Medicaid Nursing Home Policies and Risk-Adjusted Rates of Emergency Department Visits: Does Rural Location Matter?

Changes in Nursing Staff Levels and Injury-Related Emergency Department Visits among Assisted Living Residents with Alzheimers Disease and Related Dementias

OBJECTIVES

To examine the relationship between changes in nursing staff-hours per resident-day and injury-related emergency department (ED) visits among assisted living (AL) residents with Alzheimer disease and related dementias (ADRD).

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

We leveraged a data set of AL community characteristics in Ohio linked to Medicare claims data from 2007 to 2015.

METHODS

We estimated Poisson models examining the relationships of personal care aide, registered nurse (RN), licensed practical nurse (LPN), and total nursing hours with injury-related ED visits. Models were adjusted for resident characteristics (ie, age, race, sex, dual eligibility, presence and number of chronic conditions), AL community characteristics (percentage of residents on Medicaid, average resident acuity), year fixed effects, and assisted living fixed effects. We examined all injury-related ED visits and injury-related ED visits resulting in hospital admission as separate outcomes.

RESULTS

The sample included 122,700 person-months, representing 12,144 fee-for-service Medicare beneficiaries with ADRD within 455 different AL communities in Ohio between 2007 and 2015. Median total nursing hours increased from 1.34 in 2007 to 1.69 in 2015. In the fully adjusted model, an increase in 1 RN-hour per resident-day was associated with a decrease in the risk of any injury-related ED visit (incidence rate ratio 0.59, 95% CI 0.36-0.96), representing a 53% decrease. Changes in RN-hours were not associated with injury-related inpatient hospitalizations. Changes in total nursing, LPN, and personal care aide hours were not associated with changes in the risk of injury-related ED visits or inpatient hospitalizations.

CONCLUSIONS AND IMPLICATIONS

Increases in RN staffing hours were associated with reduced injury-related ED use among AL residents with ADRD. RNs provide surveillance and care oversight that may help mitigate injury risk, and they are able to physically assess residents at the time of a fall and/or injury, which can preempt unnecessary ED transfers.

Longitudinal Associations of Staff Shortages and Staff Levels with Health Outcomes in Nursing Homes

OBJECTIVES

To examine whether facility-reported staff shortages and total staff levels were independently associated with changes in nursing home (NH) outcomes in 2020.

DESIGN

Longitudinal cohort study.

SETTING AND PARTICIPANTS

A total of 8466 NHs with staffing and outcome data.

METHODS

This study used NH COVID-19 Public File (2020), Nursing Home Compare (2019-2020), and Payroll-Based Journal data (2019-2020). Outcome measures included the percentage of long-stay residents in a facility with declines in activities in daily living (ADLs), decreases in mobility, weight loss, and pressure ulcers in 2020 Q2, 2020 Q3, and 2020 Q4. Independent variables were whether NHs reported any shortage of aides or licensed nurses and total staff hours per resident day (HPRD). Separate 2-level (NH, state) Hierarchical Generalized Linear Mixed models examined the association of facility-reported shortages and staff hours with key NH resident outcomes, controlling for NH characteristics and COVID-19 infections.

RESULTS

The weekly percentage of NHs reporting any staff shortage averaged 20%. Total staff HPRD increased slightly from 3.7 in 2019 to 3.8 in 2020. Health outcomes were stable during 2019 and 2020 Q1 but worsened substantially starting in 2020 Q2. For example, the percentage of residents with mobility loss increased from 16.2% in 2020 Q1 to 27.9% in 2020 Q4. Facility-reported staff shortages were associated with an increase in the proportion of residents with an ADL decline (0.54 percentage points), mobility loss (0.80 percentage points), weight loss (0.22 percentage points), and pressure ulcers (0.22 percentage points) (all P < .01). Total staff HPRD was not associated with changes in any outcomes (all P > .05).

CONCLUSIONS AND IMPLICATIONS

NHs reported worsened health outcomes among long-stay residents in 2020, with worse outcomes found among facilities that reported staff shortages but not among those with lower total staff levels. Facility-reported shortages provide important quality information during the COVID-19 pandemic.

Environmental and structural factors driving poor quality of care: An examination of nursing homes serving Black residents

BACKGROUND

Poor quality of care in nursing homes (NHs) with high proportions of Black residents has been a problem in the US and even more pronounced during the COVID-19 pandemic. Federal and state agencies are devoting attention to identifying the best means of improving care in the neediest facilities. It is important to understand environmental and structural characteristics that may have led to poor healthcare outcomes in NHs serving high proportions of Black residents pre-pandemic.

METHODS

We conducted a cross-sectional observational study using multiple 2019 national datasets. Our exposure was the proportion of Black residents in a NH (i.e., none, <5%, 5%-19.9%, 20-49.9%, ≥50%). Healthcare outcomes examined were hospitalizations and emergency department (ED) visits, both observed and risk-adjusted. Structural factors included staffing, ownership status, bed count (0-49, 50-149, or ≥150), chain organization membership, occupancy, and percent Medicaid as a payment source. Environmental factors included region and urbanicity. Descriptive and multivariable linear regression models were estimated.

RESULTS

In the 14,121 NHs, compared to NHs with no Black residents, NHs with ≥50% Black residents tended to be urban, for-profit, located in the South, have more Medicaid-funded residents, and have lower ratios of registered-nurse (RN) and aide hours per resident per day (HPRD) and greater ratios of licensed practical nurse HPRD. In general, as the proportion of Black residents in a NH increased, hospitalizations and ED visits also increased.

DISCUSSION/IMPLICATIONS

As lower use of RNs has been associated with increased ED visits and hospitalizations in NHs generally, it is likely low RN use largely drove the differences in hospitalizations and ED visits in NHs with greater proportions of Black residents. Staffing is an area in which state and federal agencies should take action to improve the quality of care in NHs with larger proportions of Black residents.

Developing a Machine Learning Risk-adjustment Method for Hospitalizations and Emergency Department Visits of Nursing Home Residents With Dementia

BACKGROUND

Long-stay nursing home (NH) residents with Alzheimer disease and related dementias (ADRD) are at high risk of hospital transfers. Machine learning might improve risk-adjustment methods for NHs.

OBJECTIVES

The objective of this study was to develop and compare NH risk-adjusted rates of hospitalizations and emergency department (ED) visits among long-stay residents with ADRD using Extreme Gradient Boosting (XGBoost) and logistic regression.

RESEARCH DESIGN

Secondary analysis of national Medicare claims and NH assessment data in 2012 Q3. Data were equally split into the training and test sets. Both XGBoost and logistic regression predicted any hospitalization and ED visit using 58 predictors. NH-level risk-adjusted rates from XGBoost and logistic regression were constructed and compared. Multivariate regressions examined NH and market factors associated with rates of hospitalization and ED visits.

SUBJECTS

Long-stay Medicare residents with ADRD (N=413,557) from 14,057 NHs.

RESULTS

A total of 8.1% and 8.9% residents experienced any hospitalization and ED visit in a quarter, respectively. XGBoost slightly outperformed logistic regression in area under the curve (0.88 vs. 0.86 for hospitalization; 0.85 vs. 0.83 for ED visit). NH-level risk-adjusted rates from XGBoost were slightly lower than logistic regression (hospitalization=8.3% and 8.4%; ED=8.9% and 9.0%, respectively), but were highly correlated. Facility and market factors associated with the XGBoost and logistic regression-adjusted hospitalization and ED rates were similar. NHs serving more residents with ADRD and having a higher registered nurse-to-total nursing staff ratio had lower rates.

CONCLUSIONS

XGBoost and logistic regression provide comparable estimates of risk-adjusted hospitalization and ED rates.

Financial Performance is Associated With PPE Shortages in Chain-Affiliated Nursing Homes During the COVID-19 Pandemic: A Longitudinal Study

Many nursing homes operated at thin profit margins prior to the COVID-19 pandemic. This study examines the role of nursing homes' financial performance and chain affiliation in shortages of personal protection equipment (PPE) during the first year of the COVID-19 pandemic. We constructed a longitudinal file of 79 868 nursing home-week observations from 10 872 unique facilities. We found that a positive profit margin was associated with a 21.0% lower probability of reporting PPE shortages in chain-affiliated nursing homes, but not in non-chain nursing homes. Having adequate financial resources may help nursing homes address future emergencies, especially those affiliated with a multi-facility chain.

A Scoping Literature Review of Rural Institutional Elder Care

Under circumstances of pervasive global aging combined with weakened traditional family elder care, an incremental demand for institutional elder care is generated. This has led to a surge in research regarding institutional elder care. Rural residents' institutional elder care is receiving more attention as a major theme in social sciences and humanities research. Based on 94 articles related to rural institutional elder care, this study identified the most influential articles, journals and countries in rural institutional elder care research since 1995. This was done using science mapping methods through a three-step workflow consisting of bibliometric retrieval, scoping analysis and qualitative discussion. Keywords revealed five research mainstreams in this field: (1) the cognition and mental state of aged populations, (2) the nursing quality and service supply of aged care institutions, (3) the aged care management systems' establishment and improvements, (4) the risk factors of admission and discharge of aged care institutions, and (5) deathbed matters regarding the aged population. A qualitative discussion is also provided for 39 urban and rural comparative research papers and 55 pure rural research papers, summarizing the current research progress status regarding institutional elder care systems in rural areas. Gaps within existing research are also identified to indicate future research trends (such as the multi-dimensional and in-depth comparative research on institutional elder care, new rural institutional elder care model and technology, and correlative policy planning and development), which provides a multi-disciplinary guide for future research.

Decomposing Differences in Risk-Adjusted Rates of Emergency Department Visits Between Micropolitan and Urban Nursing Homes

OBJECTIVES

Nursing homes (NHs) in micropolitan areas are reported to have different facility and market factors than urban NHs, but how these factors contribute to differences in emergency department (ED) visits remains unknown. This study examined and quantified sources of micropolitan-urban differences in NH risk-adjusted rates of any ED visit, ED without hospitalization or observation stay (outpatient ED), and potentially avoidable ED (PAED) visits of long-stay residents.

DESIGN

The 2011-2013 national Medicare claims and NH Minimum Data Set (MDS) 3.0 were analyzed. We implemented generalized estimating equation models to examine micropolitan-urban differences in ED rates and Blinder-Oaxaca decompositions to quantify the contributions of NH and market factors.

SETTING AND PARTICIPANTS

The study cohort included 12,883 unique privately owned, freestanding NHs from urban and micropolitan areas.

MEASURES

Quarterly risk-adjusted rates of any ED visits, outpatient ED visits, and PAED visits were calculated from Medicare claims and MDS. NH and market characteristics were extracted from the Certification And Survey Provider Enhanced Reporting and Area Health Resources File.

RESULTS

Over the study period, risk-adjusted rates averaged 10.2%, 3.4%, and 3.3% for any ED, outpatient ED, and PAED visits, respectively. Compared with urban NHs, micropolitan NHs reported similar rates of any ED, but significantly higher rates of outpatient ED and PAED (β = 0.20% and 0.27%; both P < .05). Observable differences in NH characteristics (eg, number of beds, percentage Medicare or Medicaid residents, and employment of nurse practitioners and physician assistants) explained more than 20% of the micropolitan-urban differences in rates of outpatient ED and PAED visits; market factors (mainly Medicare Advantage penetration) explained about 46% of the differences in rates of outpatient ED visits.

CONCLUSIONS AND IMPLICATIONS

Compared with urban NHs, micropolitan NHs tend to utilize more avoidable emergency care that can be partially explained by facility size, payer mix, use of nurse practitioners and physician assistants, and market structure.

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.

Nursing Home and Market Factors and Risk-Adjusted Hospitalization Rates Among Urban, Micropolitan, and Rural Nursing Homes

OBJECTIVES

Hospitalizations are common among long-stay nursing home (NH) residents, but the role of rurality in hospitalization is understudied. This study examines the relationships between rurality, NH, and market characteristics and NH quarterly risk-adjusted hospitalization rates of long-stay residents over 10 quarters (2011 Q2-2013 Q3).

DESIGN

The longitudinal associations of NH and market factors and hospitalization rates were modeled separately on urban, micropolitan, and rural NHs using generalized estimating equation models and a fully interacted model of all NH and market characteristics with micropolitan and rural indicators to test significance of differences compared with urban NHs.

SETTING AND PARTICIPANTS

In total, 14,600 unique NHs.

MEASURES

Risk-adjusted hospitalization rates were calculated from 2011 to 2013 national Medicare claims and NH Minimum Data Set 3.0. Rurality was defined based on the 2010 Rural Urban Commuting Area codes. NH and market characteristics were extracted from Certification and Survey Provider Enhanced Reporting and Area Health Resources File.

RESULTS

Over the study period, risk-adjusted hospitalization rates averaged 9.8% (standard deviation = 8.2%). No difference was found in the overall hospitalization rates of long-stay NH residents among urban, micropolitan, and rural NHs. Generalized estimating equation models show that urban NHs with higher percentages of Medicare and Medicaid residents and any nurse practitioner/physician assistant were associated with lower rates, but these associations were insignificant in rural settings. Higher registered nurse to total nurses ratio was only associated with lower hospitalization rates in urban settings. Higher median household income was associated with lower hospitalization rates in micropolitan and rural NHs.

CONCLUSIONS/IMPLICATIONS

Rurality is not associated with hospitalization rates of long-stay residents, but NH and market factors (eg, payer distribution, staffing, and population income) may affect hospitalization differently in micropolitan/rural NHs than urban NHs. Future intervention on hospitalization should target factors unique to micropolitan/rural NHs which adopt strategies appropriate to their setting.