ArticleHealth services research2022
Changing landscape of nursing homes serving residents with dementia and mental illnesses.
Article in Health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.JAMA network open · 2023Trial
- Medicaid Payments and Racial and Ethnic Disparities in Alzheimer Disease Special Care Units.JAMA network open · 2025Article
- Hospital and Skilled Nursing Facility Networks: Informal Relationships and Their Role in the Placement of Traditional Medicare Beneficiaries With Serious Mental Illness.Health services research · 2025Article
- Association of Racial and Ethnic Composition with Staff Levels in Nursing Homes: 2013-2019.Journal of the American Medical Directors Association · 2025Article
- Racial Differences in Nursing Home Quality of Life Among Residents Living With Alzheimer's Disease and Related Dementias.Journal of aging and health · 2024Article
- Longitudinal Associations of Staff Shortages and Staff Levels with Health Outcomes in Nursing Homes.Journal of the American Medical Directors Association · 2023Article
- Information sharing to support care transitions for patients with complex mental health and social needs.Journal of the American Geriatrics Society · 2023Article
- Excess deaths from COVID-19 among Medicare beneficiaries with psychiatric diagnoses: Community versus nursing home.Journal of the American Geriatrics Society · 2023Article
- Changing landscape of nursing homes serving residents with dementia and mental illnesses.Health services research · 2022Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
Abstract
objectiveNursing 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
designUnsupervised 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
methodsWe identified 110,463 NH-year observations from 14,671 unique NHs using CASPER data. PRINCIPAL
findingsThree 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.
conclusionsUnsupervised 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.
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