Nursing staff including registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs) are critical to nursing home (NH) operations but account for approximately 27% of net revenues. Understanding how nursing staff wages affect financial performance is particularly important as policy efforts seek to expand NH minimum staffing hours. Drawing from efficiency wage theory, which posits that employers may pay above-market wages to enhance worker productivity and retention, this study examined the relationship between nursing staff wages and NH financial performance. We used secondary datasets, including Payroll-Based Journal data and Medicare cost reports (N = 37 933 facility-year observations, 2020-2022). The dependent variable was operating margin, while the independent variables were facility-level RN, LPN, and CNA wages. An instrumental variable (IV) approach was used to address potential endogeneity in RN wages, with county-level average wages (excluding the index facility) serving as the instrument. The first stage modeled RN wages as a function of the instrument, and the second stage estimated the effect of predicted wages on operating margin. Ordinary least squares models were used for LPN and CNA wages, for which endogeneity was not detected. A $1 increase in RN wages was associated with a 0.70 percentage-point decrease in operating margin ( P = .01, 95% CI [−1.27, −0.14]). For LPNs, a $1 increase was associated with a 0.17-point decrease ( P < .001, 95% CI [−0.20, −0.13]), and for CNAs, a 0.31-point decrease ( P < .001, 95% CI [−0.37, −0.26]). These findings underscore the tension between workforce investment and financial sustainability in an industry that operates in a resource-constrained environment. Policy interventions such as wage subsidies or higher Medicaid reimbursements may be necessary to balance staffing investments with financial viability.

BACKGROUND AND OBJECTIVES:Turnover among nursing staff (registered nurses, licensed practical nurses, and certified nursing assistants [CNAs]) is a long-standing challenge in nursing homes with significant implications for quality of care. This study aimed to examine the relationship between nursing staff wages and turnover. RESEARCH DESIGN AND METHODS:We used national data from 2021 to 2023, linking multiple datasets including the Payroll-Based Journal and Medicare Cost Reports (n = 37,254). Turnover was modeled separately for each nursing staff type as a fractional outcome bounded between 0 and 1. The primary predictor variable was facility-level average hourly wage for each staff type. To address potential endogeneity and reverse causality, we used a two-stage residual inclusion instrumental variables approach with county-level average wages (excluding the index facility) as the instrument. Models controlled for facility-level organizational and county-level market characteristics, with fixed effects for county and year and cluster-robust standard errors at the facility level. RESULTS:Higher CNA wages were significantly associated with lower turnover (β = -0.35, 95% CI [-0.59, -0.11], p = .005), indicating a 0.35 percentage point reduction in turnover per $1 increase in hourly wage. Wages were not significantly associated with turnover among licensed nurses. DISCUSSION AND IMPLICATIONS:Findings suggest that wage increases may be most effective for CNAs, while retaining licensed nurses likely requires complementary organizational and nonmonetary strategies. While nursing homes should strive to offer competitive wages to their staff, targeted reimbursement reforms may be necessary to overcome financial constraints.

BACKGROUND:Leadership instability in nursing homes marked by high administrator turnover threatens the well-being of vulnerable residents. Although numerous factors have been implicated, the role of ownership remains unexplored. PURPOSES:Based upon the tenets from institutional theory and strategic management theory, the primary goal of this study was to examine the impact of ownership on administrator turnover. METHODOLOGY/APPROACH:Data were derived from different sources: LTCFocus.org , Nursing Home Five-Star Quality Rating System, and Area Health Resources Files (2021-2022). The dependent variable was administrator turnover categorized as follows: 0 = no administrators left, 1 = one administrator left, and 2 = two or more administrators left. The primary independent variable was ownership/chain affiliation categorized as four possible interactions of for-profit (FP) status and chain affiliation: not-for-profit (NFP) independent, FP independent, NFP chain, and FP chain. An ordinal logistic regression model was used, and predicted turnover probabilities were calculated across the four ownership categories. RESULTS:The primary hypothesis was supported and compared to NFP independent, FP chain, FP independent, and NFP chain nursing homes that exhibited approximately 2.3, 1.7, and 1.4 times higher odds of administrator turnover. Predicted probabilities confirmed these trends: FP chain nursing homes had the lowest retention, with a 42% probability of no turnover, 32% for one administrator leaving, and 26% for two or more leaving. In contrast, NFP independent facilities had the highest retention rates, with a 62% chance of no turnover, 25% for one leaving, and 13% for two or more. Differences between groups were statistically significant ( p < .001). CONCLUSION:FP chain ownership was associated with the highest administrator turnover rates, whereas NFP facilities experienced the lowest. FP independent and NFP chain homes had intermediate probabilities of administrator turnover. PRACTICE IMPLICATIONS:Tailoring management strategies to the specific ownership structure may reduce administrator turnover and ensure consistent resident care.

Prior research has shown that extended nursing staff [registered nurses (RNs, licensed practical nurses (LPNs), and certified nursing assistants (CNAs) work hours can lead to more medical errors, declines in care quality, and higher turnover rates. This study examined the organizational and environmental factors associated with extended work hours among nursing staff in nursing homes (NHs). The study utilized multiple datasets such as Care Compare: Five-Star Quality Rating System and Payroll Based Journal, and Data were modeled using multivariable linear regression with year and state-levels fixed effects (2023, n = 42,743). Three separate models were run for for RNs, LPNs, and CNAs. The dependent variable was extended work hours, measured as the percentage of nursing staff exceeding 50 work hours per week, averaged across the year to calculate the annual facility-level rate. The key variable of interest was a categorical variable that captured the intersection of ownership status and chain affiliation: for-profit-chain (FPC), for-profit independent (FPI), not-for-profit chain (NFPC), and not-for-profit independent (NFPI). Results suggested that FPIs and FPCs experienced the highest level of extended work hours, with the largest increases observed for RNs and LPNs. Higher wages correlated positively with extended work hours for RNs and LPNs, but negatively associated for CNAs. NH size was positively associated with extended work hours across all nursing staff. All results were significant at p < 0.001. These findings highlight the need for targeted policy and regulatory interventions to mitigate extended work hours, particularly in for-profit NHs, to improve workforce sustainability and care quality.

OBJECTIVE:Nursing staff are central to ensuing high-quality care in nursing homes (NHs), yet their wages often lag behind those in other health care settings. This study aimed to examine whether higher wages for nursing staff-registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs)-were associated with better NH quality. DESIGN:This was an observational study using panel data from 2020 to 2022. SETTING AND PARTICIPANTS:The study included all Centers for Medicare and Medicaid Services-certified US NHs. The analytic data file comprised 37,577 facilities. METHODS:This study used multiple secondary datasets, including the Payroll-Based Journal, Medicare Cost Reports, Care Compare: Five-Star Quality Rating System (Five-Star QRS), and LTCFocus.org. The primary outcome was NH quality, operationalized through the quality domain of the Five-Star QRS. The primary independent variables were the facility-level average hourly wages for RNs, LPNs, and CNAs, adjusted for inflation. To address potential endogeneity, average nursing staff wages at the county level, excluding the index facility, were used as an instrument for wages. RESULTS:A 1-dollar increase in wages for RNs, LPNs, and CNAs was associated with 12% (95% CI, 1.07-1.17), 10% (95% CI, 1.05-1.15), and 8% (95% CI, 1.07-1.45) higher odds, respectively, of obtaining a higher star rating (P < .001). Marginal effects analysis showed that a 1-dollar increase in wages was associated with a 2.4%, 2.0%, and 1.8% higher likelihood of achieving a 5-star rating for RNs, LPNs, and CNAs, respectively. CONCLUSIONS AND IMPLICATIONS:Higher nursing staff wages were associated with increased odds of achieving a higher quality rating. NHs need to offer competitive wages as part of broader efforts to improve quality. Targeted reimbursement strategies may be necessary to support wage increases, especially for facilities serving a high proportion of vulnerable residents.

Nursing home (NH) care is labor intensive with total labor costs constituting nearly 70% of an average facility’s operating costs. This study aimed to assess the relationship between nursing staff [registered nurses (RNs), licensed practical nurses (LPNs), certified nursing assistants (CNAs)] extended work hours and NH financial performance, specifically their operating costs. The study utilized four datasets: Care Compare: Five-Star Quality Reporting System, Medicare Cost Reports, LTFocus.org, and the Area Health Resource Files (2020-2022). A multivariable linear regression model with two-way fixed effects (year and state) was employed to analyze the data (N = 38,966). Separate regression models were estimated for RNs, LPNs, and CNAs. The dependent variable was operating costs, which include all costs incurred in direct resident care. The independent variable was extended work hours, measured as the percentage of nursing staff exceeding 50 work hours per week, averaged across the year to calculate the annual facility-level rate. After controlling for appropriate organizational and environmental level factors, the analysis did not find significant association between nursing staff extended work hours and NH operating costs. The findings suggest that extended work hours may be a convenient strategy for NH administrators to meet resident care demands, as it does not appear to significantly impact operating costs in our study. However, relying on extended hours could have unintended consequences, such as increased nursing staff burnout, reduced job satisfaction, and potential declines in care quality. While this approach may seem financially neutral, its long-term effects on resident outcomes and workforce stability warrant closer attention.

Context: High Medicaid nursing homes are under-resourced and associated with lower resident quality of care. Culture change initiatives, a movement to transition nursing homes to more home-like environments, are a potential process to improve residents’ quality of life and care. Objective: To examine how the number of years of implementing culture change initiatives is associated with nursing home quality among high Medicaid nursing homes in the US. Methods: The study used national survey data from nursing home administrators (n = 348) merged with secondary data sources for the year 2018: LTCfocus.org, Centers for Medicare and Medicaid Services (CMS) Skilled Nursing Facility Quality Rating Program (SNF QRP), and the Area Health Resource File. The dependent variable was the nursing home quality star rating obtained from the CMS SNF QRP. The independent variable represented the number of years of implementation of culture change initiatives. Data were modelled using an ordinal logistic regression with state-level fixed effects (n = 339). Findings: Compared to nursing homes with no culture change/one year or less implementing culture change initiatives, those with six or more years had increased odds of having a higher star rating. Facilities with two to five years of implementing culture change initiatives did not significantly differ from nursing homes with no culture change/one year or less implementing culture change initiatives. Limitations: The culture change measure was self-reported by nursing home administrators. Implications: Results suggest that a more extended implementation period of culture change initiatives may be needed to see quality improvements among high Medicaid nursing homes.

Background: Nursing homes have long struggled with nursing staff shortages. These staffing gaps have led nursing homes to increasingly rely on agency or contract labor hired through third-party agencies. While agency nursing labor may enable nursing homes to maintain resident care, it costs substantially more than permanent staff. These increased expenses can put downward pressure on nursing home financial performance. Drawing from Resource Dependency Theory and Transaction Cost Economics, this study investigated the association between the use of agency nursing staff and nursing home financial performance. Methods: This study utilized five secondary data sets: Payroll-based Journal (PBJ), Care Compare FiveFiles, and LTCFocus.org for the study period 2018-2022. All Medicare and Medicaid certified U.S. nursing homes were included in the analysis (n=65,821). The dependent variable was operating margin, a widely used financial measure which indicates the entity's operating profitability. Independent variables included the proportion of agency nursing staff hours for registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs), while controlling for facility and community characteristics that may affect nursing home financial performance. A multivariable linear regression model with two-way (facility and year) fixed effects was used. Results: Regression analysis indicated that greater reliance on agency nursing staff was significantly associated with lower operating margins across all three categories: RNs [0=-0.32, 95% confidence interval (CI): -0.37, -0.27, P<0.001], LPNs (0=-0.34, 95% CI: -0.39, -0.30, P<0.001) and CNAs (0=-0.37, 95% CI: Conclusions: Agency labor may provide a convenient solution for addressing staffing gaps; however, their use may negatively impact nursing home outcomes, including financial performance. Nursing homes should prioritize the recruitment and retention of permanent nursing staff, with appropriate policy support to address workforce shortages and improve long-term sustainability.

This study investigated the trends in agency nursing staff utilization in United States nursing homes against the backdrop of longstanding staffing challenges exacerbated by the COVID-19 pandemic. It analyzed data from the Centers for Medicare and Medicaid Services Payroll-Based Journal (PBJ), LTCFocus.org, Area Health Resources Files, and Rural-Urban Commuting Area codes covering 80,244 nursing home-year observations (2017-2022). Joinpoint regression analysis revealed that agency labor utilization increased across all nursing staff categories (registered nurses, licensed practical nurses, certified nursing assistants), with a significant upward shift beginning in 2020, coinciding with the onset of the COVID-19 pandemic. The study also noted an interesting pattern of increased agency nursing staff use during weekends, possibly due to reduced availability of full-time staff. Ownership analysis revealed that not-for-profit chain facilities had the highest use of agency labor. We also examined differences in agency nursing staff utilization by nursing home size and location (urban/rural). Additionally, state-level variations in agency staff utilization were noted, highlighting regional differences in reliance on agency labor. Additional research is needed to evaluate the policy and operational implications of agency nursing staff utilization in nursing homes.

Nursing staff—including registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs)—are the primary caregivers in nursing homes (NHs), and the quality of care largely depends on their adequacy and expertise. Previous studies, primarily conducted in acute care settings, suggest that extended work hours among nursing staff can lead to more medical errors and lower care quality. This study examined the association between extended work hours among nursing staff and NH quality. It utilized multiple secondary datasets, including the Payroll-Based Journal and Care Compare: Five-Star Quality Rating System (Five-Star QRS) (2020-2022). The study focused on the quality star rating (1-5 scale) from the Five-Star QRS as the dependent variable. The independent variable was extended work hours, measured as the percentage of nursing staff exceeding 50 work hours per week, averaged across the year to calculate the annual facility-level rate. A Multivariable ordinal logistic regression with two-way (facility and year-level) fixed effects was employed with appropriate control variables (42,743). Results indicated that extended work hours were associated with lower odds of achieving a higher star rating. Specifically, for RNs, each additional hour was linked to a 1 percentage point decrease in the odds of being in a higher star rating category. For LPNs and CNAs, the decrease was 2 percentage points per additional hour. All results were statistically significant at p < .0001. Policy and managerial efforts should focus on nursing staff retention and recruitment though workload regulations may be required to ensure sustainable, high-quality NH care.

PURPOSE:The financial sustainability of nursing homes is increasingly critical as the aging US population continues to grow. Rural facilities often encounter more significant economic challenges than urban counterparts. This study investigates the disparities in financial performance between rural and urban nursing homes in the United States, emphasizing the influence of organizational and environmental factors. A comprehensive understanding of these differences is necessary for the implementation of effective policy and management interventions. METHODS:The study used a longitudinal dataset (2018-2022) comprising 66,056 nursing home-year observations. Data sources included Centers for Medicare and Medicaid Services (CMS) Cost Reports, Payroll-Based Journal, Care Compare, LTCFocus, and the Area Health Resource File. The dependent variable was the operating margin. The primary independent variable, geographic location, was classified using Rural-Urban Commuting Area (RUCA) codes. We conducted multivariable linear regression with facility-level random effects and two-way fixed effects (state and year) to assess rural-urban financial disparities while controlling for organizational and environmental factors and the impact of COVID-19. FINDINGS:Rural nursing homes had lower operating margins than urban facilities in unadjusted models. However, after adjusting for organizational factors such as size, occupancy, and payer mix, the rural-urban difference was no longer significant. Environmental factors, including population demographics and income levels, contributed to financial disparities. COVID-19 exacerbated financial challenges, disproportionately affecting rural facilities. CONCLUSIONS:Financial disparities between rural and urban nursing homes are not solely due to geographical location, but also stem from structural challenges. These insights have significant policy implications suggesting that addressing reimbursement rates, operational efficiency, and resource allocation is crucial to ensure the financial sustainability and quality care for aging populations.

Introduction:Nursing homes (NHs) serve as a safety net for vulnerable populations such as older adults and people with disabilities. Nursing Home Administrators (NHAs) play a crucial role in managing the daily operations of NHs, including overseeing direct care staff and establishing the facility's strategic direction. Unfortunately, NHs have consistently faced high NHA turnover rates, which have been linked to poor organizational performance. This study aims to investigate the relationship between NHA turnover and financial performance in NHs.Methods:Using an integrated perspective based on the upper echelons theory and the resource-based view of the firm, we investigated the association between NHA turnover and financial peformance using multiple secondary data sources, such as the Care Compare: Skilled Nursing Facility Quality Reporting Program and Brown University's Long Term Care Focus. We conducted a cross-sectional study using a multivariate linear regression model, measuring financial performance using operating margin while NHA turnover represents the number of administrators that left the organization.Results:Our findings indicate that NHs with higher NHA turnover rates have lower operating margins. Specifically, compared to facilities with no turnover, one NHA turnover is associated with a 1.14% decrease in operating margin, and two or more turnovers are associated with a 2.25% decrease.Discussion:This study contributes to the existing literature by demonstrating the financial impact of NHA turnover and provides further evidence of the need for targeted organizational and policy interventions to improve NHA retention.

Objective: To assess the association of agency nursing staff utilization with nursing home (NH) quality. Background: Nursing staff are the primary caregivers in NHs, where high-quality care is contingent upon their adequacy and expertise. Long-standing staffing challenges, exacerbated by the COVID-19 pandemic, have led NHs to rely on agency/contract labor to alleviate staffing shortages. Methods: This study used the following secondary datasets: Payroll-Based Journal, Care Compare: 5-Star Quality Rating System, LTCFocus.org, Area Health Resource Files, and Rural-Urban Commuting Area codes for 2017-2022. Multivariable ordinal logistic regression with 2-way (facility and year-level) fixed effects was employed. The study included all Centers for Medicare and Medicaid Services certified U.S. NHs. Analytic data comprised 80,244 facilities, averaging 13,374 unique NHs per year. The study focused on the quality star rating (1-5 scale) from the 5-Star Quality Rating System as the dependent variable. Independent variables included the proportion of agency nursing staff hours per resident day for registered nurses, licensed practical nurses, and certified nursing assistants while controlling for facility and community characteristics that may affect NH quality. Results: A 10% increase in agency registered nurses, licensed practical nurses, and certified nursing assistants (logged) was associated with a decrease in the odds of achieving a higher star rating by 4%, 5%, and 4%, respectively (P < 0.001). Conclusions: The use of agency nursing staff can negatively impact NH quality. Efforts to better integrate agency nursing staff into NHs, combined with strategies to recruit and retain permanent nursing staff, could lead to improved outcomes for residents.

Objective: To assess the association of agency nursing staff utilization with nursing home (NH) quality. Background: Nursing staff are the primary caregivers in NHs, where high-quality care is contingent upon their adequacy and expertise. Long-standing staffing challenges, exacerbated by the COVID-19 pandemic, have led NHs to rely on agency/contract labor to alleviate staffing shortages. Methods: This study used the following secondary datasets: Payroll-Based Journal, Care Compare: 5-Star Quality Rating System, LTCFocus.org, Area Health Resource Files, and Rural-Urban Commuting Area codes for 2017–2022. Multivariable ordinal logistic regression with 2-way (facility and year-level) fixed effects was employed. The study included all Centers for Medicare and Medicaid Services certified U.S. NHs. Analytic data comprised 80,244 facilities, averaging 13,374 unique NHs per year. The study focused on the quality star rating (1–5 scale) from the 5-Star Quality Rating System as the dependent variable. Independent variables included the proportion of agency nursing staff hours per resident day for registered nurses, licensed practical nurses, and certified nursing assistants while controlling for facility and community characteristics that may affect NH quality. Results: A 10% increase in agency registered nurses, licensed practical nurses, and certified nursing assistants (logged) was associated with a decrease in the odds of achieving a higher star rating by 4%, 5%, and 4%, respectively (P < 0.001). Conclusions: The use of agency nursing staff can negatively impact NH quality. Efforts to better integrate agency nursing staff into NHs, combined with strategies to recruit and retain permanent nursing staff, could lead to improved outcomes for residents.