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Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals

BACKGROUND: Post-acute care hospitals are often subject to patient flow pressures because of their intermediary position along the continuum of care between acute care hospitals and community care or residential long-term care settings. The purpose of this study was to identify patient attributes as...

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Autores principales: Turcotte, Luke A., Perlman, Chris M., Fries, Brant E., Hirdes, John P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451230/
https://www.ncbi.nlm.nih.gov/pubmed/30953489
http://dx.doi.org/10.1186/s12913-019-4024-2
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author Turcotte, Luke A.
Perlman, Chris M.
Fries, Brant E.
Hirdes, John P.
author_facet Turcotte, Luke A.
Perlman, Chris M.
Fries, Brant E.
Hirdes, John P.
author_sort Turcotte, Luke A.
collection PubMed
description BACKGROUND: Post-acute care hospitals are often subject to patient flow pressures because of their intermediary position along the continuum of care between acute care hospitals and community care or residential long-term care settings. The purpose of this study was to identify patient attributes associated with a prolonged length of stay in Complex Continuing Care hospitals. METHODS: Using information collected using the interRAI Resident Assessment Instrument Minimum Data Set 2.0 (MDS 2.0), a sample of 91,113 episodes of care for patients admitted to Complex Continuing Care hospitals between March 31, 2001 and March 31, 2013 was established. All patients in the sample were either discharged to a residential long-term care facility (e.g., nursing home) or to the community. Long-stay patients for each discharge destination were identified based on a length of stay in the 95th percentile. A series of multivariate logistic regression models predicting long-stay patient status for each discharge destination pathway were fit to characterize the association between demographic factors, residential history, health severity measures, and service utilization on prolonged length of stay in post-acute care. RESULTS: Risk factors for prolonged length of stay in the adjusted models included functional and cognitive impairment, greater pressure ulcer risk, paralysis, antibiotic resistant and HIV infection need for a feeding tube, dialysis, tracheostomy, ventilator or a respirator, and psychological therapy. Protective factors included advanced age, medical instability, a greater number of recent hospital and emergency department visits, cancer diagnosis, pneumonia, unsteady gait, a desire to return to the community, and a support person who is positive towards discharge. Aggressive behaviour was only a risk factor for patients discharged to residential long-term care facilities. Cancer diagnosis, antibiotic resistant and HIV infection, and pneumonia were only significant factors for patients discharged to the community. CONCLUSIONS: This study identified several patient attributes and process of care variables that are predictors of prolonged length of stay in post-acute care hospitals. This is valuable information for care planners and health system administrators working to improve patient flow in Complex Continuing Care and other post-acute care settings such as skilled nursing and inpatient rehabilitation facilities.
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spelling pubmed-64512302019-04-16 Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals Turcotte, Luke A. Perlman, Chris M. Fries, Brant E. Hirdes, John P. BMC Health Serv Res Research Article BACKGROUND: Post-acute care hospitals are often subject to patient flow pressures because of their intermediary position along the continuum of care between acute care hospitals and community care or residential long-term care settings. The purpose of this study was to identify patient attributes associated with a prolonged length of stay in Complex Continuing Care hospitals. METHODS: Using information collected using the interRAI Resident Assessment Instrument Minimum Data Set 2.0 (MDS 2.0), a sample of 91,113 episodes of care for patients admitted to Complex Continuing Care hospitals between March 31, 2001 and March 31, 2013 was established. All patients in the sample were either discharged to a residential long-term care facility (e.g., nursing home) or to the community. Long-stay patients for each discharge destination were identified based on a length of stay in the 95th percentile. A series of multivariate logistic regression models predicting long-stay patient status for each discharge destination pathway were fit to characterize the association between demographic factors, residential history, health severity measures, and service utilization on prolonged length of stay in post-acute care. RESULTS: Risk factors for prolonged length of stay in the adjusted models included functional and cognitive impairment, greater pressure ulcer risk, paralysis, antibiotic resistant and HIV infection need for a feeding tube, dialysis, tracheostomy, ventilator or a respirator, and psychological therapy. Protective factors included advanced age, medical instability, a greater number of recent hospital and emergency department visits, cancer diagnosis, pneumonia, unsteady gait, a desire to return to the community, and a support person who is positive towards discharge. Aggressive behaviour was only a risk factor for patients discharged to residential long-term care facilities. Cancer diagnosis, antibiotic resistant and HIV infection, and pneumonia were only significant factors for patients discharged to the community. CONCLUSIONS: This study identified several patient attributes and process of care variables that are predictors of prolonged length of stay in post-acute care hospitals. This is valuable information for care planners and health system administrators working to improve patient flow in Complex Continuing Care and other post-acute care settings such as skilled nursing and inpatient rehabilitation facilities. BioMed Central 2019-04-05 /pmc/articles/PMC6451230/ /pubmed/30953489 http://dx.doi.org/10.1186/s12913-019-4024-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Turcotte, Luke A.
Perlman, Chris M.
Fries, Brant E.
Hirdes, John P.
Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title_full Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title_fullStr Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title_full_unstemmed Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title_short Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals
title_sort clinical predictors of protracted length of stay in ontario complex continuing care hospitals
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451230/
https://www.ncbi.nlm.nih.gov/pubmed/30953489
http://dx.doi.org/10.1186/s12913-019-4024-2
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