Cargando…

Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model

PURPOSE: Population ageing is challenging healthcare systems with limited resources, necessitating the development of new care models to address the needs of older, frail community-dwellers. Community Virtual Wards (CVW) reduce adverse events in these patients. We examined the effect of an establish...

Descripción completa

Detalles Bibliográficos
Autores principales: Lewis, Clare, O’Caoimh, Rónán, Patton, Declan, O’Connor, Tom, Moore, Zena, Nugent, Linda E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320026/
https://www.ncbi.nlm.nih.gov/pubmed/32606633
http://dx.doi.org/10.2147/CIA.S236895
_version_ 1783551163748057088
author Lewis, Clare
O’Caoimh, Rónán
Patton, Declan
O’Connor, Tom
Moore, Zena
Nugent, Linda E
author_facet Lewis, Clare
O’Caoimh, Rónán
Patton, Declan
O’Connor, Tom
Moore, Zena
Nugent, Linda E
author_sort Lewis, Clare
collection PubMed
description PURPOSE: Population ageing is challenging healthcare systems with limited resources, necessitating the development of new care models to address the needs of older, frail community-dwellers. Community Virtual Wards (CVW) reduce adverse events in these patients. We examined the effect of an established CVW on pre-defined health trajectories (between “stable”, “deteriorating”, and “unstable” states) and characteristics that increased the likelihood of adverse healthcare outcomes (hospitalization, institutionalization and death). PATIENTS AND METHODS: We collected prospective data on frail patients admitted to a CVW in a single centre in Ireland. Relationships between risk scores, health states and adverse outcomes at 30, 60 and 90 days after admission were examined using multinomial regression analysis. RESULTS: In total, 88 community-dwellers, mean (±SD) age of 82.8 ±6.4 years, were included. Most were severely frail on the Rockwood Clinical Frailty Scale (mean 6.8/9 ±1.33). Reaching stability (“stable” state) within 30 days was a predictor for stability at 60 and 90 days and remaining at home. Stability was also associated with fewer care episodes (<2) (p=<0.001), a requirement for fewer healthcare professionals (HCP) (<7) (p<0.001) and lower risk of delirium (p<0.001). By contrast, being “unstable” at 60 days increased the numbers of HCP referrals (>7) and was predictive of more acute episodes (>2) and institutionalization or death (p<0.001). Predictors of adverse outcomes of either institutionalization or death included frailty status, function, mobility, nutrition, pressure ulcer risk and cognition. CONCLUSION: A CVW model can provide a framework for monitoring and case management to support older people to remain at home or identify those at risk of institutional care. The use of defined health states helped to stratify those at lower or higher risk in an already high-risk frail population. Level of frailty, function, mobility, nutrition, pressure ulcer risks and cognition were predictive of remaining at home and reaching a level of stability or instability/deterioration and institutional care.
format Online
Article
Text
id pubmed-7320026
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-73200262020-06-29 Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model Lewis, Clare O’Caoimh, Rónán Patton, Declan O’Connor, Tom Moore, Zena Nugent, Linda E Clin Interv Aging Original Research PURPOSE: Population ageing is challenging healthcare systems with limited resources, necessitating the development of new care models to address the needs of older, frail community-dwellers. Community Virtual Wards (CVW) reduce adverse events in these patients. We examined the effect of an established CVW on pre-defined health trajectories (between “stable”, “deteriorating”, and “unstable” states) and characteristics that increased the likelihood of adverse healthcare outcomes (hospitalization, institutionalization and death). PATIENTS AND METHODS: We collected prospective data on frail patients admitted to a CVW in a single centre in Ireland. Relationships between risk scores, health states and adverse outcomes at 30, 60 and 90 days after admission were examined using multinomial regression analysis. RESULTS: In total, 88 community-dwellers, mean (±SD) age of 82.8 ±6.4 years, were included. Most were severely frail on the Rockwood Clinical Frailty Scale (mean 6.8/9 ±1.33). Reaching stability (“stable” state) within 30 days was a predictor for stability at 60 and 90 days and remaining at home. Stability was also associated with fewer care episodes (<2) (p=<0.001), a requirement for fewer healthcare professionals (HCP) (<7) (p<0.001) and lower risk of delirium (p<0.001). By contrast, being “unstable” at 60 days increased the numbers of HCP referrals (>7) and was predictive of more acute episodes (>2) and institutionalization or death (p<0.001). Predictors of adverse outcomes of either institutionalization or death included frailty status, function, mobility, nutrition, pressure ulcer risk and cognition. CONCLUSION: A CVW model can provide a framework for monitoring and case management to support older people to remain at home or identify those at risk of institutional care. The use of defined health states helped to stratify those at lower or higher risk in an already high-risk frail population. Level of frailty, function, mobility, nutrition, pressure ulcer risks and cognition were predictive of remaining at home and reaching a level of stability or instability/deterioration and institutional care. Dove 2020-06-22 /pmc/articles/PMC7320026/ /pubmed/32606633 http://dx.doi.org/10.2147/CIA.S236895 Text en © 2020 Lewis et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Lewis, Clare
O’Caoimh, Rónán
Patton, Declan
O’Connor, Tom
Moore, Zena
Nugent, Linda E
Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title_full Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title_fullStr Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title_full_unstemmed Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title_short Risk Prediction for Adverse Outcomes for Frail Older Persons with Complex Healthcare and Social Care Needs Admitted to a Community Virtual Ward Model
title_sort risk prediction for adverse outcomes for frail older persons with complex healthcare and social care needs admitted to a community virtual ward model
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320026/
https://www.ncbi.nlm.nih.gov/pubmed/32606633
http://dx.doi.org/10.2147/CIA.S236895
work_keys_str_mv AT lewisclare riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel
AT ocaoimhronan riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel
AT pattondeclan riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel
AT oconnortom riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel
AT moorezena riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel
AT nugentlindae riskpredictionforadverseoutcomesforfrailolderpersonswithcomplexhealthcareandsocialcareneedsadmittedtoacommunityvirtualwardmodel