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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

Background: Insight 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 ca...

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Autores principales: Janssen, Daisy J.A., Rechberger, Simon, Wouters, Emiel F.M., Schols, Jos M.G.A., Johnson, Miriam J., Currow, David C., Curtis, J. Randall, Spruit, Martijn A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678953/
https://www.ncbi.nlm.nih.gov/pubmed/31252579
http://dx.doi.org/10.3390/jcm8070922
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author Janssen, Daisy J.A.
Rechberger, Simon
Wouters, Emiel F.M.
Schols, Jos M.G.A.
Johnson, Miriam J.
Currow, David C.
Curtis, J. Randall
Spruit, Martijn A.
author_facet Janssen, Daisy J.A.
Rechberger, Simon
Wouters, Emiel F.M.
Schols, Jos M.G.A.
Johnson, Miriam J.
Currow, David C.
Curtis, J. Randall
Spruit, Martijn A.
author_sort Janssen, Daisy J.A.
collection PubMed
description Background: Insight 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. Methods: Data 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. Results: 16 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. Conclusions: The 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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spelling pubmed-66789532019-08-19 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 Janssen, Daisy J.A. Rechberger, Simon Wouters, Emiel F.M. Schols, Jos M.G.A. Johnson, Miriam J. Currow, David C. Curtis, J. Randall Spruit, Martijn A. J Clin Med Article Background: Insight 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. Methods: Data 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. Results: 16 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. Conclusions: The 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. MDPI 2019-06-27 /pmc/articles/PMC6678953/ /pubmed/31252579 http://dx.doi.org/10.3390/jcm8070922 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Janssen, Daisy J.A.
Rechberger, Simon
Wouters, Emiel F.M.
Schols, Jos M.G.A.
Johnson, Miriam J.
Currow, David C.
Curtis, J. Randall
Spruit, Martijn A.
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678953/
https://www.ncbi.nlm.nih.gov/pubmed/31252579
http://dx.doi.org/10.3390/jcm8070922
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