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Out-of-pocket costs near end of life in low- and middle-income countries: A systematic review

  • Eleanor Reid ,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliations Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America, Usher Institute, University of Edinburgh, Edinburgh, Scotland

  • Arunangshu Ghoshal,

    Roles Data curation, Formal analysis, Writing – review & editing

    Affiliation Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India

  • Aisha Khalil,

    Roles Data curation, Formal analysis, Writing – review & editing

    Affiliation INFAQ Foundation, Karachi, Pakistan

  • Jingjing Jiang,

    Roles Data curation, Formal analysis, Investigation, Writing – review & editing

    Affiliation Centre for Health Policy and Management, Trinity College Dublin, Dublin, Ireland

  • Charles Normand,

    Roles Conceptualization, Investigation, Methodology, Supervision, Visualization, Writing – review & editing

    Affiliations Centre for Health Policy and Management, Trinity College Dublin, Dublin, Ireland, Cicely Saunders Institute, King’s College London, London, United Kingdom

  • Alexandria Brackett,

    Roles Data curation, Methodology, Software

    Affiliation Cushing/Whitney Medical Library, Yale University, New Haven, Connecticut, United States of America

  • Peter May

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Centre for Health Policy and Management, Trinity College Dublin, Dublin, Ireland, The Irish Longitudinal Study on Ageing, Trinity College Dublin, Dublin, Ireland



Globally, there is a rise in chronic disease, including cancer, major organ failure and dementias. Patients and their families in low- and middle-income countries (LMICs) pay a high proportion of medical costs out of pocket (OOP), and a diagnosis of serious illness often has catastrophic financial consequences. We therefore conducted a review of the literature to establish what is known about OOP costs near end of life in LMICs.


To identify, organise and report the evidence on out-of-pocket costs in adult end-of-life populations in LMIC.


A systematic search of 8 databases and a hand search of relevant systematic reviews and grey literature was performed. Two independent reviewers screened titles and abstracts, assessed papers for eligibility and extracted data. The review was registered with PROSPERO and adhered to the Preferred Reporting items for Systematic Reviews and Meta Analyses. The Mixed Methods Appraisal Tool was used to assess quality. The Wagstaff taxonomy was used to describe OOP.


After deduplication, 9,343 studies were screened, of which 51 were read and rejected as full texts, and 12 were included in the final review. OOP costs increased with advanced illness and disease severity. The main drivers of OOP were medications and hospitalizations, with high but variable percentages of the affected populations reporting financial catastrophe, lost income, foregone education and other pressures.


Despite a small number of included studies and heterogeneity in methodology and reporting, it is clear that OOP costs for care near end of life in LMIC represent an important source of catastrophic health expenditures and impoverishment. This suggests a role for widespread, targeted efforts to avoid poverty traps. Financial protection policies for those suffering from incurable disease and future research on the macro- and micro- economics of palliative care delivery in LMIC are greatly needed.



Low- and middle-income countries (LMICs) face sharply increasing incidence of non-communicable diseases such as cancer, major organ failure, and Alzheimer’s disease and related dementias [1]. Health systems widely lack capacity and resources to meet even current levels of need with curative and supportive treatment [2]. Patients and their families in LMICs pay a high proportion of costs out of pocket, and a diagnosis of serious illness often has catastrophic financial consequences for a household [3].

The end-of-life phase has unique physical, psychological and spiritual challenges [4]. There is also a widely documented association between the last year of life and health care utilization [5], particularly when people die with multiple serious chronic diseases [6]. Therefore end-of-life care brings specific financial pressures for patients and their families in terms of medical care (e.g. paying for medications) and unpaid care, foregone income, and transport to and from appointments [7].

People with terminal illness and their families in LMICs are vulnerable to bankruptcy and impoverishment as populations age, and the poorest sections of society are routinely the most vulnerable of all [8]. One particular susceptibility is spending on supposedly disease-modifying treatments, particularly in the absence of palliative care services that aim to guide the patient and family towards better choices. The downstream effects of palliative care are both improved patient reported outcomes, and cost savings [9, 10]. In LMICs, it is unknown what percentage of the high costs of medical care are borne early versus later on in the disease trajectory: it may be that early drivers of financial hardship begin at time of diagnosis, such that by the time a patient reaches end stage disease, the family has already been burdened by heavy costs. For this reason, in high income settings, there is evidence to support early initiation of palliative care, alongside curative treatments [11, 12].

Faced with impossible choices between earning income or caring for a loved one, or between retaining basic assets or paying for treatment, end-of-life care is a potential poverty trap for many [9]. Palliative care services in those countries are generally underdeveloped with widespread prevalence of unmet need [10].

Out-of-pocket costs in LMICs are a long-standing policy question [3]. The economics of end-of-life care has received growing attention in the last decade, but with a heavy focus on high-income countries where high end-of-life costs for the health system often represent overtreatment and poorly coordinated care between hospital and home settings [13]. The situation in LMICs is fundamentally different: high costs near end of life are widely borne by patients and their families, where the alternative is to receive no treatment [9]. Studies examining out-of-pocket costs and family burden have also dealt predominantly with high-income country settings [14].

Rationale and aim

We are unaware of any prior review examining the costs to patients and families in the end-of-life phase in LMICs. We therefore conduct a review of the literature to establish what is known about out-of-pocket costs near end of life in those settings. Arising results can inform efforts in low-resource settings to upscale palliative care provision, to design financial protection policies for people with non-communicable disease, and to conduct future research on the economics of palliative and end-of-life care in settings where prior attention has been minimal.

Materials & methods

Protocol and registration

We registered a protocol for this systematic review on PROSPERO (CRD42020215188). Registration date was November 19th, 2020.

Search strategy and information sources

A clinical librarian (AB) developed the search strategy after a consultation with ER and PM. AB also received related articles which helped formulate the search strategy with the use of the Yale MeSH Analyzer and were later used to validate search concepts.

The search strategy was peer-reviewed by another senior librarian. The search strategy used both keywords and controlled and indexed vocabulary combining the terms for low-and-middle income countries, cost, and palliative care.

The databases were searched from inception to August 5, 2020; the databases included: MEDLINE (Ovid), Embase (Ovid), APA PsycInfo (Ovid), Global Health (Ovid), CINAHL (Ebsco) Web of Science (indexes: SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC), Scopus, EconLit (ProQuest), and Cochrane CENTRAL. See S1 File for the search details for each database.

We supplemented database searches with other methods. One reviewer (JJ) hand-searched three potentially relevant systematic reviews [10, 15, 16]. One reviewer (AG or AK) hand-searched from 2010 to August 2020 the following journals: Lancet Global Health, BMJ Global Health and Indian Journal of Palliative Care. One reviewer (JJ) hand-searched the following websites as grey literature sources: World Bank, World Health Organization and United Nations University economics department [1719].

Eligibility criteria and study selection

Inclusion criteria.

Population. Adults (aged 18+) at the end of life or diagnosed with one of the following serious life-limiting medical illnesses: advanced cancer, serious heart disease (e.g., heart attack, PVD, CHF), major organ failure (e.g., lung, liver, kidney), advanced Alzheimer’s disease and related dementias, AIDS/HIV.

Intervention. Palliative care, supportive care and end of life, opioids, and other pain management medications.

Comparison. Any or none.

Outcome. Out-of-pocket costs incurred by patients and their families in care and treatment for end-of-life care. We include studies that measure the monetary cost of providing informal care, including costed dedicated time, income foregone through lost work, and additional costs incurred (e.g., travel, patient medications).

Setting. Low- and middle-income countries, as defined by the World Bank [20].

Study design. Any.

Exclusion criteria.

Population. Studies of children. Studies of people with other chronic diseases (e.g., TB, diabetes) as a primary diagnosis. Studies of people in the early stages of a terminal disease.

Intervention. Screening, identification, diagnosis of disease. Medications with a predominantly curative intent.

Outcome. Costs of care where the patient does not contribute their own resources in money or time, e.g., any service free at the point of use. Prevalence of out-of-pocket payment or unpaid care (e.g., “how many households have an informal carer?”) where that prevalence is not quantified as an estimation of time or cost.

Setting. Studies in high-income countries.

Other. Studies where our population, outcome and setting are not specifically reported, e.g. (1) an overview of out-of-pocket costs at the population level that does not delineate those with terminal illness or at end of life, e.g. (2) a cost of illness study for a terminal illness that does not delineate out-of-pocket and centrally funded costs. Studies where out-of-pocket costs are hypothetical and/or employed as a predictor (e.g., “Is high potential out-of-pocket costs a reason why women do not attend breast cancer screening?”; “What is the willingness to pay for different cancer treatments?”). Any publication type except research articles (e.g., letters to the editor, conference abstracts). We included only English language articles and retained eligible abstracts in other languages to assess risk of bias from the English-only constraint.

Rationale for these criteria.

We imposed three basic criteria: LMIC setting, palliative/end-of-life population and out-of-pocket costs as an outcome of interest. Among these, only the first can be categorized discretely according to objective rules (we use The World Bank) [20]. For population, we anticipated challenges in distinguishing the end-of-life phase given that life-limiting illnesses often have poor prognosis in LMIC settings. We did not require that populations are characterized as “end of life” but we did require that the disease be advanced. Populations defined as “early” in a trajectory of serious disease, as well as evaluations of prevention, including vaccination, screening and diagnosis, were excluded. Pharmacoeconomic evaluations of any drugs with life-extending intent were also excluded. For out-of-pocket costs, we defined this broadly to include literal currency spending but also unpaid care and other labor, transport costs, foregone income. Studies that report “total” costs in any circumstance, but do not report separately out-of-pocket and informal care costs, were excluded at full text review. Prior experience showed that evidence on interventions near end of life in LMICs is scant [10], but any study that described, quantified, evaluated determinants, or otherwise addressed specifically our outcome, population and setting of interest were considered eligible.

Study selection.

Each title/abstract was screened as (in)eligible by two independent reviewers (two of AG, AK, ER, PM). Disagreements were settled by consensus, with either ER or PM acting as the third reviewer.

Full texts were screened using the same process as titles/abstracts. Quality assessment of included studies was performed by two independent reviewers (one of AG and AK, and one of ER and PM) using the MMAT tool. There was no quality cut-off for inclusion, we resolved that eligible studies be reported in the context of their methods and limitations.

Data extraction and data items

Data were extracted using the same process as titles/abstracts: two independent reviewers, with a third senior reviewer (ER or PM) adjudicating any conflicts. Data were extracted to a bespoke form developed in Excel, that required data points on author, year of publication, country of data collection, year of data collection, study design, sample size (total, exposure, comparison), population, intervention/exposure, comparison, outcome of interest, main results, key themes/messages/strengths, and key limitations. The two reviewers’ outputs were then merged into a single file by a third reviewer (AG or AK), and conflicts or problems solved by consensus.

Risk of bias within individual studies and across studies

In anticipation of a small, heterogeneous literature we did not evaluate risk of bias specifically but assessed bias as part of quality assessment.

Summary measures and synthesis of results

In anticipation of a small, heterogeneous literature we did not pre-specify an outcome of interest (e.g., risk ratio or cost-effectiveness ratio) but instead adopted a flexible approach depending on identified studies, which could include descriptive studies. We planned therefore for narrative synthesis, organizing reported out-of-pocket costs according to seven measures in a well-known systematic review: (i) expenditure in absolute (international dollar) terms; (ii) measures of dispersion (or risk); (iii) the out-of-pocket budget share; (iv) progressivity; (v) the incidence of “catastrophic” expenditures; (vi) inequality in the incidence of catastrophic expenditures; (vii) the incidence of “impoverishing” out-of-pocket expenditures, as well as the addition to the poverty gap due to out-of-pocket expenditures [3].


Study selection

The database search returned a total of 13,751 records with 9,337 unique articles. The hand search identified six additional studies and the grey literature search identified no relevant studies. These 9,343 studies were screened in Covidence. We excluded 9,280 articles after screening of titles and abstracts, and a further 51 articles after reading the full text. One of these exclusions was due to not being in English [21]. Thus, we included 12 articles in our review. See Fig 1.

Study characteristics

The data extracted from the twelve included studies [2233] are presented in Table 1.

The earliest study was published in 2002 and the most recent in 2020 with a median publication year of 2018. There were six studies conducted in India, and one each conducted in China, Kenya, Pakistan, Tanzania, Thailand and Southeast Asia (covering Cambodia, Indonesia, Laos, Malaysia, Philippines, Thailand, and Vietnam). See Fig 2.

Fig 2. Map of included countries.

Black = Country included in systematic review.

There were six descriptive cross-sectional studies, of which three were conducted prospectively [26, 27, 32] and three retrospectively [22, 29, 30]. Three further prospective studies involved original data collection: one longitudinal study,[25] one cohort study [33] and one exploratory pilot study.[24] Three were retrospective case-control studies comparing people who died in hospital with those who did not. [23, 28, 31]. No study evaluated the effects of an intervention. The largest study had 94,084 participants, the smallest study had 11 participants with a median sample size of 185.5.


Six studies based their sampling frames on diagnosis of a specific disease: three in cancer, [22, 25, 29] two in liver disease [31, 32] and one in Alzheimer’s disease [26]. Three studies conducted convenience sampling via a palliative care provider [24, 27, 33]. Two studies analyzed large population-representative surveys on health and morbidity [23, 28]. One study surveyed households that had recently suffered a bereavement [30].


Nine studies evaluated outcomes specified by the taxonomy of Wagstaff et al [3]. Two studies measured prevalence of financial catastrophe, contextualizing costs according to the means of people with serious illness and their families. [25, 31] Seven studies quantified out-of-pocket spending and/or debt in absolute currency amounts [2224, 26, 28, 29, 31]. Additionally, one study quantified unpaid carer burden [26] and three studies measured objective and/or subjective financial burden [24, 30, 33].

Quality of reporting

Quality assessment were performed by two independent reviewers (one of AG and AK, and one of ER and PM) using the MMAT tool. The MMAT is intended to be used as a checklist for concomitantly appraising and/or describing studies included in systematic mixed studies reviews (reviews including original qualitative, quantitative, and mixed methods studies). There was no quality cut-off for inclusion, and studies have been reported in the context of their methods and limitations. A summary of the quality assessments is provided in Table 2. Full details of the MMAT scores are provided as S2 File.

Main results

Main results of each included study are presented in Tables 36, separated by outcome.

Table 3. Results of studies quantifying catastrophic financial circumstances.

Table 4. Results of studies quantifying out-of-pocket spending, debt.

Table 6. Results of studies reporting prevalence of objective and subjective financial burden.

Synthesis of results

Financial catastrophe.

Results with respect to financial catastrophe are summarized in Table 3.

In India Prinja et al. [31] reported that 92% of people who died in hospital with advanced liver disease suffered catastrophic finances, defined as out-of-pocket spending that exceeded 40% of subsistence income. Medicines accounted substantively for costs, meaning that publicly funded purchasing schemes could address directly this financial catastrophe.

Kimman et al. [25] followed people for a year following a cancer diagnosis in seven South East Asian countries and found that only 23% were both alive and free of financial catastrophe, defined as out-of-pocket medical costs exceeding 30% of annual income. Among the sample, 48% were alive but facing financial catastrophe, and 29% had died. Since death and financial catastrophe are reported as competing outcomes, it is not known what proportion of those who died experienced high OOP spending and as such the results are not directly comparable with those of Prinja et al [31].

Out-of-pocket costs in absolute terms.

Results with respect to costs in absolute terms are summarized in Table 4. All studies reported substantial costs for their populations of interest, and additional factors that determined or mediated costs were identified.

Three studies in the hospital setting found that OOP costs for deceased patients in inpatient care is much greater than that of survivors [23, 28, 31]. Moreover, both total costs for decedents and the difference between decedent and survivor costs appear to be growing over time [21].

Cancer costs in private health care settings were higher than those in public settings [20], and higher for patients living in urban areas than rural areas [29]. People already receiving palliative care have high levels of cost and associated debt, [24] and magnitude of costs is strongly associated with disease severity [26, 32].

Unpaid carer burden.

One study looked at unpaid carer burden, summarized in Table 5 [26]. Unpaid caregiving hours were high in all stages of Alzheimer’s disease and highest among the severe disease group. This difference was statistically significant.

Objective and subjective financial burden.

Studies quantifying the incidence or prevalence of financial burden in descriptive measures are summarized in Table 6.

These measures affirm the findings in other tables that advanced medical illness results in high costs and financial pressures. Further, illness and associated costs catalyze vicious economic circles for patients and families. Persons with serious illness overwhelmingly lose their jobs or leave the workforce [24, 33]. Family members leave their jobs and drop out of education to provide care [24, 32]. To meet costs, patients and their families borrow money [29, 32, 33] and sell assets, [24, 30, 33] and in some cases forego food, medicines and health care. [32] Financial pressures confer anxiety about the household’s future [27]. Family members feel pressure to marry, or to engage in risky or illegal activity, in order to address lost income and rising costs [24].


Key results

Patients approaching end of life in LMIC pay a high proportion of medical costs out of pocket and often suffer catastrophic financial consequences, yet there is a dearth of robust, large scale health economic data to guide hypothesis-generating, poverty-reducing solutions. Financial catastrophe from serious medical illness is not only an issue for patients and families in the end-of-life stage but creates cyclical poverty traps: lost income, increasing borrowing and debt, anxiety and insecurity, and growing pressure to address financial pressures through drastic measures. Our systematic review directly addresses this global inequity with a rigorous search and summary of the existing literature, including a quality assessment.

Strengths and limitations

Strengths of the review include the broad search terms, inclusion of grey literature, the geographical heterogeneity in the included studies country of origin, and use of two independent reviewers at each step of the review. Limitations of this review are that much of the existing literature is from household surveys and interviews, thus introducing bias however this is mitigated by country-specific estimates for OOP which were included in three of our included studies. Only studies in English were included.


Inadequate government spending on health is a recurring feature in LMICs. Weak health infrastructure leads to delays in diagnosis and resulting late disease presentations, heavy reliance on out-of-pocket payments and catastrophic health expenditures. Those patients impacted the most include those from remote areas, those with longer and repeat hospitalizations and with the following diagnoses: cancer, Alzheimer’s disease, terminal HIV/AIDs and end stage liver disease. As out-of-pocket spending is inversely proportional to life expectancy, earlier diagnoses through improved screening programs would likely result in more treatable disease, at lower cost.

Policies aimed at bolstering socioeconomic resilience and financial protection are greatly needed in LMICs. A better understanding of early versus late drivers of medical impoverishment is an urgent research priority, as this would inform these strategies. In addition to earlier detection of disease, the provision of early, home-based and widespread access to palliative care in LMIC would serve to decrease OOP and CHE for those with incurable disease, and thus should be considered as a critical health priority and global poverty-reduction strategy. Furthermore, in resource-scare environments, increased access to palliative care would have the secondary effect of liberating limited health resources for those patients with curable disease thus benefiting society at large. The need for greater access to palliative care in LMICs is clear and the evidence for its role as a poverty reduction strategy is emerging. Future research should focus on the implementation and health economic outcomes of palliative care in LMICs, thus improving care for billions of the most vulnerable patients in our global population.

Globally, demographic ageing is likely to result in an increased burden on all levels of health systems and household services, partly due to the relatively long duration of illness at the end of life. Holistic palliative care can mitigate the desperate poverty caused by life-limiting illness, particularly if initiated early in the illness, on a regular basis and on a broad scale. Home-based treatment also frees up hospitals to serve patients with reversible conditions.


Patients approaching end of life in LMIC pay a high proportion of medical costs out of pocket and often suffer financial catastrophe. These effects are long term and potential poverty traps: reduced household income, rising debt, deteriorating mental health, and narrowing life choices. Policies and interventions are needed to prevent these often-avoidable crises. Evidence to inform such policies and interventions is currently thin.

Supporting information

S1 File. Search strategy.

A text file of the search strategies used in our systematic review.


S2 File. MMAT.

Full details of the MMAT scores which are summarized in Table 2.



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