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Gott M, Ingleton C, Gardiner C, et al. Transitions to palliative care for older people in acute hospitals: a mixed-methods study. Southampton (UK): NIHR Journals Library; 2013 Nov. (Health Services and Delivery Research, No. 1.11.)

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Transitions to palliative care for older people in acute hospitals: a mixed-methods study.

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Chapter 5Survey of palliative care need at Sheffield Northern General Hospital and Royal Lancaster Infirmary (phase 3)

In this chapter we present the background, methods and results from the quantitative cross-sectional survey of hospital inpatients, which was undertaken in two UK hospitals. In doing so we address the following objectives:

  1. to explore the extent and current management of palliative care need within acute hospitals
  2. to identify patient factors predictive of key aspects of palliative care need and, in particular, physical and psychological symptom load
  3. to examine the circumstances under which transitions to a palliative care approach occur within acute hospitals, with a particular focus on the influence of age and disease type on decision-making
  4. to examine if and how information about a transition to a palliative care approach is communicated to patients and their families and how they are in involved in decision-making
  5. to identify those hospital admissions amongst people with palliative care needs that were avoidable but which occurred because of a lack of alternative service provision or support in the community
  6. to identify patient factors predictive of avoidable hospital admissions
  7. to quantify the cost of avoidable acute hospital admissions amongst those patients with palliative care needs.

Background

The majority of deaths in developed countries now occur in the acute hospital setting; in England, around 58% of people currently die in acute hospitals.112 Although recent evidence suggests a slow increase in the proportion of deaths at home in England and Wales,19 other predictions based on past trends estimate that only one in 10 people in the UK will die at home by 2030, and that an expansion of inpatient facilities by one-fifth may be required.113 The End of Life Care Strategy for England5 has highlighted the delivery of high-quality palliative and end-of-life care in the acute hospital setting as an area of priority, acknowledging that a significant proportion of patients dying in acute hospitals receive very poor care.

The identification of patients who may benefit from palliative care is recognised as problematic. Health professionals have reported differing understandings of what constitutes a ‘palliative care’ patient30 and when a palliative care approach might be appropriate.

This finding is supported by evidence from our qualitative focus groups presented in Chapter 4. There are significant implications of a lack of consensus in identifying which patients have palliative care needs, including poor continuity of care, inadequate service provision and support and excess economic cost.89,114

Given the challenge that the increasing number of hospitalisations at the end of life presents, coupled with the problem of identifying patients who would benefit from palliative care input, it is now imperative to gain a better understanding of the extent of palliative care need in the hospital setting to more appropriately map services to patient need, define priorities for care and assess the economic impact of palliative care in the acute setting.2

Methods

Survey methods

A comprehensive survey of hospital inpatients was undertaken in two UK hospitals selected for their sociodemographic diversity. The SNGH has > 1100 beds and serves a largely urban, economically disadvantaged and ethnically diverse area. In contrast, the RLI has approximately 400 beds and serves a predominantly white Caucasian semi-rural/remote rural population. Although the term ‘census’ was originally proposed to describe this phase of data collection, this has been replaced throughout by the term ‘survey’. This was because of concerns that the term ‘census’ implies a collection of a complete population data set. However, this was not possible as the ethics committee stipulated that data collection from patient notes was restricted to those patients who consented to involvement in the study.

The survey of the SNGH was undertaken over an 11-day period in May 2010 and the survey of the RLI took place over a 5-day period in November 2010. All inpatient wards, with the exception of children’s wards and mother and baby units, were included. Each ward was visited by two members of the data collection team at some point during the survey period. Inclusion criteria were age ≥ 18 years and resident on the ward at 0900 on the day that the ward was surveyed. Non-English-speaking patients and deaf patients were excluded because of a lack of translation facilities.

The approach to the inclusion of patients lacking capacity to consent for themselves was developed in line with Mental Capacity Act 2005 guidance.10 Senior medical and nursing staff, and relatives (when available) were consulted to identify any patients lacking capacity to consent. Personal consultees (relatives or close friends) were identified and, when available, were invited to participate on behalf of patients lacking capacity.

For patients/consultees who consented to participate, the following data were collected:

  1. Data from patients’ hospital case notes comprising evidence of palliative care need according to GSF prognostic indicator criteria57 (the GSF prognostic indicator guide provides 11 diagnostic criteria categories, which provide an indication of patients who might benefit from palliative care input); reason for admission; sociodemographic and diagnostic information; details of comorbidities; evidence of adoption of a palliative care approach using a list of predefined indicators (identified by health professionals during a previous qualitative phase of this study; see Chapter 4); number of hospital admissions in the last 12 months; discharge plans.
  2. For each consenting patient a member of the medical staff and a member of the nursing staff known to the patient were interviewed. Staff were asked to provide diagnostic and admission information for the patient. They were also asked whether they believed the patient to have palliative care needs according to a standardised definition (a broad and inclusive definition of palliative care was purposively selected to maximise the potential for patient identification),115 whether they would be surprised if the patient died within 12 months; about the appropriateness of the admission to hospital; and whether prognostic discussions had taken place. When possible the member of the nursing staff was the designated ‘named nurse’ for the patient and the member of the medical staff was the junior (Foundation Year 1 and 2) or senior (Specialist Trainee year 1 and year 2) house officer or the registrar.
  3. Patient-/consultee-completed questionnaires comprising sociodemographic information; a service use questionnaire developed for use with a palliative care population (Gott M, Barnes S, Payne S, Seamark D, Small N. Department of Health, 2007, unpublished report); and the Sheffield Profile for Assessment and Referral for Care (SPARC).116 SPARC is a validated holistic self-assessment tool to identify patients who would benefit from palliative care input (see Appendix 4). It provides scores across a range of physical, psychological and social domains. In cases in which consultees participated, they were asked to answer questions as they believed that the person they were acting as consultee for would have done.

All data were collected by a team of 30 researchers with previous experience in health-care research as either an academic or a clinician. Data from hospital case notes were collected by researchers with a clinical background in medicine or nursing. All researchers attended a full-day training session prior to the study commencing, which provided training in approaching patients/staff, the correct use of data collection tools and procedures for problem situations.

Data analysis

All data were recorded onto anonymised paper proformas and were subsequently transferred onto a SPSS database version 20 (SPSS Inc., Chicago, IL, USA) for data cleaning and analysis, with the guidance of the project statistician (CP). Descriptive analyses were used to describe the data from all sources.

Cohen’s kappa measure of chance-corrected agreement was used to assess agreement between sources regarding identification of patients with palliative care needs and appropriateness of admission to hospital. Logistic regression analyses were used to explore the effects of a range of predictor variables on various outcomes.

Economic analysis methods

Two palliative care consultants (BN and MB) undertook a post hoc assessment of appropriateness of admission to hospital for patients who had been identified with palliative care needs according to GSF criteria. They reviewed the survey data collected from the case notes of these patients and made a decision whether the admission was ‘potentially avoidable’ or ‘unavoidable’ or whether there were ‘insufficient data to make a decision’. For those patients whose admission was classed as potentially avoidable, an alternative place of care was suggested by the consultants.

An estimated cost was then attached to each of the admissions identified by the consultants as potentially avoidable. The cost of each hospital admission was estimated using HRG codes. HRG codes are clinically meaningful groupings of patient activity, based on both diagnoses and clinical procedures undertaken. Standard costs are assigned to each HRG code and these are used across the NHS in England to calculate the cost of a hospital admission.117

Because of ethical restrictions, HRG codes for patients in the surveys could not be obtained retrospectively from the trusts involved. The Sheffield Teaching Hospitals coding team therefore undertook an ad hoc exercise to allocate HRG codes to each admission identified as potentially avoidable across both hospitals using the data from our survey. HRG codes and tariffs for 2010/11 were used.

Admissions for patients who remain in hospital beyond the expected upper length of stay for the HRG code (trim point) would normally be allocated an additional long-stay or excess bed-day payment. In the absence of length-of-stay data for our sample of patients, we were unable to cost for excess bed-days.

We then estimated the costs of the alternative places of care suggested by our consultants for those admissions deemed avoidable. The costs of alternative places of care were taken from published national sources, inflated to 2011 prices when necessary (see Table 11). The cost of nursing home care (£106 per day) was obtained from the Personal Social Services Research Unit’s Unit Costs of Health and Social Care 2010.118 The cost of hospice care (£325 per day) was obtained from research commissioned by the National Audit Office.119 The cost of home care (£50 per day) was derived from a King’s Fund report,82 which estimated the cost of home care in the last 8 weeks of life. This cost included the following services: GPs, district nursing, Marie Curie and Macmillan nurses, ambulance journeys, hospice at home and hospice (inpatient) and equipment. An average daily cost was calculated from the 8-week figure cited in the report.

TABLE 11

TABLE 11

Total cost of alternative care for avoidable admissions

These studies all assumed a broad societal perspective120 to take account of costs irrespective of funding source. Although we would have also liked to include informal carer costs and indirect costs – those incurred as a result of lost productivity – in our calculations, this was not possible because of a lack of data. As a point of comparison, we explored a more restrictive cost perspective. This was the NHS and personal social services (PSS) perspective, which considers only those costs that fall within the remit of these two organisations. To do this we used the costs cited in a previous study,121 which indicated that only 43% of nursing home costs and 44% of hospice costs were funded by the NHS or PSS. Costs were inflated to the 2011 price year when necessary.

Results

Survey response rate

A total of 1359 inpatients were eligible for inclusion in the survey (1009 patients in Sheffield and 350 patients in Lancaster). Of the total eligible patient population, 654 (48.1%) patients agreed to participate in the study of whom 616 patients consented for themselves and 38 consented through a consultee. Patient response rates were similar for the two hospitals (SNGH 46.9%, RLI 52.9%). Details of patient recruitment at the two participating hospitals are provided in Figure 3.

FIGURE 3. Details of patient recruitment at the two participating hospitals.

FIGURE 3

Details of patient recruitment at the two participating hospitals.

Of the 654 consenting patients/consultees, complete data sets are available for 514 patients (final response rate 37.8%). A complete data set is defined as containing a case note review and a questionnaire completed by a member of either the medical staff or the nursing staff, but not necessarily both. The analyses presented in this section relate to the 514 patients with complete data sets.

Results of the case note review

Of the 514 patients, just over one-third (n = 185, 36.0%) met one or more of the GSF prognostic indicator criteria for palliative care need. Of the patients identified with palliative care needs according to GSF criteria, 53.8% were female and the median age was 78 years, with an age range of 20–103 years. The majority of these patients were aged ≥ 65 years (77.8%), with a considerable proportion aged ≥ 85 years (23.2%) (Figure 4). Table 4 shows demographic information for the sample of 185 patients with palliative care needs according to GSF criteria.

FIGURE 4. Age range of patients with palliative care needs according to GSF criteria (n = 181, no age given for four patients).

FIGURE 4

Age range of patients with palliative care needs according to GSF criteria (n = 181, no age given for four patients).

TABLE 4

TABLE 4

Demographic information for patients with palliative care needs according to GSF criteria (n = 185)

The majority of patients (70.8%) met only one GSF criterion for palliative care need; however, just under one-third (29.2%) met two or more criteria (see Table 5). Figure 5 shows the breakdown of GSF prognostic indicators amongst the patient sample.

TABLE 5

TABLE 5

Participant admission and diagnostic data (n = 185)

FIGURE 5. Numbers of patients meeting each of the GSF prognostic indicators for palliative care need (n = 185).

FIGURE 5

Numbers of patients meeting each of the GSF prognostic indicators for palliative care need (n = 185). a, Other life-limiting illnesses included cystic fibrosis, Huntington’s disease, asbestosis, etc.

The most common GSF prognostic indicator was frailty, with almost one-third of patients (27%) meeting this criteria. Heart disease (20.5%), cancer (19.5%), COPD (18.4%) and dementia (17.8%) were the next most common GSF criteria, and were roughly equal in prevalence. Other indicators, including stroke, renal disease and Parkinson’s disease, were less common.

Table 5 provides admission and diagnostic information for the patient group. Reason for admission to hospital was ascertained in all but five patients (included in the ‘other’ group). The most common reasons for admission were falls/confusion/general frailty (14.6%), complications relating to cancer (13.0%) and respiratory disease or exacerbation (13.0%). Patients had a median of two comorbid conditions, with over one-third of patients having three or more comorbidities. In the 12 months before the survey, patients had a median of one previous hospital admission and spent a mean of 42 days (lower quartile = 1.8, upper quartile = 53.0) in hospital. For the majority of patients (65.9%) there was no evidence of the adoption of a palliative care approach. Around one-third (28.6%) of patients had a do not attempt resuscitation (DNAR) order in place, but only a small number (8.1%) had been referred to specialist palliative care services.

Results of medical and nursing staff assessment of palliative care need

Medical and nursing staff were asked whether they believed patients to have palliative care needs according to the Canadian Palliative Care Association 1997 definition.115 Nurse questionnaires were completed for 473 patients; of these, nurses stated that 84 (17.8%) had palliative care needs. However, data from patients’ hospital case notes indicated that 174 (36.8%) of these 473 patients were identified as having palliative care needs according to GSF criteria (Table 6). Staff were also asked, ‘would you be surprised if this patient died (1) during this admission and (2) in the next 12 months?’ Nursing staff would not have been surprised if the patient died during the current admission in 74 (15.6%) cases and in the next 12 months in 180 (38.1%) cases. Medical staff questionnaires were completed for 297 patients; of these, doctors stated that 46 (15.5%) had palliative care needs, whereas using the GSF criteria 108 (36.4%) were identified with palliative care needs (see Table 6). Medical staff would not have been surprised if the patient died during the current admission in 50 (16.8%) cases and in the next 12 months in 123 (41.4%) cases.

TABLE 6

TABLE 6

Agreement between nursing staff, medical staff and the GSF regarding the identification of patients with palliative care needs

Table 6 shows the level of agreement between medical staff, nursing staff and the GSF regarding the identification of patients with palliative care needs. Cohen’s kappa indicates a poor agreement between nursing staff and the GSF (n = 473, kappa = 0.22) in terms of identifying patients with palliative care needs. Agreement between medical staff and the GSF was also poor (n = 297, kappa = 0.25). Agreement between medical staff and nursing staff regarding which patients had palliative care needs was moderate (n = 256, kappa = 0.42).122

Results of patient self-report data

Self-report questionnaires were completed for all 185 patients identified with palliative care needs according to GSF criteria. Questionnaires were completed by patients in 162 cases (87.6%) and by consultees in 23 cases (12.4%). The SPARC questionnaire provides a self-assessment of palliative care needs and scores variables from 0 to 3; a score of 3 on any variable indicates that the patient merits ‘immediate attention by the attending clinician’.116 The SPARC questionnaire contains variables in six domains: physical symptoms, psychological symptoms, religious and spiritual issues, independence and activity, family and social issues and treatment issues. The majority of patients (n = 154, 83.2%) scored 3 on at least one variable in one of the six domains. Physical symptoms were most troublesome with 74.6% of patients scoring 3 on one or more variable in this domain. Patients also reported high levels of psychological symptoms (43.2%) but fewer problems relating to the other domains (Figure 6). Consensus between patients and medical staff (kappa = 0.20, n = 107) and between patients and nursing staff (kappa = 0.20, n = 173) was poor regarding identification of palliative care need when a SPARC score of 3 on one or more variable was used as a proxy for self-assessed palliative care need.

FIGURE 6. Sheffield Profile for Assessment and Referral for Care questionnaire responses for patients with palliative care needs according to GSF criteria (n = 185).

FIGURE 6

Sheffield Profile for Assessment and Referral for Care questionnaire responses for patients with palliative care needs according to GSF criteria (n = 185).

Predictors of symptom burden amongst patients with palliative care needs

Binary logistic regression was performed to assess whether known diagnostic factors (GSF indicator, number of comorbidities) and/or demographic factors (age, sex, living arrangements) were able to predict symptom burden as measured by the SPARC questionnaire. Only 183 of the 185 patients were included in these analyses as two patients had insufficient case note data. As only two SPARC variables included substantial numbers of patients (psychological and physical symptoms; see Figure 6), other SPARC variables were removed as outcome measures from the logistic regression. The two outcome variables indicating symptom burden (physical and psychological symptoms) were entered as binary outcome measures indicating ‘high symptom burden’ (score of 3 on one or more variable) compared with ‘low symptom burden’ (no scores of 3 on any variables) in the logistic regression.

Each predictor variable was entered singly and not adjusted for other variables. The results of these analyses are presented in Table 7. The results indicate that patients diagnosed with heart disease were less likely than those with other diagnoses to have a high physical symptom burden [odds ratio (OR) 0.42]. The results also indicate that patients with dementia were more likely to have a high physical symptom burden (OR 3.94) and a high psychological symptom burden (OR 2.88). Female sex was a significant predictor of psychological burden (OR 2.00), and having three or more comorbidities was also a significant predictor of psychological burden (OR 3.97). Neither age nor living arrangements were significant predictors of symptom burden.

TABLE 7

TABLE 7

The results of binary logistic regression analysis to predict psychological and physical burden (n = 183)

Older patients aged ≥ 85 years

A key focus of this study was the care provided to older people at the end of life in hospital. Therefore, additional analyses were undertaken on patients who participated in the survey who were aged ≥ 85 years. Of the 654 patients who agreed to participate in the survey, 127 (19.4%) were aged ≥ 85 years. After data cleaning, complete data sets were available for 110 patients aged ≥ 85 years. Table 8 shows demographic and admission data for these 110 patients. The majority were female and the median age was 89 years. Most of the patients lived alone and all were of white ethnic origin. Reason for admission to hospital was obtained from hospital case notes. The most common reason for admission (25.5%) was general frailty (including falls, confusion or general deterioration).

TABLE 8

TABLE 8

Demographic and admission information for patients aged ≥ 85 years (n = 110)

The hospital case notes of the patients aged ≥ 85 years were examined for evidence of palliative care need according to GSF prognostic indicator criteria. Forty-four (40.0%) patients met one or more criteria for palliative care need. Frailty (16.4%) and dementia (13.6%) were the most common criteria met (Figure 7). The majority of these patients met just one GSF criterion (n = 30, 68.2%), with smaller numbers meeting two (n = 11, 25.0%) or three (n = 3, 6.8%) criteria.

FIGURE 7. Gold Standards Framework indicators met by patients aged ≥ 85 years (n = 44).

FIGURE 7

Gold Standards Framework indicators met by patients aged ≥ 85 years (n = 44).

Hospital case notes were also examined for indicators of a transition to a palliative care approach. Half of the patients (50%) who met GSF criteria for palliative care need met one or more indicator of transition to palliative care. Half of the patients had a DNAR order in place; however, there was documentation of discussion with the patient and/or family regarding the DNAR order in only 6 cases (13.6%). Even amongst patients who did not meet GSF criteria, a reasonable number (16.7%) had a DNAR order in place. Only two patients of the 44 who met GSF criteria had been referred to specialist palliative care services; however, one patient was referred to specialist palliative care despite not meeting any GSF criteria. The only patients for whom advanced care plans (1.5%) or use of syringe drivers (3.0%) had been documented did not meet GSF criteria for palliative care need.

Predictors of transitions to palliative care

Analyses relating to transitions to palliative care were undertaken on 183 of the patients with palliative care needs according to GSF criteria (two patients were excluded from the analyses because of missing data on key transition variables). Of the 183 patients, 61 (33.3%) showed evidence of transition to a palliative care approach by meeting one or more indicator of adoption of a palliative care approach (Table 9). Of these, 43 patients met just one indicator, 14 patients met two indicators and four patients met three indicators.

TABLE 9

TABLE 9

Indicators of adoption of a palliative care approach for patients with evidence of transition (n = 61)

A logistic regression was performed to assess whether various diagnostic and demographic factors were able to predict a transition to palliative care. Data were recorded for five indicators of transition to palliative care. As only one individual indicator of transition to palliative care included substantial numbers of patients (DNAR; see Table 9), a single binary outcome indicating any evidence of a transition to palliative care compared with no evidence was used for the logistic regression. Among the GSF diagnostic indicators, no patients had motor neurone disease and the frequencies for Parkinson’s disease and multiple sclerosis were very low; therefore, these last two indicators were combined with ‘other life-limiting conditions’ to form a combined indicator.

Table 10 shows that, in the unadjusted logistic regression, the significant predictors of a transition to palliative care were the GSF indicators for cancer, heart disease and stroke, together with age and living in a residential or nursing care home. The table also shows the final multivariate predictive model, which comprised three GSF diagnostic indicators (cancer, dementia, stroke) together with age. This model correctly predicted 74% of outcomes and could not be improved significantly by adding the other GSF indicators, number of comorbidities, sex or living arrangements. In this model, the odds of a transition to palliative care were multiplied by an estimated 5.1 for patients with a cancer diagnosis, by 8.0 for a stroke diagnosis and by 2.6 for a dementia diagnosis. The odds were also increased by an estimated 3% for every additional year of age (with no evidence of significant non-linearity in this relationship).

TABLE 10

TABLE 10

Relationships between potential predictors and transition to palliative care

Potentially avoidable admissions to hospital for patients with palliative care needs

Appropriateness of admission assessments were undertaken for 208 patients; this was the total number of patients who were identified with palliative care needs according to GSF criteria and for whom complete case data were available (no medical/nursing data or patient data were required for this stage of the analysis; this accounts for the slightly larger sample size than that described in Results of the case note review). The admissions of 14 (6.7%) patients were classified by our two palliative medicine consultants as potentially avoidable. Double coding of a random sample of 15% of the notes indicated high levels of agreement between the consultants, using the kappa measure of chance-corrected agreement (kappa = 0.792, n = 30).

Of the 14 patients whose admission was assessed as potentially avoidable, seven were male and seven were female. The median age of the patients was 84 years (range 75–97 years). Cancer was the primary diagnosis for 6 out of the 14 patients; three patients had a primary diagnosis of stroke; and the other patients had a primary diagnosis of encephalopathy, end-stage renal failure, Alzheimer’s disease, general frailty or hypertension. Half of the patients lived in nursing or residential care. Of the remaining patients, 50% lived alone and 50% cohabited. Most patients (n = 12) were admitted to hospital ‘out of hours’ (outside 0900–1700, Monday–Friday). Reasons for admission to hospital were confusion/general deterioration (n = 5), symptom control (n = 3), fall (n = 2), stroke (n = 2), urinary tract infection (n = 1) and intra-abdominal catastrophe (n = 1).

The mean cost of a potentially avoidable admission was estimated to be £2595 (range £451–£5363), based on the HRG tariffs assigned to each admission by the Sheffield Teaching Hospitals coding team. The distribution of costs is shown in Figure 8. The costs fall into three broad groups: < £1000 (n = 4), between £1000 and £4000 (n = 5) and > £4000 (n = 5). We can therefore estimate that the total potentially avoidable hospital cost from potentially avoidable admissions for the period of the survey was £36,334. The mean length of stay, based on the HRG codes assigned to these admissions, was 16.7 days.

FIGURE 8. Distribution of estimated costs of potentially avoidable admissions.

FIGURE 8

Distribution of estimated costs of potentially avoidable admissions.

The most commonly recommended alternative place of care for patients was a nursing home (n = 10). In addition, it was considered that three patients could have been appropriately cared for in a hospice, and one in their own home. We used the same estimate of average length of stay in these alternative places of care as that estimated for length of hospital stay (16.7 days). The overall cost of alternative places of care based on this same length of stay was estimated to be £34,807 (Table 11).

Taking into account the avoided hospital costs and the cost of providing support in alternative locations, the estimated economic impact is a potential cost saving of £1527 across both hospitals for the period of the survey. There were 1359 inpatients in the two hospitals over the survey period. This accounted for 0.9% of the total admissions over the year. Assuming that the proportion of potentially avoidable admissions identified during the survey period is indicative of the number who would be identified over the course of a year, the potential annual cost saving for the two hospitals can be estimated at just under £180,000. If the cost perspective is restricted to NHS and PSS costs, only the cost of avoided hospital admissions remains unchanged; the cost of alternative care provision falls to £15,141. Based on a NHS and PSS cost perspective, then, the potential economic impact is predicted to be a cost saving of £21,193 for the census period or £2.5M per annum for the two hospitals.

Discussion

Extent of palliative care need

Our results indicate that, according to the GSF prognostic indicator guide, over one-third of hospital inpatients (36.0%) meet the criteria for palliative care need. This figure is substantially higher than other estimates of palliative care need in the acute hospital population. A French survey in 1999 reported that only 13% of total hospital beds were occupied by palliative care patients.123 In a census undertaken in 2001, Gott and colleagues124 reported that 23% of hospital inpatients were identified as having palliative care needs. A more recent study in 201122 reported that just 9.4% of hospital patients in Belgium were identified as having palliative care needs (although this study excluded intensive care units and palliative care units). All of these studies used the subjective judgement of generalist medical and nursing staff to identify patients with palliative care need, rather than an objective measure based on diagnostic criteria, as used in this study. Our results show that, when using a systematic and objective measure, the percentage of patients with identified needs is much higher and represents a substantial proportion of the inpatient population.

Lack of consensus between medical staff, nursing staff and Gold Standards Framework prognostic indicators

One of the most significant findings from this survey is the lack of concordance between medical staff, nursing staff and GSF prognostic indicators regarding the identification of patients with palliative care needs. Although it must be acknowledged that medical and nursing staff were using a different definition of palliative care need than that in the GSF, the Canadian definition was selected on the basis that it is one of the broadest and most inclusive definitions, and is not restricted to particular diagnostic groups. Despite this, medical and nursing staff identified far fewer patients with palliative care needs than the GSF (15.5% and 17.4%, respectively, vs. 36.0%). Significantly, for the majority of patients who met GSF criteria for palliative care need (65.9%), there was no evidence of adoption of a palliative care approach.

Even amongst patients who were expected to die within 12 months, recognition of palliative care need was inconsistent. Medical and nursing staff judged that less than half of the patients they expected to die within 12 months had palliative care needs. This is despite the ‘12 months’ question constituting a key component of GSF prognostication and being advocated in policy such as in the End of Life Care Strategy for England.5 Data from the SPARC tool for self-assessment of palliative care need indicate that, of the 185 patients identified with palliative care needs according to GSF criteria, the majority (83.2%) had problems that ‘warranted immediate attention by an attending clinician’. Despite this, agreement between medical and nursing staff and patients was very poor regarding which patients had palliative care needs.

The identification of patients with palliative care needs presents a recognised challenge.2,89,114 Recent policy5 recommends that health professionals should be trained to identify patients approaching the end of life and to recognise when patients are dying. However, there is a lack of consensus regarding how these patients should be identified and this has significant implications for quality of patient care.79,83,125,126

The challenge in agreeing a consensus of definition and identification of palliative care needs has additional implications for generalist palliative care providers. Recent policy and research have sought to engage more effectively with the generalist provider;125,126 however, our survey results show that many generalists are struggling to identify patients who might benefit from palliative care input. Generalist palliative care is increasingly central to hospital-based palliative care provision. Therefore, it is crucial that generalists are provided with opportunities for greater partnership working with specialist palliative care colleagues. More generally, there is also a clear need for a consensus of definition and for standardised validated criteria for the identification of patients with palliative care needs.

Older people with palliative care needs

Data from the survey suggest that older people with frailty conditions constitute a substantial proportion of hospital inpatients with palliative care needs. Although specialist palliative care uptake is low amongst the frail elderly, it is unclear whether a specialist palliative care framework is the most appropriate model for this group. The care and services provided to older people at the end of life may best be provided by generalists such as geriatricians, as part of a comprehensive generalist-led palliative care framework. Given recent concerns about the level of care provided to older people within the acute hospital setting,127,128 priority should be given to considering ways of improving the care that older people receive at the end of life. Improving generalist palliative care to support older patients in the community, improving recognition of palliative care needs amongst older frail patients and implementing models of palliative care that are appropriate for older patients at the end of life are key priorities that need to be addressed.

Extent of transitions to palliative care

Although UK policy5 advocates an early and phased transition to a palliative care approach for any patient thought to be within the last 12 months of life, our findings indicate that only one-third (33.3%) of patients with identified palliative care needs showed evidence of any such transition. Moreover, the majority of these were identified as having made a transition by virtue of having a DNAR order in place and, although a DNAR order prevents cardiopulmonary resuscitation in the event of cardiac and/or pulmonary arrest, it does not presuppose that any other treatments or interventions that the patient receives will be palliative in intent.

The odds of a transition to palliative care were multiplied by an estimated 5.1 for patients with a cancer diagnosis, by 8.0 for a stroke diagnosis and by 2.6 for a dementia diagnosis. It is well recognised that patients with a cancer diagnosis are more likely to receive specialist palliative care than patients with non-malignant disease.5 Our results are therefore interesting in indicating that patients with a diagnosis of stroke are most likely to have made a transition to palliative care. A number of policy and educational factors may have contributed to this finding. These include the Royal College of Physicians’ guidelines for stroke129 and the DoH’s Stroke-Specific Educational Framework,130 which underlines the importance of assessment and management of end-of-life care. In the case of the dementia finding it is possible to speculate on the impact of recent recommendations that NHS hospital policy should apply the principles of palliative care to patients with dementia.26,131

However, National Institute for Health and Care Excellence (NICE)/Social Care Institute for Excellence guidelines26 identify that cardiopulmonary resuscitation may not be effective in the case of cardiopulmonary arrest for people with severe dementia. These data may therefore be an artefact of NICE guidance as opposed to a genuine shift towards appropriate palliative transitions for people with dementia.

Guidance from the British Medical Association, the Resuscitation Council (UK) and the Royal College of Nursing132 indicates that, regardless of diagnosis, advance care planning should occur alongside the implementation of a DNAR order. Our data indicate that this is not the case in acute hospitals in England. Indeed, no documented evidence of advance care planning was found for this sample of 183 patients with palliative care needs according to GSF criteria. Various barriers to advance care planning have been identified in the literature103,133 and advanced communications skills training programmes such as Connected have been initiated across some clinical settings (mandatory in oncology settings), including acute hospitals, to address these. Our findings lend weight to the need to address the gap between policy promotion of advance care planning and current practice. They also indicate a need to ensure that any such discussions are recorded in clinical notes, both to facilitate clinical decision-making and continuity of care and to facilitate future audit and research in this area.

There are no recognised definitions of what constitutes a ‘transition to palliative care’, despite this concept being widely used in UK policy.5 Capturing the timing and presence of a shift in care regime of this nature is inherently problematic, particularly given that there is evidence to suggest that end-of-life care discussions between clinical teams and patients and their families go unrecorded.134 In addition, notions of phased transitions, incorporating elements of both palliative care and curative care, can further complicate the identification of this shift. In the absence of any formal criteria for identifying a transition to palliative care, we defined a transition on the basis of findings from our earlier qualitative research phase with health professionals. However, it is recognised that the list of indicators used in this study may not be comprehensive and may require validation, and this represents a limitation of this study.

Patient symptom burden

A number of variables were shown to be significant predictors of both physical symptom burden and psychological symptom burden. Patients with heart failure were less likely to have high physical symptom burden, whereas those with dementia were more likely to report high levels of both physical symptom burden and psychological symptom burden. These data provide further evidence of elevated levels of physical symptoms amongst dementia patients, requiring interventions of a supportive and palliative nature, and add to an existing literature.135

Female sex was shown to be a significant predictor of psychological burden. Although consistent with primary care studies and other evidence on common mental disorders and sex,136 this finding is at odds with previous evidence in relation to psychological difficulties at the end life, which would suggest that the prevalence amongst male patients is higher.137 A further predictor of psychological burden was the existence of three or more comorbidities. The relationship between multiple conditions and poor psychological status has been demonstrated in community studies.138 Studies focusing on those patients eligible for palliative forms of care are limited to the relationship between disease-specific conditions, comorbidities and psychological distress. The development of new comorbidities is associated with readmission of palliative care patients.139

Dementia is again implicated as a significant predictor of psychological burden (OR 2.88) and this adds further credence to the use of palliative regimes in providing care and treatment to address psychological needs for this vulnerable patient group.140 Furthermore, it has been demonstrated on numerous occasions that this group of patients faces a number of challenges in accessing palliative and supportive regimes of care and that these challenges are both cultural and organisational.141,142 These data suggest that, in addressing the complex physical and psychological needs of an ageing population, care teams will be increasingly required to adapt integrated palliative approaches to a cognitively frail hospital population.

Economic impact of potentially avoidable hospital admissions

The total cost of hospital admissions in the last year of life for adults admitted with a primary diagnosis indicating palliative care need has been estimated to be in the region of £1.3B.117 A lack of timely access to services in the community may result in people with palliative care needs being unnecessarily admitted to hospital.121 It has been suggested that, by improving or expanding community services to allow more people to be cared for and to die at home, there is the potential for a proportion of hospital costs to be avoided.5 In 2010, the DoH reported that high-quality community-based services cost no more, and can cost less, than hospital-based care.77 However, a review126 conducted as part of this study found that the evidence base from the UK was presently too limited to support the case for offsetting the additional costs of providing high-quality community support through a reduction in hospital admissions for this patient group.

Only 7% of hospital admissions of patients identified as having palliative care needs were classified as potentially avoidable. The potential cost saving of avoiding these admissions and supporting patients in alternative places of care in the two locations under study was estimated to be just under £180,000 per annum. The proportion of admissions identified as potentially avoidable was low relative to the proportions reported in two recent UK studies.79,83 This difference is most likely attributable to the fact that, in our study, not only were data relating to admission and patient characteristics such as comorbidities, age and living arrangements considered, we also took into account the availability of local services. If local services were known to be inadequate to support the patient in the community, then the admission was considered appropriate. In contrast, Abel and colleagues79 based their retrospective case note review on the assumption that the End of Life Care Strategy for England5 had been fully implemented and that local services were always available and had capacity. Employing this method, these researchers classified one-third of all deaths in hospital as avoidable, suggesting that they could have occurred at home. The second study was conducted by the Balance of Care Group83 at a hospital in Sheffield and used a similar ‘blue sky’ approach whereby researchers assumed that alternative community facilities were always available and had capacity. In this similarly retrospective study, 40% of admissions for patients surveyed who died in hospital were considered to be inappropriate. The fact that both of these studies adopted a ‘blue sky’ approach to the availability and capacity of alternative places of care means that both face the issue of feasibility. Equally, the fact that both studies undertook a retrospective analysis using data collected after death means that their researchers were judging whether the admission was avoidable given the ‘full story’, whereas our clinicians were exercising their judgement from information available at the point of admission.

Although the 7% of hospital admissions seen as avoidable in our study may appear low, it does reflect the lack of appropriate alternative services to hospital admission in the two study sites for palliative care patients.

Our exploratory analysis of the economic data estimates a mean cost per avoided admission of £2595. Our estimate is lower than that reported by both Abel and colleagues79 and the Balance of Care Group83 and may have resulted in an underestimation of the cost savings generated by avoiding admissions. The difference between the estimates cited in these two studies and that calculated in our study may be attributable, at least in part, to limitations in our costing data. HRG codes were assigned to our patients using a more limited data set than would ordinarily be available. Also, because we did not have length-of-stay data, we were unable to include excess bed-day payments, which Abel and colleagues79 did include in their calculations.

Differences in the patient mix under consideration in each of the studies may also contribute to cost differentials. The adoption of a ‘blue sky’ scenario in the studies by Abel and colleagues79 and the Balance of Care Group83 would have resulted in a greater proportion of patients with more complex and, crucially, more expensive needs having their admissions categorised as avoidable.

Enabling more people with palliative care needs to be cared for and to die at home or in other community settings may result in a proportion of hospital costs being avoided. However, a clearer understanding of the proportion of hospital admissions that could be avoided and the economic impact of avoiding such admissions is needed. Further research is required to explore the relationship between admissions deemed avoidable given the situation at the point of admission and those deemed potentially avoidable in a hypothetical ‘blue sky’ scenario – and to demonstrate the feasibility of avoiding such admissions in clinical practice. In addition, more robust estimates of the cost of supporting patients in the community are also needed, in terms of both the proportion of patients requiring different types of care and the costs associated with such care.

Limitations

Although this study provides important evidence relating to palliative care in acute hospitals, certain limitations must be acknowledged. Although a wide range of experienced health professionals from primary and secondary care, and from specialist and generalist palliative care backgrounds, were asked during the focus group phase (see Chapter 4) to identify indicators of a palliative care transition, we accept that the list of indicators used in this study may not be comprehensive and may require validation. The GSF was developed as a tool for use in primary care and has to date received no formal validation in the hospital setting. Criticisms of the GSF include that it is a poor predictor of mortality; therefore, its use as a tool for identifying patients with palliative care needs in hospital should be further explored. However, amongst the 185 patients identified as meeting at least one GSF criteria, the subjective scores on the SPARC questionnaire suggest that this group had a high level of palliative care need. Validation of the GSF is now warranted by comparing GSF criteria, self-assessment of palliative care need and subsequent survival.

A further limitation that must be acknowledged is the relatively low patient response rate: only 37.8% of the total inpatient population agreed to participate and provided a complete data set. There is also a probable response bias as a result of the self-selected nature of the patient sample. However, as the overwhelming reason given for non-participation was that patients felt too ill, we believe that our sample constituted the ‘most well’ of the inpatient population. As such, the findings presented here may underestimate the true incidence of palliative care need in the acute hospital setting.

In 23 cases, consultees completed questionnaires on behalf of patients who lacked capacity to consent, and responses given by consultees may not be accurate. Therefore, caution is required in interpreting findings from the questionnaire responses and further research should seek to compare self-assessment and consultee assessment measures to explore consensus.

Copyright © Queen’s Printer and Controller of HMSO 2013. This work was produced by Gott et al. under the terms of a commissioning contract issued by the Secretary of State for Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK.

Included under terms of UK Non-commercial Government License.

Bookshelf ID: NBK259458

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