Grant reference ES/K004018/1

1. Older people's experiences of dignity and nutrition during hospital stays EMERGING FINDINGS Secondary data analysis using the Adult Inpatient Survey Polly Vizard and Tania Burchardt Grant reference ES/K004018/1

2. Motivation

3. Concerns about older people’s treatment in healthcare have been moving up the public policy agenda First wave of concerns: Joint Committee on Human Rights (2007)  Age UK (2010)  Patients Association (2011)  Health Service Ombudsman (2011) raised concerns about lack of support for eating and drinking, lack of dignity and respect, and other aspects of poor care

4. “First wave” followed by “tsunami” of findings: Report of the Independent Inquiry into Care Provided By Mid Staffordshire NHS Foundation Trust (2010) “The most basic standards of care were not observed [...] They were deprived of dignity and respect. [...] Patients who could not eat or drink without help did not receive it. [...]” (Mid Staffordshire NHS Foundation Trust Public Inquiry 2013a). Mid Staffordshire NHS Foundation Trust Public Inquiry (2013) (“Francis Inquiry”) Findings highlighted “serious systemic failure” (regulatory as well as management failure + substandard care remaining undetected) 290 recommendations on how to ensure improved systems of monitoring, inspection and regulation in the future

5. Three particularly relevant recommendations • The nature of standards: • Need fundamental standards of safety and quality (minimum standards, noncompliance not tolerated) and enhanced standards of quality (recommendation 13) • More effective regulation / inspection: • The need for more effective systems for enforcing compliance with fundamental standards (recommendation 14) • More effective use of information • Patient voice was not heard or listened to • More effective use of outcomes data, including better use of available patient experience data • Government response to Francis Inquiry • Government accepted many of the Francis recommendations • Specific initiatives and policies (e.g. staff training, whistle-blowing, duties of candour, Malnutrition Task Force) • Draft new Fundamental Standards of Care published 2014 include requirements that: • service users must be treated with dignity and respect (5.1) • the nutritional needs of service users must be met (9.1)

6. Link with national equality and human rights monitoring Equality and human rights legislation Equality Acts 2006 / 2010 Human Rights Act 1998 These are binding on public healthcare bodies (incl. providers) Growing importance for healthcare monitoring, regulation and inspection Equality and Human Rights Commission (EHRC) Promotes compliance with equality and human rights standards “Strategic regulator” and works with other regulators to promote equality and human rights (MOU with CQC) Statutory duty to monitor progress towards equality and human rights using indicators (reports to Parliament) Discharges this duty using the EHRC Measurement Framework

7. EHRC Measurement Framework Developed mainly 2009-2012 Rooted in the capability approach 10 domains (life, physical security, health, education, etc.) 80 indicators capturing key equality and human rights concerns, agreed through national consultation Embeds equality and human rights standards: Systematically disaggregating findings under each indicator by protected characteristics (gender, age, disability, ethnicity, religion or belief, sexual identity) + social class Quantifying risks facing groups that are often “missing” or “invisible” in national monitoring exercises (e.g. oldest of the old, older disabled women) The health domain includes indicators on: treatment with dignity and respect help with eating, during hospital stays [overviews in Burchardt and Vizard 2011, Vizard 2012] Under-exploited source of data on emerging national concern?

8. What did we do?

9. Central research question What does further and deeper secondary analysis of a previously under-exploited data source - the Adult Inpatient Survey - add to knowledge and understanding of older people’s experiences of dignity and nutrition during hospital stays? Data: the Adult Inpatient Survey (2012) • June to August 2012 • 156 acute NHS hospital trusts in England • Patients aged 16 years or older with at least one overnight stay (not maternity, terminations, psychiatric, day case, or private patients) • Target sample: based on 850 continuous discharges; questionnaires sent to home address • Achieved sample: 64,505 respondents (response rate: 51 per cent) • Tailored dataset provided by Picker Institute with permission CQC: • disaggregation within older age population • disability • + ethnicity Specialist trusts grouped

10. Focus on two survey questions “Did you get enough help from staff to eat your meals? Response options: 1 “yes, always” 2 “yes, sometimes” 3 “no” 4 “I do not need help to eat meals” “Overall, did you feel you were treated with respect and dignity while you were in the hospital?” Response options: 1 “yes, always” 2 “yes, sometimes” 3 “no”

11. Interpretation of response options “Did you get enough help from staff to eat your meals? Response options: 1 “yes, always” 2 “yes, sometimes” 3 “no” 4 “I do not need help to eat meals” “Overall, did you feel you were treated with respect and dignity while you were in the hospital?” Response options: 1 “yes, always” 2 “yes, sometimes” 3 “no” Experienced satisfactory standard of care Experienced inconsistent standard of care Experienced poor standard of care Presentation of findings depends on this interpretation Experienced satisfactory standard of care Experienced inconsistent standard of care Experienced poor standard of care

12. Data issues • Low response rate (see ‘weights’ below) • Limitations of coverage • People who die in hospital or shortly afterwards not covered • Those ill / need support to answer questions / suffering conditions such as Alzheimer's and Dementia may be less likely to respond • Focus is on acute sector (mental health institutions separately monitored) • Doesn’t cover private providers of public healthcare e.g. independent treatment centres • Self-reported experience data • Strength: asks users directly about their experiences • Potential weakness: do respondents understand the questions and answer them accurately? • Potential weakness: different groups may systematically answer questions differently (adaptive expectations – are older people less likely to complain? • Sizmur (2011), Bleich et al (2007) find that age is a key predictor of expectations • No objective information about context (eg numbers of nurses on wards)

13. Findings

14. 10 key findings • There is a widespread and systematic pattern of inconsistent or poor standards of care during hospital stays (individual instances v general significant problem) • The need for help with eating is also a general challenge rather than a specialist or marginal concern: quarter of respondents need help with eating (around 3.4 million people in a year) • More than 1 in 3 (38%) of those who need help experiencedinconsistent or poor standards of help with eating (1.3 million people, including 638,000 aged 65 or over) • Just under a quarter (23%) of inpatients experience inconsistent or poor standards of dignity and respect (2.8 million people, of whom about 1 million aged 65 or over) • Amongst over 65s, risks are higher for women, over80s, and people with limiting long-standing illness or disability (LLID)

15. 10 key findings (cont.) • Variation by hospital trust is important: percentage of those who need help with eating who experience poor standards of care ranges from 5% to 34% across different hospital trusts • Cumulative risks for over 80s considerably higher in hospital trusts where the overall proportion reporting experiences of inconsistent and poor standards of help with eating is relatively high • Implications for policy: the perception that the quantity and quality of nursing staff are inadequate, and reports of no choice of food, appear to be associated with lack of support with eating • Key lessons for monitoring, inspection and regulation: judgements about poor performance in relation to the new fundamental standards of care should be based on a “minimum threshold approach” (rather than a “deviation from average” approach) • Importance of disaggregation and identification of differential risks facing different population subgroups, not relying on population averages

16. Prevalence of experiences of poor or inconsistent standards of help with eating • (people aged 66-80, restricted to those who need help, unweighted) 61% of this subgroup experienced inconsistent or poor standards • Source: author’s calculations using the Adult Inpatient Survey, 2012, England

17. Weights • Weights provided with data set are standardisation weights • Standardise across hospital trusts for patient mix by gender, age and route of admission • Do not adjust for inpatient population size (each trust has a target sample of 850, regardless of number of patients treated in a year; small trusts are over-represented in the raw and standardised data) • CQC national summaries are based on unweighted data • We have developed a new set of patient level weights to make inferences about national inpatient population: • correcting for differential non-response within trusts by gender, age and route of admission • grossing up to size of total annual inpatient population by trust • Ideally would gross up to live discharges by trust • but Hospital Episodes Statistics data request delayed • instead use published HES data on “Finished Consultant Episodes”, adjusted to take account of national ratio of FCEs to live discharges • Applying these weights allows us to produce estimates of the number of inpatients who have experienced inconsistent and poor standards of care nationally over the course of a year

18. Weighted prevalence rates and headcounts (relative risks within the older population) Source: author’s calculations using the Adult Inpatient Survey, 2012, England. The dataset used in the calculations was provided by the Picker Institute and CQC. The final weight is based on differential non-response weights provided by the Picker Institute with the permission of the CQC and on published HES data. Notes:Eating: respondents were asked “Did you get enough help from staff to eat your meals?” and could choose from the following responses, (1) “Yes, always”; (2) “Yes, sometimes”; (3) No; (4) “I did not need help to eat meals”. The disability variable has been derived from responses to question 74 (on longstanding conditions) and question 75 (on difficulties). Missings have been dropped from the calculations in this table. Rows may not sum exactly to 100%. Dignity and respect: Respondents were asked Overall, did you feel you were treated with respect and dignity while you were in the hospital? Response options were (1) yes, always (2) yes, sometimes (3) no. Minimum unweighted bases: range help with eating 776-112; range dignity and respect 3382-138. Numbers affected rounded to the nearest 100 individuals.

19. Variation between trusts (restricted sample) There is considerable variation in the percentage of those who need help reporting not receiving enough help with eating from staff at the trust level

20. Drivers of lack of help with eating • Logistic regression exercise • Dependent variable • Binary dependent variable = whether received enough help with eating • Focus is on individuals who report with not receiving enough help with eating (strong “nos”) • Captures the distinction between those who definitely did not receive enough help from staff with eating (=1) versus everyone else (=0) Restricted sample Limits the analysis to those who indicate that they need help with eating (excluding those who do not need help) 1=needs help, didn’t get help 0=needs help, did get help Full sample Individuals for whom the capability / right to food is not fulfilled v. other individuals who enjoy this capability / right

21. Independent variables tested as part of the logistic regressions • Group 1: Individual characteristics • Age • Disability • Gender • Whether proxy respondent • Group 2: Individual journey through hospital • Route of admission (emergency or planned) • Whether stayed in a critical care unit • Number of wards stayed in • Length of stay (five bands) • Whether had an operation (ns) • Group 3: Quantity and quality of nursing care • Perceptions of the adequacy of the number of nurses • Perceptions of the quality of nurses (constructed) • Choice of food • Yes/no • Hospital trust • Three-digit hospital trust code ethnic group and IMD not available

22. Sensitivity testing and alternative specifications • Reporting analysis of poor standards of care (strong ‘nos’) • have also tested poor or inconsistent treatment of care (‘no’ or ‘sometimes’ received help) • Reporting dependent variable based on the full sample and restricted sample (i.e. excluding those who do not need help) • Reporting characteristics separately • have also tested interactions, for example between age and disability • Reporting standard regression analysis with dummies for each hospital trust • have also tested models without trust dummies, with robust standard errors adjusting for clustering at trust level • have also undertaken multilevel regression analysis • Reporting full model, but group 3 variables (especially) are possibly endogenous • model built up in stages bringing in the different groups of variables (esp. inclusion / exclusion of group 3 variables) • findings should be interpreted cautiously

23. Factors associated with not receiving enough help with eating from staff during hospital stays (full sample, 2012)

24. Factors associated with not receiving enough help with eating from staff during hospital stays (restricted sample, 2012) - key difference is group 2 variables

25. Policy implications and key lessons for monitoring, regulation and inspection

26. Reported experiences of inadequate quantity or quality of nursing care has a consistent, positive and large association with lack of support with eating • Potential policy lever? • Lack of choice of food also important • Eating in hospital is complex • Good practice guidelines e.g. Malnutrition Taskforce in relation to choice, texture, delivery systems (protected mealtimes, red tray systems) could help • Proxy responses matter • Often disregarded as just a source of measurement error • But could be useful in this context to triangulate for adaptive expectations [NW1]For both figures that follow: sort out age label and reorder bars with gender, age on top

27. How to identify poorly performing trusts in relation to fundamental standards of care? • Academic literature: how to identify poor / unusual performers from a distribution • Spiegelhalter (2005), Jones and Spiegelhalter (2011), Spiegelhalter (2012) • CQC new inspection model (following Francis recommendations / Keogh Review summer 2013; revised Sept. 2013 “hospital intelligent monitoring”) • Evaluates patterns and risks prior to inspection using a basket of 150 indicators • Makes better use of patient experience data, including indicators on dignity / respect and meeting individual nutritional needs (help with eating) based on Adult Inpatient Survey • Compares trust performance based on pre-existing annual benchmarking reports method (judgements are made based on “deviation from mean” method (scoring system, standardisation weight, overdispersion adjustment, no adjustment for inpatient size)

28. Identifying poor performance - deviation from mean methodology • Funnel plot with average as target (restricted sample 2012) Raw percentage significantly higher than average Percentage of those who need help who report not receiving enough help with eating Average = 18% Sample size NB NOT standardised or corrected for “over-dispersion”, excl. specialist trusts

29. If average TOO HIGH, danger of under-identification of poor performance? (average 18% for lack of help with eating too high??) • Systematic review of 160 individual data packs produced for trusts under “hospital intelligent monitoring” model • only a few trusts identified as “risk” or “elevated risk on the ‘help with eating’ indicator – surprising?? • Monitoring compliance with fundamental standards of care requires a different methodology to evaluating variation in hospital standardised mortality ratios (hsmrs) (where “deviation from average” method might be more legitimate??) • Judgements about poor performance should be based on a “minimum threshold approach” RATHER THAN a “deviation from average” approach (focussing on relative trust performance) • In line with the concept of a minimum standard, relevant minimum threshold (target / expectation) = zero experiences of lack of support with eating?

30. Identifying poor performance – minimum threshold approach • Funnel plot with 1% as target (restricted sample 2012) Raw percentages / - all trusts significantly higher than 1% Percentage reporting not receiving enough help with eating Minimum threshold = 1% Sample size

31. And finally, importance of looking at disaggregated risks

32. Cumulative risks amongst older people aged > 80 who need help with eating (predicted probabilities, hypothetical scenarios, 2012*) • *Predicted probabilities of not receiving enough help with eating from staff during a hospital stay (based on logistic regression model, restricted sample, variables above set at “at risk” values, other variables held at means)