Staffing subsidies and the quality of care in nursing homes

Insurance coverage, long-term care utilization, and health outcomes

How does the generosity of social insurance coverage affect the demand for healthcare and health outcomes of elderly people? This paper presents an examination of the effects of insurance coverage on long-term care (LTC) utilization and its health consequences using administrative data of the public long-term care insurance (LTCI) system in Japan. In LTCI, a recipient's health score determines their insurance coverage limit, and thresholds of the score generate discontinuous changes in the level of coverage limits. I implement a regression discontinuity design and find that coverage expansion increases recipients' LTC utilization considerably irrespective of their health status. When more generous insurance coverage is available, recipients with low care needs increase day care and rehabilitation services, whereas those with high care needs increase home care services. Moreover, using more LTC has little effect on health outcomes such as the health score and the entry into nursing homes. Together, these results suggest that generous LTCI coverage can induce excessive LTC utilization without having health benefits.

The Impact of Wages on Care Home Quality in England

BACKGROUND AND OBJECTIVES

In many countries, a large proportion of long-term care staff are paid at, or near, minimum wage, leading to concerns of negative effects on care outcomes. This study analyzed the effect of staff wages on care home quality ratings in England.

RESEARCH DESIGN AND METHODS

A national staffing database of long-term care providers was matched with local-area information on needs and supply to construct a 3-year panel (2016-2018) of English care home observations. Using multiple imputation methods to address missing data provided a data set of 12,055 observations of 5,556 care facilities (both residential and nursing homes). We analyzed the effect of the facility-level average hourly wage of care staff on national regulator quality ratings. A measure of the impact of exogenous changes in the national minimum wage on care facilities was used as an instrument for wage.

RESULTS

We find that wages positively affect care home quality ratings. Other things equal, a 10% increase in the average hourly wage of direct care workers would lead to a 7.1% increase in the likelihood that a care home will have a high-quality rating. The wage effect on quality was significant when controlling for staff skill mix, measured as the share of registered nurses in nursing home staff.

DISCUSSION AND IMPLICATIONS

This study provides important evidence of the positive impact that staff pay can have on the quality of long-term care. Our finding has important implications for appropriate levels of pay and the funding of long-term care.

Risk of Discharge to Lower-Quality Nursing Homes Among Hospitalized Older Adults With Alzheimer Disease and Related Dementias

IMPORTANCE

Individuals with Alzheimer disease and related dementias (ADRD) frequently require skilled nursing facility (SNF) care following hospitalization. Despite lower SNF incentives to care for the ADRD population, knowledge on how the quality of SNF care differs for those with vs without ADRD is limited.

OBJECTIVE

To examine whether persons with ADRD are systematically admitted to lower-quality SNFs.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional analysis of Medicare beneficiaries hospitalized between January 1, 2017, and December 31, 2019, was conducted. Data analysis was performed from January 15 to May 30, 2022. Participants were discharged to a Medicare-certified SNF from a general acute hospital. Patients younger than 65 years, enrolled in Medicare Advantage, and with prior SNF or long-term nursing home use within 1 year of hospitalization were excluded.

EXPOSURES

The quality level of all SNFs available at the patient's discharge, measured using publicly reported 5-star staffing ratings. The 5-star ratings were grouped into 3 levels (1-2 stars [reference category, low-quality], 3 stars [average-quality], and 4-5 stars [high-quality]).

MAIN OUTCOMES AND MEASURES

The outcome was the SNF a patient entered among the possible SNF destinations available at discharge. Differences in the association between SNF quality and SNF entry for patients with and without ADRD were assessed using a conditional logit model, which simultaneously controls for differences in discharging hospital, residential neighborhood, and the other characteristics (eg, postacute care specialization) of all SNFs available at discharge.

RESULTS

The sample included 2 619 464 patients (mean [SD] age, 81.3 [8.6] years; 61% women; 87% were White; 8% were Black; 22% with ADRD). The probability of discharge to higher quality SNFs was lower for patients with ADRD. If the star rating of an SNF was high instead of low, the log-odds of being discharged to it increased by 0.31 for patients with ADRD and by 0.47 for those without ADRD (difference, -0.16; P < .001). The weaker association between quality and entry for patients with ADRD indicates that they are less likely to be discharged to high-quality SNFs.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that patients with ADRD are more likely to be discharged to lower-quality SNFs. Targeted reforms, such as ADRD-specific compensation adjustments, may be needed to improve access to better SNFs for patients with ADRD.

Staffing Patterns in US Nursing Homes During COVID-19 Outbreaks

Importance

Staff absences and departures at nursing homes may put residents at risk and present operational challenges.

Objective

To quantify changes in nursing home facility staffing during and after a severe COVID-19 outbreak.

Design Setting and Participants

In this cohort study, daily staffing payroll data were used to construct weekly measures of facility staffing, absences, departures, and use of overtime and contract staff among US nursing homes experiencing a severe COVID-19 outbreak that started between June 14, 2020, and January 1, 2021. Facility outbreaks were identified using COVID-19 case data. An event-study design with facility and week fixed effects was used to investigate the association of severe outbreaks with staffing measures.

Exposures

Weeks since the beginning of a severe COVID-19 outbreak (4 weeks prior to 16 weeks after).

Main Outcomes and Measures

Total weekly staffing hours, staff counts, staff absences, departures, new hires, overtime and contract staff hours measured for all nursing staff and separately by staff type (registered nurses, licensed practical nurses, certified nursing assistants), facility self-reported staff shortages, and resident deaths.

Results

Of the included 2967 nursing homes experiencing severe COVID-19 outbreaks, severe outbreaks were associated with a statistically significant drop in nursing staffing levels owing to elevated absences and departures. Four weeks after an outbreak's start, around when average new cases peaked, staffing hours were 2.6% (95% CI, 2.1%-3.2%) of the mean below preoutbreak levels, despite facilities taking substantial measures to bolster staffing through increased hiring and the use of contract staff and overtime. Because these measures were mostly temporary, staffing declined further in later weeks; 16 weeks after an outbreak's start, staffing hours were 5.5% (95% CI, 4.5%-6.5%) of the mean below preoutbreak levels. Staffing declines were greatest among certified nursing assistants, primarily owing to smaller increases in new hires of this staff type compared with licensed practical nurses and registered nurses.

Conclusions and Relevance

In this cohort study of nursing homes experiencing severe COVID-19 outbreaks, facilities experienced considerable staffing challenges during and after outbreaks. These results suggest the need for policy action to ensure facilities' abilities to maintain adequate staffing levels during and after infectious disease outbreaks.

Changing landscape of nursing homes serving residents with dementia and mental illnesses

OBJECTIVE

Nursing homes (NHs) are serving an increasing proportion of residents with cognitive issues (e.g., dementia) and mental health conditions. This study aims to: (1) implement unsupervised machine learning to cluster NHs based on residents' dementia and mental health conditions; (2) examine NH staffing related to the clusters; and (3) investigate the association of staffing and NH quality (measured by the number of deficiencies and deficiency scores) in each cluster.

DATA SOURCES

2009-2017 Certification and Survey Provider Enhanced Reporting (CASPER) were merged with LTCFocUS.org data on NHs in the United States.

STUDY DESIGN

Unsupervised machine learning algorithm (K-means) clustered NHs based on percent residents with dementia, depression, and serious mental illness (SMI, e.g., schizophrenia, anxiety). Panel fixed-effects regressions on deficiency outcomes with staffing-cluster interactions were conducted to examine the effects of staffing on deficiency outcomes in each cluster.

DATA EXTRACTION METHODS

We identified 110,463 NH-year observations from 14,671 unique NHs using CASPER data.

PRINCIPAL FINDINGS

Three clusters were identified: low dementia and mental illnesses (Postacute Cluster); high dementia and depression, but low SMI (Long-stay Cluster); and high dementia and mental illnesses (Cognitive-mental Cluster). From 2009 to 2017, the number of Postacute Cluster NHs increased from 3074 to 5719, while the number of Long-stay Cluster NHs decreased from 6745 to 3058. NHs in Long-stay/Cognitive-mental Clusters reported slightly lower nursing staff hours in 2017. Regressions suggested the effect of increasing staffing on reducing deficiencies is statistically similar across NH clusters. For example, 1 hour increase in registered nurse hours per resident day was associated with -0.67 (standard error [SE] = 0.11), -0.88 (SE = 0.12), and -0.97 (SE = 0.15) deficiencies in Postacute Cluster, Long-stay Cluster, and Cognitive-mental Cluster, respectively.

CONCLUSIONS

Unsupervised machine learning detected a changing landscape of NH serving residents with dementia and mental illnesses, which requires assuring staffing levels and trainings are suited to residents' needs.

The effect of political control on financial performance, structure, and outcomes of US nursing homes

Objective

To evaluate the effect of partisan political control on financial performance, structure, and outcomes of for‐profit and not‐for‐profit US nursing homes.

Data Sources/Study Setting

Nineteen‐year panel (1996‐2014) of state election outcomes, financial performance data from nursing home cost reports, operational and aggregate resident characteristics from OSCAR of 13 737 nursing homes.

Study Design

A linear panel model was estimated to identify the effect of Democratic and Republican political control on next year's outcomes. Nursing home outcomes were defined as yearly facility revenues, expenses, and profits; the number of Medicaid, Medicare, and private‐pay residents; staffing levels; and selected resident outcomes.

Principal Findings

Democratic political control leads to an increase in financial flows to for‐profit nursing homes, boosting profits without producing observable improvements in resident outcomes. Republican political control leads to lower revenues and profits of for‐profit nursing homes. A shift from Medicaid to more profitable private‐pay residents following Republican political control is observed for all nursing homes. Financial performance of not‐for‐profit nursing homes is not significantly affected by changes in political control.

Conclusion

Political control of the two legislative chambers—but not of the governorship—shapes the structure of the nursing home industry as seen in provider behavior.

Factors Related to Healthcare Service Quality in Long-term Care Hospitals in South Korea: A Mixed-methods Study

Objectives

The environment of long-term care hospitals (LTCHs) is critical to the management of the quality of their services and to patient safety, as highlighted by international studies. However, there is a lack of evidence on this topic in South Korea. This study aimed to examine the factors affecting healthcare quality in LTCHs and to explore the effectiveness of their quality management.

Methods

This study used a mixed methods approach with quantitative data collected in a national survey and qualitative data from semi-structured interviews with practice-based managers. The samples included 725 nationally representative LTCHs in South Korea for the quantitative analysis and 15 administrators for the in-depth interviews.

Results

A higher installation rate of patient-safety and hygiene-related facilities and staff with longer-tenures, especially nurses, were more likely to have better healthcare quality and education for both employees and patients.

Conclusion

The need for patient-safety- and hygiene-related facilities in LTCHs that serve older adults reflects their vulnerability to certain adverse events (e.g., infections). Consistent and skillful nursing care to improve the quality of LTCHs can be achieved by developing relevant educational programs for staff and patients, thereby strengthening the relationships between them.