Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29205
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dc.contributor.authorJanssen, Daisy J. A.-
dc.contributor.authorRechberger, Simon-
dc.contributor.authorWouters, Ernie F. M.-
dc.contributor.authorSchols, Jos M. G. A.-
dc.contributor.authorJohnson, Miriam J.-
dc.contributor.authorCurrow, David C.-
dc.contributor.authorCurtis, J. Randall-
dc.contributor.authorSPRUIT, Martijn A.-
dc.date.accessioned2019-09-16T14:09:20Z-
dc.date.available2019-09-16T14:09:20Z-
dc.date.issued2019-
dc.identifier.citationJOURNAL OF CLINICAL MEDICINE, 8(7) (Art N° 922)-
dc.identifier.issn2077-0383-
dc.identifier.urihttp://hdl.handle.net/1942/29205-
dc.description.abstractBackground: 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.-
dc.language.isoen-
dc.publisherMDPI-
dc.rightsOpen access. 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/).-
dc.subject.othermortality; death; death certificates; palliative care; delivery of health care; multi-morbidity; ageing-
dc.subject.othermortality; death; death certificates; palliative care; delivery of health care; multi-morbidity; ageing-
dc.titleClustering of 27,525,663 Death Records from the United States Based on Health Conditions Associated with Death: An Example of Big Health Data Exploration-
dc.typeJournal Contribution-
dc.identifier.issue7-
dc.identifier.volume8-
local.format.pages15-
local.bibliographicCitation.jcatA1-
dc.description.notes[Janssen, Daisy J. A.; Wouters, Ernie F. M.; Spruit, Martijn A.] CIRO, Ctr Expertise Chron Organ Failure, Dept Res & Educ, NL-6085 NM Horn, Netherlands. [Janssen, Daisy J. A.] MUMC, Ctr Expertise Palliat Care, NL-6229 HX Maastricht, Netherlands. [Janssen, Daisy J. A.; Schols, Jos M. G. A.] Maastricht Univ, Dept Hlth Serv Res, NL-6229 GT Maastricht, Netherlands. [Rechberger, Simon] Viscovery Software GmbH, A-1130 Vienna, Austria. [Wouters, Ernie F. M.; Spruit, Martijn A.] MUMC, Dept Resp Med, NL-6229 HX Maastricht, Netherlands. [Schols, Jos M. G. A.] Maastricht Univ, Dept Family Med, NL-6229 HA Maastricht, Netherlands. [Johnson, Miriam J.] Univ Hull, Hull & York Med Sch, Wolfson Palliat Care Res Ctr, Kingston Upon Hull HU6 7RX, N Humberside, England. [Currow, David C.] Univ Technol Sydney, Fac Hlth, IMPACCT, Ultimo, NSW 2007, Australia. [Curtis, J. Randall] Univ Washington, Cambia Palliat Care Ctr Excellence, Harborview Med Ctr, Seattle, WA 98104 USA. [Spruit, Martijn A.] NUTRIM Sch Nutr & Translat Res Metab, NL-6229 ER Maastricht, Netherlands. [Spruit, Martijn A.] Hasselt Univ, BIOMED Biomed Res Inst, Fac Rehabil Sci, REVAL Rehabil Res Ctr, BE-3590 Diepenbeek, Belgium.-
local.publisher.placeBASEL-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.artnr922-
dc.identifier.doi10.3390/jcm8070922-
dc.identifier.isi000479003300012-
item.fullcitationJanssen, Daisy J. A.; Rechberger, Simon; Wouters, Ernie F. M.; Schols, Jos M. G. A.; Johnson, Miriam J.; Currow, David C.; Curtis, J. Randall & SPRUIT, Martijn A. (2019) 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. In: JOURNAL OF CLINICAL MEDICINE, 8(7) (Art N° 922).-
item.validationecoom 2020-
item.contributorJanssen, Daisy J. A.-
item.contributorRechberger, Simon-
item.contributorWouters, Ernie F. M.-
item.contributorSchols, Jos M. G. A.-
item.contributorJohnson, Miriam J.-
item.contributorCurrow, David C.-
item.contributorCurtis, J. Randall-
item.contributorSPRUIT, Martijn A.-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
crisitem.journal.eissn2077-0383-
Appears in Collections:Research publications
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