ArticleJournal of clinical medicine2019
Clustering of 27,525,663 Death Records from the United States Based on Health Conditions Associated with Death: An Example of big Health Data Exploration.
Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Social determinants of multimorbidity patterns: A systematic review.Frontiers in public health · 2023Pooled it
- Role of clinical pharmacists in palliative care team: A scoping review.Palliative & supportive care · 2026Article
- Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography.Journal of clinical medicine · 2023Article
- Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure.Biomolecules · 2022Article
- Short-Term Mortality in Patients with Heart Failure at the End-of-Life Stages: Hades Study.Journal of clinical medicine · 2022Article
- Fatigue in patients with chronic disease: results from the population-based Lifelines Cohort Study.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInsight into health conditions associated with death can inform healthcare policy. We aimed to cluster 27,525,663 deceased people based on the health conditions associated with death to study the associations between the health condition clusters, demographics, the recorded underlying cause and place of death.
methodsData from all deaths in the United States registered between 2006 and 2016 from the National Vital Statistics System of the National Center for Health Statistics were analyzed. A self-organizing map (SOM) was used to create an ordered representation of the mortality data.
results16 clusters based on the health conditions associated with death were found showing significant differences in socio-demographics, place, and cause of death. Most people died at old age (73.1 (18.0) years) and had multiple health conditions. Chronic ischemic heart disease was the main cause of death. Most people died in the hospital or at home.
conclusionsThe prevalence of multiple health conditions at death requires a shift from disease-oriented towards person-centred palliative care at the end of life, including timely advance care planning. Understanding differences in population-based patterns and clusters of end-of-life experiences is an important step toward developing a strategy for implementing population-based palliative care.
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