Predictors of adverse outcomes and factors associated with a risk-stratification based community virtual ward model for older persons with complex health and social care needs
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
Population ageing is occurring rapidly worldwide, particularly in more developed
countries. As a result, a greater proportion of frail older adults are expected to be living
in the community but at increased risk of emergency department (ED) presentation and
hospital admission. While risk-stratification is useful in allocating limited resources, few
instruments or models are available to support healthcare professionals to manage the
complex health and social care needs of these patients. The recent introduction of a
Community Virtual Ward (CVW) for older persons with complex healthcare needs,
reduced ED presentations and unplanned hospital admissions. The research presented
in this thesis expands on previous studies examining predictors of adverse healthcare
outcomes in community-dwellers. It also investigates the impact of health trajectories
(transient health states defined as ‘unstable’, ‘deteriorated’ and ‘stable’) and factors
associated with the risk-stratification model including individual screening and
assessment scale scores on the risk of hospitalisation, institutionalisation and death
among patients admitted to a CVW.
This study is a longitudinal non-experimental descriptive and correlational design
investigating patients selected for admission to a CVW in a single centre in Ireland. The
theoretical principles of a Markov model informed the study design. Correlations and
associations were examined using Chi-square, and Spearman’s rho tests. To examine
relationships between risk scores, health states and adverse outcomes a univariate,
multinomial and multivariable regression analysis was performed.
In total, 88 community-dwellers, with a mean age (+/- standard deviation) of 82.8 +/-6.4
years were included. Most were severely frail on the Rockwood Clinical Frailty Scale
(mean 6.8/9 +/-1.33) and highly dependent on the Barthel Index (2.7/20 +/-0.8). Health
states were predictive of adverse outcomes 60 observed up to 90 days. Reaching a
level of stability (‘stable’ state) within 60 days of admission to the CVW was a predictor
for stability at 90 days and remaining at home. Stability was also associated with less
episodes of care (<2), lower risk of experiencing delirium, and fewer numbers of health
care professional direct involvement in care (<7). In contrast an ‘unstable’ health state
observed at 60 days was predictive of institutionalisation or death with an increase in
the number (>2) of episodes of care, and higher numbers of healthcare professionals
(>7) direct involvement in care. Several screening and assessment instruments scores
covering pressure ulcer risk, functional and frailty status, mobility, nutrition and cognition
were predictive of reaching stability and risk of institutionalisation.
The CVW provides a framework for case management as a conceptual model of risk to
support older people at home or identify those at risk of institutional care. The use of
defined health states assisted in stratifying those at lower or higher risk in a high-risk
frail population. The selection of brief, targeted screening and assessment instruments
used to monitor risk in this CVW model were also helpful in stratifying participants.
Further research is needed to confirm these findings and refine this model.
First SupervisorDr. Linda Nugent
Second SupervisorDr. Declan Patton
CommentsA thesis submitted for the degree of Doctor of Philosophy from the Royal College of Surgeons in Ireland in 2019.
Published CitationLewis C. Predictors of adverse outcomes and factors associated with a risk-stratification based community virtual ward model for older persons with complex health and social care needs [PhD Thesis]. Dublin: Royal College of Surgeons in Ireland; 2019.
Degree NameDoctor of Philosophy (PhD)
Date of award30/06/2019
- Doctor of Philosophy (PhD)