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The health services burden of heart failure: an analysis using linked population health data-sets

BACKGROUND: The burden of patients with heart failure on health care systems is widely recognised, although there have been few attempts to quantify individual patterns of care and differences in health service utilisation related to age, socio-economic factors and the presence of co-morbidities. Th...

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Autores principales: Robertson, Jane, McElduff, Patrick, Pearson, Sallie-Anne, Henry, David A, Inder, Kerry J, Attia, John R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3413515/
https://www.ncbi.nlm.nih.gov/pubmed/22533631
http://dx.doi.org/10.1186/1472-6963-12-103
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author Robertson, Jane
McElduff, Patrick
Pearson, Sallie-Anne
Henry, David A
Inder, Kerry J
Attia, John R
author_facet Robertson, Jane
McElduff, Patrick
Pearson, Sallie-Anne
Henry, David A
Inder, Kerry J
Attia, John R
author_sort Robertson, Jane
collection PubMed
description BACKGROUND: The burden of patients with heart failure on health care systems is widely recognised, although there have been few attempts to quantify individual patterns of care and differences in health service utilisation related to age, socio-economic factors and the presence of co-morbidities. The aim of this study was to assess the typical profile, trajectory and resource use of a cohort of Australian patients with heart failure using linked population-based, patient-level data. METHODS: Using hospital separations (Admitted Patient Data Collection) with death registrations (Registry of Births, Deaths and Marriages) for the period 2000–2007 we estimated age- and gender-specific rates of index admissions and readmissions, risk factors for hospital readmission, mean length of stay (LOS), median survival and bed-days occupied by patients with heart failure in New South Wales, Australia. RESULTS: We identified 29,161 index admissions for heart failure. Admission rates increased with age, and were higher for males than females for all age groups. Age-standardised rates decreased over time (256.7 to 237.7/100,000 for males and 235.3 to 217.1/100,000 for females from 2002–3 to 2006–7; p = 0.0073 adjusted for gender). Readmission rates (any cause) were 27% and 73% at 28-days and one year respectively; readmission rates for heart failure were 11% and 32% respectively. All cause mortality was 10% and 28% at 28 days and one year. Increasing age was associated with more heart failure readmissions, longer LOS and shorter median survival. Increasing age, increasing Charlson comorbidity score and male gender were risk factors for hospital readmission. Cohort members occupied 954,888 hospital bed-days during the study period (any cause); 383,646 bed-days were attributed to heart failure admissions. CONCLUSIONS: The rates of index admissions for heart failure decreased significantly in both males and females over the study period. However, the impact on acute care hospital beds was substantial, with heart failure patients occupying almost 200,000 bed-days per year in NSW over the five year study period. The strong age-related trends highlight the importance of stabilising elderly patients before discharge and community-based outreach programs to better manage heart failure and reduce readmissions.
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spelling pubmed-34135152012-08-08 The health services burden of heart failure: an analysis using linked population health data-sets Robertson, Jane McElduff, Patrick Pearson, Sallie-Anne Henry, David A Inder, Kerry J Attia, John R BMC Health Serv Res Research Article BACKGROUND: The burden of patients with heart failure on health care systems is widely recognised, although there have been few attempts to quantify individual patterns of care and differences in health service utilisation related to age, socio-economic factors and the presence of co-morbidities. The aim of this study was to assess the typical profile, trajectory and resource use of a cohort of Australian patients with heart failure using linked population-based, patient-level data. METHODS: Using hospital separations (Admitted Patient Data Collection) with death registrations (Registry of Births, Deaths and Marriages) for the period 2000–2007 we estimated age- and gender-specific rates of index admissions and readmissions, risk factors for hospital readmission, mean length of stay (LOS), median survival and bed-days occupied by patients with heart failure in New South Wales, Australia. RESULTS: We identified 29,161 index admissions for heart failure. Admission rates increased with age, and were higher for males than females for all age groups. Age-standardised rates decreased over time (256.7 to 237.7/100,000 for males and 235.3 to 217.1/100,000 for females from 2002–3 to 2006–7; p = 0.0073 adjusted for gender). Readmission rates (any cause) were 27% and 73% at 28-days and one year respectively; readmission rates for heart failure were 11% and 32% respectively. All cause mortality was 10% and 28% at 28 days and one year. Increasing age was associated with more heart failure readmissions, longer LOS and shorter median survival. Increasing age, increasing Charlson comorbidity score and male gender were risk factors for hospital readmission. Cohort members occupied 954,888 hospital bed-days during the study period (any cause); 383,646 bed-days were attributed to heart failure admissions. CONCLUSIONS: The rates of index admissions for heart failure decreased significantly in both males and females over the study period. However, the impact on acute care hospital beds was substantial, with heart failure patients occupying almost 200,000 bed-days per year in NSW over the five year study period. The strong age-related trends highlight the importance of stabilising elderly patients before discharge and community-based outreach programs to better manage heart failure and reduce readmissions. BioMed Central 2012-04-25 /pmc/articles/PMC3413515/ /pubmed/22533631 http://dx.doi.org/10.1186/1472-6963-12-103 Text en Copyright ©2012 Robertson 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
Robertson, Jane
McElduff, Patrick
Pearson, Sallie-Anne
Henry, David A
Inder, Kerry J
Attia, John R
The health services burden of heart failure: an analysis using linked population health data-sets
title The health services burden of heart failure: an analysis using linked population health data-sets
title_full The health services burden of heart failure: an analysis using linked population health data-sets
title_fullStr The health services burden of heart failure: an analysis using linked population health data-sets
title_full_unstemmed The health services burden of heart failure: an analysis using linked population health data-sets
title_short The health services burden of heart failure: an analysis using linked population health data-sets
title_sort health services burden of heart failure: an analysis using linked population health data-sets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3413515/
https://www.ncbi.nlm.nih.gov/pubmed/22533631
http://dx.doi.org/10.1186/1472-6963-12-103
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