More than three million US nursing home residents were diagnosed with Alzheimers disease and related dementias (ADRD) between 2017 and 2019. This number is expected to increase as the population ages and ADRD prevalence increases. People with ADRD require specialized care from trained staff. This study addressed two questions: Are residents with ADRD concentrated in nursing homes where they are the majority? If not, what are the implications for their quality of care and life? We answered the first question by determining the ADRD census for each nursing home in the country during the period 2017-19. Using the Minimum Data Set and Medicare claims, we compared characteristics of nursing homes with high and low ADRD census along several dimensions, including staffing, resident outcomes, and resident characteristics. We found that residents with ADRD were dispersed throughout all nursing homes, with fewer than half residing in nursing homes where residents with ADRD accounted for 60-90 percent of the census. Furthermore, only facilities exceeding 90 percent of residents with ADRD seemed to offer better care. These findings raise concerns about the quality of care and life for the majority of residents with ADRD, suggesting that current National Institutes of Health dementia research initiatives and the Biden administrations policies to improve nursing home care should be coordinated.

Objectives

Although many prior studies have shown that high average levels of nurse staffing in nursing homes are associated with fewer hospitalizations, some studies have not, suggesting that the average nursing level may mask a more complex relationship. This study examines this issue by investigating the associations of daily staffing patterns and daily hospitalizations and emergency department (ED) visits.

Design

Retrospective analyses of national Payroll Based Journal (PBJ) staffing data merged with the Minimum Data Set.

Setting and participants

A total of 15,718 nursing homes nationally reporting PBJ data during 2017-2019, their staff, and residents.

Methods

We estimated facility-day-level models as conditional facility fixed-effect Poisson regressions with robust standard errors. The dependent variables were daily numbers of hospitalization and ED visits and the independent variables of interest were the number of registered nurse (RN), licensed practical nurse (LPN), and certified nurse assistant (CNA) hours on the same and prior days.

Results

The daily number of hospital transfers averaged 0.28 (SD 0.21). Daily total direct-care staffing hours averaged 288.7 (SD 188.2), with RNs accounting for 35.0, LPNs for 68.7, and CNAs for 185.0. Higher staffing was associated with more hospitalizations on the concurrent day. Higher staffing on the day prior was associated with fewer hospitalizations. The effect size was larger for RNs and LPNs (same day = ∼2%; prior day = approximately -0.7% to -0.9%) than for CNAs (same day <1%; prior day < -0.5%). ED visits not leading to hospitalizations, and analyses for subsamples exhibited similar findings.

Conclusions and implications

Our findings suggest that staff can address developing problems and prevent admissions the next day and identify emergent problems and hospitalize the same day. They also underscore the complex array of nursing home factors involved in hospitalization and ED visits, including the influence of daily staffing variation, suggesting the need for further research to better understand the associations between staffing and appropriate resident transfers to the hospital or the ED, and the potential implications for quality metrics in these domains.

OBJECTIVE: To estimate and contrast the relationships between nurse staffing and health outcomes in nursing homes with low and high dementia census, to understand the association of staffing hours with dementia care quality. DATA SOURCES AND STUDY SETTING: A national sample of nursing homes during 2017-2019 (pre-COVID). Data included the Payroll-Based Journal, Medicare Claims, Nursing Home Care Compare, and Long-Term Care Focus. STUDY DESIGN: Retrospective, regression analyses. We estimated separate linear models predicting six long-term facility-level outcomes. Independent variables included staffing hours per resident-day (HPRD) interacted with the facility percentage of dementia residents, controlling for other resident and facility characteristics. DATA COLLECTION/EXTRACTION METHODS: Hospital-based nursing homes, those with fewer than 30% dementia residents, and missing data were excluded. PRINCIPAL FINDINGS: We found that registered nurses and certified nurse assistants HPRDs were likely to exhibit positive returns in terms of outcomes throughout most of the range of HPRD for both high and low-census dementia facilities, although, high- and low-dementia facilities differed in most outcome rates at all staffing levels. Average predicted antipsychotics and activities of daily living as functions of HPRD were worse in higher dementia facilities, independent movement, and hospitalizations did not differ significantly, and Emergency Rooms and pressure sores were worse in lower dementia facilities. Average marginal effects were not statistically different [CI included zero] between the high and low dementia facilities for any outcome. CONCLUSIONS: These findings suggest that increasing staffing will improve outcomes by similar increments in both low- and high-dementia facilities for all outcomes. However, at any given level of staffing, absolute differences in outcomes between low- and high-dementia facilities remain, suggesting that additional staffing alone will not suffice to close these gaps. Further studies are required to identify opportunities for improvement in performance for both low- and high-dementia census facilities.

OBJECTIVE: This study examines how measures of staffing-turnover and instability-are associated with one another and how they independently contribute to quality of care in nursing homes. DESIGN: Cross-sectional analysis of 2021-2022 administrative data. Data included the Payroll Based Journal for daily staffing information, merged with Nursing Home Care Compare (NHCC) data for nursing home characteristics, total staffing turnover, and nursing home quality. SETTING AND PARTICIPANTS: A total of 11,840 nursing homes nationally reporting data on daily staffing and staffing turnover. METHODS: We explored correlations between measures of staffing and estimated facility-level regression models with robust standard errors. The dependent variables were indicators of nursing home quality included in the NHCC 5-star ratings. The independent variables of interest were average total staffing hours per resident-day, total staffing turnover, and total staffing instability. RESULTS: For the 11,840 nursing homes in the study, there was a weak positive correlation between turnover and instability, with some overlap between nursing homes with high instability and high turnover. Regression analysis revealed that staffing instability and turnover contributed independently to nursing home quality, with instability having a stronger association with some measures of quality and turnover with others. Staffing instability was positively and more strongly associated with long-stay residents decline in activities of daily living levels and receipt of antipsychotic drugs and short-stay residents functioning at discharge. Turnover was positively and more strongly associated with long-stay residents prevalence of pressure ulcers and worsening mobility, and short-stay residents hospitalizations. CONCLUSION AND IMPLICATIONS: Instability and turnover in total nursing home staffing independently contribute to nursing home quality. This suggests that adding measures of staffing instability to the existing measures of average staffing and staff turnover in NHCC may enhance the report cards value for providers engaged in quality improvement and consumers searching for high-quality nursing homes.