A systematic review of needs-based triggers for palliative care for early referral of older people with non-cancer conditions

doi:10.21203/rs.3.rs-1609702/v1

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Research Article

A systematic review of needs-based triggers for palliative care for early referral of older people with non-cancer conditions

https://doi.org/10.21203/rs.3.rs-1609702/v1

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published 09 Mar, 2023

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Background: Older people with non-cancer disease are less likely to be referred to palliative care services due to the inherent uncertain disease trajectory and a lack of standardised referral criteria. For older people with non-cancer conditions where prognostic estimation is unpredictable, needs-based criteria are likely more suitable. Eligibility criteria for participation in clinical trials on palliative care could inform a needs-based criteria. This review aimed to identify and synthesise eligibility criteria for trials in palliative care to construct a needs-based set of triggers for timely referral to palliative care for older people severely affected by non-cancer conditions.

Methods: Systematic review. Data sources were Medline, Embase, CINAHL, PsycINFO, CENTRAL, and ClinicalTrials.gov. were searched in September 2018 as well as hand searches. We included randomised controlled trials, including cluster randomised, pilot, and feasibility trials. We selected studies that reported the set of triggers for palliative care involvement for older people with non-cancer conditions, where >50% of the population was aged >65 years. The methodological quality of the included studies was assessed using the Cochrane Collaboration's tool for assessing risk of bias.

Results: 16 randomised controlled trials out of 6,732 papers were identified. We identified six major domains of trial eligibility criteria in three categories, time-based, needs-based, and medical history-based criteria. Needs-based criteria were composed of symptoms, functional status, and quality of life criteria. The major trial eligibility criteria were diagnostic criteria (n = 15 [94%]), followed by physical and psychological symptoms, medical history-based criteria, respectively (n = 9 [56%]).

Conclusion: For older people with non-cancer conditions, decisions about providing palliative care should be based on the present needs related to symptoms, functional status, and quality of life. Future research should investigate if the set of needs-based criteria can be used in clinical care to identify older people with non-cancer conditions likely to benefit from palliative care and acceptability of the referral criteria for older adults and their families.

Palliative Care

Aged

Systematic Review

Referral and Consultation

Inequities in the provision of palliative care remain globally, whilst palliative care should be available to all who need it regardless of their diagnosis [1]. The current global ageing and the changes in the prevalence of diseases imply that the majority of people needing palliative care worldwide is older people living with non-cancer conditions [1, 2, 3, 4]. However, there is consistent evidence that older people with non-cancer disease experience inequitable access to palliative care with low rates of referral or late referral in the last days or weeks of life [5, 6], such as in dementia [7] and heart failure [8].

There are several major barriers to referral in patients with non-cancer conditions. Ahmed, et al., in their systematic review, reported that one of the barriers to access and referral to palliative care is ‘a lack of national standardised referral criteria’ for screening patients with chronic non-cancer disease regarding their need for palliative care [9]. O'Leary, et al. showed that the highest barrier perceived by specialist palliative care (SPC) service providers was ‘the unpredictable non-cancer disease trajectory’ [10]. In primary care settings, the uncertainty of the illness trajectory was also identified as a barrier to effective primary palliative care provision for non-cancer patients [11]. As a result, in clinical practice, key triggers or prompts for older people with non-cancer conditions to access palliative care are based on variable professional opinions or experiences [12, 13]. This means referral triggers are typically informed by differences in education, interest, and understanding on the intended outcomes of palliative care.

Referral criteria are needed to address the inequity of access to palliative care for older people with non-cancer conditions. A systematic review looking at eligibility criteria for trials to inform triggers for outpatient palliative cancer care showed that there were six recurrent themes for referral, two time-based: cancer trajectory and prognosis and four needs-based criteria: physical symptoms, performance status, psychosocial distress, and end-of-life care planning [12]. As for non-cancer patients aged over 65 years, Coventry et al. explored predictor variables that could aid clinicians’ prognostic estimation [5]. Although these prognostic models attempted to estimate survival of < or = 6 months, it was difficult to predict accurately ≤ 6 months survival.

The inherent uncertain disease trajectory for older adults with non-cancer conditions requires the provision of palliative care to be based upon need, rather than time-based criteria, such as disease trajectory and prognostic criteria [14, 15]. However, there has been no systematic review of referral criteria based on palliative care needs for older people with non-cancer conditions. Eligibility criteria for participation in clinical trials on palliative care could inform a needs-based criteria for palliative care.

Aim

This systematic review aimed to identify and synthesise eligibility criteria for trials in palliative care to construct a needs-based set of triggers for timely referral to palliative care for older people severely affected by non-cancer conditions.

Study design

A systematic review. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [16].The methodological quality of the included studies was assessed using the Cochrane Collaboration's tool for assessing risk of bias. The protocol was registered in PROSPERO in November 2018 (CRD42018095, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42018095845845). We were not required to seek an institutional ethics approval because we only used publicly accessible documents.

Data sources and searches

Relevant articles were identified from six electronic searches: MEDLINE (Ovid), EMBASE (Ovid), CINAHL (EBSCOhost), PsycINFO (Ovid), the Cochrane Central Register of Controlled Trials (CENTRAL), and ClinicalTrials.gov. Search strategies were informed by previous systematic reviews related to palliative care and older people [12, 13, 17]. A full search strategy can be seen in Supplementary Information (Additional file 1). All searches were conducted from database inception to September 2018. We supplemented the electronic searches with reference chaining and citation tracking, and handsearching two palliative medicine textbooks [18, 19] and recent conference abstracts [Research Congress of the European Association for Palliative Care (EAPC), 2018]. All identified studies were managed in Mendeley. There was no language restriction in the selection of studies.

Eligibility criteria

Types of studies:

We included randomised controlled trials (RCTs), including cluster randomised trials, pilot, and feasibility trials. Feasibility trials were included, as intention is to evaluate if they can recruit patients to the trial using the stated eligibility criteria. We excluded non-randomised controlled studies to reduce selection bias and retain focus on referral criteria into a trial. We included unpublished articles, but excluded descriptive studies, editorials, commentaries, letters, and dissertations.

Types of participants:

We included adults (aged ≥ 65 years) severely affected by chronic non-cancer illness, including chronic heart failure (CHF), chronic obstructive pulmonary disease (COPD), chronic kidney failure, dementia, cirrhosis of the liver, and stroke. These conditions can cause considerable distressing symptoms and concerns [20]. Receipt of palliative care is shown to relive suffering [21, 22].We included studies where > 50% of the population was aged > 65 years and > 50% of the population were people with non-cancer conditions.

Types of interventions:

We included palliative care trials to identify individuals who could benefit from palliative care. Specialist and general palliative care interventions were included that aimed to promote quality of life for adults aged older adults ≥ 65 years severely affected by non-cancer conditions. We defined a palliative care intervention as a model or service of palliative care, not a discrete aspect of palliative care, such as oxygen therapy. We defined a palliative care model or service as comprising four key elements [23, 24, 25, 26], namely:

1. All levels of palliative care in any setting:

We referred to the model of a three-level structure: palliative care approach in all settings, general basic palliative care, and specialist palliative care with adequate skills for each level [27]. All study settings were included: community health services, including clinics and health centres, outpatient and ambulatory care settings, and inpatient units.

2. An intervention providing direct palliative care to older people:

Interventions that did not directly deliver care to patients were excluded (e.g., interventions to caregivers, education programs to healthcare professionals, or evaluations of assessment tools). We considered a palliative care service intervention if the authors described it as 'palliative' anywhere in the manuscript.

3. An intervention had multi-component services:

A palliative care service is a multidimensional and holistic approach to meet the physical, psychological, social, and spiritual needs of patients. Interventions that delivered only one component of palliative care (e.g., medication, psychotherapy, complementary therapy, decision aid) were not considered as palliative care service.

4. An intervention was provided by a multidisciplinary team:

We defined 'palliative care services' as multidisciplinary services providing comprehensive care aiming at different physical and psychosocial components of palliative care. We excluded interventions provided by only one professional (e.g., nursing intervention).

Outcome:

Types of outcome measures were not restricted. We excluded trials that focused on solely economic evaluation as a primary outcome.

Study selection and data extraction

The review author A.K. screened and assessed the identified titles and abstracts according to the inclusion criteria, followed by assessing all relevant full-articles by A.K and E.A.D.P, independently. Disagreements were resolved by consensus and discussed with C.J.E. The inter-rater agreement and inter-rater reliability between the first author A.K. and E.A.D.P were assessed with Cohen's Kappa Coefficient (κ statistic) by IBM SPSS Statistics 24. The selection process was presented in a PRISMA flow chart (Figure 1) [16]. The PRISMA guideline [16] informed the data extraction detailing trial eligibility criteria, target population, impact on clinical outcome, and stated limitations, study design, study aim, including intervention, participant eligibility criteria, participant characteristics, screening to recruitment rate and main outcomes.

Quality appraisal of included studies

The author A.K assessed the risk of bias in all included RCTs, as described in the Cochrane Handbook for Systematic Reviews of Interventions [28]. The Cochrane Risk of Bias assessment tool is composed of the following seven domains of bias: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias. The summary judgements of the level of risk of bias for each domain are presented in Table 1. We used RevMan 5.375 for tabulating a table of risk of bias and categorised them as, ‘low risk’, ‘high risk’, or ‘unclear risk’. The domain ‘blinding of participants and personnel’ was excluded when generating summary judgements as it was impossible to blind participants in a trial of palliative care service intervention.

If a trial was judged to be of low risk of bias on all of the domains other than ‘blinding of participants’, it was concluded to have a low summary risk of bias. If a trial was judged to have a high risk of bias on any of the domains other than ‘blinding of participants’, it was decided to be a high summary risk of bias, as recommended by the Cochrane Collaboration Handbook (Section 8.7.a) [29]. A trial was judged to be an unclear summary risk of bias if unclear risk of bias on one or more domains and nothing high risk of bias on any of the domains.

Data analysis and synthesis

We sought to identify and collate eligibility criteria and appraise what patterns of eligibility criteria were successful in terms of recruitment, attrition, attaining sample size, and effect on the primary outcome.

Data analysis sought to appraise the applicability of the eligibility criteria to identify patients likely to benefit from receiving palliative care. Eligibility criteria were summarized by frequency counts of domains and synthesized by intended sample size, attrition rate, causes of attrition, and limitation that reflected on the eligibility.

To assess the recruitment, we appraised whether: 1) the study recruited the relevant population to answer the study aim, 2) the actual sample size was larger than the intended sample size determined by sample size calculation, and 3) the explanation for revision of the target sample size was given.

We assessed the attrition rate in accordance with the implementation of sample size estimation, cause of attrition, and anticipated attrition rate. We used the MORECare classification of attrition to describe causes of attrition: attrition due to death (ADD), attrition due to illness (ADI), and attrition at random (AaR) [30]. While there is no standardised level of loss to follow-up which attrition related bias was identified as a problem, Schulz and Grimes noted that the readers should be concerned about the possibility of bias when the attrition rate was 20% or greater [31]. However, the weighted average attrition across palliative care trials involving adults with serious illness and increasing nearness to end of life in a systematic review was 29% [32]. For example, a review of interventional palliative oncology trials stated that the attrition rate was 26% for the primary endpoint and 44% for the end of the study [33]. Therefore, we considered high attrition rate when the rate was more than 25%.

We assessed whether there was statistically significant difference on primary outcomes between intervention and control groups and the effect size. Because the timing of outcome measurement would influence the attrition rate and the effect on outcomes, we also consider the impact of length of intervention and time points of data collection.

Study selection

The electronic search strategy identified 6,720 references. And additional 12 papers were found by hand searching and citation tracking. After removing duplicates, 5,040 studies were screened at title and abstract, and 38 assessed as full-text articles. 16 met eligibility (11 studies identified by electronic searches and five from hand search) [34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49].The process and the reasons for exclusion are reported in the flowchart (Fig. 1) [50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71].All eligible articles were written in English.

Quality appraisal

Only three studies were considered low risks of bias. Nine studies had high risks of bias, mainly due to incomplete outcome data. Four studies were assessed at unclear risks of bias because of unstated data and lack of information. The risk of bias table and graph are presented in Supplementary Information (Additional file 2). The average attrition rate was 24 %, ranging from 0% to 52%. The major cause of attrition was death. Ten papers stated that small sample size was one of the limitations. What we valued more than attrition rate when assessing incomplete outcome data was advance estimations of attrition, descriptions of reasons for missing data, and whether they integrated these into sample size calculation.

Study characteristics

This review included 16 RCTs written in English. Most studies were conducted in US. This is important to understand the context of the work and the applicability of the proposed triggers for which settings. The first study was conducted in US in 2000 [34]. (Table 1)

Study design

We included 14 phase Ⅲ RCTs and two feasibility trials. The 13 parallel RCTs compared the palliative care intervention with usual care. Three studies used fast-track design and compared a fast-track group with a waiting list group. Higginson et al. [41] used a parallel group fast-track trial design. Finally, four studies used a mixed methods trial design [38, 40, 41, 42].

Participants

The studies included 2,666 participants ranging from 14 to 517 per study [38, 39]. The mean age was 72.4 years and ranged from 65.5 years with heart failure [47] to 84.8 years with dementia [34]. Participants, were 55.2% female, ranging from 21.3%[47] to 81.8% [34]. Six studies described the ethnicity of the participants; around 62% of participants were Caucasian, followed by African Americans.

In the included 16 papers, seven were conducted with patients with CHF [40, 43, 44, 45, 46, 47, 49]. Five studies [35, 36, 37, 39, 41] included multiple diseases, three included both cancer and non-cancer conditions [36, 37, 41], one included both CHF and COPD [35], and one stated non-malignant disease [39]. Two included participants with respiratory disease, one with COPD/chronic obstructive airway disease (COAD) [38], one with interstitial lung disease (ILD) [42]. Other diagnoses were neurological diseases, one with dementia [34], and one with Parkinson’s disease (PD) [48].

Intervention and control

Seven different models of home palliative care in ten studies were identified [35, 36, 38, 39, 40, 41, 42, 45, 48]. All seven models were composed of multi-components of palliative care intervention, such as symptom management, education of self-management of disease, end-of-life discussions, case conferences, documentation, regular home visits, or a telephone hotline. Five studies [34, 37, 43, 46, 49] provided inpatient care and one [47] implemented outpatient palliative care services. Inpatient palliative care services in five studies were developed based on the standard referral process of the hospital palliative care team or developed for the trial. As for control group, usual care differed across studies due to the wide variety of health systems and local service provisions. Several studies followed national or government guidelines.

Primary outcomes

Seven of the 16 studies set quality of life (QOL) as a primary outcome, and the measures varied (Table 1). Four used disease-specific QOL measurements, two used HF-specific QOL measures; The Kansas City Cardiomyopathy Questionnaire (KCCQ), one used a QOL domain in the Chronic Respiratory Disease Questionnaire (CRDQ), one used the 39-Item Parkinson's Disease Questionnaire (PDQ-39).

Table 1

Characteristics of Included Studies

Author (year),

Country

Study design,

Study aim (including the intervention)

Study setting

Mean age (SD/range),

Gender (female %),

Diagnosis

Primary outcome

Effect on primary outcome

Risk of bias

Ahronheim [34]

(2000), US 

Parallel RCT,

To determine if a palliative care approach could be implemented for patients with advanced dementia and if this approach could enhance patient comfort.

hospital

I/C=83.9 (range 63-99)/85.6 (72-100), I/C=77.1/86.3%, Dementia

･Mean number of hospitalizations

･Average length of stay, mortality

No significant difference

clear

Aiken [35] (2006), US 

Parallel RCT,

To document outcomes of an RCT of the PhoenixCare (home-based palliative care) demonstration program and coordinated care/case management for seriously chronically ill individuals who simultaneously received active treatment.

home

I/C=68(14)/70(13),

I/C=58/70%,

HF, COPD

･Self-management of illness

･Preparation for end of life

･Physical and mental functioning

･Service use

Significant higher scores on the SF-36™ Physical functioning score at the 9-month point. (p<0.05)

High

Brumley [36] (2007), US 

Parallel RCT,

To determine whether an in-home palliative care intervention for terminally ill patients can improve patient satisfaction, reduce medical care costs, and increase the proportion of patients dying at home.

home

74 (12.0),

49%,

Cancer, CHF, COPD

･Satisfaction with care

･Use of medical services

･Site of death

Greater improvement in satisfaction with care at 30, 90-day.

(OR53.37, 95%CI:1.42–8.10)

(OR53.37, 95%CI:0.65–4.96)

clear

Gade [37]

(2008), US 

Parallel RCT,

To measure the impact of an interdisciplinary palliative care service on patient satisfaction, clinical outcomes, and cost of care for 6 months posthospital discharge.

hospital

I/C=73.6(12.6)

/73.1 (13.2), I/C=59%/51%,

Cancer, CHF

･Symptom control

･Levels of emotional/spiritual support

･Patient satisfaction

Higher mean satisfaction with hospital care and providers.

(p >0.001)

High

Farquhar [38] (2009), UK 

Phase2: fast-track RCT,

To test the feasibility of single-blinding in a fast-track pragmatic RCT of BIS versus standard care for patients with a different non-malignant disease (COPD) and their informal carers.

home

Median 69 (range53-80),

39%,

COPD/COAD

･Distress due to breathlessness measured using a VAS (0-10)

Not stated

Low

Farquhar [39](2016), UK 

Fast-track RCT,

To establish the effectiveness and cost effectiveness of BIS in advanced non-malignant conditions.

home

F/W=72.3 (10.6)

/72.2 (9.4)

F/W=36/42%,

Non-malignant disease

･Distress due to breathlessness measured using an NRS (0-10)

Non-significant greater reduction.

(–0.24, 95% CI: –1.30-0.82)

Low

Brännström [40] (2014),

Sweden 

Parallel RCT,

To evaluate the effects of the Person-centred and integrated CHF and palliative home care intervention on symptom burden, QOL, and functional classes compared with usual care.

home

I/C= 81.9(7.2)

/76.6 (10.2),

I/C= 27.8 %/30.6%,

･Symptom burden

･Health-related QOL

･Functional classes

Improvement in total symptom score and HRQQL.

(p <0.05)

High

Higginson [41](2014), UK 

Parallel group fast-track RCT,

To assess the eﬀectiveness of early palliative care integrated with respiratory services for patients with advanced disease and refractory breathlessness.

home

I/C= 66 (11)/68 (11),

I/C=47/37%,

COPD, cancer, ILD, CHF

･Patient-reported breathlessness mastery

･A QOL domain in the CRDQ

Mastery in the BSS group improved.

(MD: 0.58, 95% CI: 0.01–1.15, p=0.048; ES 0.44) Total QOL improved.

Low

Bajwah [42] (2015), UK 

Phase2: fast-track RCT,

To obtain preliminary information on the impact of a case conference intervention delivered in the home on palliative care concerns of patients and their carers, and to evaluate feasibility and acceptability.

home

F/W=67.1(10.9)

/70.6 (10.3),

F/W=23/33%,

ILD (IPF, NSIP)

･Palliative Care Outcome Scale (POS) (a measure of symptoms and concerns)

Signiﬁcantly greater reduction in total POS between baseline and week 4 for the fast-track group. (ES: −0.7; 95% CI −1.2-−0.1)

High

Sidebottom [43]

(2015), US 

Parallel RCT,

To assess if inpatient palliative care for HF patients is associated with improvements in symptom burden, depressive symptoms, QOL, or differential use of services.

hospital

I/C= 76.0 (11.9)

/70.9 (13.6),

I/C= 52.6 %/42.2%.

Acute HF

･Symptom burden

･Depressive symptoms

･QOL

At 1 and 3 months, larger improvement on all three outcomes in the intervention group after adjustment for age, gender, and marital status.

High

Wong [44]

(2016), 

Hong Kong 

Parallel RCT,

To examine the effects of home-based transitional palliative care for patients with ESHF after hospital discharge.

home

I/C=78.3 (16.8)

/78.4 (10.0),

I/C=56.1%/39%,

Advanced HF

･Count of readmission within 4 and 12 weeks after index discharge.

Signiﬁcantly lower readmission rate at 12 weeks. (intervention 33.6% vs control 61.0% χ2=6.8, p=0.009).

clear

Ng [45]

(2018),

Hong Kong 

Parallel RCT,

To examine the effect of a home-based palliative heart failure program on QOL, symptoms burden, functional status, patient satisfaction, and caregiver burden among patients with ESHF.

home

I/C=78.3 (16.8)

/78.4 (10.0),

I/C=56.1%/39%

End-stage HF

･QOL (McGill QOL Questionnaire-Hong Kong)

Significant improvements in the physical (p=0.011), psychological (p=0.04), and existential (p=0.027) domains.

High

Rogers [46]

(2017), US 

Parallel RCT,

To investigate whether an interdisciplinary palliative care intervention in addition to evidence-based HF care improves certain outcomes.

hospital

I/C=71.9 (12.4)

/69.8 (13.4),

I/C=44%/50.7%,

Advanced HF

･HF-specific QOL (KCCQ)

･General and palliative care-specific, health-related QOL (FACIT-Pal)

Clinically significant incremental improvement in KCCQ and FACIT-Pal scores from randomization to 6 months.

High

Bakelman [47] (2018), US 

Parallel RCT,

To determine whether a symptom and psychosocial collaborative care intervention improves heart failure specific health status, depression, and symptom burden in patients with heart failure.

out

patient

65.5 (11.4),

21%,

CHF

･Patient-reported HF-specific health status measured by KCCQ

Not significant improvement.

clear

Eggers [48]

(2018), Germany 

Parallel RCT,

To identify if an integrated model of care for PD patients has access to PD patients at the end of life.

home

I/C=69.8 (8.4)

/69.9 (7.8),

I/C=31/35%,

･QOL (PDQ-39)

QOL signiﬁcantly improved in the intervention group over a 6-month period. (2.2 points (95%CI: −4.4 - 0.1); p = 0.044)

High

O'Donnell [49] (2018), US 

Pilot RCT,

To determine if early initiation of social worker–aided palliative care (goals of care conversations) would improve prognostic understanding, elicit advanced care preferences, and influence care plans for high-risk patients discharged after HF hospitalization.

hospital

I/C=74.7(11.2)

/69.2(10.2),

I/C=46.1/37.5%,

Advanced HF

･Percentage of patients with physician-level documentation of advanced care preferences

Not significant improvement.

High

Abbreviations:I/C intervention/control, F/W fast track/waiting list, ILD interstitial lung disease, IPF idiopathic pulmonary fibrosis, NSID non-specific interstitial pneumonia, VAS visual analogue scale, NRS numerical rating scale, CRDQ the chronic respiratory disease questionnaire, MD mean difference, SD standard deviation, ES effect size, KCCQ the Kansas city cardiomyopathy questionnaire, PDQ the Parkinson's disease questionnaire, BSS breathlessness support service, BIS breathlessness intervention service, ESHF end-stage heart failure, PD Parkinson's disease, FACIT-Pal the functional assessment of chronic illness therapy-palliative

Summary of eligibility criteria of included studies

Six main domains for eligibility criteria were identified, including diagnostic criteria (n = 15 out of 16 included studies [94%]), symptoms (physical and psychological) (n = 9 [56%]), medical history-based (n = 9 [56%]), prognostic criteria (n = 7 [44%]), functional status (n = 3 [19%]), QOL (n = 2 [13%]), and other criteria (n=3 [19%]). We categorised these domains into three major criteria themes: time-based, needs-based, and medical history-based.

In Table 2, we used the initial letter of each domain to show which category the eligibility trials were categorised. The letter D stands for ‘Diagnostic Criteria’, P for ‘Prognostic’, S for ‘Symptoms’, Q for ‘QOL’, F for ‘Functional Status’, M for ‘Medical History and Treatment’, and O for ‘Other’. The number of domains were calculated by adding the number of domains used in the trial as eligibility criteria. Since some standardised measures covered several domains, we analysed the domain in the measurements and counted the number of domains. For example, Bekelman et al. [47] used a score of HF-specific health status (KCCQ) to assess eligibility. As KCCQ is a reliable and valid measure of symptoms, functional status, and QOL, the number of domains counted was three [72].Table 3 gives an overview of the different criteria and use by respective disease groups.

Time-based criteria

Diagnostic criteria:

Diagnostic criteria was a set of signs, symptoms, and tests for use in routine clinical care to guide the care of individual patients. In the 11 studies that included HF, five studies [35, 40, 44, 45, 49] used the New York Heart Association (NYHA) classification of II-IV [49], or NYHA III-IV [35, 40, 43, 45] Brumley et al. [36] included not only participants with HF, but also COPD and cancer, and used the Palliative Performance Scale to assess disease severity. Rogers et al. [46] measured signs of volume overload in accordance with the HF diagnosis. But, three HF studies [37, 41, 43] used no diagnostic criteria.

Similarly, diagnostic eligibility criteria was used in studies on lung disease and dementia. Aiken et al. [35] in a study on COPD used measures of hypoxemia, oxygen saturation, pO2, and oxygen requirements, and Bajwah et al. [42] on ILD used high-resolution computed tomography of lung or a composite physiologic index. Other four studies on lung disease did not clearly state diagnostic eligibility criteria. [36, 38, 39, 41]. The dementia study [34] used the Functional Assessment Staging Test (FAST) to categorise dementia stage, based on the level of functioning and ability to perform daily living activities [73].

Prognostic Criteria:

Seven studies included prognostic eligibility criteria [35, 36, 37, 40, 44, 45, 46]. The ‘surprise question’ was used in four studies [36, 37, 44, 45]. The question is, “Would I be surprised if this patient died in the next 12 months?”, which has been used to identify patients at a high risk of death who might benefit from palliative care services [74]. Three [44, 45, 46] used HF-specific standardised prognostic measures. Wong et al. [44] and Ng et al. [45]used multi-components of the prognostic indicator guidance to identify end-stage heart failure (ESHF) [75]. The indicators are constituted by three steps, which initiate intuitive surprise questions, followed by general and specific clinical indicators. In the three steps, they used only the last step, heart disease-specific clinical indicators. In the indicators that contain four domains: diagnose, prognosis, symptom, and medical history, the prognostic criteria are the ‘surprise question’ (a patient thought to be in the last year of life). Rogers et al. [46]used the North American Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) risk score which uses clinical information to derive a discharge model for six months risk of rehospitalisation and mortality [76]. The ESCAPE risk score is based on the presence of risk factors such as blood urea nitrogen (BUN), a six-minute walk, sodium, or daily diuretic dosage. According to the total score, the predicted six-month mortality can be shown by a percentage ranging from 5% risk of death to 94% [76].

Need-based criteria:

Focused on three main areas of symptoms, function and quality of life, including:

Symptoms

Over the half of the 16 included studies set an existence of physical/psychological symptoms as eligibility criterion [35, 38, 39, 40, 41, 44, 45, 46, 47]. As for physical symptoms, Aiken et al. [35] included HF or COPD patients suffering from fatigue, palpitation, dyspnoea, or angina with any activity. For participants with HF, Brännström et al. [40] checked the presence of cardiac cachexia with involuntary non-oedematous weight loss ≥6% of total body weight within the preceding 6–12 months, and Bakelman et al. [47] confirmed reporting at least one of the target symptoms of fatigue, shortness of breath, pain, and/or depression. Three studies that provided breathlessness intervention/support service examined whether breathlessness existed in spite of optimisation of the underlying illness [38, 40, 41]. Among them, Higginson et al. [41] used the MRC dyspnoea scale to assess the degree of refractory breathlessness. Only three studies [44, 45, 47] contained psychological symptoms as eligibility criterion.

Functional status

Three studies included criterion that assess functional or performance status in their eligibility [34, 36, 47]. Brumley et al. [36] included the Palliative Performance Scale (PPS) [77]as a modified Karnofsky performance status scale of function to assess the progressive decline of palliative participants and their health conditions. Ahronheim et al. [34] used FAST for systematic examination of the functional changes occurring in patients with dementia. The other study employed KCCQ to assess functional status alongside symptoms and QOL [47].

Quality of Life

Only two trials used QOL for trial eligibility [40, 47]. Bakelman et al. [47] used KCCQ in their trial as a measurement of the patient’s perception of their health status which includes how their heart failure impacts their QOL within a 2-week recall period. Brännström et al. [40] measured QOL using a Visual Analogue Scale (VAS). VAS is commonly used to rate subjective experiences [78].

Medical history-based criteria:

We identified nine articles that included medical history and treatment criteria. Among nine, six were criteria related to repeated unplanned hospital admissions due to the deterioration of illness [34, 40, 44, 45, 46, 49]. The study of dementia by Ahronheim et al. [34] used medical history-based eligibility criteria of hospitalization for acute illness occurred with advanced dementia. However, as many participants died when they were admitted to a hospital, the authors assert this criteria limited study recruitment and attainment of sample size. Treatment-based criteria included previous/current administrative data, such as intravenous therapy support (e.g., diuretics), required diuretic dosing, and results of heart function [35, 36, 47].

Other Criteria:

We found three other criteria which can be considered as psychosocial eligibility. Higginson et al. [41] asked patients their willingness to engage with a breathlessness support service. Farquhar et al. [38, 39] assessed whether patients might benefit from a self-management programme.

Table 2

Comparison of Trial Eligibility Criteria

Author (year)	Trial eligibility criteria (D: Diagnostic criteria, P: Prognostic criteria, S: Symptoms, Q: QOL, F: Functional status, M: Medical history/treatment, O: Others)	N of domains	Intended sample size	Sample / sample size  (attrition %)	Causes of attrition (causes/N of loss)	Limitation that reflected on the eligibility
Ahronheim [34] (2000)	M: Hospitalization for acute illness D, F: FAST 6d or greater	3	Not stated	99/99 (0%)	NA	Sample was small. (Patients should be identified prior to the acute hospitalization)
Aiken [35]  (2006)	D: NYHA IIIB – IV (HF), Oxygen saturations, pO2, oxygen requirements (COPD) P: Expert judgment based on available prognostic data S: Fatigue, palpitation, dyspnoea, or angina due with any activity M: Recent exacerbation (treatment in a hospital within the 3-month prior to enrolment)	4	Post-hoc calculation	112/192 at 3-month (42%), 92/192 at 6-month (52%)	Medical causes (death, hospice, skilled nursing facilities)	The prognostication criteria were limited. One third of all participants died or transferred to hospice in the first 3 months.
Brumley [36]  (2007)	D: CHF, COPD, cancer. (severity was assessed by PPS), P: Surprise Question F: PPS, M: Visited ED or hospital at least once within the previous year of enrolment	4	300	297/310 (4%)	Died before intervention (8/13), Withdraw (5/13)	Not stated about the eligibility criteria.
Gade [37]    (2008)	D: Life-limiting diagnosis (no criteria) P: Surprise Question	2	550	512/517 (1%)	Withdrew prior to the intervention.	Not stated about the eligibility criteria.
Farquhar [38] (2009)	D: COPD/COAD (no criteria) S: Breathlessness in spite of optimisation of underlying illness O: Patients who might benefit from a self-management programme.	3	Phase 2: Maximum of 28	13/14 (7%)	Died  (1/1)	Not stated about the eligibility criteria.
Farquhar [39]  (2016)	D: Non-malignant (no criteria) S, O: Same as the phase 2 trial	3	60	72/87 (17%)	Died (2/15)	Not stated about the eligibility criteria.
Brännström [40] (2014)	D: NYHA III−IV (CHF) At least one of the following: P: <1 year (no criteria), S: Cardiac cachexia - weight loss, Q: QOL (VAS) M: Hospitalization of worsening HF that resolved with the IV, continual IV support	5	72	60/72 (17%)	Died (12/12)	Patients with a high number of severe co-morbidities lead small sample
Higginson [41] (2014)	D: Cancer, COPD, CHF, ILD, MND (no criteria) S: Refractory breathlessness (MRC scale) O: Willing to engage with BSS	3	110	82/105 (22%)	Died (4/23), withdrew (5/23), illness (8/23), unable to contact	Eligibility criteria prevented extrapolation of study results to patients in the last month of life.
Bajwah [42]  (2015)	D: High resolution CT or composite physiologic index scores (ILD).	1	Phase2: 52	35/53 (34%)	Died (7/18), no return of questionnaire but contactable (7/18)	The criteria for excluded patients were not recorded which may have provided valuable information.
Sidebottom [43] (2015)	D: Acute HF (reports from the electronic record)	1	500	143/232 (38%)	Not completed survey, reason unknown (68/89), Died (19/89)	Losses to follow-up
Wong [44] (2016)	Two of the following identified as ESHF by the Prognostic Indicator Guidance D: NYHA (III-IV) P: Surprise Question, S: Existence of physical/psychological symptoms despite optimal tolerated therapy M: Repeated hospital admissions with symptoms of HF (three within 1year)	4	Not stated	68/84 (19%)	Discontinued interven tion (e.g., die) (14/16)	The loss of follow-up was high due to mainly death and deterioration.
Ng [45] (2018)	D, P, S: Same as Wong³⁷ M: Repeated hospitalization (>two in last six months)	4	78	45/84 (46%)	Death, too ill, refusal (29/39)	Small sample due to the subjects being too weak or cognitively impaired.
Rogers [46] (2017)	D: HF with at least 1 sign of volume overload, P: ESCAPE risk score S: Dyspnoea at rest or minimal exertion, M: Hospitalization for acute HF	4	200 →150	84/150 (44%)	Died (43/66)	High mortality and loss of follow-up reflect the difficulty of retaining seriously ill patients.
Bakelman [47] (2018)	S: At least one symptom (fatigue, shortness of breath, pain, depression) F, Q: KCCQ, M: Diuretic dosing, LVEF, BNP, NT pro-BNP	4	312	248/317 (22%)	Deceased (8/69)  Withdraw (8/69)	The missing patient-reported data is similar to other studies of seriously ill populations
Eggers [48] (2018)	D: Parkinson’s disease (no criteria)	1	150	107/150 (29%)	Withdraw (18/43), loss of contact (15/43)	Exclusion criteria (dementia or severe depression) are a serious limitation for the inclusion of late-stage PD.
O'Donnell [49] (2018)	D: NYHA II-IV M: Hospitalization with high-risk features	2	Not stated	31/50 (38%)	Died (19/19)	Small sample size
*Abbreviations:* N number, HF heart failure, CHF congestive heart failure, ESHF end-stage heart failure, COPD chronic obstructive pulmonary disease, COAD chronic obstructive airways disease, ILD interstitial lung disease, MND motor neurone disease, FAST Functional Assessment Staging Tool, NYHA New York Heart Association, ED emergency department, PPS Palliative Performance Scale, IV intravenous, MRC Medical Research Council, VAS Visual Analogue Scale, JVP Jugular Venous pressure, ESCAPE risk score The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness risk score, KCCQ a Kansas City Cardiomyopathy Questionnaire Short Version, LVEF left ventricular ejection fraction, NT pro-BNP N-terminal prohormone level of BNP

Table 3

Summary of Trial Eligibility Criteria by Disease Type

Diagnostic criteria	HF	NYHA II-IV [49], NYHA III-IV [40, 44, 45], NYHA IIIB or IV [36]
	COPD	Oxygen saturations of less than 88%, or baseline pO₂ less than 55, and to be on continuous oxygen [35]
	ILD	End stage idiopathic ﬁbrotic lung disease as judged by either high resolution CT or composite physiologic index scores >50. Clinical status, oxygen requirements, severe PH for too unwell patients [42]
	Dementia	FAST 6d or greater [34]
	Other (no criteria)	Hospitalized with life-limiting diagnosis [37] COPD/COAD (no criteria) [38] Non-malignant disease[39] Advanced disease (cancer, COPD, CHF, ILD, MND) [41] Acute HF (reports from the electronic health record) [43] Parkinson’s disease (no criteria) [47]
Prognostic criteria	General	Surprise Question: Life expectancy of 12 months or less. “Would I be surprised if this patient died in the next 12 months?” [36, 37, 44, 45]
	HF	ESCAPE risk score ≥4 (indicating >50% predicted 6-month mortality) [46]
	HF	ESHF by the Prognostic Indicator Guidance (Hospitalization with at least one of the following high-risk features) [44, 45] 1. Prior hospitalization for HF within 1 year 2. Age ≥80 years 3. CKD (estimated GFR ≥≤ 45 mL/min/m2 177) 4. Systolic Blood Pressure ≤100 mm Hg 5. Serum sodium ≤ 130 mEq/L 6. Cardiogenic Shock (Cardiac Index ≤ 2.0) 7. Serious Non-Cardiovascular Illness (e.g. advanced stage cancer, COPD, or the like)
	Other (no criteria)	Live for up to 2 years, based on expert judgment that drew on available prognostic data [35]
	Other (no criteria)	Life expectancy of <1 year [39]
Symptoms (physical /psycho logical)	General	MRC dyspnoea scale score (refractory breathlessness) [41]
	HF	Symptoms (fatigue, palpitation, dyspnoea, or angina) due with any activity [35]
		Cardiac cachexia (involuntary non-oedematous weight loss ≥6% of total body weight within the preceding 6–12 months) [40]
		Existence of physical/psychological symptoms despite optimal tolerated therapy [44, 45]
		Dyspnoea at rest or minimal exertion plus at least 1 sign of volume overload (JVP >10 cm, peripheral oedema, congestion on chest x-ray) [45]
		At least one symptom (fatigue, shortness of breath, pain, and/or depression) [47]
	COPD	Breathlessness in spite of optimisation of underlying illness [38, 39]
Functional status	General	Palliative performance scale 70% or less [36]
	HF	HF–specific health status (KCCQ score of ≤ 70) [47]
	Dementia	FAST of 6d or greater [34]
QOL	General	QOL (VAS < 50) [40]
QOL	HF	HF–specific health status (KCCQ score of ≤ 70) [47]
Medical history /treatment	HF	Repeated hospital admissions with symptoms of HF (three within 1year [42]/ >2 in last 6 months [45])
		At least one hospitalized episode of worsening HF that resolved with the injection/infusion of diuretics or the addition of other HF treatment in the preceding 6 months and regarded as being ‘optimally treated’ according to the responsible physician [40]
		Need for frequent or continual IV support [40]
		Previously validated administrative data supplemented with data on required diuretic dosing (furosemide ≥80mg/d or equivalent), left ventricular ejection fraction of 40% or less, BNP levels of 250 pg/mL or more, or N-terminal prohormone level of BNP of 1000pg/mL or more [47]
	HF (no criteria)	Hospitalization for acute HF [46] Hospitalization with high-risk features [49]
	HF/COPD	Recent exacerbation (treatment in an ED, urgent care facility, or hospital within the 3 months prior to enrolment) [35]
	HF/COPD	Visited ED or hospital at least once within the previous year of enrolment [36]
	Dementia	Hospitalization for acute illness [34]
Others	General	Patients who might benefit from a self-management programme [38, 39]
Others	General	Willing to engage with willing to engage with short-term home physiotherapy and occupational therapy [41]

Main findings of the study

We systematically reviewed and synthesised the eligibility criteria of 16 RCTs in palliative care. The results inform a needs-based set of triggers for timely referral to palliative care for older people severely affected by non-cancer conditions. Key characteristics for eligibility for older people with non-cancer condition are those who experience refractory symptoms, loss of functional status, or decreased QOL with evidence of potential benefit from palliative care. Eligibility criteria that were ‘successful’ tended to utilize at least one domain of needs-based criteria. Five studies used successful eligibility criteria according to the recruitment, attrition rate, and effect on primary outcomes in each study. [36, 38, 40, 41, 44].

What this study adds

Decisions about informing palliative care should be based on individual needs related to symptoms, functional status, and QOL. Symptom control is a common reason for a palliative care referral, and they are also core domains that patients and families use to judge the care that they receive [79]. However, only one study used standardised measures, MRC dyspnoea scale, to assess symptom control [41]. Four studies[38, 39, 44, 45] measured physical symptoms such as breathlessness in spite of optimisation of underlying illness, though the measurements are not standardised tools. It implies that using of a validated measure for palliative care population is uncommon when considering referral to palliative care.

Symptoms

Comprehensive assessment aligned to philosophy of palliative care is essential to identify patients likely to benefit from receiving palliative care. In this review, eligibility criteria is limited to mainly physical symptoms with little consideration of psychological symptoms e.g. anxiety, depression. Outcome measures of specific physical symptoms such as pain are well developed, but psychological symptoms are liable to be considered less serious than physical symptoms.

Best practice of symptom assessment is patient self-report outcomes for example using patient-reported outcome measures (PROMs/PROs) rather than clinician assessment due to the subjective nature of symptoms [80]. However, considering the illness trajectory and deterioration in physical/cognitive abilities in palliative care populations, reporting by proxies such as relatives or healthcare professionals is important especially for older people [81]. For older people with non-cancer conditions, loss of mental capacity is common with advancing age associated with for example severe dementia and nearness to end of life. Therefore, measures used in palliative care need to be validated for the population and clinical practice, and for both self and proxy reporting [82]. Some outcome measures include a proxy version, for example the Integrated Palliative Care Outcome Scale (IPOS) [83]. This allows for the adjusting of proxy ratings if the patient is not able to complete the measure as their disease progresses.

Functional status and quality of life

Functional status and QOL are important needs-based triggers for older people with non-cancer conditions. Functional status is defined by American Thoracic Society as an individual's ability to perform normal daily activities required to meet basic needs, fulfil usual roles, and maintain health and well-being [84]. Most patients experience progressive functional disability and subsequent health decline during the course of their disease. Moreover, some studies reported that functional status is significantly associated with health-related QOL (HRQOL) in people with non-cancer conditions [85]. It is likely to be used standardised measures to assess functional status based on the results in this review that standardised measurements of functional status are used in three studies [34, 36, 47]. Although disease-specific functional assessment measures can be available in some non-cancer diseases, the Australia-modified Karnofsky Performance Status (AKPS) which is a modified version for palliative care is widely used and appropriate for multiple care settings in palliative care populations.

The main goal of care in palliative care for older people with non-cancer diseases is QOL with provision based on need [15, 23].Quality of life can be defined as a complex, multifaceted construct that requires multiple approaches from different theoretical angles [86]. As quality of life can reflect on unmet need, decline in QOL can be a trigger for referral. In this review, eligibility criteria related to QOL were uncommon. There are few relevant assessment tools addressing functional status and HRQOL for populations with multiple chronic conditions [87].

Willingness to engage with intervention

Psychosocial eligibility criteria were uncommon, limited to views on willingness to engage with the intervention [38, 39, 41]. One of the major differences between palliative care and other fields of healthcare is the holistic approach it takes, including psychosocial and spiritual dimensions in addition to the physical suffering. Willingness to receive palliative care may reflect the patient's preference and could form a needs-based trigger for a referral on preference for palliative care. However, respondents who decide to join a clinical trial may differ in characteristics compared to those who decline. This may cause response bias in a trial and those indicating preference for palliative care, or not, for example low level of health literacy of illness may preclude understanding on benefit of receiving palliative care service and impede individuals’ access to palliative care services. The Health Literacy Skills conceptual framework introduced by Squires et al. [88] illustrates mediators between health literacy and health outcomes. According to the framework, lack of knowledge about available palliative care services means patients do not request or access these services [89, 90]. Educating individuals about the role and function of palliative care, and confirming the willingness to engage with the intervention, may be one of the simplest ways to assess needs-based triggers for a referral on preference for palliative care.

Limited availability of validated assessment tools

A barrier to using individual needs-based triggers for referral criteria is the limited availability of validated and brief standardised assessment tools encompassing symptom severity, functional status, and QOL for older people with non-cancer condition. Whilst generic measures are able to be used on a large range of health and in various health conditions and populations, specific measures specifically developed to measure outcomes in palliative care are more responsive to needs-based triggers than generic outcome measures. Validated comprehensive measures for palliative care are available and used in clinical care, for example Edmonton Symptom Assessment Scale (ESAS) [91], and the IPOS [83]with condition specific measure for dementia and multi-morbidity (IPOS-Dem) [92].They can cover holistic domains such as physical, psychological, social or spiritual dimensions. As palliative care focuses to provide holistic care, an outcome measure to assess palliative care needs for people with non-cancer diseases should ideally cover several of these domains [93].

Implications for further research and practice

The provision of palliative care should be based on needs assessment [94]. Our findings indicate that needs-based criteria are more likely to suit for older people with non-cancer conditions. Decisions about informing palliative care should be based on the present needs related to symptoms, functional status, and quality of life. Our review produced the initial step toward developing standardized referral criteria for clinical practice. Future research should investigate if the set of needs-based criteria can be used in clinical care to identify older people with non-cancer conditions likely to benefit from palliative care and acceptability of the referral criteria for older adults and their families. Suitable needs-based referral criteria should meet the varied needs of people with different illness trajectories and different complexities of need for palliative care [94]. We recommend using measure that encompass symptoms, QOL and functional status. Simple comprehensive measures developed and validated for palliative care population are practical for quick assessment of the palliative care needs, for example IPOS [83] or ESAS [91]. As palliative care needs vary widely, continued assessment of needs-based triggers might be required. Standardised measure that can aid clinicians to assess palliative needs and concerns should be easy to use for all health care professionals and feasible to use under a time constraint in clinical settings.

Strengths and limitations of the study

A key strength of our review is that we analysed trial eligibility criteria without restriction to diagnosis. This intended to identify flexible referral criteria applicable across non-cancer conditions and multimorbidity. However, most participants in the included studies had heart failure. This strengthens the applicability of needs-based set of triggers for this population group, but limits wider application to all older patients with non-cancer conditions. There is great variability among older population aged over 65, compared to any other age group. The impact of heterogeneity of older population aged over 65 with mixed diagnosis on our results should also be considered carefully, though some studies that included mixed diagnosis attempted to reduce the heterogeneity of multimorbidity by identifying disease combinations. More research stratified into age, diagnostic group, number of co-morbidities is needed. Finally, the included studies were predominantly conducted in high income countries in Europe and the US. This limits generalisability to non-Western regions and low-middle income countries.

Our systematic review is the initial step toward developing needs-based standardised triggers for palliative care referral for older people with non-cancer conditions. For older people with non-cancer conditions, decisions about providing palliative care should be based on the present needs related to symptoms, functional status, and quality of life. Future research should investigate if the set of needs-based criteria can be used in clinical care to identify older people with non-cancer conditions likely to benefit from palliative care and acceptability of the referral criteria for older adults and their families.

BIS: Breathlessness Intervention Service

BNP: Brain Natriuretic Peptide

BSS: Breathlessness Support Service

BUN: Blood Urea Nitrogen

CHF: Congestive Heart Failure

CI: Confidence Interval

COAD: Chronic Obstructive Airways Disease

COPD: Chronic Obstructive Pulmonary Disease

CRD: Centre for Reviews and Dissemination

CRDQ: the Chronic Respiratory Disease Questionnaire

CT: Computed Tomography

EAPC: European Association for Palliative Care

ED: Emergency Department

EOL: End of Life

ESAS: Edmonton Symptom Assessment System

ESCAPE risk score: The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness risk score

ESHF: End-Stage Heart Failure

F/W: Follow-up group/ Waiting-list group

FACIT-Pal: The Functional Assessment of Chronic Illness Therapy-Palliative

FAST: Functional Assessment Staging Tool

FEV1: Forced Expiratory Volume in 1 Second

HF: Heart Failure

HRQOL: Health-related quality of life

I/C: Intervention/Control

ILD: Interstitial Lung Disease

IPF: Idiopathic pulmonary fibrosis

IV: Intravenous

JVP: Jugular venous pressure

KCCQ: a Kansas City Cardiomyopathy Questionnaire Short Version

LVEF: Left Ventricular Ejection Fraction

MD: Mean Difference

MND: Motor Neurone Disease

MRC: Medical Research Council

NRS: Numerical Rating Scale

NSIP: Nonspecific Interstitial Pneumonia

NT pro-BNP: N-terminal prohormone level of BNP

NYHA: New York Heart Association

PC: Palliative Care

PD: Parkinson’s Disease

PDQ: The Parkinson's Disease Questionnaire

POS: Palliative Care Outcome Scale

PPS: Palliative Performance Scale

PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analyses

PROSPERO: The International Prospective Register of Systematic Reviews

QOL: Quality of Life

RCT: Randomised Controlled Trial

SPC: Specialist Palliative Care

UC: Usual Care

VAS: Visual Analogue Scale

WHO: World Health Organization

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The full search strategy and the risk of bias table has been described in Supplementary Information. Any further data analysed during this study are available from the corresponding author on reasonable request.

Competing interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Funding

The author A.K. received no financial support for the research, authorship and publication of this article. C.J.E is funded by a Health Education England/National Institute of Health Research Senior Clinical Lectureship.

Authors' contributions

Conceptualisation: CJE; Methodology: AK, CJE; Data analysis and Writing: AK; Supervision: CJE. All authors read and approved the final manuscript.

Acknowledgements

We thank all the authors who participated in this research; Dr. Catherine J Evans for providing utmost support, Dr. Matthew Maddocks for checking the protocol, Ms. Elizabeth Alejandra Dominguez Palomerae for the support of an independent full paper review.

Foreman KJ, Marquez N, Dolgert A, Fukutaki K, Fullman N, McGaughey M, et al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories. Lancet. 2018;392(10159):2052-90.
Hall S, Petkova H, Tsouros AD, Costantini M and Higginson IJ. Palliative care for older people: better practices. WHO Regional Office for Europe. 2011. https://www.euro.who.int/__data/assets/pdf_file/0017/143153/e95052.pdf. Accessed 24 Apr 2022.
Addington-Hall J, Higginson IJ. Palliative care for non-cancer patients. Oxford: Oxford University Press; 2001.
Sleeman KE, de Brito M, Etkind S, Nkhoma K, Guo P, Higginson IJ, et al. The escalating global burden of serious health-related suffering: projections to 2060 by world regions, age groups, and health conditions. Lancet Glob Health. 2019;7(7):e883-e92.
Coventry PA, Grande GE, Richards DA, Todd CJ. Prediction of appropriate timing of palliative care for older adults with non-malignant life-threatening disease: a systematic review. Age Ageing. 2005;34(3):218-27.
Burt J, Raine R. The effect of age on referral to and use of specialist palliative care services in adult cancer patients: a systematic review. Age Ageing. 2006;35(5):469-76.
Sampson EL, Candy B, Davis S, Gola AB, Harrington J, King M, et al. Living and dying with advanced dementia: A prospective cohort study of symptoms, service use and care at the end of life. Palliat Med. 2018;32(3):668-81.
Kavalieratos D, Kamal AH, Abernethy AP, Biddle AK, Carey TS, Dev S, et al. Comparing unmet needs between community-based palliative care patients with heart failure and patients with cancer. J Palliat Med. 2014;17(4):475-81.
Ahmed N, Bestall JC, Ahmedzai SH, Payne SA, Clark D, Noble B. Systematic review of the problems and issues of accessing specialist palliative care by patients, carers and health and social care professionals. Palliat Med. 2004;18(6):525-42.
O'Leary N, Tiernan E. Survey of specialist palliative care services for noncancer patients in Ireland and perceived barriers. Palliat Med. 2008;22(1):77-83.
Oishi A, Murtagh FE. The challenges of uncertainty and interprofessional collaboration in palliative care for non-cancer patients in the community: a systematic review of views from patients, carers and health-care professionals. Palliat Med. 2014;28(9):1081-98.
Hui D, Meng YC, Bruera S, Geng Y, Hutchins R, Mori M, et al. Referral Criteria for Outpatient Palliative Cancer Care: A Systematic Review. Oncologist. 2016;21(7):895-901.
Evans CJ IL, Ellis-Smith C, Nicholson C, Costa A, Oluyase AO, Namisango E, et al.. Rapid Scoping Review of Service Delivery Models to Maximise Quality of Life for Older People at the End of Life. World Health Organisation (WHO) by King’s College London. 2017. https://extranet.who.int/kobe_centre/sites/default/files/pdf/QOL_scoping_review_report_EN_0.pdf. Accessed 24 Apr 2022.
Connor SR, Bermedo MCS. Global Atlas of Palliative Care at the End of Life. Worldwide Palliative Care Alliance (WPCA). 2014. https://www.who.int/nmh/Global_Atlas_of_Palliative_Care.pdf. Accessed 24 Apr 2022.
Evans CJ, Ison L, Ellis-Smith C, Nicholson C, Costa A, Oluyase AO, et al. Service Delivery Models to Maximize Quality of Life for Older People at the End of Life: A Rapid Review. Milbank Q. 2019;97(1):113-75.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
Gomes B, Calanzani N, Curiale V, McCrone P, Higginson IJ. Effectiveness and cost-effectiveness of home palliative care services for adults with advanced illness and their caregivers. Cochrane Database Syst Rev. 2013(6):CD007760.
Bruera E. Textbook of palliative medicine. London: Hodder Arnold; 2009.
Hanks G, Cherny N, Christakis N, Fallon M, Kaasa S, Portenoy R. Oxford Textbook of Palliative Medicine. Oxford: Oxford University Press; 2009.
Chaudhry SI, Murphy TE, Gahbauer E, Sussman LS, Allore HG, Gill TM. Restricting symptoms in the last year of life: a prospective cohort study. JAMA Intern Med. 2013;173(16):1534-40.
Quinn KL, Shurrab M, Gitau K, Kavalieratos D, Isenberg SR, Stall NM, et al. Association of Receipt of Palliative Care Interventions With Health Care Use, Quality of Life, and Symptom Burden Among Adults With Chronic Noncancer Illness: A Systematic Review and Meta-analysis. JAMA. 2020;324(14):1439-50.
Knaul FM, Farmer PE, Krakauer EL, De Lima L, Bhadelia A, Jiang Kwete X, et al. Alleviating the access abyss in palliative care and pain relief-an imperative of universal health coverage: the Lancet Commission report. Lancet. 2018;391(10128):1391-454.
Gómez Batiste X, Connor S. Building integrated palliative care programs and services. WHO Collaborating Centre Public Health Palliative Care Programmes. 2017. https://www.fnh.cl/publicaciones/BuildingIntegratedPalliativeCareProgramsandServices.pdf. Accessed 24 Apr 2022.
Luckett T, Phillips J, Agar M, Virdun C, Green A, Davidson PM. Elements of effective palliative care models: a rapid review. BMC Health Serv Res. 2014;14:136.
Quill TE, Abernethy AP. Generalist plus specialist palliative care--creating a more sustainable model. N Engl J Med. 2013;368(13):1173-5.
Davidson P, Halcomb E, Hickman L, Phillips J, Graham B. Beyond the rhetoric: what do we mean by a 'model of care'? Aust J Adv Nurs. 2006;23(3):47-55.
Palliative Care Australia. National Palliative Care Standards. 5th edition. 2018. https://palliativecare.org.au/wp-content/uploads/dlm_uploads/2018/11/PalliativeCare-National-Standards-2018_Nov-web.pdf. Accessed 24 Apr 2022.
Training.cochrane.org. Cochrane Handbook for Systematic Reviews of Interventions. https://training.cochrane.org/handbook. Accessed 24 Apr 2022.
Cochrane Handbook for Systematic Reviews of Interventions. Table 8.7.a: Possible approach for summary assessments of the risk of bias for each important outcome (across domains) within and across studies. https://handbook-5-1.cochrane.org/chapter_8/table_8_7_a_possible_approach_for_summary_assessments_of_the.htm. Accessed 24 Apr 2022.
Higginson IJ, Evans CJ, Grande G, Preston N, Morgan M, McCrone P, et al. Evaluating complex interventions in end of life care: the MORECare statement on good practice generated by a synthesis of transparent expert consultations and systematic reviews. BMC Med. 2013;11:111.
Fergusson D, Aaron SD, Guyatt G, Hébert P. Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis. BMJ. 2002;325(7365):652-4.
Oriani A, Dunleavy L, Sharples P, Perez Algorta G, Preston NJ. Are the MORECare guidelines on reporting of attrition in palliative care research populations appropriate? A systematic review and meta-analysis of randomised controlled trials. BMC Palliat Care. 2020;19(1):6.
Hui D, Glitza I, Chisholm G, Yennu S, Bruera E. Attrition rates, reasons, and predictive factors in supportive care and palliative oncology clinical trials. Cancer. 2013;119(5):1098-105.
Ahronheim JC, Morrison RS, Morris J, Baskin S, Meier DE. Palliative care in advanced dementia: a randomized controlled trial and descriptive analysis. J Palliat Med. 2000;3(3):265-73.
Aiken LS, Butner J, Lockhart CA, Volk-Craft BE, Hamilton G, Williams FG. Outcome evaluation of a randomized trial of the PhoenixCare intervention: program of case management and coordinated care for the seriously chronically ill. J Palliat Med. 2006;9(1):111-26.
Brumley R, Enguidanos S, Jamison P, Seitz R, Morgenstern N, Saito S, et al. Increased satisfaction with care and lower costs: results of a randomized trial of in-home palliative care. J Am Geriatr Soc. 2007;55(7):993-1000.
Gade G, Venohr I, Conner D, McGrady K, Beane J, Richardson RH, et al. Impact of an inpatient palliative care team: a randomized control trial. J Palliat Med. 2008;11(2):180-90.
Farquhar MC, Higginson IJ, Fagan P, Booth S. The feasibility of a single-blinded fast-track pragmatic randomised controlled trial of a complex intervention for breathlessness in advanced disease. BMC Palliat Care. 2009;8:9.
Farquhar MC, Prevost AT, McCrone P, Brafman-Price B, Bentley A, Higginson IJ, et al. The clinical and cost effectiveness of a Breathlessness Intervention Service for patients with advanced non-malignant disease and their informal carers: mixed findings of a mixed method randomised controlled trial. Trials. 2016;17:185.
Brännström M, Boman K. Effects of person-centred and integrated chronic heart failure and palliative home care. PREFER: a randomized controlled study. Eur J Heart Fail. 2014;16(10):1142-51.
Higginson IJ, Bausewein C, Reilly CC, Gao W, Gysels M, Dzingina M, et al. An integrated palliative and respiratory care service for patients with advanced disease and refractory breathlessness: a randomised controlled trial. Lancet Respir Med. 2014;2(12):979-87.
Bajwah S, Ross JR, Wells AU, Mohammed K, Oyebode C, Birring SS, et al. Palliative care for patients with advanced fibrotic lung disease: a randomised controlled phase II and feasibility trial of a community case conference intervention. Thorax. 2015;70(9):830-9.
Sidebottom AC, Jorgenson A, Richards H, Kirven J, Sillah A. Inpatient palliative care for patients with acute heart failure: outcomes from a randomized trial. J Palliat Med. 2015;18(2):134-42.
Wong FK, Ng AY, Lee PH, Lam PT, Ng JS, Ng NH, et al. Effects of a transitional palliative care model on patients with end-stage heart failure: a randomised controlled trial. Heart. 2016;102(14):1100-8.
Ng AYM, Wong FKY. Effects of a Home-Based Palliative Heart Failure Program on Quality of Life, Symptom Burden, Satisfaction and Caregiver Burden: A Randomized Controlled Trial. J Pain Symptom Manage. 2018;55(1):1-11.
Rogers JG, Patel CB, Mentz RJ, Granger BB, Steinhauser KE, Fiuzat M, et al. Palliative Care in Heart Failure: The PAL-HF Randomized, Controlled Clinical Trial. J Am Coll Cardiol. 2017;70(3):331-41.
Bekelman DB, Allen LA, McBryde CF, Hattler B, Fairclough DL, Havranek EP, et al. Effect of a Collaborative Care Intervention vs Usual Care on Health Status of Patients With Chronic Heart Failure: The CASA Randomized Clinical Trial. JAMA Intern Med. 2018;178(4):511-9.
Eggers C, Dano R, Schill J, Fink GR, Timmermann L, Voltz R, et al. Access to End-of Life Parkinson's Disease Patients Through Patient-Centered Integrated Healthcare. Front Neurol. 2018;9:627.
O'Donnell AE, Schaefer KG, Stevenson LW, DeVoe K, Walsh K, Mehra MR, et al. Social Worker-Aided Palliative Care Intervention in High-risk Patients With Heart Failure (SWAP-HF): A Pilot Randomized Clinical Trial. JAMA Cardiol. 2018;3(6):516-9.
Beernaert K, Smets T, Cohen J, Verhofstede R, Costantini M, Eecloo K, et al. Improving comfort around dying in elderly people: a cluster randomised controlled trial. Lancet. 2017;390(10090):125-34.
Buckingham S, Kendall M, Ferguson S, MacNee W, Sheikh A, White P, et al. HELPing older people with very severe chronic obstructive pulmonary disease (HELP-COPD): mixed-method feasibility pilot randomised controlled trial of a novel intervention. NPJ Prim Care Respir Med. 2015;25:15020.
Chapman DG, Toseland RW. Effectiveness of advanced illness care teams for nursing home residents with dementia. Soc Work. 2007;52(4):321-9.
Di Pollina L, Guessous I, Petoud V, Combescure C, Buchs B, Schaller P, et al. Integrated care at home reduces unnecessary hospitalizations of community-dwelling frail older adults: a prospective controlled trial. BMC Geriatr. 2017;17(1):53.
Engelhardt JB, McClive-Reed KP, Toseland RW, Smith TL, Larson DG, Tobin DR. Effects of a program for coordinated care of advanced illness on patients, surrogates, and healthcare costs: a randomized trial. Am J Manag Care. 2006;12(2):93-100.
Fischer SM, Cervantes L, Fink RM, Kutner JS. Apoyo con Cariño: a pilot randomized controlled trial of a patient navigator intervention to improve palliative care outcomes for Latinos with serious illness. J Pain Symptom Manage. 2015;49(4):657-65.
Grande GE, Todd CJ, Barclay SI, Farquhar MC. Does hospital at home for palliative care facilitate death at home? Randomised controlled trial. BMJ. 1999;319(7223):1472-5.
Hanks GW, Robbins M, Sharp D, Forbes K, Done K, Peters TJ, et al. The imPaCT study: a randomised controlled trial to evaluate a hospital palliative care team. Br J Cancer. 2002;87(7):733-9.
Higginson IJ, McCrone P, Hart SR, Burman R, Silber E, Edmonds PM. Is short-term palliative care cost-effective in multiple sclerosis? A randomized phase II trial. J Pain Symptom Manage. 2009;38(6):816-26.
Hughes SL, Cummings J, Weaver F, Manheim L, Braun B, Conrad K. A randomized trial of the cost effectiveness of VA hospital-based home care for the terminally ill. Health Serv Res. 1992;26(6):801-17.
Kimbell B, Murray SA, Byrne H, Baird A, Hayes PC, MacGilchrist A, et al. Palliative care for people with advanced liver disease: A feasibility trial of a supportive care liver nurse specialist. Palliat Med. 2018;32(5):919-29.
Kinley J, Hockley J, Stone L, Dewey M, Hansford P, Stewart R, et al. The provision of care for residents dying in U.K. nursing care homes. Age Ageing. 2014;43(3):375-9.
Kinley J, Stone L, Dewey M, Levy J, Stewart R, McCrone P, et al. The effect of using high facilitation when implementing the Gold Standards Framework in Care Homes programme: a cluster randomised controlled trial. Palliat Med. 2014;28(9):1099-109.
Naylor MD, Brooten DA, Campbell RL, Maislin G, McCauley KM, Schwartz JS. Transitional care of older adults hospitalized with heart failure: a randomized, controlled trial. J Am Geriatr Soc. 2004;52(5):675-84.
Pantilat SZ, O'Riordan DL, Dibble SL, Landefeld CS. Hospital-based palliative medicine consultation: a randomized controlled trial. Arch Intern Med. 2010;170(22):2038-40.
Rabow MW, Dibble SL, Pantilat SZ, McPhee SJ. The comprehensive care team: a controlled trial of outpatient palliative medicine consultation. Arch Intern Med. 2004;164(1):83-91.
Taube E, Kristensson J, Midlöv P, Jakobsson U. The use of case management for community-dwelling older people: the effects on loneliness, symptoms of depression and life satisfaction in a randomised controlled trial. Scand J Caring Sci. 2018;32(2):889-901.
Temkin-Greener H, Mukamel DB, Ladd H, Ladwig S, Caprio TV, Norton SA, et al. Impact of Nursing Home Palliative Care Teams on End-of-Life Outcomes: A Randomized Controlled Trial. Med Care. 2018;56(1):11-8.
Thoonsen B, Groot M, Engels Y, Prins J, Verhagen S, Galesloot C, et al. Early identification of and proactive palliative care for patients in general practice, incentive and methods of a randomized controlled trial. BMC Fam Pract. 2011;12:123.
Thoonsen B, Vissers K, Verhagen S, Prins J, Bor H, van Weel C, et al. Training general practitioners in early identification and anticipatory palliative care planning: a randomized controlled trial. BMC Fam Pract. 2015;16:126.
Zimmer JG, Groth-Juncker A, McCusker J. Effects of a physician-led home care team on terminal care. J Am Geriatr Soc. 1984;32(4):288-92.
Zimmer JG, Groth-Juncker A, McCusker J. A randomized controlled study of a home health care team. Am J Public Health. 1985;75(2):134-41.
Arnold SV, Spertus JA, Lei Y, Allen KB, Chhatriwalla AK, Leon MB, et al. Use of the Kansas City Cardiomyopathy Questionnaire for monitoring health status in patients with aortic stenosis. Circ Heart Fail. 2013;6(1):61-7.
Sclan SG, Reisberg B. Functional assessment staging (FAST) in Alzheimer's disease: reliability, validity, and ordinality. Int Psychogeriatr. 1992;4 Suppl 1:55-69.
Downar J, Goldman R, Pinto R, Englesakis M, Adhikari NK. The "surprise question" for predicting death in seriously ill patients: a systematic review and meta-analysis. CMAJ. 2017;189(13):E484-E93.
Thomas K. The GSF Prognostic Indicator Guidance, Prognostic Indicator Guidance (PIG). The Gold Standards Framework Centre In End of Life Care CIC; 2011. https://www.goldstandardsframework.org.uk/cd-con-tent/uploads/files/General%20Files/Prognostic%20Indicator%20Guidance%20October%202011.pdf. Accessed 24 Apr 2022.
O'Connor CM, Hasselblad V, Mehta RH, Tasissa G, Califf RM, Fiuzat M, et al. Triage after hospitalization with advanced heart failure: the ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) risk model and discharge score. J Am Coll Cardiol. 2010;55(9):872-8.
Lau F, Downing GM, Lesperance M, Shaw J, Kuziemsky C. Use of Palliative Performance Scale in end-of-life prognostication. J Palliat Med. 2006;9(5):1066-75.
Hauser K, Walsh D. Visual analogue scales and assessment of quality of life in cancer. J Support Oncol. 2008;6(6):277-82.
　　Eagar K, Clapham SP, Allingham SF. Palliative care is effective: but hospital symptom outcomes superior. BMJ Support Palliat Care. 2020;10(2):186-190.
McColl E. Best practice in symptom assessment: a review. Gut. 2004;53 Suppl 4:iv49-54.
Herr KA, Garand L. Assessment and measurement of pain in older adults. Clin Geriatr Med. 2001;17(3):457-78, vi.
Evans CJ, Benalia H, Preston NJ, Grande G, Gysels M, Short V, et al. The selection and use of outcome measures in palliative and end-of-life care research: the MORECare International Consensus Workshop. J Pain Symptom Manage. 2013;46(6):925-37.
Murtagh FE, Ramsenthaler C, Firth A, Groeneveld EI, Lovell N, Simon ST, et al. A brief, patient- and proxy-reported outcome measure in advanced illness: Validity, reliability and responsiveness of the Integrated Palliative care Outcome Scale (IPOS). Palliat Med. 2019;33(8):1045-57.
Qol.thoracic.org. Functional Status. 2021. https://qol.thoracic.org/sections/key-concepts/functional-status.html. Accessed 24 Apr 2022.
Habraken JM, van der Wal WM, Ter Riet G, Weersink EJ, Toben F, Bindels PJ. Health-related quality of life and functional status in end-stage COPD: a longitudinal study. Eur Respir J. 2011;37:280-288
　　Theofilou P. Quality of Life: Definition and Measurement. Europe's Journal of Psychology. 2013;9(1):p150-62.
Dy SM, Pfoh ER, Salive ME, Boyd CM. Health-related quality of life and functional status quality indicators for older persons with multiple chronic conditions. J Am Geriatr Soc. 2013;61(12):2120-7.
Squiers L, Peinado S, Berkman N, Boudewyns V, McCormack L. The health literacy skills framework. J Health Commun. 2012;17 Suppl 3:30-54.
Lewis JM, DiGiacomo M, Currow DC, Davidson PM. Dying in the margins: understanding palliative care and socioeconomic deprivation in the developed world. J Pain Symptom Manage. 2011;42(1):105-18.
Matsuyama RK BW, Ingram K, Lyckholm L, Wilson-Genderson M, Smith TJ. Will Patients Want Hospice or Palliative Care if They Do Not Know What It Is? Journal of Hospice & Palliative Nursing. 2011;13:p41-6.
Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care. 1991;7(2):6-9.
Ellis-Smith C, Higginson IJ, Daveson BA, Henson LA, Evans CJ, BuildCARE. How can a measure improve assessment and management of symptoms and concerns for people with dementia in care homes? A mixed-methods feasibility and process evaluation of IPOS-Dem. PLoS One. 2018;13(7):e0200240.
Bausewein C, Daveson B, Benalia H, Simon ST, Higginson IJ. Outcome Measurement in Palliative Care The Essentials. PRISMA. 2014. https://www.eapcnet.eu/wp-content/uploads/2021/03/Outcome-Measurement-in-Palliative-Care-The-Essentials-.pdf. Accessed 24 Apr 2022.
Palliative Care Australia. Palliative Care Service Development Guidelines. Palliative Care Service Development Guideline. 2018. https://palliativecare.org.au/wp-content/uploads/dlm_uploads/2018/02/PalliativeCare-Service-Delivery-2018_web-1.pdf. Accessed 24 Apr 2022.

No competing interests reported.

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A systematic review of needs-based triggers for palliative care for early referral of older people with non-cancer conditions

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