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Predicting mortality of residents at admission to nursing home: A longitudinal cohort study
BACKGROUND: An increasing numbers of deaths occur in nursing homes. Knowledge of the course of development over the years in death rates and predictors of mortality is important for officials responsible for organizing care to be able to ensure that staff is knowledgeable in the areas of care needed...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3112069/ https://www.ncbi.nlm.nih.gov/pubmed/21507213 http://dx.doi.org/10.1186/1472-6963-11-86 |
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author | Hjaltadóttir, Ingibjörg Hallberg, Ingalill Rahm Ekwall, Anna Kristensson Nyberg, Per |
author_facet | Hjaltadóttir, Ingibjörg Hallberg, Ingalill Rahm Ekwall, Anna Kristensson Nyberg, Per |
author_sort | Hjaltadóttir, Ingibjörg |
collection | PubMed |
description | BACKGROUND: An increasing numbers of deaths occur in nursing homes. Knowledge of the course of development over the years in death rates and predictors of mortality is important for officials responsible for organizing care to be able to ensure that staff is knowledgeable in the areas of care needed. The aim of this study was to investigate the time from residents' admission to Icelandic nursing homes to death and the predictive power of demographic variables, health status (health stability, pain, depression and cognitive performance) and functional profile (ADL and social engagement) for 3-year mortality in yearly cohorts from 1996-2006. METHODS: The samples consisted of residents (N = 2206) admitted to nursing homes in Iceland in 1996-2006, who were assessed once at baseline with a Minimum Data Set (MDS) within 90 days of their admittance to the nursing home. The follow-up time for survival of each cohort was 36 months from admission. Based on Kaplan-Meier analysis (log rank test) and non-parametric correlation analyses (Spearman's rho), variables associated with survival time with a p-value < 0.05 were entered into a multivariate Cox regression model. RESULTS: The median survival time was 31 months, and no significant difference was detected in the mortality rate between cohorts. Age, gender (HR 1.52), place admitted from (HR 1.27), ADL functioning (HR 1.33-1.80), health stability (HR 1.61-16.12) and ability to engage in social activities (HR 1.51-1.65) were significant predictors of mortality. A total of 28.8% of residents died within a year, 43.4% within two years and 53.1% of the residents died within 3 years. CONCLUSION: It is noteworthy that despite financial constraints, the mortality rate did not change over the study period. Health stability was a strong predictor of mortality, in addition to ADL performance. Considering these variables is thus valuable when deciding on the type of service an elderly person needs. The mortality rate showed that more than 50% died within 3 years, and almost a third of the residents may have needed palliative care within a year of admission. Considering the short survival time from admission, it seems relevant that staff is trained in providing palliative care as much as restorative care. |
format | Online Article Text |
id | pubmed-3112069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31120692011-06-11 Predicting mortality of residents at admission to nursing home: A longitudinal cohort study Hjaltadóttir, Ingibjörg Hallberg, Ingalill Rahm Ekwall, Anna Kristensson Nyberg, Per BMC Health Serv Res Research Article BACKGROUND: An increasing numbers of deaths occur in nursing homes. Knowledge of the course of development over the years in death rates and predictors of mortality is important for officials responsible for organizing care to be able to ensure that staff is knowledgeable in the areas of care needed. The aim of this study was to investigate the time from residents' admission to Icelandic nursing homes to death and the predictive power of demographic variables, health status (health stability, pain, depression and cognitive performance) and functional profile (ADL and social engagement) for 3-year mortality in yearly cohorts from 1996-2006. METHODS: The samples consisted of residents (N = 2206) admitted to nursing homes in Iceland in 1996-2006, who were assessed once at baseline with a Minimum Data Set (MDS) within 90 days of their admittance to the nursing home. The follow-up time for survival of each cohort was 36 months from admission. Based on Kaplan-Meier analysis (log rank test) and non-parametric correlation analyses (Spearman's rho), variables associated with survival time with a p-value < 0.05 were entered into a multivariate Cox regression model. RESULTS: The median survival time was 31 months, and no significant difference was detected in the mortality rate between cohorts. Age, gender (HR 1.52), place admitted from (HR 1.27), ADL functioning (HR 1.33-1.80), health stability (HR 1.61-16.12) and ability to engage in social activities (HR 1.51-1.65) were significant predictors of mortality. A total of 28.8% of residents died within a year, 43.4% within two years and 53.1% of the residents died within 3 years. CONCLUSION: It is noteworthy that despite financial constraints, the mortality rate did not change over the study period. Health stability was a strong predictor of mortality, in addition to ADL performance. Considering these variables is thus valuable when deciding on the type of service an elderly person needs. The mortality rate showed that more than 50% died within 3 years, and almost a third of the residents may have needed palliative care within a year of admission. Considering the short survival time from admission, it seems relevant that staff is trained in providing palliative care as much as restorative care. BioMed Central 2011-04-20 /pmc/articles/PMC3112069/ /pubmed/21507213 http://dx.doi.org/10.1186/1472-6963-11-86 Text en Copyright ©2011 Hjaltadóttir et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hjaltadóttir, Ingibjörg Hallberg, Ingalill Rahm Ekwall, Anna Kristensson Nyberg, Per Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title | Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title_full | Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title_fullStr | Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title_full_unstemmed | Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title_short | Predicting mortality of residents at admission to nursing home: A longitudinal cohort study |
title_sort | predicting mortality of residents at admission to nursing home: a longitudinal cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3112069/ https://www.ncbi.nlm.nih.gov/pubmed/21507213 http://dx.doi.org/10.1186/1472-6963-11-86 |
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