continuing Care Retirement Community, payer-mix, patient casemix, and urban/rural indicators. Adjusted Profit Margin defines profit as net income plus administrator s compensation to account for higher compensation for the owner-managers. ***, **, and * represent significance at 1%, 5%, and 10% levels.

9 The Gerontologist, 2017, Vol. 00, No ; Huang et al., 2016). Furthermore, when there is a lack of transparency and product market is not competitive, the entrenchment of owner-managers is more likely (Dyck & Zingales, 2004). The literature generally links managerial entrenchment with negative corporate consequences. However, our empirical results do not support this point of view, as we would expect owner-managers to focus on the bottom line and have lower staffing levels. The second alternative explanation is that owner-managers use their control power to enhance the operation of the organization. Because owner-mangers are directly engaged with staff and residents on a daily basis, they may be more engaged and aware of issues as they arise. Furthermore, when problems do arise owner-mangers have greater freedom to enact policies and make decisions that improve the moral of staff and the lives of residents (Choi, Flynn, & Aiken, 2012). These policies can lead to impactful changes which enhance the overall financial performance of a facility even with higher staffing levels. Limitations Although we find that owner-managed NHs have higher nursing staff levels, similar quality and financial performance to nonowner-managed NHs, our study is limited in a few ways. First, we are limited by the data we utilize. Many of the quality and staffing measures are self-reported. It is unclear if any accuracy issues are more likely to occur in NHs operated by or not operated by owner-managers, which may bias our results. Or, the self-report errors may be independent from managerial ownership and the measurement error only leads to larger standard errors but does not bias our findings. Additionally, our data only reports whether key administrators own 5% or more of the nursing facility, and we are unable to determine if our results would vary with the size of equity ownership (e.g., majority-owner of greater than 50%). If many of the owner-managers are the majority-owners, management entrenchment and managerial control can be more influential than the principal-agent model. Second, Ohio s situation may not be representative of other states. Although Ohio is a large state with varied corporate ownership-structures, until the Department of Health and Human Services begins reporting more ownership information due to the passage of The Nursing Home Transparency and Improvement Act of 2009, Ohio is one of the only available sources of information on managerial ownership. Third, as discussed in the method section, the statistical identification of our NH fixed-effect model comes from switches in the owner-manager variable over time. This can lead to potential bias in our results if these switches are nonrandom, but these biases can go in both directions. We examined whether owners-mangers select into NHs with better financial performance and compared switchers to non-switchers in terms of characteristics and NH outcomes. Our robustness checks suggest that these switches are unlikely to be a major concern, but future research is needed to examine this issue using plausible exogenous changes in managerial ownership. Finally, owner-managers may systematically admit a different population of patients, which can affect the quality outcomes. Accounting for this selection problem can help to understand if owner-managed NHs admit sicker patients and therefore, their higher staffing levels do not yield superior quality. Implications Since most NH residents are paid for by Medicaid, and the Medicaid program reimburses at the lowest rates, NH administrators are faced with the challenge of balancing the needs and expectations of staff, residents, and owners in a resource-constrained environment (Siegel et al., 2015). When these administrators are part of larger corporate chains, standardized policies and short-term profitability goals may leave administrators with limited options but lower staffing and quality. In contrast, owners-managers may have greater flexibility in balancing the needs for more resources relative to profits, and may be able to focus on the long-run financial performance and other organizational goals (e.g., quality reputation; Castle, 2001). The fact that owner-managed NHs have higher staffing levels and similar financial performance suggests that this flexibility is leading to positive externalities which we cannot directly measure (e.g., lower staff turnover, higher resident satisfaction, lower supplies costs). From a practical standpoint, allowing managers greater flexibility and focusing more on long-run performance over short-run goals may result in better operated NHs. Although we are unable to address if these are specific mechanisms that lead to these positive externalities without additional qualitative research, our result suggests that the factors that make owner-managers different than nonowner-managers have the potentials to yield better NH outcomes. Because disproportionately more owner-managed NHs do not belong to chains, our results also shed lights on the difference between chain and non-chain NHs. Conclusion NHs operated by owner-managers are smaller, less likely to belong to chains, and have smaller percentage of Medicare patients. After adjusting for these differences, NHs that are operated by owner-managers have higher nursing staff levels, but have statistically similar quality and financial performance. These results do not fully support the classical principal-agent model. Some potential explanations for these results are owner-managers have greater flexibility in enacting timely policies and may be able to invest in long-run operation instead of focusing on short-term performance. Although our results suggest that having an

10 10 The Gerontologist, 2017, Vol. 00, No. 00 equity stake in a NH does not affect quality measures that are aggregated at the facility level, additional work is warranted to examine these effects across a broader range of quality measures, including patient and family satisfaction and staff turnover, as well as using patient-level quality data. What is clear is that NH ownership structures are more nuanced than simply broadly categorizing facilities as FP or NFP, and this complexity of ownership needs to be considered when broadly referring to FP NHs in research and policy discussions. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Acknowledgments We thank two anonymous referees for their valuable comments and also thank Lisa Bowman at The Ohio Department of Job and Family Services who made the data available for this study. Conflict of Interest S. S. Huang and J. R. 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