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

Authors Lewis C, O'Caoimh R, Patton D, O'Connor T, Moore Z, Nugent LE

Received 31 October 2019

Accepted for publication 2 May 2020

Published 22 June 2020 Volume 2020:15 Pages 915—926


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Richard Walker

Clare Lewis,1 Rónán O’Caoimh,2,3 Declan Patton,1 Tom O’Connor,1 Zena Moore,1 Linda E Nugent1

1School of Nursing and Midwifery, Royal College of Surgeons Ireland, Dublin, Ireland; 2Clinical Sciences Institute, National University of Ireland Galway, Galway City H91 TK33, Ireland; 3Mercy University Hospital, Cork City T12 WE28, Ireland

Correspondence: Clare Lewis Email

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.

Keywords: community virtual ward, older persons, complex care, case management, risk prediction, health states

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