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Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study
OBJECTIVES: To determine whether stroke patients’ acute hospital length of stay (AHLOS) varies between hospitals, over and above case mix differences and to investigate the hospital-level explanatory factors. DESIGN: A multicentre prospective cohort study. SETTING: Eight National Health Service acut...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500188/ https://www.ncbi.nlm.nih.gov/pubmed/30948571 http://dx.doi.org/10.1136/bmjopen-2018-024506 |
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author | Tørnes, Michelle McLernon, David Bachmann, Max Musgrave, Stanley Warburton, Elizabeth A Potter, John F Myint, Phyo Kyaw |
author_facet | Tørnes, Michelle McLernon, David Bachmann, Max Musgrave, Stanley Warburton, Elizabeth A Potter, John F Myint, Phyo Kyaw |
author_sort | Tørnes, Michelle |
collection | PubMed |
description | OBJECTIVES: To determine whether stroke patients’ acute hospital length of stay (AHLOS) varies between hospitals, over and above case mix differences and to investigate the hospital-level explanatory factors. DESIGN: A multicentre prospective cohort study. SETTING: Eight National Health Service acute hospital trusts within the Anglia Stroke & Heart Clinical Network in the East of England, UK. PARTICIPANTS: The study sample was systematically selected to include all consecutive patients admitted within a month to any of the eight hospitals, diagnosed with stroke by an accredited stroke physician every third month between October 2009 and September 2011. PRIMARY AND SECONDARY OUTCOME MEASURES: AHLOS was defined as the number of days between date of hospital admission and discharge or death, whichever came first. We used a multiple linear regression model to investigate the association between hospital (as a fixed-effect) and AHLOS, adjusting for several important patient covariates, such as age, sex, stroke type, modified Rankin Scale score (mRS), comorbidities and inpatient complications. Exploratory data analysis was used to examine the hospital-level characteristics which may contribute to variance between hospitals. These included hospital type, stroke monthly case volume, service provisions (ie, onsite rehabilitation) and staffing levels. RESULTS: A total of 2233 stroke admissions (52% female, median age (IQR) 79 (70 to 86) years, 83% ischaemic stroke) were included. The overall median AHLOS (IQR) was 9 (4 to 21) days. After adjusting for patient covariates, AHLOS still differed significantly between hospitals (p<0.001). Furthermore, hospitals with the longest adjusted AHLOS’s had predominantly smaller stroke volumes. CONCLUSIONS: We have clearly demonstrated that AHLOS varies between different hospitals, and that the most important patient-level explanatory variables are discharge mRS, dementia and inpatient complications. We highlight the potential importance of stroke volume in influencing these differences but cannot discount the potential effect of unmeasured confounders. |
format | Online Article Text |
id | pubmed-6500188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-65001882019-05-21 Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study Tørnes, Michelle McLernon, David Bachmann, Max Musgrave, Stanley Warburton, Elizabeth A Potter, John F Myint, Phyo Kyaw BMJ Open Epidemiology OBJECTIVES: To determine whether stroke patients’ acute hospital length of stay (AHLOS) varies between hospitals, over and above case mix differences and to investigate the hospital-level explanatory factors. DESIGN: A multicentre prospective cohort study. SETTING: Eight National Health Service acute hospital trusts within the Anglia Stroke & Heart Clinical Network in the East of England, UK. PARTICIPANTS: The study sample was systematically selected to include all consecutive patients admitted within a month to any of the eight hospitals, diagnosed with stroke by an accredited stroke physician every third month between October 2009 and September 2011. PRIMARY AND SECONDARY OUTCOME MEASURES: AHLOS was defined as the number of days between date of hospital admission and discharge or death, whichever came first. We used a multiple linear regression model to investigate the association between hospital (as a fixed-effect) and AHLOS, adjusting for several important patient covariates, such as age, sex, stroke type, modified Rankin Scale score (mRS), comorbidities and inpatient complications. Exploratory data analysis was used to examine the hospital-level characteristics which may contribute to variance between hospitals. These included hospital type, stroke monthly case volume, service provisions (ie, onsite rehabilitation) and staffing levels. RESULTS: A total of 2233 stroke admissions (52% female, median age (IQR) 79 (70 to 86) years, 83% ischaemic stroke) were included. The overall median AHLOS (IQR) was 9 (4 to 21) days. After adjusting for patient covariates, AHLOS still differed significantly between hospitals (p<0.001). Furthermore, hospitals with the longest adjusted AHLOS’s had predominantly smaller stroke volumes. CONCLUSIONS: We have clearly demonstrated that AHLOS varies between different hospitals, and that the most important patient-level explanatory variables are discharge mRS, dementia and inpatient complications. We highlight the potential importance of stroke volume in influencing these differences but cannot discount the potential effect of unmeasured confounders. BMJ Publishing Group 2019-04-03 /pmc/articles/PMC6500188/ /pubmed/30948571 http://dx.doi.org/10.1136/bmjopen-2018-024506 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Epidemiology Tørnes, Michelle McLernon, David Bachmann, Max Musgrave, Stanley Warburton, Elizabeth A Potter, John F Myint, Phyo Kyaw Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title | Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title_full | Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title_fullStr | Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title_full_unstemmed | Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title_short | Does service heterogeneity have an impact on acute hospital length of stay in stroke? A UK-based multicentre prospective cohort study |
title_sort | does service heterogeneity have an impact on acute hospital length of stay in stroke? a uk-based multicentre prospective cohort study |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500188/ https://www.ncbi.nlm.nih.gov/pubmed/30948571 http://dx.doi.org/10.1136/bmjopen-2018-024506 |
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