Hostname: page-component-6766d58669-88psn Total loading time: 0 Render date: 2026-05-19T20:24:58.377Z Has data issue: false hasContentIssue false

Older people's experiences of dignity and support with eating during hospital stays: analytical framework, policies and outcomes

Published online by Cambridge University Press:  05 October 2021

Polly Vizard*
Affiliation:
Centre for Analysis of Social Exclusion, London School of Economics, London, UK
Tania Burchardt
Affiliation:
Centre for Analysis of Social Exclusion, London School of Economics, London, UK
*
*Corresponding author. Email: p.a.vizard@lse.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

There is growing recognition of the importance of dignity and support with eating as markers of high-quality and older-person-centred hospital services. We use data on these markers from the national Adult Inpatient Survey for England to build up statistical evidence on older people's experiences. We find that poor and inconsistent experiences of being treated with dignity and respect, and of receiving support with eating, affect a substantial proportion of inpatients across the vast majority of acute hospital trusts. There has been remarkably little change over time, although small improvements provide some grounds for optimism relating to policy developments in the period following the Francis Inquiry. Amongst people over 65, the prevalence of inconsistent and poor experiences of dignity and support with eating was higher amongst the ‘oldest of the old’ (inpatients aged over 80), individuals who experience a long-standing limiting illness or disability, and women. The highest rates of prevalence were observed amongst disabled women over 80. Perceptions of inadequate nursing quantity and quality, and lack of choice of food, stand out from logistic regression analysis as having consistent, large associations with lack of support with eating. These factors provide potential policy levers since they are within the control of hospitals to a certain extent. In drawing lessons from our analysis for inspection, regulation and monitoring, we highlight the importance of inequalities analysis – including systematic disaggregation and separate identification of at risk sub-groups (e.g. older disabled women) – rather than relying on a ‘population average approach’.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press
Figure 0

Figure 1. World Health Organization analytical model (healthy ageing over the lifecourse).Note: This figure is the authors' summary and representation of the WHO healthy ageing framework. WHO's explanation of the healthy ageing framework is set out in WHO (2015a).

Figure 1

Table 1. Inpatient experiences of dignity and help with eating (2014, weighted)

Figure 2

Figure 2. Trends in the percentage of patients reporting not being treated with dignity and respect or not receiving help with eating, 2004–2019.Sources: Estimates for 2004–2014 (dotted lines) are the authors’ own calculations using Adult Inpatient Survey microdata (annual versions deposited at the UK Data Archive) and are unweighted. Estimates for 2010–2019 (solid line) are weighted estimates published in Care Quality Commission (2020).

Figure 3

Figure 3. Inpatient experiences of dignity and help with eating by hospital trust (2014, weighted).Notes: A tailored version of the 2014 dataset was used for the analysis based on an agreement with the Care Quality Commission (CQC). The data are weighted using a new set of patient-level weights. These have been calculated using a differential non-response variable provided by the CQC and a grossing-variable that takes account of the size of local inpatient populations which has been derived from Hospital Episode Statistics data (Health and Social Care Information Centre, 2015a, 2015b). Each dot represents a hospital trust, with the exception of specialist trusts which have been grouped for this analysis. They are ordered left to right from ‘best’ to ‘worst’.Source: Authors’ calculations using the Adult Inpatient Survey, 2014.

Figure 4

Table 2. Estimates of the factors associated with a high probability of receiving poor or inconsistent help with eating (odds ratios from multilevel models, Models 1–5)

Figure 5

Table 3. Estimates of the factors associated with a high probability of receiving poor or inconsistent help with eating (odds ratios from multilevel interaction models, Models 6 and 7)

Figure 6

Figure 4. The association between individual hospital trust and inpatients’ risk of experiencing poor or inconsistent support with eating (caterpillar plots, all respondents, 2014).Notes: A tailored version of the 2014 dataset was used for the analysis based on an agreement with the Care Quality Commission. The caterpillar plots show the estimated residuals for hospital trusts, that is, the difference between the random intercept for each trust and the mean random intercept for all trusts. The residuals are calculated as the difference between the observed score and the score predicted by the regression equation.Source: Authors’ calculations using the Adult Inpatient Survey, 2014.