https://orcid.org/0000-0001-7202-8676
Figures
Abstract
Objective
A non-negligible proportion of sub-Saharan African (SSA) households experience catastrophic costs accessing healthcare. This study aimed to systematically review the existing evidence to identify factors associated with catastrophic health expenditure (CHE) incidence in the region.
Methods
We searched PubMed, CINAHL, Scopus, CNKI, Africa Journal Online, SciELO, PsycINFO, and Web of Science, and supplemented these with search of grey literature, pre-publication server deposits, Google Scholar®, and citation tracking of included studies. We assessed methodological quality of included studies using the Appraisal tool for Cross-Sectional Studies for quantitative studies and the Critical Appraisal Skills Programme checklist for qualitative studies; and synthesized study findings according to the guidelines of the Economic and Social Research Council.
Results
We identified 82 quantitative, 3 qualitative, and 4 mixed-methods studies involving 3,112,322 individuals in 650,297 households in 29 SSA countries. Overall, we identified 29 population-level and 38 disease-specific factors associated with CHE incidence in the region. Significant population-level CHE-associated factors were rural residence, poor socioeconomic status, absent health insurance, large household size, unemployed household head, advanced age (elderly), hospitalization, chronic illness, utilization of specialist healthcare, and utilization of private healthcare providers. Significant distinct disease-specific factors were disability in a household member for NCDs; severe malaria, blood transfusion, neonatal intensive care, and distant facilities for maternal and child health services; emergency surgery for surgery/trauma patients; and low CD4-count, HIV and TB co-infection, and extra-pulmonary TB for HIV/TB patients.
Citation: Eze P, Lawani LO, Agu UJ, Amara LU, Okorie CA, Acharya Y (2022) Factors associated with catastrophic health expenditure in sub-Saharan Africa: A systematic review. PLoS ONE 17(10): e0276266. https://doi.org/10.1371/journal.pone.0276266
Editor: Dylan A. Mordaunt, Flinders University, AUSTRALIA
Received: July 4, 2022; Accepted: October 4, 2022; Published: October 20, 2022
Copyright: © 2022 Eze et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Over 930 million people globally suffered undue financial hardship while obtaining healthcare and about 100 million people were forced into poverty yearly from out-of-pocket (OOP) health expenses in 2019 [1]. As the predominant healthcare financing system in sub-Saharan Africa (SSA), OOP payments have hindered the region’s drive towards universal health coverage (UHC) [2]. Besides, OOP healthcare financing is inefficient and highly inequitable, further impoverishing the poorest households in the region [2, 3].
Catastrophic health expenditure (CHE)–defined as OOP payment above an estimated threshold share of total household expenditure at which the household is forced to sacrifice other basic needs, sell assets, incur debts, or be impoverished [4]–engenders a vicious cycle of poverty for some households that choose to seek services and leads to more illnesses for those who cannot afford OOP costs [5]. Improving financial protection to minimize the extent to which households incur CHE and are pushed into poverty due to high medical spending has received substantial attention [1, 4, 6]. To this end, the United Nations in 2015 included CHE incidence as a key indicator to track progress towards UHC (SDG 3.8.2) [1, 4, 6]. Reducing CHE incidence is one of the key objectives of the global, regional, and national health policy drive towards UHC and human development [1, 5].
Our previous study had demonstrated that a non-negligible proportion of households annually experience CHE in SSA (16.5% at the 10% total household expenditure threshold and 8.8% at the non-food expenditure threshold) [7]. There is, however, a wide demand for a better understanding of the factors associated with catastrophic OOP expenditure in the region to fine-tune interventions to adequately protect households [5]. Hence, this study aims to systematically review the literature to identify the patients, household, and health system level factors associated with CHE incidence in SSA countries. For a comprehensive review, we sought both quantitative and qualitative studies, as qualitative studies may identify key themes not found, described, or discussed in quantitative studies [8, 9]. Our findings could help identify at-risk populations for community-wide and/or vertical disease-specific interventions.
Methods
The protocol for this systematic review was registered on PROSPERO: CRD42021274830; and the findings reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [10].
Search strategy
We searched PubMed, CINAHL, CNKI, AJOL, African Index Medicus, PsycINFO, SciELO, Scopus, and Web of Science for studies published from 01 January 2000 to 31 December 2021 conducted in any of the 48 World Bank-defined SSA countries. Two authors (PE and LOL) independently searched the literature in February 2022 using search terms covering catastrophic health expenditure, financial catastrophe, risk factors, “factors associated with”, and sub-Sahara Africa–S1 Table. Boolean operators “AND” and “OR” were used to broaden the search. We also searched grey literature websites: New York Academy of Medicine Grey Literature and Open Grey; pre-publication server deposits: medRxIV and PrePubMed; Google Scholar®; and tracked references of included studies for relevant articles. We considered studies published in any of the six African Union languages: Arabic, English, French, Kiswahili, Portuguese, and Spanish; and translated non-English publications using a translation service. We underwent a moderation exercise to ensure uniformity; screened abstracts according to prior eligibility criteria (S2 Table); retrieved full texts for eligible studies; and resolved discrepancies by discussion. We used Mendeley Desktop® to identify and remove duplicates.
Data extraction
At least two authors (PE, LOL, LUA, CAO, and UJA) independently extracted data from included studies using a template. We extracted the following data from each included study: authors names, publication status, study setting, publication year, study design, data source and authors’ description of the data representativeness, study period, sampling method, sample size (in households), and factors associated with CHE. We extracted reported adjusted odds ratio with the confidence interval at 5.0% statistical significance for each CHE-associated factor. Where two or more studies used the same secondary data to identify CHE-associated factors, we first assessed both studies for unique factors, but if similar factors were evaluated, we then considered the peer-review status of the studies; prioritizing peer-reviewed studies over non-peer-reviewed studies. Where a study described CHE-associated factor using more than one CHE definition, we extracted data for both definitions {10% total household expenditure (THE) and 40% non-food expenditure (NFE)}. For qualitative studies; we manually extracted all text under the headings ‘results/conclusions’. We cross-checked all extracted data for discrepancies which were resolved through discussion.
Risk of bias assessment
At least two authors (PE, CAO, LUA, UJA, and LOL) independently assessed the quality of included quantitative studies using the Appraisal tool for Cross-Sectional Studies (AXIS tool) [11], and the Critical Appraisal Skills Programme (CASP) checklist for qualitative studies [12]. We resolved discrepancies in quality assessment scores by discussion until 100% agreement. We categorized the articles’ quality into high (studies met ≥ 70% of the quality criteria), moderate (between 40% and 69% of the quality criteria), and low (< 40% of the quality criteria). We used Microsoft Excel® to organize extracted data.
Data analysis
We first summarized the included studies descriptively. To synthesize the evidence, we performed meta-analysis and narrative synthesis following the Cochrane Handbook for Systematic Reviews of Interventions and the Economic and Social Research Council (ESRC) Methods Programme [9, 13] guidelines. We pooled studies reporting quantitative estimates (odds ratios) from regression or matching analysis for CHE-associated factors in a random-effects meta-analysis to obtain pooled effect estimates. Random effects meta-analysis allows for differences in the treatment effect from study to study because of real differences in the treatment effect in each study as well as sampling variability [14]. Analyses were conducted using Stata version 16.1 (STATA Corp, College Station, TX). Where meta-analysis was not possible due to difference in the definition of CHE-associated factors, we analyzed the reported quantitative estimates narratively.
For qualitative data, we independently performed line-by-line coding of text to group similar concepts and developed new codes when necessary. We organized free codes into descriptive major themes and sub-themes using an inductive approach as detailed by Thomas and Harden [15]. Each reviewer first did this independently and then as a group. Through discussion more abstract or analytical themes emerged and we resolved discrepancies between reviewers through discussion and consensus was achieved on all occasions. Finally, we globally assessed findings from both quantitative studies including meta-analysis for each CHE-associated factor–based of breadth of evaluation in included studies, consistency of an effect on CHE incidence, and methodological quality of included studies evaluating this factor–and when available, triangulated these with the participants’ lived experiences reported in qualitative studies to categorize each CHE-associated factor as either significant or marginal. We categorized a factor as “significant” if it was widely evaluated factors that consistently diminished or exaggerated the likelihood of CHE incidence. Otherwise, we categorized such factor as “marginal”.
Results
Study characteristics
We identified 965 unique articles published between 2000 and 2021 (Fig 1). Of these articles, 122 full-text articles were screened for eligibility and 89 studies met inclusion criteria for this review [16–104] (Table 1). Included studies were 80 peer-reviewed publications, four working papers, and five dissertations, and covered 3,112,322 individuals in 650,297 households in 29 SSA countries. Included articles were published between 2005 to 2021 (Fig 2); were predominantly English-language articles (n = 85; 95.5%); mostly used nationally-representative samples (n = 48; 53.9%); and mostly estimated CHE incidence using ‘non-food expenditure’ definition (n = 53; 59.6%)–Table 2.
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses; CHE: Catastrophic health expenditures.
Of the 89 included studies, 70 (78.6%) were rated as high quality, 16 (18.0%) as moderate quality, and the remaining 3 (3.6%) as low quality–Table 1. Of note, all included quantitative studies used sample frames that closely represented the target population (AXIS tool Item 5) and used selection procedures that likely selected samples representative of the underlying population (AXIS tool Item 6). Also, included qualitative studies used sampling techniques that ensured the identification and selection of individuals that recently suffered catastrophic health expenses.
Catastrophic health expenditure-associated factors
Included studies involved 82 population-based studies reporting quantitative estimates, of which a total of 73 were included in the 71 different random-effects meta-analysis. Nine studies were included in narrative synthesis. Quantitative data from four mixed methods studies were also included in the narrative synthesis. Results from quantitative meta-analysis were reported in two broad categories: population-level factors and disease-specific factors (Tables 3 and 4). Seven studies reporting qualitative data (3 qualitative studies and 4 mixed-methods) met the inclusion criteria, all of which were included in thematic analysis (Table 5). Qualitative data revealed two main themes associated with households’ CHE incidence: low socioeconomic status and being uninsured (Table 6). We presented excerpts of supportive qualitative findings with the relevant quantitative findings and a thematic analysis map in S1 Fig.
Population-level factors
Household characteristics.
Household characteristics that are associated with CHE incidence include residence [16, 20, 21, 28, 39, 41, 43, 45, 46, 50, 52, 56, 58, 62–65, 67, 68, 73–76, 78, 91–94, 98, 99, 103], socioeconomic status [16, 17, 21, 25–28, 34, 35, 39, 41, 43, 45, 46, 50, 52, 53, 55, 56, 58, 59, 62, 63, 65–68, 73, 75, 83, 91–93, 95, 98, 99, 103, 104], household size [17, 20, 21, 25, 26, 28, 34, 39, 41, 43, 45, 50, 53, 58, 62, 63, 65, 66, 68, 73, 75, 76, 83, 92, 93, 95, 98, 99, 104], health insurance status [17, 18, 21, 23, 26–28, 39, 44, 46, 47, 52, 53, 59, 62, 64, 66, 74–76, 83, 92, 94], social safety recipient [27, 35, 38], and marginalization status [28]. Meta-analysis of comparable studies suggests that only socio-economic status (10% THE: OR = 1.99 (95% CI = 1.32–2.98) and 40% NFE: OR = 3.02 (95% CI = 2.23–4.08)) and household size (10% THE: OR = 1.07 (95% CI = 1.02–1.13) and 40% NFE: OR = 1.06 (95% CI = 1.00–1.12)) were significantly associated with CHE incidence (Table 3).
Rural households are at a particularly high risk of catastrophic costs. A multi-country World Health Survey showed that “households living in urban areas consistently seemed to be better protected against catastrophic health expenditure” than rural households [91]. Rural residence, combined with distance to health facilities, increases rural households’ exposure to financial catastrophe[52].
The poorest households were at a higher risk of CHE than richer households [28, 43, 46, 51, 53, 81, 87, 91], as the following statement from a respondent reflects:
“I got treatment for my first child from the hospital, and they charged us a lot of money. We did not have anything left after, and my husband was hiding. After a long time, we were able to borrow money from a relative…” [87]
Health insurance coverage and social safety nets both protect households from CHE, although quantitative analysis suggests this protection is inconsistent.
“Health insurance makes a lot of things cheap for me. I collect the drugs at almost no cost, even when I pay 1000, it doesn’t even matter because I know the drugs that I am given cost much more than that. The other day, they didn’t have the drugs I wanted, when I got to a pharmacy outside and I bought it with my money, then I realized I how much I have been enjoying” [51].
Household head factors.
Several studies reported the relationship between CHE incidence and the sex/gender [17, 21, 28, 34, 35, 39, 41, 43, 45, 50, 52, 55, 56, 58, 62, 63, 65–68, 73, 75, 76, 78, 91–93, 95, 98, 99, 103, 104], age [17, 25, 28, 34, 35, 39, 43, 46, 50, 52, 58, 65–68, 75, 76, 92, 95, 104], marital status [20, 39, 43, 45, 62, 63, 76, 78, 92, 93, 95, 98, 104], education status [17, 20, 21, 26, 34, 39, 43, 45, 50, 56, 62, 63, 65–67, 73, 75, 76, 78, 91–93, 95, 99, 103, 104], and employment status [17, 21, 28, 35, 39, 43, 45, 46, 50, 52, 56, 62, 63, 67, 73, 75, 76, 78, 92, 95, 104] of the household head. Of these factors, only the employment status was significantly associated with CHE incidence (Table 3). In settings without universal insurance coverage, when the household head (who are often the main, or even the only, income earner) is unable to work due to own or a family member’s illness, the combination of lost income and health expenses is devastating [81, 87]. Also, households headed by a retiree were particularly at high risk of CHE incidence, as high as 75% [28, 78].
Household members factors.
CHE incidence was significantly associated with advanced age [17, 21, 26, 28, 39, 41, 43, 45, 50, 52, 56, 62, 63, 65, 68, 73, 75, 78, 83, 91–93, 98, 103], chronic illness [21, 25, 26, 28, 34, 39, 45, 56, 62, 67, 68, 74–76, 83, 92, 93, 95, 99], and hospitalization [17, 25, 27, 41, 52, 58, 62, 68, 83, 94, 103, 104]; but not associated with presence of children < 5-years of age [21, 35, 39, 41, 43, 45, 50, 62, 63, 65, 66, 68, 73, 75, 83, 91, 98], women of child-bearing age [50], disability [17, 34, 65, 66, 91, 98, 99], or obesity [39] in the household (Table 3). Tobacco smoking increased the likelihood of CHE incidence (OR = 1.11 (95% CI = 1.10–1.12)) [16].
Health system factors.
Several studies evaluated the link between CHE incidence and the level of health facility were care was sought [25, 35, 45, 56, 67], health facility type [17, 21, 25, 35, 39, 45, 52, 56, 68, 73, 75, 93, 94], distance to health facility [41, 46, 56, 58, 62, 65, 67, 68, 93], number of health facilities in district/county [28], and prior care from traditional healers [27, 34]. Of these, health facility type, and health facility level were significantly associated with CHE incidence–Table 3. A few studies, however, showed that accessing care from private healthcare providers decreased households’ risk of catastrophic expenditure, although the level and type of care sought from these providers was not clear [21, 52, 93].
Disease-specific determinants
Non-communicable diseases (NCDs).
NCDs significantly increased households’ likelihood of incurring CHE. Cancer increased the likelihood of a household incurring CHE by 7.6%, diabetes 3.5%, TB 3.4%, hypertension 1.9%, and other cardiac diseases by 0.9%. Overall, having a chronic diseases member in a household increased the likelihood of CHE incidence by 2.2% [80]. For households affected by NCDs, CHE incidence was significantly associated with poor socioeconomic status [48, 49, 51, 57, 80, 96, 100, 101], employment status [51, 57, 80, 96, 100, 101], old age [48, 49, 51, 80, 96], and disability [48]. However, household head’s sex [48, 49, 51, 57, 71, 80, 101], marital status [51, 57, 71, 80, 96, 101], education status [48, 49, 51, 57, 71, 80, 101], employment status [51, 57, 80, 96, 100, 101], household residence [48, 49, 57, 71, 80, 100, 101], and religion [101] were not associated with CHE incidence (Table 4). Having health insurance was protective of catastrophic costs [51, 71, 80]–as in the population level.
Reproductive, neonatal, and child healthcare.
For households that sought reproductive, newborn, and child healthcare, CHE incidence was linked to household residence [22], socioeconomic status [38, 42, 77], household size [42], health insurance [42], education status [22, 30, 42], employment status [38, 42], health facility level [77], type of healthcare provider [77], distance to health facility [22], pre-natal illness/hospitalization [77], complicated delivery [77], HIV+ pregnancy [42], and neonatal admission [77]–Table 4. Of these, household residence, socio-economic status, insurance status, household head employment status, pre-natal hospitalization, delivery complications, and neonatal admission were significantly associated with CHE incidence.
“I had asked the nurses to keep my baby if they wanted, and to let me go look for money until I could pull together the necessary sum.” [77]
“I got treatment for my first child from the hospital, and they charged us a lot of money. We did not have anything left after, and my husband was hiding. After a long time, we were able to borrow money from a relative…” [87]
Surgery and trauma care.
For households that sought surgical or trauma care, CHE incidence was associated with residence, socioeconomic status, health insurance status, and sex, age, marital status, education, and employment status of household head–Table 4. Other factors include old age, hospitalization, healthcare provider type, specialist care, intensive care unit admission, and emergency surgery [31, 40, 79, 81, 82, 84, 89, 90].
“…all my family ran away because of the [surgical] expenses‥” [81]
Chronic infectious disease (HIV, TB, HBV, and HCV).
CHE incidence for households that sought healthcare for HIV, TB, HBV, and HCV infections was linked to 19 sociodemographic and health system factors [24, 29, 32, 33, 36, 38, 61, 69, 72, 80, 102] (Table 4). Of these, socioeconomic status [24, 29, 38, 69, 72, 80, 102], health insurance [24, 29, 72, 80], employment status [29, 36, 38], hospitalization [24, 102], healthcare provider type [24, 102], HIV-TB coinfection [24, 69, 102], and extra-pulmonary TB [24] were significantly associated with CHE incidence. Notably, while HIV care decentralization improves equity in access to ART, it does not fully remove the risk of CHE, unless other innovative reforms in health financing are implemented [33]. While HIV patients’ healthcare is largely subsidized, the costs of TB, HBV, HCV care are mostly borne directly by the patients. Therefore, the latter households face significantly higher risks of CHE [36, 61, 80].
Malaria.
The included studies identified six sociodemographic factors—household residence, socioeconomic status, household head’s sex, age, education, and employment status—and two health system factors: healthcare provider type and distance to the health facility [54, 97]. Of these, only socioeconomic status was significantly associated with CHE incidence for malaria treatment (Table 4).
Neglected tropical diseases (NTDs).
For households that sought healthcare for NTDs, seven socio-demographic factors—household residence, socio-economic status, health insurance, and the sex, age, education, and religion of the patients—were linked with CHE incidence [37, 85] (Table 4). Of these factors, only socioeconomic status was significantly associated with CHE incidence.
Discussion
Factors associated with CHE incidence among SSA households are multidimensional and diverse. Overall, a few points emerge from this review. First, the majority of included studies used regression analysis to evaluate the factors associated with CHE incidence. Given that included studies utilized different definitions for evaluated factors, meta-analysis was possible for fewer included studies. However, all included studies were evaluated and synthesized narratively. Secondly, studies evaluating CHE incidence in SSA countries mostly used the ‘capacity-to-pay’ or ‘non-food expenditure’ definition while fewer studies used the ratio of OOP to total household income [7]. However, studies that used both definitions suggests that CHE-associated factors were largely similar between the definitions [19, 21, 30, 60, 68, 78, 92, 93]. Reporting CHE incidence and CHE-associated factors using both definitions enhances comparability between studies. Also, despite the progress SSA countries have made towards universal health insurance, households are still exposed to CHE [46, 66, 84]. Yet, it is likely that many low-income uninured households in SSA countries without universal insurance choose not to seek health care rather than face the financial hardship associated with out-of-pocket healthcare payments [46, 51, 99].
At the population level, our review highlights rural residence, low socioeconomic status, lack of health insurance, advanced age, chronic illness, hospitalization, utilization of private healthcare provider, and utilization of specialist care as the most significant determinants of CHE incidence. Our findings are consistent with findings in comparable regions such as Southeast Asia [105, 106] and South America [107, 108]. Due to widespread poverty, most SSA households cannot afford insurance premiums and so rely on OOP payment for healthcare [2, 109]. Given the highly regressive impact of OOP payment [2, 3], most studies in SSA region demonstrate households’ socioeconomic status as a risk factor for CHE [3, 109]. Rural residence in SSA countries is a proximal indicator of limited household income [50, 91, 103]. This is compounded by lack of health facilities in the rural settings, transportation costs to reach urban health facilities, or the indirect expenditure, such as the costs incurred by an accompanying caretaker[20, 21, 76, 91]. Having an elderly person in the household increases the chances of incurring CHE [21, 26, 63, 103]. This is as expected because elderly persons require more healthcare [21], and are more likely to have chronic illnesses [26, 28]. Both factors increase health expenditures and often require working family members to quit their jobs. Hospitalization, utilization of private healthcare provider, and/or specialist (tertiary) healthcare all increase the possibility of incurring CHE [25, 41, 62, 75, 94]. Given that most SSA countries do not have financial risk protection mechanisms in place, this situation is even grim as the CHE definitions used in included studies does not consider households with unmet healthcare needs.
Factors distinctly associated with CHE incidence at the disease-specific level include disability in a household member for NCDs; severe malaria, blood transfusion, and distant health facilities for maternal and child health services; emergency/unplanned surgery for surgery and trauma patients; and low CD4 count, HIV and TB co-infection, and extra-pulmonary TB for HIV and TB patients. For households affected by NCDs, disability imposes further financial burden in the form of extra health expenses and lost income [51]. The farther the distance of health facilities from the place of residence, the higher the direct non-medical costs, including transportation and accommodation costs. Hence, rural households are therefore more likely to incur CHE for maternal and child healthcare [22, 97]. For similar reasons, blood transfusion and severe malaria treatments are rarely available at rural health facilities, and require hospitalization and specialist care–which increase CHE risks [22, 54]. For patients requiring HIV and TB care, low CD4-count, HIV and TB co-infection, and extra-pulmonary TB are all indicative of poor health status requiring increased usage of healthcare services with a higher risk of incurring CHE [24, 29, 102].
Strengths and limitations
To the best of our knowledge, this is the first systematic review to comprehensively map the factors associated with CHE incidence in SSA. We also identified determinants for both population and disease-specific level CHE incidence which enables easy identification of populations that are most at risk for community-wide and/or vertical disease-specific interventions. Furthermore, our review combined both quantitative and qualitative studies to synthesize evidence that is both generalizable and sufficiently nuanced.
Our study has a few limitations. First, our review does not capture factors associated with households who cannot meet treatment costs–a gap that future studies can address using new variables that capture these households. Also, as we identified determinants of CHE incidence using two thresholds, we may have missed some factors that might have been reported using other thresholds. Thirdly, there is the inherent difficulty in mapping and adjudicating the evidence on these factors identified from the studies as either significant or marginal. Ultimately, these were subjective judgments based on the authors’ understanding of the texts in included studies that are not as error-proof as might be hoped for. To address this, a multi-rater system was used–each factor was independently adjudicated by at least two authors–to minimize subjectivity. Finally, our categorization of some determinants as marginal does not imply dismissal of the influence of these factors in some unique settings. In some settings and for different households, these “marginal” factors could have greater eminence.
Policy implications
Our review provides significant contextual evidence for policy discussion and health financing reforms by identifying the sociodemographic characteristics of households that are most likely to suffer financial catastrophe in SSA countries. This is a critical step toward developing comprehensive social protection mechanisms–a key vehicle for achieving UHC. Our study provides key details for fine-tuning the different means of identifying households for targeted or supplemental protection such as means testing, proximal means testing, geographic targeting, or participatory wealth ranking [109].
Conclusion
Our study suggests that the key factors associated with population and disease-specific CHE incidence in SSA countries are rural residence, low socioeconomic status, lack of health insurance, having an elderly household member, chronic illness, hospitalization, use of private healthcare providers, and use of tertiary/specialist healthcare. Highlighting these factors in a comprehensive review underscores potential strategies for implementing/improving financial risk protection measures to achieve UHC in these SSA countries.
Supporting information
S1 Table. Search strategy.
Search period was from 01 January 1990 to 31 December 2021.
https://doi.org/10.1371/journal.pone.0276266.s001
(DOCX)
S2 Table. Eligibility criteria for studies reporting factors associated with catastrophic health expenditure in sub-Saharan Africa (SSA) countries.
https://doi.org/10.1371/journal.pone.0276266.s002
(DOCX)
References
- 1.
World Health Organization. Universal Health Coverage (UHC) [Internet]. 2021 [cited 2022 Jul 1]. Available from: https://www.who.int/health-topics/universal-health-coverage#tab=tab_1
- 2. Ponsar F, Tayler-Smith K, Philips M, Gerard S, Van Herp M, Reid T, et al. No cash, no care: How user fees endanger health-lessons learnt regarding financial barriers to healthcare services in Burundi, Sierra Leone, Democratic Republic of Congo, Chad, Haiti and Mali. Int Health [Internet]. 2011;3(2):91–100. Available from: pmid:24038181
- 3. Saksena P, Hsu J, Evans DB. Financial Risk Protection and Universal Health Coverage: Evidence and Measurement Challenges. PLoS Med. 2014;11(9). pmid:25244520
- 4. Wagstaff A, Flores G, Hsu J, Smitz MF, Chepynoga K, Buisman LR, et al. Progress on catastrophic health spending in 133 countries: a retrospective observational study. Lancet Glob Heal. 2018;6(2):e169–79. pmid:29248367
- 5. Ifeagwu SC, Yang JC, Parkes-Ratanshi R, Brayne C. Health financing for universal health coverage in Sub-Saharan Africa: a systematic review. Glob Heal Res Policy. 2021;6(1). pmid:33641673
- 6. Wagstaff A, Neelsen S. A comprehensive assessment of universal health coverage in 111 countries: a retrospective observational study. Lancet Glob Heal. 2020;8(1):e39–49. pmid:31837954
- 7. Eze P, Lawani O, Agu J, Acharya Y. Catastrophic health expenditure in sub-Saharan Africa: systematic review and meta-analysis. Bull World Health Organ. 2022;100(5):337–51. pmid:35521041
- 8. Barbour RS. The case for combining qualitative and quantitative approaches in health services research. J Heal Serv Res Policy. 1999;4(1):39–43. pmid:10345565
- 9. Popay J, Roberts H, Sowden A, Petticrew M, Arai L, Rodgers M, et al. Guidance on the conduct of narrative synthesis in systematic reviews [Internet]. Vol. 1. A Product from the ESRC Methods Programme; 2006. b92 p. Available from: https://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/fhm/dhr/chir/NSsynthesisguidanceVersion1-April2006.pdf
- 10. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ. 2009;339(7716):332–6.
- 11. Downes MJ, Brennan ML, Williams HC, Dean RS. Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS). BMJ Open. 2016;6(12):1–7.
- 12.
Critical Appraisal Skills Programme (CASP). CASP Qualitative Studies Checklist [Internet]. 2022 [cited 2022 Apr 11]. Available from: https://casp-uk.net/casp-tools-checklists/
- 13.
Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al. Cochrane Handbook for Systematic Reviews of Interventions Version 6.1 [updated September 2020]. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al., editors. Cochrane. Cochrane; 2020.
- 14. Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. Bmj. 2011;342(7804):964–7. pmid:21310794
- 15. Thomas J, Harden A. Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Med Res Methodol. 2008;8(45). pmid:18616818
- 16. Adeniji F, Lawanson O. Tobacco use and the risk of catastrophic healthcare expenditure. Tob Control Public Heal East Eur. 2018;7(1):1–8.
- 17. Adisa O. Investigating determinants of catastrophic health spending among poorly insured elderly households in urban Nigeria. Int J Equity Health [Internet]. 2015;14:79. Available from: pmid:26370774
- 18. Aidam PW, Nketiah-amponsah E, Kutame R. The effect of health Insurance on out-of-pocket payments, catastrophic expenditures and healthcare utilization in Ghana: Case of Ga South Municipality. J Self-Governance Manag Econ. 2016;4(3):42–65.
- 19.
Akazili J. Equity in health care financing in Ghana. The University of Cape Town; 2010.
- 20. Akinkugbe O, Chama-Chiliba CM, Tlotlego N. Health Financing and Catastrophic Payments for Health Care: Evidence from Household-level Survey Data in Botswana and Lesotho. African Dev Rev. 2012;24(4):358–70.
- 21. Aregbeshola BS, Khan SM. Determinants of catastrophic health expenditure in Nigeria. Eur J Heal Econ. 2018;19(4):521–32. pmid:28555372
- 22. Arsenault C, Fournier P, Philibert A, Sissoko K, Coulibaly A, Tourigny C, et al. Emergency obstetric care in Mali: catastrophic spending and its impoverishing effects on households. Bull World Health Organ. 2013;91(3):207–16. pmid:23476093
- 23. Aryeetey GC, Westeneng J, Spaan E, Jehu-Appiah C, Agyepong IA, Baltussen R. Can health insurance protect against out-of-pocket and catastrophic expenditures and also support poverty reduction? Evidence from Ghana’s National Health Insurance Scheme. Int J Equity Health. 2016;15:116. pmid:27449349
- 24. Assebe LF, Negussie EK, Jbaily A, Tolla MTT, Johansson KA. Financial burden of HIV and TB among patients in Ethiopia: a cross-sectional survey. BMJ Open. 2020;10(6):e036892. pmid:32487582
- 25. Atake EH, Amendah DD. Porous safety net: Catastrophic health expenditure and its determinants among insured households in Togo. BMC Health Serv Res. 2018;18:175. pmid:29530045
- 26. Attia-Konan AR, Oga ASS, Touré A, Kouadio KL. Distribution of out of pocket health expenditures in a sub-Saharan Africa country: Evidence from the national survey of household standard of living, Côte d’Ivoire. BMC Res Notes [Internet]. 2019;12:25. Available from: pmid:30646940
- 27. Babikir A, Satty A, Mwambi H. Determinants of out-of-pocket health expenditure and their welfare implications in a South African context. J Econ Financ Sci. 2018;11(1):a177.
- 28. Barasa EW, Maina T, Ravishankar N. Assessing the impoverishing effects, and factors associated with the incidence of catastrophic health care payments in Kenya. Int J Equity Health. 2017;16:31. pmid:28166779
- 29. Beaulière A, Touré S, Alexandre PK, Koné K, Pouhé A, Kouadio B, et al. The financial burden of morbidity in HIV-infected adults on antiretroviral therapy in Côte d’Ivoire. PLoS One. 2010;5(6):1–7. pmid:20585454
- 30. Borde MT, Loha E, Johansson KA, Lindtjørn B. Financial risk of seeking maternal and neonatal healthcare in southern Ethiopia: A cohort study of rural households. Int J Equity Health. 2020;19:69. pmid:32423409
- 31. Botman M, Hendriks TCC, de Haas LEM, Mtui GS, Binnerts J, Nuwass EQ, et al. Access to Burn Care in Low- and Middle-Income Countries: An Assessment of Timeliness, Surgical Capacity, and Affordability in a Regional Referral Hospital in Tanzania. J Burn Care Res. 2021.
- 32. Bousmah M al Q, Nishimwe ML, Kuaban C, Boyer S. Free access to antiretroviral treatment and protection against the risk of catastrophic health expenditure in people living with HIV: evidence from Cameroon. BMC Health Serv Res. 2021;21(313):1–7.
- 33. Boyer S, Abu-Zaineh M, Blanche J, Loubière S, Bonono RC, Moatti JP, et al. Does HIV services decentralization protect against the risk of catastrophic health expenditures? Some lessons from Cameroon. Health Serv Res. 2011;46(6):2029–56. pmid:22092226
- 34. Brinda EM, Rodríguez Andrés A, Enemark U. Correlates of out-of-pocket and catastrophic health expenditures in Tanzania: Results from a national household survey. BMC Int Health Hum Rights. 2014;14:5. pmid:24597486
- 35. Buigut S, Ettarh R, Amendah DD. Catastrophic health expenditure and its determinants in Kenya slum communities. Int J Equity Health [Internet]. 2015;14:46. pmid:25971679
- 36. Chabrol F, Noah DN, Tchoumi EP, Vidal L, Kuaban C, Carrieri MP, et al. Screening, diagnosis and care cascade for viral hepatitis B and C in Yaoundé, Cameroon: A qualitative study of patients and health providers coping with uncertainty and unbearable costs. BMJ Open. 2019;9(e025415). pmid:30898817
- 37. Chukwu JN, Meka AO, Nwafor CC, Oshia DC, Madichie NO, Ekeke N, et al. Financial burden of health care for Buruli ulcer patients in Nigeria: The patients’ perspective. Int Health. 2017;9(1):36–43. pmid:27986841
- 38. Cleary S, Birch S, Chimbindi N, Silal S, McIntyre D. Investigating the affordability of key health services in South Africa. Soc Sci Med [Internet]. 2013;80:37–46. Available from: pmid:23415590
- 39. Counts CJ, Skordis-Worrall J. Recognizing the importance of chronic disease in driving healthcare expenditure in Tanzania: Analysis of panel data from 1991 to 2010. Health Policy Plan. 2016;31(4):434–43. pmid:26318536
- 40. Dhufera HT, Jbaily A, Verguet S, Tolla MT, Johansson KA, Memirie ST. Financial risk of road traffic trauma care in public and private hospitals in Addis Ababa, Ethiopia: A cross-sectional observational study. Injury [Internet]. 2022;53(1):23–9. Available from: pmid:34819231
- 41. Doamba EJ, Ouedrago A, Prinyanka S. Dépenses catastrophiques de santé et leur impact sur l’appauvrissement des ménages et l’utilisation des services de santé: Cas du Burkina Faso. African Heal Monit. 2013;(17):36–40.
- 42. Dyer SJ, Sherwood K, Mcintyre D, Ataguba JE. Catastrophic payment for assisted reproduction techniques with conventional ovarian stimulation in the public health sector of South Africa: Frequency and coping strategies. Hum Reprod. 2013;28(10):2755–64. pmid:23878180
- 43. Ebaidalla EM, Ali MEM. Determinants and impact of household’s out-of-pocket healthcare expenditure in Sudan: evidence from urban and rural population*. Middle East Dev J. 2019;11(2):181–98.
- 44. Ebaidalla EM. Does Health Insurance Reduce Catastrophic Health Expenditure in Sudan? J Dev Areas. 2021;55(4):11–25.
- 45. Edoka I, McPake B, Ensor T, Amara R, Edem-Hotah J. Changes in catastrophic health expenditure in post-conflict Sierra Leone: An Oaxaca-blinder decomposition analysis. Int J Equity Health. 2017;16:166. pmid:28870228
- 46. Ekman B. Catastrophic health payments and health insurance: Some counterintuitive evidence from one low-income country. Health Policy (New York). 2007;83(2–3):304–13. pmid:17379351
- 47. Fink G, Robyn PJ, Sié A, Sauerborn R. Does health insurance improve health? Evidence from a randomized community-based insurance rollout in rural Burkina Faso. J Health Econ [Internet]. 2013;32(6):1043–56. Available from: pmid:24103498
- 48. Hailemichael Y, Hailemariam D, Tirfessa K, Docrat S, Alem A, Medhin G, et al. Catastrophic out-of-pocket payments for households of people with severe mental disorder: A comparative study in rural Ethiopia. Int J Ment Health Syst [Internet]. 2019;13:39. Available from: pmid:31164919
- 49. Hailemichael Y, Hanlon C, Tirfessa K, Docrat S, Alem A, Medhin G, et al. Catastrophic health expenditure and impoverishment in households of persons with depression: A cross-sectional, comparative study in rural Ethiopia. BMC Public Health. 2019;19:930. pmid:31296207
- 50.
Hilaire HG. Socio-economic Status and Health Expenditure of Households in Benin [Internet]. Nairobi, Kenya; 2018. Report No.: AERC Research Paper 347. Available from: https://ideas.repec.org/p/aer/wpaper/347.html
- 51.
Ibukun C o, Adebayo AA. Economic Burden of Non-communicable Diseases and Poverty in Nigeria: A Cross-sectional Study. In: Mojekwu JN, Thwala W, Aigbavboa C, Atepor L, Sackey S, editors. Sustainable Education and Development. Spring Nature Switzerland AG; 2021. p. 425–44.
- 52. Ibukun C, Komolafe E. Household Catastrophic Health Expenditure: Evidence from Nigeria. Microeconomics Macroecon [Internet]. 2018;6(1):1–8. Available from: http://article.sapub.org/10.5923.j.m2economics.20180601.01.html
- 53. Ilesanmi OS, Adebiyi AO, Fatiregun AA. National health insurance scheme: How protected are households in Oyo State, Nigeria from catastrophic health expenditure? Int J Heal Policy Manag. 2014;2(4):175–80. pmid:24847483
- 54. Ilunga-Ilunga F, Levêque A, Laokri S, Dramaix M. Incidence of catastrophic health expenditures for households: An example of medical attention for the treatment of severe childhood malaria in Kinshasa reference hospitals, Democratic Republic of Congo. J Infect Public Health [Internet]. 2015;8(2):136–44. Available from: pmid:25264234
- 55. Janssens W, Goedecke J, Bree GJD, Aderibigbe SA, Akande TM, Mesnard A. The financial burden of non-communicable chronic diseases in rural Nigeria: Wealth and gender heterogeneity in health care utilization and health expenditures. PLoS One [Internet]. 2016;11(11):e0166121. Available from: pmid:27832107
- 56. Kaonga O, Banda C, Masiye F. Hardship financing of out-of-pocket payments in the context of free healthcare in Zambia. PLoS One. 2019;14(4):e0214750. pmid:30969979
- 57. Kasahun GG, Gebretekle GB, Hailemichael Y, Woldemariam AA, Fenta TG. Catastrophic healthcare expenditure and coping strategies among patients attending cancer treatment services in Addis Ababa, Ethiopia. BMC Public Health. 2020;20(984). pmid:32571275
- 58. Khatry MMO, Ahmed TEOT, Sakho KA. Rapport sur les dépenses catastrophiques et l’impact des paiements directs sur l’appauvrissement des ménages: Cas de la Mauritanie. African Heal Monit. 2013;(17):41–5.
- 59. Kihaule A. Impact of micro health insurance plans on protecting households against catastrophic health spending in Tanzania. GSTF J Nurs Heal Care. 2015;2(2):71–9.
- 60. Kimani DN, Mugo MG, Kioko UM. Catastrophic Health Expenditures And Impoverishment In Kenya. Eur Sci J. 2016;12(15):434–52.
- 61. Kirubi B, Ong’ang’o J, Nguhiu P, Lönnroth K, Rono A, Sidney-Annerstedt K. Determinants of household catastrophic costs for drug sensitive tuberculosis patients in Kenya. Infect Dis poverty [Internet]. 2021;10:95. Available from: pmid:34225790
- 62. Kusi A, Hansen KS, Asante FA, Enemark U. Does the National Health Insurance Scheme provide financial protection to households in Ghana? BMC Health Serv Res. 2015;15:331. pmid:26275412
- 63. Kwesiga B, Aliti T, Nabukhonzo P, Najuko S, Byawaka P, Hsu J, et al. What has been the progress in addressing financial risk in Uganda? Analysis of catastrophe and impoverishment due to health payments. BMC Health Serv Res. 2020;20:741. pmid:32787844
- 64.
Lamiraud K, Booysen F, Scheil-Adlung X. The impact of social health protection on access to health care, health expenditure and improvement: A case study of South Africa [Internet]. Geneva; 2005. (Extension of Social Security Paper). Report No.: No. 23. Available from: https://www.ilo.org/secsoc/information-resources/publications-and-tools/Workingpapers/WCMS_207709/lang—en/index.htm
- 65. Lu C, Chin B, Lewandowski JL, Basinga P, Hirschhorn LR, Hill K, et al. Towards universal health coverage: An evaluation of Rwanda Mutuelles in its first eight years. PLoS One. 2012;7(6):e39282. pmid:22723985
- 66. Lu C, Liu K, Li L, Yang Y. Sensitivity of measuring the progress in financial risk protection to survey design and its socioeconomic and demographic determinants: A case study in Rwanda. Soc Sci Med. 2017;178:11–8. pmid:28189819
- 67. Masiye F, Kaonga O, Kirigia JM. Does user fee removal policy provide financial protection from catastrophic health care payments? evidence from Zambia. PLoS One. 2016;11(1):e0146508. pmid:26795620
- 68. Mulaga AN, Kamndaya MS, Masangwi SJ. Examining the incidence of catastrophic health expenditures and its determinants using multilevel logistic regression in Malawi. PLoS One. 2021;16(3):e0248752. pmid:33788900
- 69. Muttamba W, Tumwebaze R, Mugenyi L, Batte C, Sekibira R, Nkolo A, et al. Households experiencing catastrophic costs due to tuberculosis in Uganda: magnitude and cost drivers. BMC Public Health. 2020;20(1):1–10.
- 70. Mutyambizi C, Pavlova M, Hongoro C, Booysen F, Groot W. Incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment for diabetes care in South Africa: A study at two public hospitals in Tshwane. Int J Equity Health. 2019;18(73). pmid:31118033
- 71. Mwai D, Muriithi M. Catastrophic health expenditure and household impoverishment: A case of prevalence of Non-Communicable Diseases in Kenya. Epidemiol Biostat Public Heal. 2016;13(1):1–7.
- 72. Negin J, Randell M, Raban MZ, Nyirenda M, Kalula S, Madurai L, et al. Health expenditure and catastrophic spending among older adults living with HIV. Glob Public Health. 2016;12(10):1282–96. pmid:27132656
- 73.
Ngcamphalala C. Financial health protection in Swaziland: an assessment of financial catastrophe and impoverishment from out-of-pocket payments. The University of Cape Town; 2015.
- 74. Nguyen HT, Rajkotia Y, Wang H. The financial protection effect of Ghana national health insurance scheme: Evidence from a study in two rural districts. Int J Equity Health. 2011;10:1–12.
- 75. Njagi P, Arsenijevic J, Groot W. Decomposition of changes in socioeconomic inequalities in catastrophic health expenditure in Kenya. PLoS One. 2020;15(12):e0244428. pmid:33373401
- 76. Njuguna N, Kimani DN, Kinyajui B. Determinants and distribution of catastrophic health expenditures and impoverishment in Kenya. J Econ Dev Stud. 2017;5(2):78–85.
- 77. Ntambue AM, Malonga FK, Cowgill KD, Dramaix-Wilmet M, Donnen P. Incidence of catastrophic expenditures linked to obstetric and neonatal care at 92 facilities in Lubumbashi, Democratic Republic of the Congo, 2015. BMC Public Health. 2019;19:948. pmid:31307419
- 78. Nundoochan A, Thorabally Y, Monohur S, Hsu J. Impact of out of pocket payments on financial risk protection indicators in a setting with no user fees: The case of Mauritius. Int J Equity Health. 2019;18:63. pmid:31053077
- 79. Nwanna–Nzewunwa O, Oke R, Agwang E, Ajiko MM, Yoon C, Carvalho M, et al. The societal cost and economic impact of surgical care on patients’ households in rural Uganda; a mixed method study. BMC Health Serv Res. 2021;21(568). pmid:34107950
- 80.
Nyansarora NV. Variation of Catastrophic Health Expenditure By Chronic Disease in Kenya [Internet]. Universrity of Nairobi, Kenya; 2020. Available from: http://erepository.uonbi.ac.ke/handle/11295/153820
- 81. Obembe T, Fonn S. Affording unavoidable emergency surgical care—The lived experiences and payment coping strategies of households in Ibadan metropolis, Southwestern Nigeria. PLoS One [Internet]. 2020;15(5):0232882. Available from: pmid:32433652
- 82. Obembe TA, Levin J, Fonn S. Prevalence and factors associated with catastrophic health expenditure among slum and non-slum dwellers undergoing emergency surgery in a metropolitan area of South Western Nigeria. PLoS One. 2021;16(8 August):1–21.
- 83. Ogaji DS, Adesina AD. The predictors of catastrophic health expenditure among households in Yenagoa, Bayelsa State. Niger Delta Med J. 2018;2(1):9–23.
- 84. Okoroh J, Sarpong DOB, Essoun S, Riviello R, Harris H, Weissman JS. Does insurance protect individuals from catastrophic payments for surgical care? An analysis of Ghana’s National Health Insurance Scheme at Korle-Bu teaching Hospital. BMC Health Serv Res. 2020;20(45). pmid:31952520
- 85. Olatunya OS, Ogundare EO, Fadare JO, Oluwayemi IO, Agaja OT, Adeyefa BS, et al. The financial burden of sickle cell disease on households in Ekiti, Southwest Nigeria. Clin Outcomes Res. 2015;7:545–53. pmid:26622186
- 86. Onah MN, Govender V. Out-of-pocket payments, health care access and utilisation in south-eastern Nigeria: A gender perspective. PLoS One. 2014;9(4):e93887. pmid:24728103
- 87. Onarheim HK, Molla SM, Muluken G, Marie MK, Frithof NO, Ingrid M. Selling my sheep to pay for medicines—Household priorities and coping strategies in a setting without universal health coverage. BMC Health Serv Res. 2018;18(153).
- 88.
Owusu-Sekyere LA. Financial protection against Catastrophic Health Expenditures among Ghanaian households. The University of Ghana; 2015.
- 89. Petitfour L, Bonnet E, Mathevet I, Nikiema A, Ridde V. Out-of-pocket payments and catastrophic expenditures due to traffic injuries in Ouagadougou, Burkina Faso. Health Econ Rev. 2021;11(46). pmid:34928432
- 90. Rickard JL, Ngarambe C, Ndayizeye L, Smart B, Majyambere JP, Riviello R. Risk of Catastrophic Health Expenditure in Rwandan Surgical Patients with Peritonitis. World J Surg. 2018;42(6):1603–9. pmid:29143091
- 91.
Saksena P, Xu K, Durairaj V. The drivers of catastrophic expenditure: outpatient services, hospitalization or medicines? World Health Report (2010) Background Paper, 21. Geneva, Switzerland; 2010.
- 92. Salari P, Di Giorgio L, Ilinca S, Chuma J. The catastrophic and impoverishing effects of out-of-pocket healthcare payments in Kenya, 2018. BMJ Glob Heal. 2019;4:e001809.
- 93. Sanoussi Y, Ametoglo M. Ampleur Et déterminants des dépenses catastrophiques de santé: cas des ménages togolais (Magnitude and Determinants of Catastrophic Health Expenditure: Case of Togolese Households). SSRN Electron J [Internet]. 2019; Available from: https://ssrn.com/abstract=3440106
- 94. Séne LM, Cissé M. Catastrophic out-of-pocket payments for health and poverty nexus: evidence from Senegal. Int J Heal Econ Manag [Internet]. 2015;15(3):307–28. Available from: pmid:27878680
- 95. Shikuro D, Yitayal M, Kebede A, Debie A. Catastrophic out-of-pocket health expenditure among rural households in the semi-pastoral community, western Ethiopia: A community-based cross-sectional study. Clin Outcomes Res. 2020;12:761–9. pmid:33408491
- 96. Shumet Y, Mohammed SA, Kahissay MH, Demeke B. Catastrophic health expenditure among chronic patients attending dessie referral hospital, Northeast Ethiopia. Clin Outcomes Res. 2021;13:99–107.
- 97.
Sichone W. Financial catastrophe associated with out-of-pocket payments for malaria treatment in children under the age of five years in Zambia. The University of Zambia; 2020.
- 98. Sow M, Diop M, Mbengue A, AW A, Sall FL, Cisse A, et al. Rapport d’analyse sur les dépenses catastrophiques de santé et leur impact sur l’appauvrissement et l’utilisation des services au Sénégal, 2005 et 2011. African Heal Monit. 2013;(17):46–50.
- 99. Su TT, Kouyaté B, Flessa S. Catastrophic household expenditure for health care in a low-income society: A study from Nouna District, Burkina Faso. Bull World Health Organ. 2006;84(1):21–7. pmid:16501711
- 100. Tolla MT, Norheim OF, Verguet S, Bekele A, Amenu K, Abdisa SG, et al. Out-of-pocket expenditures for prevention and treatment of cardiovascular disease in general and specialised cardiac hospitals in Addis Ababa, Ethiopia: A cross-sectional cohort study. BMJ Glob Heal. 2017;2(2).
- 101. Tsega G, Getaneh G, Taddesse G. Are Ethiopian diabetic patients protected from financial hardship? PLoS One. 2021;16(1 January):1–14. pmid:33503048
- 102. Ukwaja KN, Alobu I, Abimbola S, Hopewell PC. Household catastrophic payments for tuberculosis care in Nigeria: Incidence, determinants, and policy implications for universal health coverage. Infect Dis Poverty. 2013;2(1):1–9.
- 103. Xu K, Evans DB, Kadama P, Nabyonga J, Ogwal PO, Nabukhonzo P, et al. Understanding the impact of eliminating user fees: Utilization and catastrophic health expenditures in Uganda. Soc Sci Med. 2006;62(4):866–76. pmid:16139936
- 104. Zeng W, Lannes L, Mutasa R. Utilization of health care and burden of out-of-pocket health expenditure in Zimbabwe: Results from a national household survey. Heal Syst Reform [Internet]. 2018;4(4):300–12. Available from: pmid:30398403
- 105. Doshmangir L, Yousefi M, Hasanpoor E, Eshtiagh B, Haghparast-Bidgoli H. Determinants of catastrophic health expenditures in Iran: A systematic review and meta-analysis. Cost Eff Resour Alloc. 2020;18(1):1–21. pmid:32467673
- 106. Pandey A, Ploubidis GB, Clarke L, Dandona L. Trends in catastrophic health expenditure in india: 1993 to 2014. Bull World Health Organ. 2018;96(1):18–28. pmid:29403097
- 107. Koch KJ, Cid Pedraza C, Schmid A. Out-of-pocket expenditure and financial protection in the Chilean health care system—A systematic review. Health Policy (New York). 2017;121(5):481–94. pmid:28359550
- 108.
Diaz MDM, Sarti FM, Campino ACC, Iunes R. Catastrophic Health Expenditure in Brazil: Regional Differences, Budget Constraints and Private Health Insurance. In: Household spending and impoverishment. Boston: Harvard Global Equity Initiative; 2012.
- 109. Umeh CA. Identifying the poor for premium exemption: a critical step towards universal health coverage in Sub-Saharan Africa. Glob Heal Res Policy. 2017;2(1):2–4. pmid:29202070