The End Of Life Experiences Of People Living With Socio-Economic Deprivation In The Developed World: An Integrative Review

The End Of Life Experiences Of People Living With Socio-Economic Deprivation In The Developed World: An Integrative Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The End Of Life Experiences Of People Living With Socio-Economic Deprivation In The Developed World: An Integrative Review Sarah P Bowers, Ming Chin, Maire O'Riordan, Emma Carduff This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1302205/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Those experiencing socioeconomic deprivation have poorer quality of health throughout their life course which can result in poorer quality of death – with decreased access to palliative care services, greater use of acute care, and a disparity in deaths at home compared with patients from less deprived populations. Aim: To summarise the current global evidence from developed countries on end-of-life experience for those living with socio-economic deprivation. Design: Integrative review in accordance with PRISMA . A thorough search of major databases from 2010-2020, using clear definitions of end-of-life care and well-established proxy indicators of socio-economic deprivation. Empirical research describing experience of adult patients in the last year of life care were included. Results: Forty studies were included from a total of 3508 after screening and selection. These were deemed to be of high quality; from a wide range of countries with varying healthcare systems; and encompassed all palliative care settings for patients with malignant and non-malignant diagnoses. Three themes were identified: 1) the multi-dimensional experience at end-of-life, 2) preferences and planning and 3) the uptake and utilization of services. Conclusions: Current models of healthcare services are not meeting the needs of those experiencing socio-economic deprivation at the end-of-life. Further work is needed to understand the disparity in care, particularly around ensuring patients voices are heard and can influence service development and delivery. Palliative Care Terminal Care Socioeconomic Factors Social Class Delivery of Health Care Integrative review Figures Figure 1 Introduction On a global scale, it is now recognized that people experiencing socioeconomic deprivation (SED) are spending more of their shorter lives in ill health and are carrying a higher burden of chronic disease, multimorbidity and symptom burden than more affluent neighbours (1-3). Socioeconomic deprivation is an independent risk factor for higher mortality in both cancer and non-cancer populations (4-6) and is associated with higher use and cost of healthcare in the last year of life (7) (8). Given that people living with poverty are carrying this inequitable high burden of poor health outcomes, equal access to palliative care would be expected when compared with those in more affluent areas. However, it is now recognised that people with lower incomes have a potentially poorer experience at end-of-life (EOL) (6), with reduced referral and access to specialist palliative care services in and out of hours (9, 10) (11), are more likely to use ambulance and A&E and to be admitted to and die in hospital (7, 12, 13), rather than at home or in a hospice (9, 10, 14-17). People with lower wealth have recently been found to have had more hospital admissions in the last two years of life(18) and this is often a substitute for elective, community-based healthcare services (19). Families living in poverty may need to compromise on food and heating and incur significant debts when someone dies (20) and report significantly less support and satisfaction with care received at the EOL (6). A qualitative evidence synthesis, undertaken in 2019, identified that access to preferred place of death was limited by human factors, such as social support, personal and cultural beliefs, poor communication, and environmental factors, such as suitability of the home environment and availability of resources within health and care services. (21). An earlier review highlighted barriers such as accessibility, availability, affordability and acceptability (22). As quantitative evidence describing the disparity in access and delivery of palliative care between socioeconomic groups continues to grow, there is still little understanding of how people living in poverty experience living and dying with a life-limiting illness. This review feeds directly into ongoing empirical work to understand the experiences of home death for people at the EOL who are living with poverty (grant number and webpage). and complements a recently published paper by Rowley and colleagues which served as a call to action for researchers, policy-makers and clinicians working with people experiencing poverty at EOL (23). By understanding what inequalities and disparities persist, practitioners and policy makers can meaningfully address the issue at individual, institutional and societal levels and progress can be made to narrow the gap. The aim of this review is to describe current global evidence from developed countries on the experiences of people at the EOL who are living with SED. Methods Design An integrative literature review approach was chosen to facilitate synthesising and concept building given the multiple evidence sources and methodologies. We conducted our review according to the methods described by Whittemore and Knafl (24). This study was registered on PROSPERO (CRD42019151906) (25) and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses. (PRISMA) (26) Definitions We used the NICE definition for EOL which includes people who are likely to die within 12 months, with advanced, progressive, or incurable diseases or acute life-threatening conditions (27). We also referred to Rietjens recent article to develop our search terms related to palliative care (28). The definitions available for socioeconomic status are less distinct. Clear definitions are rare (i.e. the United Kingdom Index of Multiple Deprivation), do not encompass the complex nature of SED and are particularly poor at capturing rural SED (29). We therefore reviewed the evidence on proxy indicators of SED in addition to systematic reviews of the same topic to devise the evidence-based list of search terms related to SED which are presented in table 1. (7, 30, 31). This review did not include papers from developing countries given their unique challenges to resources and the delivery of healthcare. Papers solely about access to palliative care services and place of death were excluded because we knew of recently published reviews about place of death and access (32) (13, 33, 34) Search strategy Key search terms were agreed between SB and EC, with support from a librarian based at NHS Greater Glasgow & Clyde, and these were combined with standard Boolean operators (Table 1). The following databases were searched to capture the wide range of research and disciplines involved in SED at the EOL – Medline, Embase, CINAHL, ASSIA and PsychInfo. The most relevant systematic review to describe palliative care in the context of SED was reported in 2010 (22) and thus we limited our search from January 2010 to March 2020. Inclusion and exclusion criteria were agreed to ensure we obtained relevant, original research (Table 2). Table 1 – Search Terms Palliative care AND Socio-economic SED Palliative care Palliat* Terminal care Terminal* ill* Terminal diagnos* Dying Advanced illness* Life limit* EOL Last year of life EOLC Advanced cancer Advanced progressive illness Socioeconomic factor* Low income Social class* Social depriv* Working class* Social* disadvantage* Low education Uneducated Social inequal* Index of depriv* Socioeconomic status Poor Poverty Occupation Table 2. Inclusion and Exclusion criteria Inclusion criteria Exclusion criteria Articles reporting the experiences of adult patients with a diagnosis of terminal illness who were approaching the EOL from the perspective of the patient or the unpaid/family caregiver Articles reporting the experiences of those under the age of 18 Articles which described a population of participants who were socio-economically deprived Articles reporting the experiences of patients living with chronic illness but not thought to be at the EOL Research was conducted in high income countries (as per World Bank List of economies (35) Articles reporting the perceptions of health professionals I.e. health professional proxy accounts of experience Articles were peer reviewed empirical research Articles which were focused on place of death or on access to palliative care for people at the EOL Published in English Systematic reviews, reports, commentaries, editorials, conference proceedings, case reports, grey literature Study selection Initial screening by title and abstract was conducted by SB and MC. Both authors screened the first 20 papers for inclusion to ensure consistency. Full texts were then reviewed according to the inclusion and exclusion criteria. Where there was uncertainty, papers were read by EC and a decision was made as a team. Quality Appraisal Given the breadth of research designs obtained by integrative reviews, there is no gold standard for quality appraisal (24). However, a research critique framework developed by Caldwell et al (36) was considered suitable to assess quality in both qualitative and quantitative papers. Bloomer et al 2017 used the Caldwell criteria in a recent integrative review and shared the flowchart they had developed (37). The methodological strengths and weaknesses of each included study were assessed independently with SB and MC using the Caldwell 11 point criteria. Final scores were corroborated and differences discussed. Data abstraction and synthesis We followed the four steps as described by Whittemore and Knafl: 1) data reduction, 2) data display, 3) data comparison, 4) conclusion drawing (24). The papers were reviewed and data extracted on: full reference, continent, language, how SED was defined, how EOL was defined, aim, objectives or research questions, design, setting for data collection, participants, diagnosis, sample size, tools, key findings, limitations as described, author conclusions, references to other relevant studies. The content was analysed and an initial list of themes were developed. The full text papers were then re-read, and the data applied to each theme. The themes were then revisited, relationships explored and themes consolidated. This process resulted in the final 3 global themes. Findings Included studies In total, 2458 studies were found after removal of duplicates as illustrated in figure 1. Initial screening of titles and abstracts resulted in 236 papers for full-text review. Ultimately, 40 studies were included in the analysis. A list of these papers is included in table 3. In total, 38 out of 40 papers were of high quality with a score of 9/11 or higher, the remaining 2 papers scored 8/11. Given the experiences of people living in SED have not been well described in detail in the literature, we did not exclude on the basis of quality. FIGURE 1 SHOULD BE PLACED HERE Figure 1 Prisma flow diagram of search results Most studies originated in North America (23/40); 8 in Europe (one of these was UK based); 7 in Asia; 1 Australia and 1 was cross-continent between USA and Europe. The studies were conducted in different healthcare settings including community, hospital and hospice. Some were population studies. Most studies (28/40) recruited patients with cancer diagnoses; 11 did not specify a particular diagnosis and only one looked exclusively at patients with a non-malignant diagnosis – Chronic Obstructive Pulmonary Disease (COPD). Quantitative designs were most commonly used (34/40). There were 3 qualitative studies and the remaining 3 using mixed methodologies. The total sample size of the included studies was 439423 (range = 18 – 307188). The studies included used a variety of definitions to define SED. Twenty-two studies used only one marker in their analysis: education status (n=7); household income (n=4); insurance status (n=3 from the USA); subgroups of employment (n=2); specifically designed SED scores as the single marker of SED (n=2) i.e. the Carstairs SED score and the Index of Relative Disadvantage; decedent postal code linked to nationally available data on poverty rates and estimated income (n=2); patient self-reported financial strain (n=1); structurally vulnerable (n=1). The remaining 18 studies used multifactorial markers of SED. TABLE 3 SHOULD BE PLACED HERE Multi-dimensional EOL experience In total 10 studies (38-47), discussed physical, emotional and social symptom burden. Lower income and education levels were generally associated with higher physical symptom burden, with pain being widely reported (38, 44). Poverty was also found to be associated with increased receipt of medication for pain, dyspnoea and emotional distress (45). However, the association between higher physical symptom burden and SED was not sustained in one study (41) where no difference was found in symptom burden between insured and uninsured patients. The evidence on the relationship between SED and psychological wellbeing is conflicting. While one study found that financial difficulty was associated with lower functional, emotional and spiritual wellbeing (46) another found that unemployed patients with cancer had less anxiety and depression (42) Similarly, Dhingra et al found that patients living in impoverished neighbourhoods reported very low illness burden (defined as physical functioning, symptom distress, unmet needs and quality of life)(39). One study showed that lower education was associated with higher hopelessness and depression rates(47) but education levels generally did not impact on levels of psychological distress, anxiety or depression scores (42, 46). There is no consistent evidence regarding coping ability. Tang et al showed that higher education was associated with higher post-traumatic growth scores, showing positive personal development and adjustment to trauma(40). However, Chochinov et al reported that patients with higher education were more likely to report feelings of having lost control, unfinished business, and poorer coping with activities of daily living(43). Social and financial support Only 2 studies described the social support available to patients, from government agencies and more informal routes (48, 49). Lewis et al described limited family support, often a sole caregiver, and sometimes fragile relationships in situations that could be compounded by violence and alcohol. There was a heavy reliance on other sources of support, but welfare support and government housing agencies were described as difficult to access and community support (including informal support from neighbours and formalised primary care and community nursing support) was described as inconsistent, unpredictable and inadequate to meet patient need (48). Once a connection was able to be established, patients who had previously engaged with government agencies prior to their illness described subsequent interactions as a positive experience. However, for those who had no prior connection, the experience, particularly around negotiating benefits was challenging (48). In one study, women with breast cancer in the US expressed a desire to maintain social connections, describing this as a key aspect of a meaningful life, alongside creative outlets and spirituality. For those living alone, in lower socioeconomic populations, neighbourhood networks were essential to sustain care and social needs (49). Financial hardship Four studies in countries with both publicly funded and private healthcare systems described the impact of ill-health on finances when living with pre-existing poverty (49-52). Financial distress was common prior to diagnosis but worsened after due to medical costs and inability to work. Patients who had low income or who were in financial poverty allocated a larger proportion of family income to health expenses and were more likely to report catastrophic health expenditure and higher health costs at the EOL (51, 52). Similarly, a qualitative study of low-income patients with breast cancer in America found that most patients had difficulty meeting basic needs, inadequate financial resources, and were unable to work, resulting in them feeling burdensome and useless (49) Drug reimbursement due to terminal illness (DRTI) is a scheme available in Denmark for patients with incurable disease and a short life expectancy allowing for prescription medicines to be obtained free of charge. However, the authors noted that patients with lower income were less likely to access DRTI (52). Preferences and planning at EOL Preferences for EOL care were described in 5 studies (53-57). Overall, patients with higher education level were more likely to choose supportive care. Tang et al reported that patients with higher education level were more likely to accurately know their prognosis, which was in turn associated with greater odds of preferring comfort-orientated and hospice-based care at the EOL (55). Carlucci et al provided patients with advanced COPD theoretical scenarios and found those with a higher education level were more likely not to choose EOL sustaining treatments such as intubation and non-invasive ventilation. Of note, the study also suggested that all participants’ understanding of choices were suboptimal, with over 40% of participants being unable to correctly define the comfort/supportive option(54). Saeed et al found that education did not affect participants’ preference to receive comfort/supportive care (53), however the sample consisted of mainly highly educated participants. Treatment Intensity at the EOL Treatment intensity at EOL was described in 8 studies.(58-62) (63) (64) (65) In most of the studies included, patients with lower income, lower education levels, or no insurance, were generally more likely to receive intensive treatment at the EOL(58-61). Such treatments included chemotherapy, attendance at emergency departments or >14 days hospitalisation prior to death, intensive care admission, use of mechanical ventilation and cardiopulmonary resuscitation. Lower income and lower education level also led to increased rate of transfer from home or nursing home to secondary care in the last months of life (63). Having an inpatient hospice admission during the last 6 months of life reduced hospital admissions by almost half. However, patients with lower income and lower education were less likely to utilise hospice (64). A few studies were contradictory. A Taiwanese study showed that whilst low income was associated with increased likelihood of hospital admission beyond 14 days and death in an acute hospital, higher income patients were more likely to attend the emergency department and be admitted to intensive care units (59). One study of cancer patients showed that those with higher education levels were more likely to receive diagnostic and therapeutic procedures at the EOL(62). Bergman et al described an analysis of a dedicated programme for men with low income and prostate cancer, and found rates of chemotherapy use, emergency and intensive care admissions and inpatient stays for those in the programme were comparable to the general population(65). Future Care Planning Future care planning, designation of power of attorney, EOL discussions, and completion of written instructions for care at EOL was described in 3 studies (44, 53, 66). Khosla et al found that although higher household income increased the odds of having a legally designated power of attorney for healthcare, this did not impact on EOL discussions or written instructions. They also showed that education level did not impact advanced care planning behaviour (66). Carr et al found that having assets significantly increased the likelihood of participants having a living will or legal power of attorney but did not impact on informal EOL discussions(44). In contrast, another study looking at a sample of lower income patients found that education level and financial strain did not affect completion of advanced care directives(53). Service uptake and utilization Nine studies described what and how palliative care services were used (38, 52, 64, 67-72). The evidence shows that even when patients had equal access to palliative care services, differences in the uptake of these persisted across different indicators of socioeconomic status. For example, those with higher income or living in a neighbourhood with a higher socioeconomic status, were significantly more likely to have inpatient hospice admissions(64). The literature points to a distinction between which services are desired or used by patients based on their socioeconomic status. Ankuda et al showed that patients with financial strain described the connection to social services offered by an at home palliative care service including transportation, help with navigating insurance policies or benefits and food stamps as what mattered most due to self-perceived poverty, disability and high medication cost(67). Another reason for reliance on practical or social support may be explained by the availability of informal caregivers. For example, Bijnsdorp et al described a positive correlation between educational attainment and availability of partner care-networks, defined as care provided primarily by a partner in the last year of life, particularly for patients younger than 77.9 years (72). Similarly, a home-based palliative care service in Canada found a difference in unpaid caregiving hours provided for those with the highest socioeconomic status and the lowest socioeconomic status of 6.18 hours and 2.66 hours, respectively(68). When those experiencing SED have accessed specialist palliative care services, there is some evidence that they use them more thereafter. The literature shows that this is the case for both routine and non-routine care and across the different services offered by palliative care. For example, patients with either limited insurance (Medicaid) or no health insurance had more follow up appointments with a hospital palliative care service (38). This finding persisted for universal, publicly funded health insurance systems. Two Canadian home-based palliative care services showed that patients with higher levels of SED and lower levels of educational attainment had increased propensity and intensity of support worker and nurse visits (68, 71). The type of support from General Practitioners may also show some slight variation for patients in the last year of life. For example, patients with cancer in the last year of life were more likely to have GP face-to-face visits if they had a lower income (69). Patient satisfaction with palliative care services There is limited and conflicting evidence relating socioeconomic status to patient satisfaction with palliative care services as described in six of the included studies(49, 67, 73-76). Lower levels of education were linked in one study to higher satisfaction with care (74) whilst another showed no association with ratings on quality of death and dying for patients or family(77). Patients with financial strain rated a home palliative care programme the highest of all socioeconomic groups(67). The available qualitative research pointed to concerns from patients experiencing SED around the use of palliative care services. For example, patients described that having reduced financial means and lack of access to private insurance meant they did not receive the same high quality care (77). Patients living in poverty felt a negative bias and stigmatization from healthcare professionals towards them due to their lower socioeconomic class and this impacted on perception of the care received (77). One general practitioner out-of-hours service in a deprived area in Scotland was found to be stressful and cumbersome to use with patients describing bad experiences or feeling their care needs were too complex for this service(75). A Canadian study of those who were homeless, or at risk of such, described that patients often had their care needs unidentified and unmet. However, when patients were linked to palliative care services, they reported feeling listened to and reported that services were extremely accommodating and attentive to their needs (76). Discussion We reviewed, integrated and summarised evidence on the EOL experiences of people living with SED in developed countries. Forty heterogenous studies were identified from a wide range of countries with varying healthcare systems and encompassed both malignant and non-malignant diseases. Three global themes were identified relating to the multi-dimensional EOL experience, preferences and planning and service uptake and utilization. The following key findings were identified - those living with SED have: increased symptom burden; difficulty navigating complex healthcare systems at the EOL and increased intensity of use of these once a link is established; a preference for, and are more likely to have, intensive treatment at the EOL; limited formal and informal social support; a greater propensity to experience financial distress; and, less participation in advanced care planning. This review demonstrated that specifically designed initiatives and services can be beneficial for those living in SED (65). Previous research has shown that people experiencing SED use palliative care services differently and that current universally available models often fail to meet patients’ needs (7, 9-12, 15-18, 52, 78). Navigating and negotiating multiple and complex systems in order to access essential support may be overwhelming, particularly when compounded by unpredictable community support (48, 49) and a lack of unpaid family caregiving (68, 72). Our work lends further argument to the call for proportionate universalism, where marginalised groups need systems to be designed to incorporate their needs, rather than needing them to adapt to a universal healthcare system, and for time and resources to be proportionate to the level of disadvantage (79, 80). Dying can be expensive, for both patients and the people caring for them. In addition to existing financial constraint, further loss of income, changes to benefits and treatment-related costs can be catastrophic (49, 51, 81). Interestingly, even when a drug reimbursement system was available in Denmark, patients from poorer backgrounds were less likely to claim it (52). This supports what we already know – that financial benefits do not always reach those who need them most. In the UK alone, up to £6.2billion of income-related benefits went unclaimed in 2018-2019 (82). Ultimately, patients and families may not get access to the financial support they need to mitigate the costs associated with EOL, including fees for diagnostic interventions, hospice or home care and reduced household income as relatives become unemployed unpaid caregivers. This financial distress can leave patients and caregivers feeling devalued, and financially burdensome (49). Our findings highlight that in order to tackle the systemic issues of social justice which impact on EOL experience, we must adopt multidisciplinary and multi-agency approaches to support families to navigate health and social care and benefits systems. Our review suggests that people experiencing SED valued the non-medical support from palliative care services most, particularly around use of social and supportive services and were less likely to have informal caregivers (48, 68). Our findings showed that people living in SED absorbed palliative care services when they could gain access to them, with demonstrable higher intensity of use, particularly with regards to outpatient and community-based services (38, 68, 69, 71). Additionally, our review suggests that patients also have greater physical and psychological symptom burden (38, 44, 83), thus making the greater use of palliative care services unsurprising. However, an alternative explanation could be that services and existing resources are failing to meet the complex needs of people experiencing SED, thus leading to repeated consultations. Barriers to quality care identified in this review have been multifactorial, complex, and difficult to address on a single level. Without significant changes to the way we deliver healthcare, the complexity of these barriers will only serve to widen the quality-of-care gap between deprived and affluent populations yet again, proving the inverse care law true. Although our review demonstrated that people living with SED had both a preference for, and tendency to receive intensive treatments at the EOL(58, 59, 61-65, 84) choosing such treatments is likely multidimensional and reflective of advanced care planning and patient advocacy, rather than socioeconomic status. Recent research from Scotland added weight to these findings, with Mason et al demonstrating that for those in the last year of life, living in SED used more unscheduled care (11). People living with SED may have more interaction with health and social care professionals and thus potentially more opportunity to engage with future care planning, yet this is not translating to the actual experience at the EOL. Whilst Davies et al have demonstrated that part of the increased uptake of hospital-based services may be due to poorer health and function for those living in SED (18), until we start asking people about their EOL care experiences and preferences at the right time, in the right way, with consideration given to their limited opportunities to make choices throughout the life course, we will fail to understand the potentially complex nature of future planning for this group. Strengths & Limitations This review summarises a thorough analysis of the literature from the developed world about the experience of those dying in SED. We include high quality studies from a variety of settings, healthcare systems and countries thus allowing our work to be transferable and applicable across the developed world. Excluding papers addressing well-explored issues of access and preferred place of death has allowed us to focus on the patient voice and experience. Although we included a wide variety of different healthcare settings and systems in various countries, this also meant that there were a wide variety of cultural and societal differences which may limit the generalisability across settings. Whilst we had intended to draw out the patient voice, only 3 studies using a qualitative design and a further 3 studies using mixed quantitative and qualitative research methods. As our findings show, the evidence was heterogenous and often contradictory, which can be challenging to analyse and synthesise. The lack of a standard definition for SED may have contributed to the heterogenous evidence and led researchers of the included papers seeking definitions that could be easily obtained. Implications for policy, practice and research The voices of people experiencing SED at the EOL are underrepresented. The COVID-19 pandemic has disproportionately affected people living with poverty (85, 86), forced more families into poverty and has highlighted the fragility of health systems across the globe. Health inequalities are now a stark focus for policymakers globally (87). Inclusive and participatory research, which enables patients and families to feed directly into this policy making and service design is a priority. We need to actively and broadly engage with policies beyond our specialism, to take into account the complex needs of this group in societies and systems. Our review highlighted a dearth of research on spirituality at the EOL for people living with poverty. Further exploration into this important but neglected area is recommended. We also need to understand why people are more likely to experience pain and receive intensive treatment at EOL. In general, patients with lower income were less likely to complete advanced care planning. Further exploration into the link between these two things is important but it is vital that health and social care professionals understand attitudes, experiences and preferences for future care discussions. The generalisability of SED research would be improved if standard markers could be agreed upon, at least in similar healthcare systems. Whilst this is not a critique of any particular SED marker, it may be that using a combination of SED markers, or a specifically designed SED score such as the Carstairs SED score would be more appropriate(88). This echoes the work of social epidemiologists who advocate that valid measurements of socioeconomic status are required and propose the use of multidimensional, composite models which allow for capturing more context (89). Conclusion As a direct cause of the COVID-19 pandemic, it is estimated that somewhere between 88 and 115 million people worldwide will be forced into extreme poverty, and issues of inequity have been exacerbated (35). In the UK, this is happening on the background of a decade of stalling life expectancy, austerity and rising health inequalities between socioeconomic groups and regions(3). Our comprehensive review shows that SED needs to be a key facilitator in identifying those who are likely to have a greater health burden and thus requiring specialist care at the end of life. Ultimately, future palliative care services cannot adopt a ‘one size fits all’ approach, shaped by our majority populations, rather they should be adaptable and flexible to provide different levels of support based on individualised need. Multidisciplinary and multi-agency approaches are needed to navigate healthcare and benefits systems and tackle the systemic issues of social justice which impact on EOL experience. Abbreviations SED – socio-economic deprivation EOL – end of life Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials All data analysed are included in published literature that were identified through the following bibliographic databases: Medline, Embase, CINAHL, ASSIA and PsychInfo. A list of included studies can be found in table 3. For further information about the availability of these data, please contact the corresponding author. Competing interests The authors declare that they have no competing interests. Funding The post of Emma Carduff is funded by Marie Curie. Emma Carduff is Co-Applicant on an Economic and Social Research Council grant (ES/S014373/1) entitled Dying in the Margins: uncovering the reasons for unequal access to home dying for the socio-economically deprived. Authors' contributions EC, SB and MOR conceptualised the review. SB and EC conducted the literature searches. SB and MC conducted the screening of abstracts. All authors were involved in reviewing the final set of papers, analysing the data. All authors made major contributions to preparing the manuscript. All authors read and approved the final manuscript. Acknowledgements Dr Anne Finucane for commenting on the protocol Dr Melissa Bloomer advised us on use of the Caldwell criteria for assessing the quality of the articles included in this study. Shona MacNeilage at the NHS Greater Glasgow and Clyde library service helped develop the search strategies. References 1. Mair FS, Jani BD. Emerging trends and future research on the role of socioeconomic status in chronic illness and multimorbidity. The Lancet Public health. 2020;5(3):e128-e9. 2. Santos Salas A, Watanabe SM, Tarumi Y, Wildeman T, Hermosa García AM, Adewale B, et al. Social disparities and symptom burden in populations with advanced cancer: specialist palliative care providers’ perspectives. Supportive Care in Cancer. 2019. 3. Marmot MA, J; Boyce, T; Goldblatt, P; Morrison, J. Health Equity in England: The Marmot Review 10 Years On. Institute of Health Equity. 2020. 4. Singh GK, Jemal A. Socioeconomic and Racial/Ethnic Disparities in Cancer Mortality, Incidence, and Survival in the United States, 1950–2014: Over Six Decades of Changing Patterns and Widening Inequalities. Journal of Environmental and Public Health. 2017;2017:2819372. 5. Hastert TA, Beresford SA, Sheppard L, White E. Disparities in cancer incidence and mortality by area-level socioeconomic status: a multilevel analysis. J Epidemiol Community Health. 2015;69(2):168-76. 6. Office for National Statistics. National Survey of Bereaved People (VOICES) 2015: Quality of care delivered in the last 3 months of life for adults who died in England. 2016. 7. Davies JM, Sleeman KE, Leniz J, Wilson R, Higginson IJ, Verne J, et al. Socioeconomic position and use of healthcare in the last year of life: A systematic review and meta-analysis. PLoS medicine. 2019;16(4):e1002782. 8. Asaria M, Doran T, Cookson R. The costs of inequality: whole-population modelling study of lifetime inpatient hospital costs in the English National Health Service by level of neighbourhood deprivation. J Epidemiol Community Health. 2016;70(10):990-6. 9. Macfarlane M, Carduff E. Does place of death vary by deprivation for patients known to specialist palliative care services? BMJ Support Palliat Care. 2018;8(4):428-30. 10. Buck J, Webb L, Moth L, Morgan L, Barclay S. Persistent inequalities in Hospice at Home provision. BMJ Support Palliat Care. 2020;10(3):e23. 11. Mason B, Kerssens JJ, Stoddart A, Murray SA, Moine S, Finucane AM, et al. Unscheduled and out-of-hours care for people in their last year of life: a retrospective cohort analysis of national datasets. BMJ Open. 2020;10(11):e041888. 12. Barratt H, Asaria M, Sheringham J, Stone P, Raine R, Cookson R. Dying in hospital: socioeconomic inequality trends in England. Journal of Health Services Research & Policy. 2017;22(3):149-54. 13. Neergaard MA, Brunoe AH, Skorstengaard MH, Nielsen MK. What socio-economic factors determine place of death for people with life-limiting illness? A systematic review and appraisal of methodological rigour. Palliative medicine. 2019;33(8):900-25. 14. Sleeman KE, Davies JM, Verne J, Gao W, Higginson IJ. The changing demographics of inpatient hospice death: Population-based cross-sectional study in England, 1993–2012. Palliative medicine. 2016;30(1):45-53. 15. Gao W, Ho YK, Verne J, Glickman M, Higginson IJ. Changing patterns in place of cancer death in England: a population-based study. PLoS Med. 2013;10(3):e1001410. 16. Koffman J, Burke G, Dias A, Raval B, Byrne J, Gonzales J, et al. Demographic factors and awareness of palliative care and related services. Palliat Med. 2007;21(2):145-53. 17. Dixon JK, D; Matosevic,T; Clark, C; Knapp, K. Equity in the provision of palliative care in the UK: review of evidence. Personal Social Services Research Unit, London School of Economics and Political Science, London. 2015. 18. Davies JM, Maddocks M, Chua KC, Demakakos P, Sleeman KE, Murtagh FEM. Socioeconomic position and use of hospital-based care towards the end of life: a mediation analysis using the English Longitudinal Study of Ageing. The Lancet Public health. 2021;6(3):e155-e63. 19. Walsh B, Laudicella M. Disparities In Cancer Care And Costs At The End Of Life: Evidence From England's National Health Service. Health affairs (Project Hope). 2017;36(7):1218-26. 20. Gott M, Allen R, Moeke-Maxwell T, Gardiner C, Robinson J. 'No matter what the cost': A qualitative study of the financial costs faced by family and whānau caregivers within a palliative care context. Palliat Med. 2015;29(6):518-28. 21. Turner V, Flemming K. Socioeconomic factors affecting access to preferred place of death: A qualitative evidence synthesis. Palliat Med. 2019;33(6):607-17. 22. Lewis JM, DiGiacomo M, Currow DC, Davidson PM. Dying in the margins: understanding palliative care and socioeconomic deprivation in the developed world. Journal of pain and symptom management. 2011;42(1):105-18. 23. Rowley J, Richards N, Carduff E, Gott M. The impact of poverty and deprivation at the end of life: a critical review. Palliative Care and Social Practice. 2021;15:26323524211033873. 24. Whittemore R, Knafl K. The integrative review: updated methodology. Journal of advanced nursing. 2005;52(5):546-53. 25. Carduff E, Bowers SP, Chin M, O'Riordan M,. The experiences of people living with socio-economic deprivation who are approaching the end of life: an integrative review. 2019 [Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019151906 (last accessed 21st January 2022). 26. 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. J Clin Epidemiol. 2021;134:178-89. 27. National Institute for Health and Care Excellence. End of life care for adults: service delivery NICE guideline [NG142] 2017 [Available from: https://www.nice.org.uk/guidance/ng142 [accessed 17th January 2022]. 28. Rietjens JA, Bramer WM, Geijteman EC, van der Heide A, Oldenmenger WH. Development and validation of search filters to find articles on palliative care in bibliographic databases. Palliative medicine. 2019;33(4):470-4. 29. Martin D, Brigham P, Roderick P, Barnett S, Diamond I. The (mis)Representation of Rural Deprivation. Environment and Planning A: Economy and Space. 2000;32(4):735-51. 30. Galobardes B, Shaw M, Lawlor DA, Lynch JW. Indicators of socioeconomic position (part 2). Journal of epidemiology and community health. 2006;60(2):95. 31. Galobardes B, Shaw M, Lawlor DA, Lynch JW, Smith GD. Indicators of socioeconomic position (part 1). Journal of Epidemiology & Community Health. 2006;60(1):7-12. 32. Nelson KE, Wright R, Peeler A, Brockie T, Davidson PM. Sociodemographic Disparities in Access to Hospice and Palliative Care: An Integrative Review. American Journal of Hospice and Palliative Medicine®. 2021;38(11):1378-90. 33. Mondor L, Wodchis WP, Tanuseputro P. Persistent socioeconomic inequalities in location of death and receipt of palliative care: A population-based cohort study. Palliative Medicine. 2020;34(10):1393-401. 34. French M, Keegan T, Anestis E, Preston N. Exploring socioeconomic inequities in access to palliative and end-of-life care in the UK: a narrative synthesis. BMC Palliat Care. 2021;20(1):179. 35. World Bank. World Bank List of Economies (June 2020) [Available from: https://databank.worldbank.org/data/download/site-content/CLASS.xls (last accessed 21st January 2022). 36. Caldwell K, Henshaw L, Taylor G. Developing a framework for critiquing health research: An early evaluation. Nurse Education Today. 2011;31(8):e1-e7. 37. Bloomer MJ, Hutchinson AM, Brooks L, Botti M. Dying persons’ perspectives on, or experiences of, participating in research: An integrative review. Palliative Medicine. 2018;32(4):851-60. 38. Azhar A, Yennurajalingam S, Ramu A, Zhang H, Haider A, Williams JL, et al. Timing of referral and characteristics of uninsured, Medicaid, and insured patients referred to the outpatient supportive care center at a comprehensive cancer center. Journal of pain and symptom management. 2018;55(3):973-8. 39. Dhingra L, Dieckmann NF, Knotkova H, Chen J, Riggs A, Breuer B, et al. A high-touch model of community-based specialist palliative care: latent class analysis identifies distinct patient subgroups. Journal of pain and symptom management. 2016;52(2):178-86. 40. Tang ST, Lin KC, Chen JS, Chang WC, Hsieh CH, Chou WC. Threatened with death but growing: changes in and determinants of posttraumatic growth over the dying process for Taiwanese terminally ill cancer patients. Psycho‐Oncology. 2015;24(2):147-54. 41. Cervantez SR, Tenner LL, Schmidt S, Aduba IO, Jones JT, Ali N, et al. Symptom burden and palliative referral disparities in an ambulatory South Texas cancer center. Frontiers in oncology. 2018;8:443. 42. Maric DM, Jovanovic DM, Golubicic IV, Nagorni-Obradovic LJ, Stojsic JM, Pekmezovic TD. Psychological well-being in advanced NSCLC patients in Serbia: impact of sociodemographic and clinical factors. Neoplasma. 2010;57(1):1-7. 43. Chochinov HM, Hassard T, McClement S, Hack T, Kristjanson LJ, Harlos M, et al. The landscape of distress in the terminally ill. J Pain Symptom Manage. 2009;38(5):641-9. 44. Carr D. Is Death “The Great Equalizer”? The Social Stratification of Death Quality in the United States. The ANNALS of the American Academy of Political and Social Science. 2016;663(1):331-54. 45. Saphire ML, Prsic EH, Canavan ME, Wang SJ, Presley CJ, Davidoff AJ. Patterns of Symptom Management Medication Receipt at End-of-Life Among Medicare Beneficiaries With Lung Cancer. J Pain Symptom Manage. 2020;59(4):767-77.e1. 46. Jacob J, Palat G, Verghese N, Chandran P, Rapelli V, Kumari S, et al. Health-related quality of life and its socio-economic and cultural predictors among advanced cancer patients: Evidence from the APPROACH cross-sectional survey in Hyderabad-India. BMC palliative care. 2019;18(1):94. 47. Sahin ZA, Tan M, Polat H. Hopelessness, depression and social support with end of life Turkish cancer patients. Asian Pacific Journal of Cancer Prevention. 2013;14(5):2823-8. 48. Lewis JM, DiGiacomo M, Currow DC, Davidson PM. Social capital in a lower socioeconomic palliative care population: a qualitative investigation of individual, community and civic networks and relations. BMC palliative care. 2014;13(1):30. 49. Adler SR, Coulter YZ, Stone K, Glaser J, Duerr M, Enochty S. End-of-life concerns and experiences of living with advanced breast cancer among medically underserved women. Journal of pain and symptom management. 2019;58(6):959-67. 50. Yi D, Johnston BM, Ryan K, Daveson BA, Meier DE, Smith M, et al. Drivers of care costs and quality in the last 3 months of life among older people receiving palliative care: A multinational mortality follow-back survey across England, Ireland and the United States. Palliative Medicine. 2020;34(4):513-23. 51. Leng A, Jing J, Nicholas S, Wang J. Catastrophic health expenditure of cancer patients at the end-of-life: a retrospective observational study in China. BMC palliative care. 2019;18(1):43. 52. Daugaard C, Neergaard MA, Vestergaard AHS, Nielsen MK, Johnsen SP. Socioeconomic inequality in drug reimbursement during end-of-life care: a nationwide study. J Epidemiol Community Health. 2019;73(5):435-42. 53. Saeed F, Xing G, Tancredi DJ, Epstein RM, Fiscella KA, Norton SA, et al. Is Annual income a predictor of completion of advance directives (ADs) in patients with cancer. American Journal of Hospice and Palliative Medicine®. 2019;36(5):402-7. 54. Carlucci A, Vitacca M, Malovini A, Pierucci P, Guerrieri A, Barbano L, et al. End-of-life discussion, patient understanding and determinants of preferences in very severe COPD patients: A multicentric study. COPD: Journal of Chronic Obstructive Pulmonary Disease. 2016;13(5):632-8. 55. Tang ST, Liu TW, Chow JM, Chiu CF, Hsieh RK, Chen CH, et al. Associations between accurate prognostic understanding and end-of-life care preferences and its correlates among Taiwanese terminally ill cancer patients surveyed in 2011-2012. Psychooncology. 2014;23(7):780-7. 56. Schou-Andersen M, Ullersted MP, Jensen AB, Neergaard MA. Factors associated with preference for dying at home among terminally ill patients with cancer. Scand J Caring Sci. 2016;30(3):466-76. 57. Wales J, Kalia S, Moineddin R, Husain A. The Impact of Socioeconomic Status on Place of Death Among Patients Receiving Home Palliative Care in Toronto, Canada: A Retrospective Cohort Study. J Palliat Care. 2020;35(3):167-73. 58. Brown CE, Engelberg RA, Sharma R, Downey L, Fausto JA, Sibley J, et al. Race/ethnicity, socioeconomic status, and healthcare intensity at the end of life. Journal of palliative medicine. 2018;21(9):1308-16. 59. Huang C-Y, Hung Y-T, Chang C-M, Juang S-Y, Lee C-C. The association between individual income and aggressive end-of-life treatment in older cancer decedents in Taiwan. PloS One. 2015;10(1):e0116913. 60. Tucker‐Seeley RD, Abel GA, Uno H, Prigerson H. Financial hardship and the intensity of medical care received near death. Psycho‐Oncology. 2015;24(5):572-8. 61. Chang C-M, Wu C-C, Yin W-Y, Juang S-Y, Yu C-H, Lee C-C. Low socioeconomic status is associated with more aggressive end-of-life care for working-age terminal cancer patients. The oncologist. 2014;19(12):1241. 62. Koroukian SM, Schiltz NK, Warner DF, Given CW, Schluchter M, Owusu C, et al. Social determinants, multimorbidity, and patterns of end-of-life care in older adults dying from cancer. Journal of geriatric oncology. 2017;8(2):117-24. 63. Krishnan P, Thompson G, McClement S. Predicting hospital transfers among nursing home residents in the last months of life. International Journal of Palliative Nursing. 2017;23(11):535-42. 64. Karikari-Martin P, McCann JJ, Farran CJ, Hebert LE, Haffer SC, Phillips M. Race, Any Cancer, Income, or Cognitive Function: What Inf luences Hospice or Aggressive Services Use at the End of Life Among Community-Dwelling Medicare Beneficiaries? Am J Hosp Palliat Care. 2016;33(6):537-45. 65. Bergman J, Chi AC, Litwin MS. Quality of end-of-life care in low-income, uninsured men dying of prostate cancer. Cancer. 2010;116(9):2126-31. 66. Khosla N, Curl AL, Washington KT. Trends in Engagement in Advance Care Planning Behaviors and the Role of Socioeconomic Status. Am J Hosp Palliat Care. 2016;33(7):651-7. 67. Ankuda CK, Kersting K, Guetterman TC, Haefner J, Fonger E, Paletta M, et al. What matters most? A mixed methods study of critical aspects of a home-based palliative program. American Journal of Hospice and Palliative Medicine®. 2018;35(2):236-43. 68. Cai J, Guerriere DN, Zhao H, Coyte PC. Socioeconomic differences in and predictors of home-based palliative care health service use in Ontario, Canada. International journal of environmental research and public health. 2017;14(7):802. 69. Neergaard MA, Olesen F, Sondergaard J, Vedsted P, Jensen AB. Are Cancer Patients' Socioeconomic and Cultural Factors Associated with Contact to General Practitioners in the Last Phase of Life? Int J Family Med. 2015;2015:952314. 70. Bhatraju P, Friedenberg AS, Uppal A, Evans L. Factors associated with utilization of an inpatient palliative care consultation service in an urban public hospital. American Journal of Hospice and Palliative Medicine®. 2014;31(6):641-4. 71. Masucci L, Guerriere DN, Zagorski B, Coyte PC. Predictors of health service use over the palliative care trajectory. Journal of palliative medicine. 2013;16(5):524-30. 72. Bijnsdorp FM, Pasman HRW, Francke AL, Evans N, Peeters CF, van Groenou MIB. Who provides care in the last year of life? A description of care networks of community-dwelling older adults in the Netherlands. BMC palliative care. 2019;18(1):41. 73. Lee JJ, Long AC, Curtis JR, Engelberg RA. The Influence of Race/Ethnicity and Education on Family Ratings of the Quality of Dying in the ICU. J Pain Symptom Manage. 2016;51(1):9-16. 74. Chang YJ, Kwon YC, Lee WJ, Do YR, Seok LK, Kim HT, et al. Burdens, needs and satisfaction of terminal cancer patients and their caregivers. Asian Pacific journal of cancer prevention : APJCP. 2013;14(1):209-16. 75. Fergus C, Chinn D, Murray S. Assessing and improving out-of-hours palliative care in a deprived community: a rapid appraisal study. Palliative Medicine. 2010;24(5):493-500. 76. Stajduhar KI, Mollison A, Giesbrecht M, McNeil R, Pauly B, Reimer-Kirkham S, et al. “Just too busy living in the moment and surviving”: barriers to accessing health care for structurally vulnerable populations at end-of-life. BMC Palliative Care. 2019;18(1):1-14. 77. Aoun S, Bentley B, Funk L, Toye C, Grande G, Stajduhar KJ. A 10-year literature review of family caregiving for motor neurone disease: Moving from caregiver burden studies to palliative care interventions. Palliative Medicine. 2013;27(5):437-46. 78. Sleeman KE, Davies JM, Verne J, Gao W, Higginson IJ. The changing demographics of inpatient hospice death: Population-based cross-sectional study in England, 1993-2012. Palliat Med. 2016;30(1):45-53. 79. McFadden A, Siebelt L, Gavine A, Atkin K, Bell K, Innes N, et al. Gypsy, Roma and Traveller access to and engagement with health services: a systematic review. European journal of public health. 2018;28(1):74-81. 80. Scotland Public Health. Proportionate Universalism Briefing. 17/10/2014. 81. Sadler E, McKevitt C. 'Expert carers': An emergent normative model of the caregiver. Social Theory & Health. 2012;11(1):40-58. 82. Gov.uk. Income-related benefits: estimates of take-up [Available from: https://www.gov.uk/government/collections/income-related-benefits-estimates-of-take-up--2 (last accessed 21st January 2022). 83. Williams C. Chronic illness and informal carers: 'Non-persons' in the health system, neither carers, workers or citizens. Health Sociology Review. 2012;21(1):58-68. 84. Tucker-Seeley RD, Abel GA, Uno H, Prigerson H. Financial hardship and the intensity of medical care received near death. Psychooncology. 2015;24(5):572-8. 85. Scottish Government. Coronavirus (COVID-19): impact on equality [updated 17/09/2020. Available from: https://www.gov.scot/publications/the-impacts-of-covid-19-on-equality-in-scotland/. 86. Carmody P, McCan G, Colleran C, O'Halloran C. COVID-19 in the Global South: Impacts and Responses. 2020 21/10/2020. 87. Organisation for Economic Co-operation and Development. A systemic resilience approach to dealing with Covid-19 and future shocks [Available from: https://www.oecd.org/coronavirus/policy-responses/a-systemic-resilience-approach-to-dealing-with-covid-19-and-future-shocks-36a5bdfb/ (last accessed 21st January 2022). 88. Public Health Scotland. The Carstairs and Morris Index [Available from: https://www.isdscotland.org/Products-and-services/Gpd-support/Deprivation/Carstairs/ (last accessed 17th January 2022). 89. Oakes JM, Rossi PH. The measurement of SES in health research: current practice and steps toward a new approach. Social science & medicine. 2003;56(4):769-84. Table Table 3 Summary of included studies. Author Aim Setting (and country) Sample Study Design and method Main Findings Quality Score Daugaard et al (2019) To examine the association between social and socioeconomic position and drug reimbursement due to terminal illness (DRTI) registration among patients who are terminally ill in Denmark. Population-based (Denmark) Terminally ill patients who died 2006 – 2015 with cancer or seven other chronic illnesses (n=307188). Quantitative Database analysis No association between education and DRTI.  Higher prevalence of DRTI in middle/high income patients, however palliative care needs may be under-recognised in low income patients.  Lower prevalence of DRTI in employed patients. 11 Ankuda et al (2018) To identify what services are critical and why they matter to patients in a home-based palliative program. Hospice – home based program (US)  Enrollees in the program (n=18). Mixed   Individual interviews and survey  Participants living in poverty had more non-routine and social work visits and found the social services provided by a home hospice service to be the most critical aspect of care. 9 Azhar et al (2018) To compare time of referral and characteristics (level of symptom distress) among uninsured (indigent), low-insured (Medicaid), and insured patients presenting to the supportive care center. Outpatient center (US) Patients with advanced cancer (500)  Quantitative   Survey to participants Uninsured and low/partially insured patients had higher ESAS pain scores Indigent patients had:      More encounters with palliative care team per month      Higher levels of distress      Higher risk for aberrant opioid usage and       More frequently on opioids at time of referral to centre Insurance status did not impact timing of palliative care referral or follow-up. 10 Brown et al (2018) To examine the association between race/ethnicity, other key social determinants of health, and healthcare intensity in the last 30 days of life for those with chronic, life-limiting illness. Population-based (US) All patients who died from 1 of 9 chronic conditions between January 2010 and December 2015 (n=22068). Quantitative   Database analysis Lower income was associated with higher likelihood of receiving high intensity care (i.e., treatment in an intensive care unit, receipt of mechanical ventilation, receipt of cardiopulmonary resuscitation) in the last 30 days of life. 11 Cervantez et al (2018) To evaluate how insurance coverage and ethnicity impact distribution of symptom burden and how those factors influence palliative access for patients at a South Texas cancer center. Outpatient center (US). Patients who attended clinics (n=604). Quantitative   Survey to participants. Symptom burden was similar in insured and uninsured patients, but there was a four-fold delay in first palliative care visit in uninsured group. 8 Saeed et al (2018) To test the hypothesis that men and those with lower levels of educational attainment would have less favourable attitudes towards palliative care. Community and hospital-based cancer clinics (US) Patients with cancer (n=383). Quantitative   Secondary analysis of pre-existing VOICES dataset. Most patients would desire palliative care if no further anti-cancer treatment would be helpful. No difference in preferences between those with different levels of education. 11 Cai et al (2017) To examine the socioeconomic differences in the propensity and intensity of health service use for the three main home-based services (physician visits, nurse visits and personal support worker hours), and to explore the determinants of the use of home-based palliative care services. Home-based palliative care program (Canada) Adult primary caregivers of patients who were diagnosed with malignant neoplasm (n=181). Quantitative   Survey administered to participants.     Patients with lower socioeconomic status were more likely to receive at least one home-based nurse visit or personal support worker (PSW) visit. Lower socioeconomic status was associated with higher intensity of health service use. Socioeconomic status is a significant predictor of propensity and intensity of home-based nurse and PSW visit even after controlling for health status. Patients with higher levels of education were less likely to receive at least one home-based PSW visit. 11 Koroukian et al (2017) To gain a better understanding of the correlates of aggressive end-of-life care and hospice use in older adults dying from cancer, by accounting for both social determinants of health and multimorbidity. Population-based (US) Participants <66 years who died from cancer with complete Medicare claims history (n=835). Quantitative  Database analysis. Percentage of patients receiving cancer-directed treatment increased with higher education and income. No significant difference by income or education for admission to hospital. Enrolment in hospice was generally higher with higher levels of education or income. There was a U-shaped distribution between in-hospital death and income and education. 10 Krishnan et al (2017) To examine the family and facility factors that may influence the decision to transfer nursing home residents to hospital in the last month of life. Nursing homes (Canada) Adult relatives of residents who had died in the past year and was self-reported as the most involved in their care in their last month of life (n=119). Quantitative   Survey to participants. There was a higher prevalence of hospital transfers among deceased whose family members had lower income. Low income family members were 3 times more likely to send patient to hospital.  No statistically significant relationship was noted between employment or education level of the family members and terminal hospital transfers. 11 Carlucci et al (2016) To elicit the patients’ end-of-life preferences in very severe chronic obstructive pulmonary disease. Hospital (Italy) Patients with very severe COPD (n=43). Mixed   Individual interview Survey to participants. Patients with lower education were more likely to choose endotracheal tube intubation. Higher education level is the strongest predictor of probability of choosing palliative care option with oxygen and morphine. 9 Dhingra et al (2016) To evaluate a diverse population served by an interdisciplinary model of community-based specialist palliative care and the variation in service delivery over time and identify subgroups with distinct illness burden profiles. Community palliative care program (US) Patients referred to the program (n=894). Quantitative   Survey to participants. Patients who reported very low illness burden more likely to reside in impoverished neighbourhoods. 11 Karikari-Martin et al (2016) To examine whether differences in hospice use and use of aggressive services in the last 12 months of life are influenced by race or any cancer diagnosis while adjusting for the covariates age, gender, marital status, education level, neighbourhood socioeconomic status, cognitive function, and physical function. A geographically-defined community in Chicago (US) Participants <65 years enrolled Medicare for at least 1 year before death (n=2954). Quantitative   Secondary analysis of pre-existing CHAP data. Higher neighbourhood level socioeconomic status and higher income each significantly increased the likelihood of using hospice. Race has a more powerful effect on hospice use than socioeconomic status neighbourhood.  Higher education was associated with a significantly decreased risk of hospitalization at the end of life. 10 Khosla et al (2016) To investigate the association between socioeconomic status (i.e., education and household income) and anticipatory care planning (ACP) over time using data from the Health and Retirement Study (HRS), a nationally representative survey of middle-aged and older adults living in the contiguous United States. Health and Retirement Study (HRS) (US) Spouses, partners or proxy informants of HRS respondents (n=6052). Quantitative   Survey to participants. Very limited support was found for the hypothesis that socioeconomic status would predict ACP. Higher household income increased the odds of having a legally designated power of attorney for health care but had no impact on end of life discussions or written instructions. Education level did not predict engagement in ACP behaviours. 10 Lee et al (2016) To understand the association of minority race/ethnicity and education with family ratings of the quality of dying and death. Hospital Intensive Care Units (US) Families of patients who died (n=1290). Quantitative   Survey to participants. Education was not significantly associated with ratings on the quality of death questionnaire for either patient or family models.   11 Schou-Andersen et al (2016) To investigate whether demographic and socio-economic factors were associated with preference for dying at home. Community (Denmark) Relatives of adults who died from cancer (n=282). Quantitative   Survey to participants, database analysis.   At the beginning of palliative period, low income patients more likely to prefer dying at home than high income patients, however medium income patients less likely. At the end of the palliative period, no association between preference for dying at home and income. 11 Huang et al (2016) To examine the association of individual income and end-of-life care in older cancer decedents in Taiwan. Population-based (Taiwan) Adults aged over 65 years with cancer (n=28978). Quantitative  Database analysis. Low income was associated with more aggressive end of life care. Older cancer decedents with low income were more likely to stay in hospital <14 days and die in acute hospital. Older cancer decedents with moderate/high income were more likely to have visited the emergency department and admitted to intensive care more frequently. 10 Neergaard et al (2015) To analyse associations between GP contacts at the end of life and socioeconomic and cultural characteristics of Danish cancer patients. Community (Denmark) Relatives of adults who died from cancer (n=584). Quantitative   Secondary analysis of pre-existing dataset. GP face-to-face appointments were higher for decedents with cancer who had low income than those with normal/high income. 11 Tang et al (2015) To describe longitudinal changes in post-traumatic growth (PTG) during the dying process and to identify determinants of PTG among terminally ill cancer patients. Hospital inpatient units (Taiwan) Terminally ill cancer patients (n=313). Quantitative   Survey to participants. Patients with at least senior high school education achieved higher post-traumatic growth scores than those with low education. 11 Tucker-Seeley et al (2015) To investigate the association between financial hardship and intensive care in the last week of life. Cancer Centers, as part of the Coping with Cancer (CwC) study (US) Caregivers of deceased cohort (n=281). Quantitative   Secondary analysis of pre-existing CwC data. Patients who reported financial hardship had higher odds of receiving intensive end of life care. No association between educational attainment or health insurance status and aggressive end of life care. When treatment preferences were included in the fully adjusted model, the association between financial hardship and intensive EOLC was slightly attenuated but remained statistically significant. 11 Bhatraju et al (2014) To evaluate the factors that were associated with palliative care consultation (PCC) utilization in patients who died in an urban municipal public hospital in the United States, and to examine the association of PCC utilization with symptom management and advance directives at the end of life. Hospital – Inpatients (US) Patients who died in the units (n=378). Quantitative   Retrospective chart review. Higher level of education was associated with palliative care consultation (PCC) utilisation. Patients who had PCC were more likely to receive opiates in final 72 hours of life, but there was no observed difference in benzodiazepine use. 9 Chang et al (2014) To assess the association between aggressiveness of end-of-life care and socioeconomic status in working-age terminal cancer patients in Taiwan between 2009 and 2011. Population-based (Taiwan) Adult cancer patients (n=32800). Quantitative   Database analysis. High and moderate socioeconomic status patients had:            Lower scores for aggressive end of life care      Less chemotherapy      Fewer emergency department visits      Less intensive care unit admission      Lower rates of dying in acute care hospitals. 11 Lewis et al (2014) To explore the nature of social capital in a socioeconomically disadvantaged group of palliative care patients and carers, using a social capital questionnaire to guide and frame discussions. Community (Australia) Patients who were known to the palliative care service (n=22). Qualitative   Individual interviews Overall provision of informal care generally by sole caregiver with intermittent family support. Established neighbour and inter-sectoral networks essential for sustaining care and social needs  Did not feel very engaged with community. Limited communication due to cultural differences  Formalised community care support described as overall being somewhat inconsistent and unpredictable. Patients and carers unsure of formal care being provided. Contact with government agencies (welfare support and government housing) described as positive generally 11 Tang et al (2014) To investigate the associations between accurate prognostic understanding and end-of-life care preferences, and to identify correlates of accurate prognostic understanding among terminally ill cancer patients. Hospital (Taiwan) Terminally ill cancer patients (n=2452). Quantitative   Survey to participants. Patients with at least senior high school education were 1.28 times more likely to accurately know prognosis. Accurate prognostic understanding associated with greater odds of preferring comfort-oriented care and increased preference for hospice care. 11 Chang et al (2013) To describe how much burden terminal cancer patients and their caregivers had experienced, what support they most needed, and the differences between them. Hospital (South Korea)   Patients with terminal cancer (n=481) and their caregivers (n=381). Quantitative   Survey to participants. Low level of education predicted satisfaction about overall care. 11 Masucci et al (2013) To examine the predictors of the propensity and intensity of five main health service categories in the last three months of life for home-based palliative-care patients. Community. Home-based (Canada) Family caregivers of patients with malignant neoplasm (n=109). Quantitative   Individual interviews, database analysis. Patients in the highest deprivation group had higher intensity of home-based nurse visits. 11 Sahin et al (2013) To evaluate the relationship between different demographic variables and hopelessness, depression and social support in end of life Turkish cancer patients. Hospital (Turkey) Patients with cancer (n=216). Quantitative   Survey to participants. Patients with lower education had higher hopelessness scores, but not depression or social support. 11 Bergman et al (2010) To assess the quality of end of life care in low income uninsured men prospectively enrolled in a specific public assistance program. Population-based (US) All low-income, uninsured men in the program (n=60). Quantitative   Retrospective chart review, database analysis.   No patients had chemotherapy initiated within 3 months of death, and only 6% had chemo within 2 weeks of death. Use of hospital resources (emergency department visits, inpatient admissions, intensive care) was uniformly low. Hospice utilisation was comparable and timing of referral was better than population. 8 Fergus et al (2010) To identify key challenges and improvements to out-of-hours palliative care in a mixed urban and rural deprived area. Community (United Kingdom) Mixed; Patients (n=6), carers (n=1) and healthcare professionals (29) Mixed   Individual interviews, database analysis, observation Patients voiced reluctance to use Out of hours primary care phoneline due to:      Stressful and cumbersome process of making initial   contact      Bad experiences previously       Misunderstanding of its function      Reluctance to speak to an unknown person      Had bad experiences previously      Did not realise had ‘special notes’ so assumed would be too complex 11 Maric et al (2010) To estimate the frequency of anxiety and depression symptoms in patients with advanced lung cancer, and the associations of these with demographic, socioeconomic and clinical factors. Hospital (Serbia) Patients with stage 3B and 4 non-small cell lung cancer (n=100). Quantitative Survey to participants. No difference in levels of psychological distress between education groups or rural versus urban groups. However, unemployed patients had significantly less anxiety and depressive symptoms. 9 Chochinov et al (2009) To use the Patient Dignity Inventory (PDI), a novel, reliable and validated measure of end-of-life distress, to describe a broad landscape of distress in patients who are terminally ill. Population-based (Canada) Patients in this program who received palliative care (n=253). Quantitative   Survey to participants. Patients who were more educated were significantly more likely to report feelings of having lost control, feelings of unfinished business and not being able to perform tasks of daily living. 10 Carr et al (2016) To explore the extent to which socioeconomic status indicators are associated with attributes considered essential to the quality of one's death. Population-based (US) Mixed; Bereaved spouses (n=408), patients (n=5276)  Quantitative   Secondary analysis of pre-existing datasets. Limited evidence that socioeconomic status affects death quality, except in pain at the end of life. Wealthier participants were less likely to report severe pain at the end of life, and are more likely to engage in advanced care planning. 10 Adler et al (2019) To explore the lived experiences of medically underserved women with advanced breast cancer. Community – clinic (US)  Patients with breast cancer and annual family income below 200% of the federal poverty level (n=63). Qualitative   Individual interviews Consistent issue of financial distress at the end of life, including difficulty meeting basic needs, inadequate financial resources, inability to work. Patients had concerns about not being “useful” when unemployed and being financially burdensome Perceived bias in healthcare – some patients felt they were not treated as well by healthcare professionals Patients viewed fewer financial means, lack of access to private insurance and cancer centres, and minority status as barriers to high quality care. They remained highly attentive to others’ needs and worked to maintain caretaking roles despite own struggles. They made effort to attend to practical matters. Many downplayed desires to discuss dying due to pressure of staying positive. They appreciated meaningful aspects of life (social relationships, creative outlets, spirituality) and felt altruism was important before and during illness. 10 Bijnsdorp et al (2019) To identify different types of home-based care networks of community dwelling older adults in the Netherlands, and to assess the association between the different types of home based care networks and the health status and sociodemographic characteristics of care recipients. Community (Netherlands) Respondents who died within 12 months of their last interview, lived at home, and received personal and/or household care (n=146). Quantitative   Survey to participants Those with higher education were more likely to have informal care provided by partners whereas those with lower educational attainment more likely to require formal care. 11 Davidoff et al (2020) To examine patterns of symptom management at end of life for older adults who died of lung cancer. Population-based (US) Individuals who had at least one day in the outpatient non-hospice setting during the last month before death (n=16246),  Quantitative   Database analysis High poverty levels were associated with increased receipt of pain, dyspnoea and emotional distress medication. 10 Yi et al (2020) To compare health and social care costs, quality and their drivers in the last 3 months of life for older adults across countries. Hospital and Community (UK, Ireland, US) Carers of patients who had accessed a participating palliative care team (n=767) Quantitative   Survey to participants   Only 4% reported difficult/very difficult financial circumstances, 10% reported just about alright. Higher care costs if “difficulty living on current income”. Hospital care accounts for over 80% total health and social costs, community and palliative costs were low. 11 Jacob et al (2019) To assess health related quality of life (HRQoL) of advanced cancer patients in terms of general wellbeing (physical, functional, emotional, and social/family wellbeing), pain experiences, psychological state, and spiritual wellbeing, and determine the relationship between belonging to a disadvantaged group and HRQoL outcomes. Hospital (India) Patients with cancer (n=210). Quantitative   Survey to participants Patients with higher financial difficulty scores reported lower functional wellbeing, lower emotional wellbeing, lower meaning/peace (subscale of spiritual wellbeing), and higher anxiety and depression scores. Level of education did not affect this. Even in setting where cancer treatment is free, those with higher financial difficulty scores report lower quality of life outcomes. Scores of this population generally lower than patients in higher income countries e.g., USA. 11 Leng et al (2019) To explore the prevalence, determinants and consequences of catastrophic health expenditure (CHE) among urban and rural end-of-life cancer patients in China. Community (China) Families of deceased cancer patients (n=792). Quantitative   Face to face interviews There were very high levels of catastrophic healthcare expenditure (CHE) at end of life throughout. 1/3 of patients borrowed money from family and friends. Households with higher income were less likely to incur CHE. Rural, low income patients were least likely to access healthcare, inpatient care, and most likely to only use outpatient care. Use of inpatient and outpatient services in these patients increased the risk of CHE. Rural patients allocated higher proportion of household income to healthcare and associated expenditures. 11 Saeed et al (2019) To study the effect of income and education on the completion of advanced directives. Community and hospital (US) Patients with cancer (n=265) Quantitative   Secondary analysis of pre-existing VOICE dataset. Nearly a third of lower income patients had not completed advanced directives (AD). Patients with lower income had lower AD scores, but there was no significant association between education or perceived financial strain and AD scores. 11 Stajduhar et al (2019) To identify barriers to assessing care among structurally vulnerable people at the end of life. Community (Canada) Mixed; People experiencing structural vulnerability in a Western Canadian province (n=25), their support persons (n=25) and formal service providers (n=69).  Qualitative   Repeated participant observation, individual interviews  Structural vulnerability was defined in this study as people living in poverty, in unstable housing, while experiencing various forms of oppression and stigma, e.g., racism, ongoing or past trauma and violence, social isolation, mental and cognitive issues, behavioural issues, substance use, interactions with the criminal justice system, or physical disability.   These patients were found to have significant barriers in having their palliative needs met including:        Survival imperative – focussing on basic care needs;      Normalization of dying – often had been told they would die due to addictions      Problem of identification – often not signposted to appropriate health, social benefits      Professional risk and safety management – due to stigmatization from health care professionals      Cracks of a silo-ed care system – complexity of the care systems made them difficult to navigate. 10 Wales et al (2020) To examine the association between socioeconomic status and other demographic factors on place of death in a population receiving home palliative care in Toronto, Canada.  Community - Home palliative care service (Canada) Patients who died with home-based palliative care service (n=2066). Quantitative   Retrospective chart review Rate of preference for home death was significantly lower in lowest income quintile. 11 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 10 May, 2022 Reviews received at journal 16 Apr, 2022 Reviewers agreed at journal 03 Apr, 2022 Reviews received at journal 25 Mar, 2022 Reviewers agreed at journal 14 Mar, 2022 Reviewers invited by journal 05 Mar, 2022 Editor assigned by journal 25 Feb, 2022 Editor invited by journal 25 Feb, 2022 Submission checks completed at journal 25 Feb, 2022 First submitted to journal 27 Jan, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1302205","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":86542209,"identity":"3f4da137-d8d8-4256-b3c1-abe83ff8d3a8","order_by":0,"name":"Sarah P Bowers","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYJACZgaGA2AG44cKhgTStDBLnIFpIaATroWBt40ILfLtZx9+LmC4I2dwvPfxB8l5d/LkG9gffvj4A7cWgzPpxtIzGJ4ZG5w5biZRuO1ZscEBHmPJGXhsMWBIY5DmYTicuO1GGhuD5LbDiRsYeNiYefA5rP8Z82+wlvvPmD/wzjmcOL+B/RleLQxAw6G2sDFI8DYcTmw4wGCGV4vBjWds1jwGz4ztzwD1ShwDOuwwyC9p+ByWxnybp+KOnGT7MeaPH2qADmtvf/jhgw0eh0HsQuYwE1I9CkbBKBgFo4AgAADFdFEJSAT6cQAAAABJRU5ErkJggg==","orcid":"","institution":"NHS Tayside","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"P","lastName":"Bowers","suffix":""},{"id":86542210,"identity":"904fe711-3b23-4cae-963d-5b15314bf475","order_by":1,"name":"Ming Chin","email":"","orcid":"","institution":"University Hospital Wishaw","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"Chin","suffix":""},{"id":86542211,"identity":"1d690b95-b9b1-4f27-bc70-52f89635b866","order_by":2,"name":"Maire O'Riordan","email":"","orcid":"","institution":"Marie Curie Hospice, Glasgow","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maire","middleName":"","lastName":"O'Riordan","suffix":""},{"id":86542212,"identity":"ad827de7-0631-4fa5-950e-8f8117dcaf94","order_by":3,"name":"Emma Carduff","email":"","orcid":"","institution":"Marie Curie Hospice, Glasgow","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Emma","middleName":"","lastName":"Carduff","suffix":""}],"badges":[],"createdAt":"2022-01-27 10:14:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1302205/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1302205/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":18694280,"identity":"e9dbc24d-e524-473e-9554-d333c42dac25","added_by":"auto","created_at":"2022-02-28 16:42:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28360,"visible":true,"origin":"","legend":"\u003cp\u003ePrisma flow diagram of search results\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1302205/v1/f451e79ed1c948e9a14d8e74.png"},{"id":18694281,"identity":"6765766b-c75e-4b3c-82eb-b58a5000ac29","added_by":"auto","created_at":"2022-02-28 16:43:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":410729,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1302205/v1/87cea4f6-5a4e-41b3-a66f-0d8883c77326.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe End Of Life Experiences Of People Living With Socio-Economic Deprivation In The Developed World: An Integrative Review\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOn a global scale, it is now recognized that people experiencing socioeconomic deprivation (SED) are spending more of their shorter lives in ill health and are carrying a higher burden of chronic disease, multimorbidity and symptom burden than more affluent neighbours\u0026nbsp;(1-3). Socioeconomic deprivation is an independent risk factor for higher mortality in both cancer and non-cancer populations\u0026nbsp;(4-6)\u0026nbsp;and is associated with higher use and cost of healthcare in the last year of life\u0026nbsp;(7)\u0026nbsp;(8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven that people living with poverty are carrying this inequitable high burden of poor health outcomes, equal access to palliative care would be expected when compared with those in more affluent areas. However, it is now recognised that people with lower incomes have a potentially poorer experience at end-of-life (EOL)\u0026nbsp;(6), with reduced referral and access to specialist palliative care services in and out of hours\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(9, 10) (11), are more likely to use ambulance and A\u0026amp;E and to be admitted to and die in hospital (7, 12, 13), rather than at home or in a hospice (9, 10, 14-17). People with lower wealth have recently been found to have had more hospital admissions in the last two years of life(18) and this is often a substitute for elective, community-based healthcare services (19). Families living in poverty may need to compromise on food and heating and incur significant debts when someone dies (20) and report significantly less support and satisfaction with care received at the EOL (6). A qualitative evidence synthesis, undertaken in 2019, identified that access to preferred place of death was limited by human factors, such as social support, personal and cultural beliefs, poor communication, and environmental factors, such as suitability of the home environment and availability of resources within health and care services. (21). \u0026nbsp;An earlier review highlighted barriers such as accessibility, availability, affordability and acceptability (22).\u003c/p\u003e\n\u003cp\u003eAs quantitative evidence describing the disparity in access and delivery of palliative care between socioeconomic groups continues to grow, there is still little understanding of how people living in poverty experience living and dying with a life-limiting illness. This review feeds directly into ongoing empirical work to understand the experiences of home death for people at the EOL who are living with poverty (grant number and webpage). and complements a recently published paper by Rowley and colleagues which served as a call to action for researchers, policy-makers and clinicians working with people experiencing poverty at EOL (23). By understanding what inequalities and disparities persist, practitioners and policy makers can meaningfully address the issue at individual, institutional and societal levels and progress can be made to narrow the gap. The aim of this review is to describe current global evidence from developed countries on the experiences of people at the EOL who are living with SED.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eDesign\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAn integrative literature review approach was chosen to facilitate synthesising and concept building\u003csup\u003e\u0026nbsp;\u003c/sup\u003egiven the multiple evidence sources and methodologies. We conducted our review according to the methods described by Whittemore and Knafl\u0026nbsp;(24). This study was registered on PROSPERO (CRD42019151906)\u0026nbsp;(25)\u0026nbsp;and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses. (PRISMA)\u0026nbsp;(26)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDefinitions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe used the NICE definition for EOL which includes people who are likely to die within 12 months, with advanced, progressive, or incurable diseases or acute life-threatening conditions\u0026nbsp;(27). We also referred to Rietjens recent article to develop our search terms related to palliative care\u0026nbsp;(28). The definitions available for socioeconomic status are less distinct. Clear definitions are rare (i.e. the United Kingdom Index of Multiple Deprivation), do not encompass the complex nature of SED and are particularly poor at capturing rural SED\u0026nbsp;(29). We therefore reviewed the evidence on proxy indicators of SED in addition to systematic reviews of the same topic to devise the evidence-based list of search terms related to SED which are presented in table 1.\u0026nbsp;(7, 30, 31). This review did not include papers from developing countries given their unique challenges to resources and the delivery of healthcare.\u003c/p\u003e\n\u003cp\u003ePapers solely about access to palliative care services and place of death were excluded because we knew of recently published reviews about place of death and access (32) (13, 33, 34)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSearch strategy\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eKey search terms were agreed between SB and EC, with support from a librarian based at NHS Greater Glasgow \u0026amp; Clyde, and these were combined with standard Boolean operators (Table 1). The following databases were searched to capture the wide range of research and disciplines involved in SED at the EOL \u0026ndash; Medline, Embase, CINAHL, ASSIA and PsychInfo. The most relevant systematic review to describe palliative care in the context of SED was reported in 2010 (22) and thus we limited our search from January 2010 to March 2020. Inclusion and exclusion criteria were agreed to ensure we obtained relevant, original research (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 \u0026ndash; Search Terms\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Palliative care \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; AND \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Socio-economic SED\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"48.23196605374823%\"\u003e\n \n \u003cli\u003ePalliative care\u003c/li\u003e\n \u003cli\u003ePalliat*\u003c/li\u003e\n \u003cli\u003eTerminal care\u003c/li\u003e\n \u003cli\u003eTerminal* ill*\u003c/li\u003e\n \u003cli\u003eTerminal diagnos*\u003c/li\u003e\n \u003cli\u003eDying\u003c/li\u003e\n \u003cli\u003eAdvanced illness*\u003c/li\u003e\n \u003cli\u003eLife limit*\u003c/li\u003e\n \u003cli\u003eEOL\u003c/li\u003e\n \u003cli\u003eLast year of life\u003c/li\u003e\n \u003cli\u003eEOLC\u003c/li\u003e\n \u003cli\u003eAdvanced cancer\u003c/li\u003e\n \u003cli\u003eAdvanced progressive illness\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"51.76803394625177%\"\u003e\n \n \u003cli\u003eSocioeconomic factor*\u003c/li\u003e\n \u003cli\u003eLow income\u003c/li\u003e\n \u003cli\u003eSocial class*\u003c/li\u003e\n \u003cli\u003eSocial depriv*\u003c/li\u003e\n \u003cli\u003eWorking class*\u003c/li\u003e\n \u003cli\u003eSocial* disadvantage*\u003c/li\u003e\n \u003cli\u003eLow education\u003c/li\u003e\n \u003cli\u003eUneducated\u003c/li\u003e\n \u003cli\u003eSocial inequal*\u003c/li\u003e\n \u003cli\u003eIndex of depriv*\u003c/li\u003e\n \u003cli\u003eSocioeconomic status\u003c/li\u003e\n \u003cli\u003ePoor\u003c/li\u003e\n \u003cli\u003ePoverty\u003c/li\u003e\n \u003cli\u003eOccupation\u003c/li\u003e\n \n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2. Inclusion and Exclusion criteria\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eInclusion criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eExclusion criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles reporting the experiences of adult patients with a diagnosis of terminal illness who were approaching the EOL from the perspective of the patient or the unpaid/family caregiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles reporting the experiences of those under the age of 18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles which described a population of participants who were socio-economically deprived\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles reporting the experiences of patients living with chronic illness but not thought to be at the EOL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eResearch was conducted in high income countries (as per World Bank List of economies\u0026nbsp;(35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles reporting the perceptions of health professionals I.e. health professional proxy accounts of experience\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles were peer reviewed empirical research\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eArticles which were focused on place of death or on access to palliative care for people at the EOL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003ePublished in English\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eSystematic reviews, reports, commentaries, editorials, conference proceedings, case reports, grey literature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eStudy selection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInitial screening by title and abstract was conducted by SB and MC. Both authors screened the first 20 papers for inclusion to ensure consistency. Full texts were then reviewed according to the inclusion and exclusion criteria. Where there was uncertainty, papers were read by EC and a decision was made as a team.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eQuality Appraisal\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGiven the breadth of research designs obtained by integrative reviews, there is no gold standard for quality appraisal (24). However, a research critique framework developed by Caldwell et al (36) was considered suitable to assess quality in both qualitative and quantitative papers. Bloomer et al 2017 used the Caldwell criteria in a recent integrative review and shared the flowchart they had developed \u0026nbsp;(37). The methodological strengths and weaknesses of each included study were assessed independently with SB and MC using the Caldwell 11 point criteria. Final scores were corroborated and differences discussed.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData abstraction and synthesis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe followed the four steps as described by Whittemore and Knafl: 1) data reduction, 2) data display, 3) data comparison, 4) conclusion drawing (24). The papers were reviewed and data extracted on: full reference, continent, language, how SED was defined, how EOL was defined, aim, objectives or research questions, design, setting for data collection, participants, diagnosis, sample size, tools, key findings, limitations as described, author conclusions, references to other relevant studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe content was analysed and an initial list of themes were developed. The full text papers were then re-read, and the data applied to each theme. The themes were then revisited, relationships explored and themes consolidated. This process resulted in the final 3 global themes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIncluded studies\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn total, 2458 studies were found after removal of duplicates as illustrated in figure 1. Initial screening of titles and abstracts resulted in 236 papers for full-text review. Ultimately, 40 studies were included in the analysis. A list of these papers is included in table 3.\u0026nbsp;In total, 38 out of 40 papers were of high quality with a score of 9/11 or higher, the remaining 2 papers scored 8/11. Given the experiences of people living in SED have not been well described in detail in the literature, we did not exclude on the basis of quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFIGURE 1 SHOULD BE PLACED HERE\u003c/p\u003e\n\u003cp\u003eFigure 1\u0026nbsp;Prisma flow diagram of search results\u003c/p\u003e\n\u003cp\u003eMost studies originated in North America (23/40); 8 in Europe (one of these was UK based); 7 in Asia; 1 Australia and 1 was cross-continent between USA and Europe. The studies were conducted in different healthcare settings including community, hospital and hospice. Some were population studies. Most studies (28/40) recruited patients with cancer diagnoses; 11 did not specify a particular diagnosis and only one looked exclusively at patients with a non-malignant diagnosis \u0026ndash; Chronic Obstructive Pulmonary Disease (COPD). Quantitative designs were most commonly used (34/40). There were 3 qualitative studies and the remaining 3 using mixed methodologies. The total sample size of the included studies was 439423 (range = 18 \u0026ndash; 307188).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe studies included used a variety of definitions to define SED. Twenty-two studies used only one marker in their analysis: education status (n=7); household income (n=4); insurance status (n=3 from the USA); subgroups of employment (n=2); specifically designed SED scores as the single marker of SED (n=2) i.e. the Carstairs SED score and the Index of Relative Disadvantage; decedent postal code linked to nationally available data on poverty rates and estimated income (n=2); patient self-reported financial strain (n=1); structurally vulnerable (n=1). The remaining 18 studies used multifactorial markers of SED.\u003c/p\u003e\n\u003cp\u003eTABLE 3 SHOULD BE PLACED HERE\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMulti-dimensional EOL experience\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn total 10 studies\u0026nbsp;(38-47), discussed physical, emotional and social symptom burden. Lower income and education levels were generally associated with higher physical symptom burden, with pain being widely reported\u0026nbsp;(38, 44). Poverty was also found to be associated with increased receipt of medication for pain, dyspnoea and emotional distress\u0026nbsp;(45). However, the association between higher physical symptom burden and SED was not sustained in one study\u0026nbsp;(41)\u0026nbsp;where no difference was found in symptom burden between insured and uninsured patients.\u003c/p\u003e\n\u003cp\u003eThe evidence on the relationship between SED and psychological wellbeing is conflicting. While one study found that financial difficulty was associated with lower functional, emotional and spiritual wellbeing\u0026nbsp;(46)\u0026nbsp;another found that unemployed patients with cancer had less anxiety and depression\u0026nbsp;(42)\u0026nbsp;Similarly, Dhingra et al found that patients living in impoverished neighbourhoods reported very low illness burden (defined as physical functioning, symptom distress, unmet needs and quality of life)(39). One study showed that lower education was associated with higher hopelessness and depression rates(47)\u003csup\u003e\u0026nbsp;\u003c/sup\u003ebut education levels generally did not impact on levels of psychological distress, anxiety or depression scores\u0026nbsp;(42, 46).\u003c/p\u003e\n\u003cp\u003eThere is no consistent evidence regarding coping ability. Tang et al showed that higher education was associated with higher post-traumatic growth scores, showing positive personal development and adjustment to trauma(40). However, Chochinov et al reported that patients with higher education were more likely to report feelings of having lost control, unfinished business, and poorer coping with activities of daily living(43).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSocial and financial support\u003c/p\u003e\n\u003cp\u003eOnly 2 studies described the social support available to patients, from government agencies and more informal routes\u0026nbsp;(48, 49). Lewis et al described limited family support, often a sole caregiver, and sometimes fragile relationships in situations that could be compounded by violence and alcohol. There was a heavy reliance on other sources of support, but welfare support and government housing agencies were described as difficult to access and community support (including informal support from neighbours and formalised primary care and community nursing support) was described as inconsistent, unpredictable and inadequate to meet patient need\u0026nbsp;(48). Once a connection was able to be established, patients who had previously engaged with government agencies prior to their illness described subsequent interactions as a positive experience. However, for those who had no prior connection, the experience, particularly around negotiating benefits was challenging\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(48).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn one study, women with breast cancer in the US expressed a desire to maintain social connections, describing this as a key aspect of a meaningful life, alongside creative outlets and spirituality. For those living alone, in lower socioeconomic populations, neighbourhood networks were essential to sustain care and social needs\u0026nbsp;(49).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinancial hardship\u003c/p\u003e\n\u003cp\u003eFour studies in countries with both publicly funded and private healthcare systems described the impact of ill-health on finances when living with pre-existing poverty\u0026nbsp;(49-52). Financial distress was common prior to diagnosis but worsened after due to medical costs and inability to work. Patients who had low income or who were in financial poverty allocated a larger proportion of family income to health expenses and were more likely to report catastrophic health expenditure and higher health costs at the EOL\u0026nbsp;(51, 52).\u003c/p\u003e\n\u003cp\u003eSimilarly, a qualitative study of low-income patients with breast cancer in America found that most patients had difficulty meeting basic needs, inadequate financial resources, and were unable to work, resulting in them feeling burdensome and useless\u0026nbsp;(49)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDrug reimbursement due to terminal illness (DRTI) is a scheme available in Denmark for patients with incurable disease and a short life expectancy allowing for prescription medicines to be obtained free of charge. However, the authors noted that patients with lower income were less likely to access DRTI (52).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePreferences and planning at EOL\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePreferences for EOL care were described in 5 studies (53-57). Overall, patients with higher education level were more likely to choose supportive care. Tang et al reported that patients with higher education level were more likely to accurately know their prognosis, which was in turn associated with greater odds of preferring comfort-orientated and hospice-based care at the EOL (55). \u003csup\u003e\u0026nbsp;\u003c/sup\u003eCarlucci et al provided patients with advanced COPD theoretical scenarios and found those with a higher education level were more likely not to choose EOL sustaining treatments such as intubation and non-invasive ventilation. Of note, the study also suggested that all participants\u0026rsquo; understanding of choices were suboptimal, with over 40% of participants being unable to correctly define the comfort/supportive option(54). Saeed et al found that education did not affect participants\u0026rsquo; preference to receive comfort/supportive care\u0026nbsp;(53), however the sample consisted of mainly highly educated participants.\u003c/p\u003e\n\u003cp\u003eTreatment Intensity at the EOL\u003c/p\u003e\n\u003cp\u003eTreatment intensity at EOL was described in 8 studies.(58-62)\u0026nbsp;(63)\u0026nbsp;(64)\u0026nbsp;(65)\u0026nbsp;In most of the studies included, patients with lower income, lower education levels, or no insurance, were generally more likely to receive intensive treatment at the EOL(58-61). Such treatments included chemotherapy, attendance at emergency departments or \u0026gt;14 days hospitalisation prior to death, intensive care admission, use of mechanical ventilation and cardiopulmonary resuscitation. Lower income and lower education level also led to increased rate of transfer from home or nursing home to secondary care in the last months of life\u0026nbsp;(63). Having an inpatient hospice admission during the last 6 months of life reduced hospital admissions by almost half. However, patients with lower income and lower education were less likely to utilise hospice\u0026nbsp;(64).\u003c/p\u003e\n\u003cp\u003eA few studies were contradictory. A Taiwanese study showed that whilst low income was associated with increased likelihood of hospital admission beyond 14 days and death in an acute hospital, higher income patients were more likely to attend the emergency department and be admitted to intensive care units\u0026nbsp;(59). One study of cancer patients showed that those with higher education levels were more likely to receive diagnostic and therapeutic procedures at the EOL(62). Bergman et al described an analysis of a dedicated programme for men with low income and prostate cancer, and found rates of chemotherapy use, emergency and intensive care admissions and inpatient stays for those in the programme were comparable to the general population(65).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture Care Planning\u003c/p\u003e\n\u003cp\u003eFuture care planning, designation of power of attorney, EOL discussions, and completion of written instructions for care at EOL was described in 3 studies\u0026nbsp;(44, 53, 66). Khosla et al found that although higher household income increased the odds of having a legally designated power of attorney for healthcare, this did not impact on EOL discussions or written instructions. They also showed that education level did not impact advanced care planning behaviour\u0026nbsp;(66). Carr et al found that having assets significantly increased the likelihood of participants having a living will or legal power of attorney but did not impact on informal EOL discussions(44). In contrast, another study looking at a sample of lower income patients found that education level and financial strain did not affect completion of advanced care directives(53).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eService uptake and utilization\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNine studies described what and how palliative care services were used\u0026nbsp;(38, 52, 64, 67-72).\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThe evidence shows that even when patients had equal access to palliative care services, differences in the uptake of these persisted across different indicators of socioeconomic status. For example, those with higher income or living in a neighbourhood with a higher socioeconomic status, were significantly more likely to have inpatient hospice admissions(64).\u003c/p\u003e\n\u003cp\u003eThe literature points to a distinction between which services are desired or used by patients based on their socioeconomic status. Ankuda et al showed that patients with financial strain described the connection to social services offered by an at home palliative care service including transportation, help with navigating insurance policies or benefits and food stamps as what mattered most due to self-perceived poverty, disability and high medication cost(67). Another reason for reliance on practical or social support may be explained by the availability of informal caregivers. For example, Bijnsdorp et al described a positive correlation between educational attainment and availability of partner care-networks, defined as care provided primarily by a partner in the last year of life, particularly for patients younger than 77.9 years\u0026nbsp;(72). Similarly, a home-based palliative care service in Canada found a difference in unpaid caregiving hours provided for those with the highest socioeconomic status and the lowest socioeconomic status of 6.18 hours and 2.66 hours, respectively(68).\u003c/p\u003e\n\u003cp\u003eWhen those experiencing SED have accessed specialist palliative care services, there is some evidence that they use them more thereafter. The literature shows that this is the case for both routine and non-routine care and across the different services offered by palliative care. For example, patients with either limited insurance (Medicaid) or no health insurance had more follow up appointments with a hospital palliative care service\u0026nbsp;(38). \u0026nbsp;This finding persisted for universal, publicly funded health insurance systems. Two Canadian home-based palliative care services showed that patients with higher levels of SED and lower levels of educational attainment had increased propensity and intensity of support worker and nurse visits\u0026nbsp;(68, 71). The type of support from General Practitioners may also show some slight variation for patients in the last year of life. For example, patients with cancer in the last year of life were more likely to have GP face-to-face visits if they had a lower income\u0026nbsp;(69).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatient satisfaction with palliative care services\u003c/p\u003e\n\u003cp\u003eThere is limited and conflicting evidence relating socioeconomic status to patient satisfaction with palliative care services as described in six of the included studies(49, 67, 73-76). Lower levels of education were linked in one study to higher satisfaction with care (74) whilst another showed no association with ratings on quality of death and dying for patients or family(77). Patients with financial strain rated a home palliative care programme the highest of all socioeconomic groups(67).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe available qualitative research pointed to concerns from patients experiencing SED around the use of palliative care services. For example, patients described that having reduced financial means and lack of access to private insurance meant they did not receive the same high quality care (77). Patients living in poverty felt a negative bias and stigmatization from healthcare professionals towards them due to their lower socioeconomic class and this impacted on perception of the care received (77). One general practitioner out-of-hours service in a deprived area in Scotland was found to be stressful and cumbersome to use with patients describing bad experiences or feeling their care needs were too complex for this service(75). A Canadian study of those who were homeless, or at risk of such, described that patients often had their care needs unidentified and unmet. However, when patients were linked to palliative care services, they reported feeling listened to and reported that services were extremely accommodating and attentive to their needs (76).\u003c/p\u003e"},{"header":"Discussion ","content":"\u003cp\u003eWe reviewed, integrated and summarised evidence on the EOL experiences of people living with SED in developed countries. Forty heterogenous studies were identified from a wide range of countries with varying healthcare systems and encompassed both malignant and non-malignant diseases. Three global themes were identified relating to the multi-dimensional EOL experience, preferences and planning and service uptake and utilization. The following key findings were identified - those living with SED have: increased symptom burden; difficulty navigating complex healthcare systems at the EOL and increased intensity of use of these once a link is established; a preference for, and are more likely to have, intensive treatment at the EOL; limited formal and informal social support; a greater propensity to experience financial distress; and, less participation in advanced care planning.\u003c/p\u003e\n\u003cp\u003eThis review demonstrated that specifically designed initiatives and services can be beneficial for those living in SED\u0026nbsp;(65). Previous research has shown that people experiencing SED use palliative care services differently and that current universally available models often fail to meet patients\u0026rsquo; needs\u0026nbsp;(7, 9-12, 15-18, 52, 78). Navigating and negotiating multiple and complex systems in order to access essential support may be overwhelming, particularly when compounded by unpredictable community support\u0026nbsp;(48, 49)\u0026nbsp;and a lack of unpaid family caregiving\u0026nbsp;(68, 72). Our work lends further argument to the call for proportionate universalism, where marginalised groups need systems to be designed to incorporate their needs, rather than needing them to adapt to a universal healthcare system, and for time and resources to be proportionate to the level of disadvantage\u0026nbsp;(79, 80).\u003c/p\u003e\n\u003cp\u003eDying can be expensive, for both patients and the people caring for them. In addition to existing financial constraint, further loss of income, changes to benefits and treatment-related costs can be catastrophic\u0026nbsp;(49, 51, 81). Interestingly, even when a drug reimbursement system was available in Denmark, patients from poorer backgrounds were less likely to claim it\u0026nbsp;(52). This supports what we already know \u0026ndash; that financial benefits do not always reach those who need them most. In the UK alone, up to \u0026pound;6.2billion of income-related benefits went unclaimed in 2018-2019\u0026nbsp;(82). Ultimately, patients and families may not get access to the financial support they need to mitigate the costs associated with EOL, including fees for diagnostic interventions, hospice or home care and reduced household income as relatives become unemployed unpaid caregivers. This financial distress can leave patients and caregivers feeling devalued, and financially burdensome\u0026nbsp;(49). Our findings highlight that in order to tackle the systemic issues of social justice which impact on EOL experience, we must adopt multidisciplinary and multi-agency approaches to support families to navigate health and social care and benefits systems. Our review suggests that people experiencing SED valued the non-medical support from palliative care services most, particularly around use of social and supportive services and were less likely to have informal caregivers\u0026nbsp;(48, 68).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings showed that people living in SED absorbed palliative care services when they could gain access to them, with demonstrable higher intensity of use, particularly with regards to outpatient and community-based services\u0026nbsp;(38, 68, 69, 71). Additionally, our review suggests that patients also have greater physical and psychological symptom burden\u0026nbsp;(38, 44, 83), thus making the greater use of palliative care services unsurprising. However, an alternative explanation could be that services and existing resources are failing to meet the complex needs of people experiencing SED, thus leading to repeated consultations. Barriers to quality care identified in this review have been multifactorial, complex, and difficult to address on a single level. Without significant changes to the way we deliver healthcare, the complexity of these barriers will only serve to widen the quality-of-care gap between deprived and affluent populations yet again, proving the inverse care law true.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough our review demonstrated that people living with SED had both a preference for, and tendency to receive intensive treatments at the EOL(58, 59, 61-65, 84) choosing such treatments is likely multidimensional and reflective of advanced care planning and patient advocacy, rather than socioeconomic status. Recent research from Scotland added weight to these findings, with Mason et al demonstrating that for those in the last year of life, living in SED used more unscheduled care (11). People living with SED may have more interaction with health and social care professionals and thus potentially more opportunity to engage with future care planning, yet this is not translating to the actual experience at the EOL. Whilst Davies et al have demonstrated that part of the increased uptake of hospital-based services may be due to poorer health and function for those living in SED (18), until we start asking people about their EOL care experiences and preferences at the right time, in the right way, with consideration given to their limited opportunities to make choices throughout the life course, we will fail to understand the potentially complex nature of future planning for this group.\u003c/p\u003e"},{"header":"Strengths \u0026 Limitations","content":"\u003cp\u003eThis review summarises a thorough analysis of the literature from the developed world about the experience of those dying in SED. We include high quality studies from a variety of settings, healthcare systems and countries thus allowing our work to be transferable and applicable across the developed world. Excluding papers addressing well-explored issues of access and preferred place of death has allowed us to focus on the patient voice and experience.\u003c/p\u003e\n\u003cp\u003eAlthough we included a wide variety of different healthcare settings and systems in various countries, this also meant that there were a wide variety of cultural and societal differences which may limit the generalisability across settings. Whilst we had intended to draw out the patient voice, only 3 studies using a qualitative design and a further 3 studies using mixed quantitative and qualitative research methods. As our findings show, the evidence was heterogenous and often contradictory, which can be challenging to analyse and synthesise. The lack of a standard definition for SED may have contributed to the heterogenous evidence and led researchers of the included papers seeking definitions that could be easily obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for policy, practice and research\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe voices of people experiencing SED at the EOL are underrepresented. The COVID-19 pandemic has disproportionately affected people living with poverty\u0026nbsp;(85, 86), forced more families into poverty and has highlighted the fragility of health systems across the globe. Health inequalities are now a stark focus for policymakers globally\u0026nbsp;(87). Inclusive and participatory research, which enables patients and families to feed directly into this policy making and service design is a priority. We need to actively and broadly engage with policies beyond our specialism, to take into account the complex needs of this group in societies and systems.\u003c/p\u003e\n\u003cp\u003eOur review highlighted a dearth of research on spirituality at the EOL for people living with poverty. Further exploration into this important but neglected area is recommended. We also need to understand why people are more likely to experience pain and receive intensive treatment at EOL. In general, patients with lower income were less likely to complete advanced care planning. Further exploration into the link between these two things is important but it is vital that health and social care professionals understand attitudes, experiences and preferences for future care discussions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe generalisability of SED research would be improved if standard markers could be agreed upon, at least in similar healthcare systems. Whilst this is not a critique of any particular SED marker, it may be that using a combination of SED markers, or a specifically designed SED score such as the Carstairs SED score would be more appropriate(88). This echoes the work of social epidemiologists who advocate that valid measurements of socioeconomic status are required and propose the use of multidimensional, composite models which allow for capturing more context\u0026nbsp;(89).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAs a direct cause of the COVID-19 pandemic, it is estimated that somewhere between 88 and 115 million people worldwide will be forced into extreme poverty, and issues of inequity have been exacerbated (35). In the UK, this is happening on the background of a decade of stalling life expectancy, austerity and rising health inequalities between socioeconomic groups and regions(3). Our comprehensive review shows that SED needs to be a key facilitator in identifying those who are likely to have a greater health burden and thus requiring specialist care at the end of life. Ultimately, future palliative care services cannot adopt a \u0026lsquo;one size fits all\u0026rsquo; approach, shaped by our majority populations, rather they should be adaptable and flexible to provide different levels of support based on individualised need. Multidisciplinary and multi-agency approaches are needed to navigate healthcare and benefits systems and tackle the systemic issues of social justice which impact on EOL experience.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSED \u0026ndash; socio-economic deprivation\u003c/p\u003e\n\u003cp\u003eEOL \u0026ndash; end of life\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analysed are included in published literature that were identified through the following bibliographic databases: Medline, Embase, CINAHL, ASSIA and PsychInfo. A list of included studies can be found in table 3. For further information about the availability of these data, please contact the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe post of Emma Carduff is funded by Marie Curie. Emma Carduff is Co-Applicant on an Economic and Social Research Council grant (ES/S014373/1) entitled Dying in the Margins: uncovering the reasons for unequal access to home dying for the socio-economically deprived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEC, SB and MOR conceptualised the review. SB and EC conducted the literature searches. SB and MC conducted the screening of abstracts. All authors were involved in reviewing the final set of papers, analysing the data. All authors made major contributions to preparing the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eDr Anne Finucane for commenting on the protocol\u003c/li\u003e\n \u003cli\u003eDr Melissa Bloomer advised us on use of the Caldwell criteria for assessing the quality of the articles included in this study.\u003c/li\u003e\n \u003cli\u003eShona MacNeilage at the NHS Greater Glasgow and Clyde library service helped develop the search strategies.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003cp\u003e1.\u0026nbsp;Mair FS, Jani BD. Emerging trends and future research on the role of socioeconomic status in chronic illness and multimorbidity. The Lancet Public health. 2020;5(3):e128-e9.\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp;Santos Salas A, Watanabe SM, Tarumi Y, Wildeman T, Hermosa Garc\u0026iacute;a AM, Adewale B, et al. Social disparities and symptom burden in populations with advanced cancer: specialist palliative care providers\u0026rsquo; perspectives. Supportive Care in Cancer. 2019.\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp;Marmot MA, J; Boyce, T; Goldblatt, P; Morrison, J. Health Equity in England: The Marmot Review 10 Years On. Institute of Health Equity. 2020.\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp;Singh GK, Jemal A. Socioeconomic and Racial/Ethnic Disparities in Cancer Mortality, Incidence, and Survival in the United States, 1950\u0026ndash;2014: Over Six Decades of Changing Patterns and Widening Inequalities. Journal of Environmental and Public Health. 2017;2017:2819372.\u003c/p\u003e\n\u003cp\u003e5.\u0026nbsp;Hastert TA, Beresford SA, Sheppard L, White E. Disparities in cancer incidence and mortality by area-level socioeconomic status: a multilevel analysis. J Epidemiol Community Health. 2015;69(2):168-76.\u003c/p\u003e\n\u003cp\u003e6.\u0026nbsp;Office for National Statistics. National Survey of Bereaved People (VOICES) 2015: Quality of care delivered in the last 3 months of life for adults who died in England. 2016.\u003c/p\u003e\n\u003cp\u003e7.\u0026nbsp;Davies JM, Sleeman KE, Leniz J, Wilson R, Higginson IJ, Verne J, et al. Socioeconomic position and use of healthcare in the last year of life: A systematic review and meta-analysis. PLoS medicine. 2019;16(4):e1002782.\u003c/p\u003e\n\u003cp\u003e8.\u0026nbsp;Asaria M, Doran T, Cookson R. The costs of inequality: whole-population modelling study of lifetime inpatient hospital costs in the English National Health Service by level of neighbourhood deprivation. J Epidemiol Community Health. 2016;70(10):990-6.\u003c/p\u003e\n\u003cp\u003e9.\u0026nbsp;Macfarlane M, Carduff E. Does place of death vary by deprivation for patients known to specialist palliative care services? BMJ Support Palliat Care. 2018;8(4):428-30.\u003c/p\u003e\n\u003cp\u003e10.\u0026nbsp;Buck J, Webb L, Moth L, Morgan L, Barclay S. Persistent inequalities in Hospice at Home provision. BMJ Support Palliat Care. 2020;10(3):e23.\u003c/p\u003e\n\u003cp\u003e11.\u0026nbsp;Mason B, Kerssens JJ, Stoddart A, Murray SA, Moine S, Finucane AM, et al. Unscheduled and out-of-hours care for people in their last year of life: a retrospective cohort analysis of national datasets. BMJ Open. 2020;10(11):e041888.\u003c/p\u003e\n\u003cp\u003e12.\u0026nbsp;Barratt H, Asaria M, Sheringham J, Stone P, Raine R, Cookson R. Dying in hospital: socioeconomic inequality trends in England. Journal of Health Services Research \u0026amp; Policy. 2017;22(3):149-54.\u003c/p\u003e\n\u003cp\u003e13.\u0026nbsp;Neergaard MA, Brunoe AH, Skorstengaard MH, Nielsen MK. What socio-economic factors determine place of death for people with life-limiting illness? A systematic review and appraisal of methodological rigour. Palliative medicine. 2019;33(8):900-25.\u003c/p\u003e\n\u003cp\u003e14.\u0026nbsp;Sleeman KE, Davies JM, Verne J, Gao W, Higginson IJ. The changing demographics of inpatient hospice death: Population-based cross-sectional study in England, 1993\u0026ndash;2012. Palliative medicine. 2016;30(1):45-53.\u003c/p\u003e\n\u003cp\u003e15.\u0026nbsp;Gao W, Ho YK, Verne J, Glickman M, Higginson IJ. Changing patterns in place of cancer death in England: a population-based study. PLoS Med. 2013;10(3):e1001410.\u003c/p\u003e\n\u003cp\u003e16.\u0026nbsp;Koffman J, Burke G, Dias A, Raval B, Byrne J, Gonzales J, et al. Demographic factors and awareness of palliative care and related services. Palliat Med. 2007;21(2):145-53.\u003c/p\u003e\n\u003cp\u003e17.\u0026nbsp;Dixon JK, D; Matosevic,T; Clark, C; Knapp, K. Equity in the provision of palliative care in the UK: review of evidence. Personal Social Services Research Unit, London School of Economics and Political Science, London. 2015.\u003c/p\u003e\n\u003cp\u003e18.\u0026nbsp;Davies JM, Maddocks M, Chua KC, Demakakos P, Sleeman KE, Murtagh FEM. Socioeconomic position and use of hospital-based care towards the end of life: a mediation analysis using the English Longitudinal Study of Ageing. The Lancet Public health. 2021;6(3):e155-e63.\u003c/p\u003e\n\u003cp\u003e19.\u0026nbsp;Walsh B, Laudicella M. Disparities In Cancer Care And Costs At The End Of Life: Evidence From England\u0026apos;s National Health Service. Health affairs (Project Hope). 2017;36(7):1218-26.\u003c/p\u003e\n\u003cp\u003e20.\u0026nbsp;Gott M, Allen R, Moeke-Maxwell T, Gardiner C, Robinson J. \u0026apos;No matter what the cost\u0026apos;: A qualitative study of the financial costs faced by family and whānau caregivers within a palliative care context. Palliat Med. 2015;29(6):518-28.\u003c/p\u003e\n\u003cp\u003e21.\u0026nbsp;Turner V, Flemming K. Socioeconomic factors affecting access to preferred place of death: A qualitative evidence synthesis. Palliat Med. 2019;33(6):607-17.\u003c/p\u003e\n\u003cp\u003e22.\u0026nbsp;Lewis JM, DiGiacomo M, Currow DC, Davidson PM. Dying in the margins: understanding palliative care and socioeconomic deprivation in the developed world. Journal of pain and symptom management. 2011;42(1):105-18.\u003c/p\u003e\n\u003cp\u003e23.\u0026nbsp;Rowley J, Richards N, Carduff E, Gott M. The impact of poverty and deprivation at the end of life: a critical review. Palliative Care and Social Practice. 2021;15:26323524211033873.\u003c/p\u003e\n\u003cp\u003e24.\u0026nbsp;Whittemore R, Knafl K. The integrative review: updated methodology. Journal of advanced nursing. 2005;52(5):546-53.\u003c/p\u003e\n\u003cp\u003e25.\u0026nbsp;Carduff E, Bowers SP, Chin M, O\u0026apos;Riordan M,. The experiences of people living with socio-economic deprivation who are approaching the end of life: an integrative review. 2019 [Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019151906 (last accessed 21st January 2022).\u003c/p\u003e\n\u003cp\u003e26.\u0026nbsp;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. J Clin Epidemiol. 2021;134:178-89.\u003c/p\u003e\n\u003cp\u003e27.\u0026nbsp;National Institute for Health and Care Excellence. End of life care for adults: service delivery NICE guideline [NG142] 2017 [Available from: https://www.nice.org.uk/guidance/ng142 [accessed 17th January 2022].\u003c/p\u003e\n\u003cp\u003e28.\u0026nbsp;Rietjens JA, Bramer WM, Geijteman EC, van der Heide A, Oldenmenger WH. Development and validation of search filters to find articles on palliative care in bibliographic databases. Palliative medicine. 2019;33(4):470-4.\u003c/p\u003e\n\u003cp\u003e29.\u0026nbsp;Martin D, Brigham P, Roderick P, Barnett S, Diamond I. The (mis)Representation of Rural Deprivation. Environment and Planning A: Economy and Space. 2000;32(4):735-51.\u003c/p\u003e\n\u003cp\u003e30.\u0026nbsp;Galobardes B, Shaw M, Lawlor DA, Lynch JW. Indicators of socioeconomic position (part 2). Journal of epidemiology and community health. 2006;60(2):95.\u003c/p\u003e\n\u003cp\u003e31.\u0026nbsp;Galobardes B, Shaw M, Lawlor DA, Lynch JW, Smith GD. Indicators of socioeconomic position (part 1). Journal of Epidemiology \u0026amp; Community Health. 2006;60(1):7-12.\u003c/p\u003e\n\u003cp\u003e32.\u0026nbsp;Nelson KE, Wright R, Peeler A, Brockie T, Davidson PM. Sociodemographic Disparities in Access to Hospice and Palliative Care: An Integrative Review. American Journal of Hospice and Palliative Medicine\u0026reg;. 2021;38(11):1378-90.\u003c/p\u003e\n\u003cp\u003e33.\u0026nbsp;Mondor L, Wodchis WP, Tanuseputro P. Persistent socioeconomic inequalities in location of death and receipt of palliative care: A population-based cohort study. Palliative Medicine. 2020;34(10):1393-401.\u003c/p\u003e\n\u003cp\u003e34.\u0026nbsp;French M, Keegan T, Anestis E, Preston N. Exploring socioeconomic inequities in access to palliative and end-of-life care in the UK: a narrative synthesis. BMC Palliat Care. 2021;20(1):179.\u003c/p\u003e\n\u003cp\u003e35.\u0026nbsp;World Bank. World Bank List of Economies (June 2020) \u0026nbsp;[Available from: https://databank.worldbank.org/data/download/site-content/CLASS.xls (last accessed 21st January 2022).\u003c/p\u003e\n\u003cp\u003e36.\u0026nbsp;Caldwell K, Henshaw L, Taylor G. Developing a framework for critiquing health research: An early evaluation. Nurse Education Today. 2011;31(8):e1-e7.\u003c/p\u003e\n\u003cp\u003e37.\u0026nbsp;Bloomer MJ, Hutchinson AM, Brooks L, Botti M. Dying persons\u0026rsquo; perspectives on, or experiences of, participating in research: An integrative review. Palliative Medicine. 2018;32(4):851-60.\u003c/p\u003e\n\u003cp\u003e38.\u0026nbsp;Azhar A, Yennurajalingam S, Ramu A, Zhang H, Haider A, Williams JL, et al. Timing of referral and characteristics of uninsured, Medicaid, and insured patients referred to the outpatient supportive care center at a comprehensive cancer center. Journal of pain and symptom management. 2018;55(3):973-8.\u003c/p\u003e\n\u003cp\u003e39.\u0026nbsp;Dhingra L, Dieckmann NF, Knotkova H, Chen J, Riggs A, Breuer B, et al. A high-touch model of community-based specialist palliative care: latent class analysis identifies distinct patient subgroups. Journal of pain and symptom management. 2016;52(2):178-86.\u003c/p\u003e\n\u003cp\u003e40.\u0026nbsp;Tang ST, Lin KC, Chen JS, Chang WC, Hsieh CH, Chou WC. Threatened with death but growing: changes in and determinants of posttraumatic growth over the dying process for Taiwanese terminally ill cancer patients. Psycho‐Oncology. 2015;24(2):147-54.\u003c/p\u003e\n\u003cp\u003e41.\u0026nbsp;Cervantez SR, Tenner LL, Schmidt S, Aduba IO, Jones JT, Ali N, et al. Symptom burden and palliative referral disparities in an ambulatory South Texas cancer center. Frontiers in oncology. 2018;8:443.\u003c/p\u003e\n\u003cp\u003e42.\u0026nbsp;Maric DM, Jovanovic DM, Golubicic IV, Nagorni-Obradovic LJ, Stojsic JM, Pekmezovic TD. Psychological well-being in advanced NSCLC patients in Serbia: impact of sociodemographic and clinical factors. Neoplasma. 2010;57(1):1-7.\u003c/p\u003e\n\u003cp\u003e43.\u0026nbsp;Chochinov HM, Hassard T, McClement S, Hack T, Kristjanson LJ, Harlos M, et al. The landscape of distress in the terminally ill. J Pain Symptom Manage. 2009;38(5):641-9.\u003c/p\u003e\n\u003cp\u003e44.\u0026nbsp;Carr D. Is Death \u0026ldquo;The Great Equalizer\u0026rdquo;? The Social Stratification of Death Quality in the United States. The ANNALS of the American Academy of Political and Social Science. 2016;663(1):331-54.\u003c/p\u003e\n\u003cp\u003e45.\u0026nbsp;Saphire ML, Prsic EH, Canavan ME, Wang SJ, Presley CJ, Davidoff AJ. Patterns of Symptom Management Medication Receipt\u0026nbsp;at\u0026nbsp;End-of-Life Among Medicare Beneficiaries\u0026nbsp;With\u0026nbsp;Lung Cancer. J Pain Symptom Manage. 2020;59(4):767-77.e1.\u003c/p\u003e\n\u003cp\u003e46.\u0026nbsp;Jacob J, Palat G, Verghese N, Chandran P, Rapelli V, Kumari S, et al. Health-related quality of life and its socio-economic and cultural predictors among advanced cancer patients: Evidence from the APPROACH cross-sectional survey in Hyderabad-India. BMC palliative care. 2019;18(1):94.\u003c/p\u003e\n\u003cp\u003e47.\u0026nbsp;Sahin ZA, Tan M, Polat H. Hopelessness, depression and social support with end of life Turkish cancer patients. Asian Pacific Journal of Cancer Prevention. 2013;14(5):2823-8.\u003c/p\u003e\n\u003cp\u003e48.\u0026nbsp;Lewis JM, DiGiacomo M, Currow DC, Davidson PM. Social capital in a lower socioeconomic palliative care population: a qualitative investigation of individual, community and civic networks and relations. BMC palliative care. 2014;13(1):30.\u003c/p\u003e\n\u003cp\u003e49.\u0026nbsp;Adler SR, Coulter YZ, Stone K, Glaser J, Duerr M, Enochty S. End-of-life concerns and experiences of living with advanced breast cancer among medically underserved women. Journal of pain and symptom management. 2019;58(6):959-67.\u003c/p\u003e\n\u003cp\u003e50.\u0026nbsp;Yi D, Johnston BM, Ryan K, Daveson BA, Meier DE, Smith M, et al. Drivers of care costs and quality in the last 3 months of life among older people receiving palliative care: A multinational mortality follow-back survey across England, Ireland and the United States. Palliative Medicine. 2020;34(4):513-23.\u003c/p\u003e\n\u003cp\u003e51.\u0026nbsp;Leng A, Jing J, Nicholas S, Wang J. Catastrophic health expenditure of cancer patients at the end-of-life: a retrospective observational study in China. BMC palliative care. 2019;18(1):43.\u003c/p\u003e\n\u003cp\u003e52.\u0026nbsp;Daugaard C, Neergaard MA, Vestergaard AHS, Nielsen MK, Johnsen SP. Socioeconomic inequality in drug reimbursement during end-of-life care: a nationwide study. J Epidemiol Community Health. 2019;73(5):435-42.\u003c/p\u003e\n\u003cp\u003e53.\u0026nbsp;Saeed F, Xing G, Tancredi DJ, Epstein RM, Fiscella KA, Norton SA, et al. Is Annual income a predictor of completion of advance directives (ADs) in patients with cancer. American Journal of Hospice and Palliative Medicine\u0026reg;. 2019;36(5):402-7.\u003c/p\u003e\n\u003cp\u003e54.\u0026nbsp;Carlucci A, Vitacca M, Malovini A, Pierucci P, Guerrieri A, Barbano L, et al. End-of-life discussion, patient understanding and determinants of preferences in very severe COPD patients: A multicentric study. COPD: Journal of Chronic Obstructive Pulmonary Disease. 2016;13(5):632-8.\u003c/p\u003e\n\u003cp\u003e55.\u0026nbsp;Tang ST, Liu TW, Chow JM, Chiu CF, Hsieh RK, Chen CH, et al. Associations between accurate prognostic understanding and end-of-life care preferences and its correlates among Taiwanese terminally ill cancer patients surveyed in 2011-2012. Psychooncology. 2014;23(7):780-7.\u003c/p\u003e\n\u003cp\u003e56.\u0026nbsp;Schou-Andersen M, Ullersted MP, Jensen AB, Neergaard MA. Factors associated with preference for dying at home among terminally ill patients with cancer. Scand J Caring Sci. 2016;30(3):466-76.\u003c/p\u003e\n\u003cp\u003e57.\u0026nbsp;Wales J, Kalia S, Moineddin R, Husain A. The Impact of Socioeconomic Status on Place of Death Among Patients Receiving Home Palliative Care in Toronto, Canada: A Retrospective Cohort Study. J Palliat Care. 2020;35(3):167-73.\u003c/p\u003e\n\u003cp\u003e58.\u0026nbsp;Brown CE, Engelberg RA, Sharma R, Downey L, Fausto JA, Sibley J, et al. Race/ethnicity, socioeconomic status, and healthcare intensity at the end of life. Journal of palliative medicine. 2018;21(9):1308-16.\u003c/p\u003e\n\u003cp\u003e59.\u0026nbsp;Huang C-Y, Hung Y-T, Chang C-M, Juang S-Y, Lee C-C. The association between individual income and aggressive end-of-life treatment in older cancer decedents in Taiwan. PloS One. 2015;10(1):e0116913.\u003c/p\u003e\n\u003cp\u003e60.\u0026nbsp;Tucker‐Seeley RD, Abel GA, Uno H, Prigerson H. Financial hardship and the intensity of medical care received near death. Psycho‐Oncology. 2015;24(5):572-8.\u003c/p\u003e\n\u003cp\u003e61.\u0026nbsp;Chang C-M, Wu C-C, Yin W-Y, Juang S-Y, Yu C-H, Lee C-C. Low socioeconomic status is associated with more aggressive end-of-life care for working-age terminal cancer patients. The oncologist. 2014;19(12):1241.\u003c/p\u003e\n\u003cp\u003e62.\u0026nbsp;Koroukian SM, Schiltz NK, Warner DF, Given CW, Schluchter M, Owusu C, et al. Social determinants, multimorbidity, and patterns of end-of-life care in older adults dying from cancer. Journal of geriatric oncology. 2017;8(2):117-24.\u003c/p\u003e\n\u003cp\u003e63.\u0026nbsp;Krishnan P, Thompson G, McClement S. Predicting hospital transfers among nursing home residents in the last months of life. International Journal of Palliative Nursing. 2017;23(11):535-42.\u003c/p\u003e\n\u003cp\u003e64.\u0026nbsp;Karikari-Martin P, McCann JJ, Farran CJ, Hebert LE, Haffer SC, Phillips M. Race, Any Cancer, Income, or Cognitive Function: What Inf luences Hospice or Aggressive Services Use at the End of Life Among Community-Dwelling Medicare Beneficiaries? Am J Hosp Palliat Care. 2016;33(6):537-45.\u003c/p\u003e\n\u003cp\u003e65.\u0026nbsp;Bergman J, Chi AC, Litwin MS. Quality of end-of-life care in low-income, uninsured men dying of prostate cancer. Cancer. 2010;116(9):2126-31.\u003c/p\u003e\n\u003cp\u003e66.\u0026nbsp;Khosla N, Curl AL, Washington KT. Trends in Engagement in Advance Care Planning Behaviors and the Role of Socioeconomic Status. Am J Hosp Palliat Care. 2016;33(7):651-7.\u003c/p\u003e\n\u003cp\u003e67.\u0026nbsp;Ankuda CK, Kersting K, Guetterman TC, Haefner J, Fonger E, Paletta M, et al. What matters most? A mixed methods study of critical aspects of a home-based palliative program. American Journal of Hospice and Palliative Medicine\u0026reg;. 2018;35(2):236-43.\u003c/p\u003e\n\u003cp\u003e68.\u0026nbsp;Cai J, Guerriere DN, Zhao H, Coyte PC. Socioeconomic differences in and predictors of home-based palliative care health service use in Ontario, Canada. International journal of environmental research and public health. 2017;14(7):802.\u003c/p\u003e\n\u003cp\u003e69.\u0026nbsp;Neergaard MA, Olesen F, Sondergaard J, Vedsted P, Jensen AB. Are Cancer Patients\u0026apos; Socioeconomic and Cultural Factors Associated with Contact to General Practitioners in the Last Phase of Life? Int J Family Med. 2015;2015:952314.\u003c/p\u003e\n\u003cp\u003e70.\u0026nbsp;Bhatraju P, Friedenberg AS, Uppal A, Evans L. Factors associated with utilization of an inpatient palliative care consultation service in an urban public hospital. American Journal of Hospice and Palliative Medicine\u0026reg;. 2014;31(6):641-4.\u003c/p\u003e\n\u003cp\u003e71.\u0026nbsp;Masucci L, Guerriere DN, Zagorski B, Coyte PC. Predictors of health service use over the palliative care trajectory. Journal of palliative medicine. 2013;16(5):524-30.\u003c/p\u003e\n\u003cp\u003e72.\u0026nbsp;Bijnsdorp FM, Pasman HRW, Francke AL, Evans N, Peeters CF, van Groenou MIB. Who provides care in the last year of life? A description of care networks of community-dwelling older adults in the Netherlands. BMC palliative care. 2019;18(1):41.\u003c/p\u003e\n\u003cp\u003e73.\u0026nbsp;Lee JJ, Long AC, Curtis JR, Engelberg RA. The Influence of Race/Ethnicity and Education on Family Ratings of the Quality of Dying in the ICU. J Pain Symptom Manage. 2016;51(1):9-16.\u003c/p\u003e\n\u003cp\u003e74.\u0026nbsp;Chang YJ, Kwon YC, Lee WJ, Do YR, Seok LK, Kim HT, et al. Burdens, needs and satisfaction of terminal cancer patients and their caregivers. Asian Pacific journal of cancer prevention : APJCP. 2013;14(1):209-16.\u003c/p\u003e\n\u003cp\u003e75.\u0026nbsp;Fergus C, Chinn D, Murray S. Assessing and improving out-of-hours palliative care in a deprived community: a rapid appraisal study. Palliative Medicine. 2010;24(5):493-500.\u003c/p\u003e\n\u003cp\u003e76.\u0026nbsp;Stajduhar KI, Mollison A, Giesbrecht M, McNeil R, Pauly B, Reimer-Kirkham S, et al. \u0026ldquo;Just too busy living in the moment and surviving\u0026rdquo;: barriers to accessing health care for structurally vulnerable populations at end-of-life. BMC Palliative Care. 2019;18(1):1-14.\u003c/p\u003e\n\u003cp\u003e77.\u0026nbsp;Aoun S, Bentley B, Funk L, Toye C, Grande G, Stajduhar KJ. A 10-year literature review of family caregiving for motor neurone disease: Moving from caregiver burden studies to palliative care interventions. Palliative Medicine. 2013;27(5):437-46.\u003c/p\u003e\n\u003cp\u003e78.\u0026nbsp;Sleeman KE, Davies JM, Verne J, Gao W, Higginson IJ. The changing demographics of inpatient hospice death: Population-based cross-sectional study in England, 1993-2012. Palliat Med. 2016;30(1):45-53.\u003c/p\u003e\n\u003cp\u003e79.\u0026nbsp;McFadden A, Siebelt L, Gavine A, Atkin K, Bell K, Innes N, et al. Gypsy, Roma and Traveller access to and engagement with health services: a systematic review. European journal of public health. 2018;28(1):74-81.\u003c/p\u003e\n\u003cp\u003e80.\u0026nbsp;Scotland Public Health. Proportionate Universalism Briefing. \u0026nbsp;17/10/2014.\u003c/p\u003e\n\u003cp\u003e81.\u0026nbsp;Sadler E, McKevitt C. \u0026apos;Expert carers\u0026apos;: An emergent normative model of the caregiver. Social Theory \u0026amp; Health. 2012;11(1):40-58.\u003c/p\u003e\n\u003cp\u003e82.\u0026nbsp;Gov.uk. Income-related benefits: estimates of take-up \u0026nbsp;[Available from: https://www.gov.uk/government/collections/income-related-benefits-estimates-of-take-up--2 (last accessed 21st January 2022).\u003c/p\u003e\n\u003cp\u003e83.\u0026nbsp;Williams C. Chronic illness and informal carers: \u0026apos;Non-persons\u0026apos; in the health system, neither carers, workers or citizens. Health Sociology Review. 2012;21(1):58-68.\u003c/p\u003e\n\u003cp\u003e84.\u0026nbsp;Tucker-Seeley RD, Abel GA, Uno H, Prigerson H. Financial hardship and the intensity of medical care received near death. Psychooncology. 2015;24(5):572-8.\u003c/p\u003e\n\u003cp\u003e85.\u0026nbsp;Scottish Government. Coronavirus (COVID-19): impact on equality [updated 17/09/2020. Available from: https://www.gov.scot/publications/the-impacts-of-covid-19-on-equality-in-scotland/.\u003c/p\u003e\n\u003cp\u003e86.\u0026nbsp;Carmody P, McCan G, Colleran C, O\u0026apos;Halloran C. COVID-19 in the Global South: Impacts and Responses. 2020 21/10/2020.\u003c/p\u003e\n\u003cp\u003e87.\u0026nbsp;Organisation for Economic Co-operation and Development. A systemic resilience approach to dealing with Covid-19 and future shocks \u0026nbsp;[Available from: https://www.oecd.org/coronavirus/policy-responses/a-systemic-resilience-approach-to-dealing-with-covid-19-and-future-shocks-36a5bdfb/ (last accessed 21st January 2022).\u003c/p\u003e\n\u003cp\u003e88.\u0026nbsp;Public Health Scotland. The Carstairs and Morris Index \u0026nbsp;[Available from: https://www.isdscotland.org/Products-and-services/Gpd-support/Deprivation/Carstairs/ (last accessed 17th January 2022).\u003c/p\u003e\n\u003cp\u003e89.\u0026nbsp;Oakes JM, Rossi PH. The measurement of SES in health research: current practice and steps toward a new approach. Social science \u0026amp; medicine. 2003;56(4):769-84.\u003c/p\u003e"},{"header":"Table","content":"\u003cp\u003eTable 3 Summary of included studies.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSetting (and country)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Design and method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain Findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuality Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eDaugaard et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the association between social and socioeconomic position and drug reimbursement due to terminal illness (DRTI) registration among patients who are terminally ill in Denmark.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (Denmark)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eTerminally ill patients who died 2006 \u0026ndash; 2015 with cancer or seven other chronic illnesses (n=307188).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDatabase analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eNo association between education and DRTI.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHigher prevalence of DRTI in middle/high income patients, however palliative care needs may be under-recognised in low income patients.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLower prevalence of DRTI in employed patients.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eAnkuda et al (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo identify what services are critical and why they matter to patients in a home-based palliative program.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospice \u0026ndash; home based program (US)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eEnrollees in the program (n=18).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interviews and survey\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eParticipants living in poverty had more non-routine and social work visits and found the social services provided by a home hospice service to be the most critical aspect of care.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eAzhar et al (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo compare time of referral and characteristics (level of symptom distress) among uninsured (indigent), low-insured (Medicaid), and insured patients presenting to the supportive care center.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eOutpatient center (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with advanced cancer (500)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eUninsured and low/partially insured patients had higher ESAS pain scores\u003c/li\u003e\n \u003cli\u003eIndigent patients had:\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;More encounters with palliative care team per month\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Higher levels of distress\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Higher risk for aberrant opioid usage and\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;More frequently on opioids at time of referral to centre\u003c/li\u003e\n \u003cli\u003eInsurance status did not impact timing of palliative care referral or follow-up.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eBrown et al (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the association between race/ethnicity, other key social determinants of health, and healthcare intensity in the last 30 days of life for those with chronic, life-limiting illness.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAll patients who died from 1 of 9 chronic conditions between January 2010 and December 2015 (n=22068).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDatabase analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eLower income was associated with higher likelihood of receiving high intensity care (i.e., treatment in an intensive care unit, receipt of mechanical ventilation, receipt of cardiopulmonary resuscitation) in the last 30 days of life.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eCervantez et al (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo evaluate how insurance coverage and ethnicity impact distribution of symptom burden and how those factors influence palliative access for patients at a South Texas cancer center.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eOutpatient center (US).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients who attended clinics (n=604).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eSymptom burden was similar in insured and uninsured patients, but there was a four-fold delay in first palliative care visit in uninsured group.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eSaeed et al (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo test the hypothesis that men and those with lower levels of educational attainment would have less favourable attitudes towards palliative care.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity and hospital-based cancer clinics (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with cancer (n=383).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing VOICES dataset.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eMost patients would desire palliative care if no further anti-cancer treatment would be helpful.\u003c/li\u003e\n \u003cli\u003eNo difference in preferences between those with different levels of education.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eCai et al (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the socioeconomic differences in the propensity and intensity of health service use for the three main home-based services (physician visits, nurse visits and personal support worker hours), and to explore the determinants of the use of home-based palliative care services.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHome-based palliative care program (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAdult primary caregivers of patients who were diagnosed with malignant neoplasm (n=181).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey administered to participants.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with lower socioeconomic status were more likely to receive at least one home-based nurse visit or personal support worker (PSW) visit.\u003c/li\u003e\n \u003cli\u003eLower socioeconomic status was associated with higher intensity of health service use.\u003c/li\u003e\n \u003cli\u003eSocioeconomic status is a significant predictor of propensity and intensity of home-based nurse and PSW visit even after controlling for health status.\u003c/li\u003e\n \u003cli\u003ePatients with higher levels of education were less likely to receive at least one home-based PSW visit.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eKoroukian et al (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo gain a better understanding of the correlates of aggressive end-of-life care and hospice use in older adults dying from cancer, by accounting for both social determinants of health and multimorbidity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eParticipants \u0026lt;66 years who died from cancer with complete Medicare claims history (n=835).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;Database analysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePercentage of patients receiving cancer-directed treatment increased with higher education and income.\u003c/li\u003e\n \u003cli\u003eNo significant difference by income or education for admission to hospital.\u003c/li\u003e\n \u003cli\u003eEnrolment in hospice was generally higher with higher levels of education or income.\u003c/li\u003e\n \u003cli\u003eThere was a U-shaped distribution between in-hospital death and income and education.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eKrishnan et al (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the family and facility factors that may influence the decision to transfer nursing home residents to hospital in the last month of life.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eNursing homes (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAdult relatives of residents who had died in the past year and was self-reported as the most involved in their care in their last month of life (n=119).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eThere was a higher prevalence of hospital transfers among deceased whose family members had lower income.\u003c/li\u003e\n \u003cli\u003eLow income family members were 3 times more likely to send patient to hospital.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNo statistically significant relationship was noted between employment or education level of the family members and terminal hospital transfers.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eCarlucci et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo elicit the patients\u0026rsquo; end-of-life preferences in very severe chronic obstructive pulmonary disease.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (Italy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with very severe COPD (n=43).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interview\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with lower education were more likely to choose endotracheal tube intubation.\u003c/li\u003e\n \u003cli\u003eHigher education level is the strongest predictor of probability of choosing palliative care option with oxygen and morphine.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eDhingra et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo evaluate a diverse population served by an interdisciplinary model of community-based specialist palliative care and the variation in service delivery over time and identify subgroups with distinct illness burden profiles.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity palliative care program (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients referred to the program (n=894).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients who reported very low illness burden more likely to reside in impoverished neighbourhoods.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eKarikari-Martin et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine whether differences in hospice use and use of aggressive services in the last 12 months of life are influenced by race or any cancer diagnosis while adjusting for the covariates age, gender, marital status, education level, neighbourhood socioeconomic status, cognitive function, and physical function.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eA geographically-defined community in Chicago (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eParticipants \u0026lt;65 years enrolled Medicare for at least 1 year before death (n=2954).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing CHAP data.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eHigher neighbourhood level socioeconomic status and higher income each significantly increased the likelihood of using hospice.\u003c/li\u003e\n \u003cli\u003eRace has a more powerful effect on hospice use than socioeconomic status neighbourhood.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHigher education was associated with a significantly decreased risk of hospitalization at the end of life.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eKhosla et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo investigate the association between socioeconomic status (i.e., education and household income) and anticipatory care planning (ACP) over time using data from the Health and Retirement Study (HRS), a nationally representative survey of middle-aged and older adults living in the contiguous United States.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHealth and Retirement Study (HRS) (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eSpouses, partners or proxy informants of HRS respondents (n=6052).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eVery limited support was found for the hypothesis that socioeconomic status would predict ACP.\u003c/li\u003e\n \u003cli\u003eHigher household income increased the odds of having a legally designated power of attorney for health care but had no impact on end of life discussions or written instructions.\u003c/li\u003e\n \u003cli\u003eEducation level did not predict engagement in ACP behaviours.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eLee et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo understand the association of minority race/ethnicity and education with family ratings of the quality of dying and death.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital Intensive Care Units (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eFamilies of patients who died (n=1290).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eEducation was not significantly associated with ratings on the quality of death questionnaire for either patient or family models.\u003c/li\u003e\n \n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eSchou-Andersen et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo investigate whether demographic and socio-economic factors were associated with preference for dying at home.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (Denmark)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eRelatives of adults who died from cancer (n=282).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants, database analysis.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eAt the beginning of palliative period, low income patients more likely to prefer dying at home than high income patients, however medium income patients less likely.\u003c/li\u003e\n \u003cli\u003eAt the end of the palliative period, no association between preference for dying at home and income.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eHuang et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the association of individual income and end-of-life care in older cancer decedents in Taiwan.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (Taiwan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAdults aged over 65 years with cancer (n=28978).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;Database analysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eLow income was associated with more aggressive end of life care.\u003c/li\u003e\n \u003cli\u003eOlder cancer decedents with low income were more likely to stay in hospital \u0026lt;14 days and die in acute hospital.\u003c/li\u003e\n \u003cli\u003eOlder cancer decedents with moderate/high income were more likely to have visited the emergency department and admitted to intensive care more frequently.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eNeergaard et al (2015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo analyse associations between GP contacts at the end of life and socioeconomic and cultural characteristics of Danish cancer patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (Denmark)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eRelatives of adults who died from cancer (n=584).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing dataset.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eGP face-to-face appointments were higher for decedents with cancer who had low income than those with normal/high income.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eTang et al (2015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo describe longitudinal changes in post-traumatic growth (PTG) during the dying process and to identify determinants of PTG among terminally ill cancer patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital inpatient units (Taiwan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eTerminally ill cancer patients (n=313).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with at least senior high school education achieved higher post-traumatic growth scores than those with low education.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eTucker-Seeley et al (2015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo investigate the association between financial hardship and intensive care in the last week of life.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCancer Centers, as part of the Coping with Cancer (CwC) study (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eCaregivers of deceased cohort (n=281).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing CwC data.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients who reported financial hardship had higher odds of receiving intensive end of life care.\u003c/li\u003e\n \u003cli\u003eNo association between educational attainment or health insurance status and aggressive end of life care.\u003c/li\u003e\n \u003cli\u003eWhen treatment preferences were included in the fully adjusted model, the association between financial hardship and intensive EOLC was slightly attenuated but remained statistically significant.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eBhatraju et al (2014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo evaluate the factors that were associated with palliative care consultation (PCC) utilization in patients who died in an urban municipal public hospital in the United States, and to examine the association of PCC utilization with symptom management and advance directives at the end of life.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital \u0026ndash; Inpatients (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients who died in the units (n=378).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRetrospective chart review.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eHigher level of education was associated with palliative care consultation (PCC) utilisation.\u003c/li\u003e\n \u003cli\u003ePatients who had PCC were more likely to receive opiates in final 72 hours of life, but there was no observed difference in benzodiazepine use.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eChang et al (2014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo assess the association between aggressiveness of end-of-life care and socioeconomic status in working-age terminal cancer patients in Taiwan between 2009 and 2011.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (Taiwan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAdult cancer patients (n=32800).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDatabase analysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eHigh and moderate socioeconomic status patients had: \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Lower scores for aggressive end of life care\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Less chemotherapy\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Fewer emergency department visits\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Less intensive care unit admission\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Lower rates of dying in acute care hospitals.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eLewis et al (2014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo explore the nature of social capital in a socioeconomically disadvantaged group of palliative care patients and carers, using a social capital questionnaire to guide and frame discussions.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients who were known to the palliative care service (n=22).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQualitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interviews\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eOverall provision of informal care generally by sole caregiver with intermittent family support.\u003c/li\u003e\n \u003cli\u003eEstablished neighbour and\u0026nbsp;inter-sectoral networks essential for sustaining care and social needs\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDid not feel very engaged with community.\u003c/li\u003e\n \u003cli\u003eLimited communication due to cultural differences\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFormalised community care support described as overall being somewhat inconsistent and unpredictable.\u003c/li\u003e\n \u003cli\u003ePatients and carers unsure of formal care being provided.\u003c/li\u003e\n \u003cli\u003eContact with government agencies (welfare support and government housing) described as positive generally\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eTang et al (2014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo investigate the associations between accurate prognostic understanding and\u003cbr\u003e\u0026nbsp;end-of-life care preferences, and to identify correlates of accurate prognostic understanding among terminally ill cancer patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (Taiwan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eTerminally ill cancer patients (n=2452).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with at least senior high school education were 1.28 times more likely to accurately know prognosis.\u003c/li\u003e\n \u003cli\u003eAccurate prognostic understanding associated with greater odds of preferring comfort-oriented care and increased preference for hospice care.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eChang et al (2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo describe how much burden terminal cancer patients and their caregivers had experienced, what support they most needed, and the differences between them.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (South Korea)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with terminal cancer (n=481) and their caregivers (n=381).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eLow level of education predicted satisfaction about overall care.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eMasucci et al (2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the predictors of the propensity and intensity of five main health service categories in the last three months of life for home-based palliative-care patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity. Home-based (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eFamily caregivers of patients with malignant neoplasm (n=109).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interviews, database analysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients in the highest deprivation group had higher intensity of home-based nurse visits.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eSahin et al (2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo evaluate the relationship between different demographic variables and hopelessness, depression and social support in end of life Turkish cancer patients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (Turkey)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with cancer (n=216).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with lower education had higher hopelessness scores, but not depression or social support.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eBergman et al (2010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo assess the quality of end of life care in low income uninsured men prospectively enrolled in a specific public assistance program.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eAll low-income, uninsured men in the program (n=60).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRetrospective chart review, database analysis.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eNo patients had chemotherapy initiated within 3 months of death, and only 6% had chemo within 2 weeks of death.\u003c/li\u003e\n \u003cli\u003eUse of hospital resources (emergency department visits, inpatient admissions, intensive care) was uniformly low.\u003c/li\u003e\n \u003cli\u003eHospice utilisation was comparable and timing of referral was better than population.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eFergus et al (2010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo identify key challenges and improvements to out-of-hours palliative care in a mixed urban and rural deprived area.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (United Kingdom)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eMixed; Patients (n=6), carers (n=1) and healthcare professionals (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interviews, database analysis, observation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients voiced reluctance to use Out of hours primary care phoneline due to:\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Stressful and cumbersome process of making initial \u0026nbsp; contact\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Bad experiences previously\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Misunderstanding of its function\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Reluctance to speak to an unknown person\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Had bad experiences previously\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Did not realise had \u0026lsquo;special notes\u0026rsquo; so assumed would be too complex\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eMaric et al (2010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo estimate the frequency of anxiety and depression symptoms in patients with advanced lung cancer, and the associations of these with demographic, socioeconomic and clinical factors.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (Serbia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with stage 3B and 4 non-small cell lung cancer (n=100).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eNo difference in levels of psychological distress between education groups or rural versus urban groups.\u003c/li\u003e\n \u003cli\u003eHowever, unemployed patients had significantly less anxiety and depressive symptoms.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eChochinov et al (2009)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo use the Patient Dignity Inventory (PDI), a novel, reliable and validated measure of end-of-life distress, to describe a broad landscape of distress in patients who are terminally ill.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients in this program who received palliative care (n=253).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients who were more educated were significantly more likely to report feelings of having lost control, feelings of unfinished business and not being able to perform tasks of daily living.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eCarr et al (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo explore the extent to which socioeconomic status indicators are associated with attributes considered essential to the quality of one\u0026apos;s death.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eMixed; Bereaved spouses (n=408), patients (n=5276)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing datasets.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eLimited evidence that socioeconomic status affects death quality, except in pain at the end of life.\u003c/li\u003e\n \u003cli\u003eWealthier participants were less likely to report severe pain at the end of life, and are more likely to engage in advanced care planning.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eAdler et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo explore the lived experiences of medically underserved women with advanced breast cancer.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity \u0026ndash; clinic (US)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with breast cancer and annual family income below 200% of the federal poverty level (n=63).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQualitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndividual interviews\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eConsistent issue of financial distress at the end of life, including difficulty meeting basic needs, inadequate financial resources, inability to work.\u003c/li\u003e\n \u003cli\u003ePatients had concerns about not being \u0026ldquo;useful\u0026rdquo; when unemployed and being financially burdensome\u003c/li\u003e\n \u003cli\u003ePerceived bias in healthcare \u0026ndash; some patients felt they were not treated as well by healthcare professionals\u003c/li\u003e\n \u003cli\u003ePatients viewed fewer financial means, lack of access to private insurance and cancer centres, and minority status as barriers to high quality care.\u003c/li\u003e\n \u003cli\u003eThey remained highly attentive to others\u0026rsquo; needs and worked to maintain caretaking roles despite own struggles. They made effort to attend to practical matters.\u003c/li\u003e\n \u003cli\u003eMany downplayed desires to discuss dying due to pressure of staying positive.\u003c/li\u003e\n \u003cli\u003eThey appreciated meaningful aspects of life (social relationships, creative outlets, spirituality) and felt altruism was important before and during illness.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eBijnsdorp et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo identify different types of home-based care networks of community dwelling older adults in the Netherlands, and to assess the association between the different types of home based care networks and the health status and sociodemographic characteristics of care recipients.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (Netherlands)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eRespondents who died within 12 months of their last interview, lived at home, and received personal and/or household care (n=146).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eThose with higher education were more likely to have informal care provided by partners whereas those with lower educational attainment more likely to require formal care.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eDavidoff et al (2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine patterns of symptom management at end of life for older adults who died of lung cancer.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003ePopulation-based (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eIndividuals who had at least one day in the outpatient non-hospice setting during the last month before death (n=16246),\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDatabase analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eHigh poverty levels were associated with increased receipt of pain, dyspnoea and emotional distress medication.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eYi et al (2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo compare health and social care costs, quality and their drivers in the last 3 months of life for older adults across countries.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital and Community (UK, Ireland, US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eCarers of patients who had accessed a participating palliative care team (n=767)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eOnly 4% reported difficult/very difficult financial circumstances, 10% reported just about alright.\u003c/li\u003e\n \u003cli\u003eHigher care costs if \u0026ldquo;difficulty living on current income\u0026rdquo;.\u003c/li\u003e\n \u003cli\u003eHospital care accounts for over 80% total health and social costs, community and palliative costs were low.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eJacob et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo assess health related quality of life (HRQoL) of advanced cancer patients in terms of general wellbeing (physical, functional, emotional, and social/family wellbeing), pain experiences, psychological state, and spiritual wellbeing, and determine the relationship between belonging to a disadvantaged group and HRQoL outcomes.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eHospital (India)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with cancer (n=210).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSurvey to participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003ePatients with higher financial difficulty scores reported lower functional wellbeing, lower emotional wellbeing, lower meaning/peace (subscale of spiritual wellbeing), and higher anxiety and depression scores. Level of education did not affect this.\u003c/li\u003e\n \u003cli\u003eEven in setting where cancer treatment is free, those with higher financial difficulty scores report lower quality of life outcomes.\u003c/li\u003e\n \u003cli\u003eScores of this population generally lower than patients in higher income countries e.g., USA.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eLeng et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo explore the prevalence, determinants and consequences of catastrophic health expenditure (CHE) among urban and rural end-of-life cancer patients in China.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (China)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eFamilies of deceased cancer patients (n=792).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFace to face interviews\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eThere were very high levels of catastrophic healthcare expenditure (CHE) at end of life throughout.\u003c/li\u003e\n \u003cli\u003e1/3 of patients borrowed money from family and friends.\u003c/li\u003e\n \u003cli\u003eHouseholds with higher income were less likely to incur CHE.\u003c/li\u003e\n \u003cli\u003eRural, low income patients were least likely to access healthcare, inpatient care, and most likely to only use outpatient care. Use of inpatient and outpatient services in these patients increased the risk of CHE.\u003c/li\u003e\n \u003cli\u003eRural patients allocated higher proportion of household income to healthcare and associated expenditures.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eSaeed et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo study the effect of income and education on the completion of advanced directives.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity and hospital (US)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients with cancer (n=265)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary analysis of pre-existing VOICE dataset.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eNearly a third of lower income patients had not completed advanced directives (AD).\u003c/li\u003e\n \u003cli\u003ePatients with lower income had lower AD scores, but there was no significant association between education or perceived financial strain and AD scores.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eStajduhar et al (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo identify barriers to assessing care among structurally vulnerable people at the end of life.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003eMixed; People experiencing structural vulnerability in a Western Canadian province (n=25), their support persons (n=25) and formal service providers (n=69).\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQualitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRepeated participant observation, individual interviews\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eStructural vulnerability was defined in this study as people living in poverty, in unstable housing, while experiencing various forms of oppression and stigma, e.g., racism, ongoing or past trauma and violence, social isolation, mental and cognitive issues, behavioural issues, substance use, interactions with the criminal justice system, or physical disability. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThese patients were found to have significant barriers in having their palliative needs met including: \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Survival imperative \u0026ndash; focussing on basic care needs;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Normalization of dying \u0026ndash; often had been told they would die due to addictions\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Problem of identification \u0026ndash; often not signposted to appropriate health, social benefits\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Professional risk and safety management \u0026ndash; due to stigmatization from health care professionals\u003c/li\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Cracks of a silo-ed care system \u0026ndash; complexity of the care systems made them difficult to navigate.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003eWales et al (2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.00709219858156%\"\u003e\n \u003cp\u003eTo examine the association between socioeconomic status and other demographic factors on place of death in a population receiving home palliative care in Toronto, Canada.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.47517730496454%\"\u003e\n \u003cp\u003eCommunity - Home palliative care service (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.4822695035461%\"\u003e\n \u003cp\u003ePatients who died with home-based palliative care service (n=2066).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.340425531914894%\"\u003e\n \u003cp\u003eQuantitative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRetrospective chart review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.099290780141843%\"\u003e\n \n \u003cli\u003eRate of preference for home death was significantly lower in lowest income quintile.\u003c/li\u003e\n \n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Palliative Care, Terminal Care, Socioeconomic Factors, Social Class, Delivery of Health Care, Integrative review","lastPublishedDoi":"10.21203/rs.3.rs-1302205/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1302205/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eThose experiencing socioeconomic deprivation have poorer quality of health throughout their life course which can result in poorer quality of death – with decreased access to palliative care services, greater use of acute care, and a disparity in deaths at home compared with patients from less deprived populations.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAim:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eTo summarise the current global evidence from developed countries on end-of-life experience for those living with socio-economic deprivation.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDesign:\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eIntegrative review in accordance with PRISMA\u003cem\u003e. \u003c/em\u003eA thorough search of major databases from 2010-2020, using clear definitions of end-of-life care and well-established proxy indicators of socio-economic deprivation. Empirical research describing experience of adult patients in the last year of life care were included.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eForty studies were included from a total of 3508 after screening and selection. These were deemed to be of high quality; from a wide range of countries with varying healthcare systems; and encompassed all palliative care settings for patients with malignant and non-malignant diagnoses. Three themes were identified: 1) the multi-dimensional experience at end-of-life, 2) preferences and planning and 3) the uptake and utilization of services.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eCurrent models of healthcare services are not meeting the needs of those experiencing socio-economic deprivation at the end-of-life. Further work is needed to understand the disparity in care, particularly around ensuring patients voices are heard and can influence service development and delivery.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"The End Of Life Experiences Of People Living With Socio-Economic Deprivation In The Developed World: An Integrative Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-02-28 16:42:56","doi":"10.21203/rs.3.rs-1302205/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-05-10T05:29:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-16T10:44:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d9783530-b772-4d93-9132-2c1005c3d15d","date":"2022-04-03T11:58:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-03-25T13:44:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e0c8a48b-a936-4320-8728-e86fe1bc759d","date":"2022-03-14T19:02:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-03-05T05:07:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-02-25T12:06:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-02-25T11:40:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-02-25T11:36:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Palliative Care","date":"2022-01-27T10:08:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0241191a-3093-44d3-9a36-a2b96f1808a8","owner":[],"postedDate":"February 28th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-09-19T10:14:20+00:00","versionOfRecord":[],"versionCreatedAt":"2022-02-28 16:42:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1302205","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1302205","identity":"rs-1302205","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}