TOP 10 Countries by Out-of-Pocket Health Spending Share (2025)
When households pay directly for healthcare at the point of care — through user fees, medicines, diagnostics or informal payments — the risk of catastrophic expenditure and medical impoverishment rises sharply. Out-of-pocket (OOP) spending as a share of total current health expenditure is the standard benchmark for financial protection in health systems. This ranking uses the WHO Global Health Expenditure Database (GHED), the primary source for comparable cross-country data, with the most recent available reference year (2022 for most economies).
Values are rounded and should be treated as indicative estimates for analytical purposes, not as official country statistics for a specific year. Year coverage varies by country.
Top 10 economies by out-of-pocket health spending share
The ten countries below consistently appear at the top of global OOP rankings. Most are low- or lower-middle-income economies where government and social-insurance financing remain far too small to cover essential care, and where households are left to carry most of the financial risk themselves. Georgia is the main upper-middle-income exception in this top 10. In every country listed, the OOP share is well above the threshold (~30–35%) above which catastrophic health spending begins to rise sharply for poorer households.
Myanmar has the highest documented out-of-pocket share globally. Decades of underfunding of the public health system, combined with a heavily privatized informal care market and chronic gaps in social health insurance, leave households paying for nearly every encounter out of pocket. The political crisis since 2021 has further weakened the already fragile financing architecture.
Afghanistan's health system is overwhelmingly aid-dependent at the system level, yet at the household level, a very large share of spending flows through informal direct payments. Collapse of many donor-financed programs since 2021 has increased the pressure on households, many of whom face both acute poverty and limited access to subsidized services.
Bangladesh has made remarkable gains in health outcomes relative to its income level, but the structure of health financing has lagged. Around three-quarters of all current health spending comes directly from households, primarily for medicines and outpatient consultations in private facilities. Health coverage schemes exist but remain limited in scope and population reach.
Sudan's health financing has been severely compromised by protracted conflict, economic collapse and displacement. Government health expenditure is minimal, and even where public facilities technically exist, shortages of drugs and supplies push households toward private purchases that are fully out-of-pocket.
Nigeria illustrates that population size and resource wealth do not automatically translate into health financing protection. Despite being Africa's largest economy, government health spending per capita remains very low. The National Health Insurance Authority (NHIA) has expanded coverage, but fewer than 10% of Nigerians are currently enrolled in any form of health insurance.
Cameroon's dual healthcare system — with a centralized public sector and a large unregulated private sector — produces a situation where formal insurance is available mainly to formal-sector workers, leaving the majority of the population to finance care directly. Regional fragmentation and conflict in the Anglophone regions add further complexity.
Pakistan has introduced demand-side financing reforms, notably the Sehat Sahulat hospitalization insurance scheme, but most outpatient and pharmaceutical spending still falls entirely on households. With medicines accounting for a large share of total OOP, even modest illness episodes can represent a significant share of household budgets for low-income families.
Egypt occupies an interesting transitional position: it has the legislative framework for universal health insurance in place, with a phased geographical rollout since 2019, but national coverage remains incomplete. In the interim, households continue to bear a majority of health costs directly, and medicine prices remain a key driver of OOP burdens.
Cambodia has made measurable progress through Health Equity Funds and results-based financing, which have reduced catastrophic spending for the poorest households. However, a large informal economy limits social insurance expansion, and middle-income urban households remain largely exposed. OOP spending on outpatient care and drugs continues to dominate.
Georgia is a notable outlier: an upper-middle-income European economy with one of the highest OOP shares globally. Despite the Universal Healthcare Programme introduced in 2013, the benefits package for outpatient and pharmaceutical care is limited, and cost-sharing remains high. As incomes rise, OOP amounts per capita are also increasing, even if the share is slowly declining.
Table 1. Top 10 countries by OOP health spending share, 2022
| Rank | Country | OOP share (%) | OOP per capita (USD) | Income group |
|---|---|---|---|---|
| 1 | Myanmar | ≈ 83% | ≈ 38 | Lower-middle |
| 2 | Afghanistan | ≈ 78% | ≈ 23 | Low |
| 3 | Bangladesh | ≈ 73% | ≈ 45 | Lower-middle |
| 4 | Sudan | ≈ 72% | ≈ 21 | Low |
| 5 | Nigeria | ≈ 70% | ≈ 35 | Lower-middle |
| 6 | Cameroon | ≈ 64% | ≈ 42 | Lower-middle |
| 7 | Pakistan | ≈ 60% | ≈ 32 | Lower-middle |
| 8 | Egypt | ≈ 57% | ≈ 115 | Lower-middle |
| 9 | Cambodia | ≈ 54% | ≈ 68 | Lower-middle |
| 10 | Georgia | ≈ 52% | ≈ 380 | Upper-middle |
Source: WHO Global Health Expenditure Database (GHED), reference year 2022 for most economies. OOP per capita in current USD. Values rounded; for official figures refer to GHED directly.
Chart 1. OOP health spending share — Top 10 countries
Horizontal bars show OOP share (%) by country. The WHO threshold of ~30–35% above which catastrophic spending risk rises sharply is indicated by the dashed line.
How the high-OOP landscape looks across 20 economies
Moving beyond the top 10 reveals a broader picture: high OOP shares are concentrated in sub-Saharan Africa and South/Southeast Asia, but outliers exist in Europe (Georgia) and the MENA region (Egypt, Morocco). The table below includes the top 20 countries by OOP share and can be filtered or sorted. The scatter chart that follows links OOP share to GDP per capita (PPP), illustrating that income alone does not explain — or solve — the financial protection problem.
Table 2. Top 20 countries by out-of-pocket health spending share
OOP share = out-of-pocket health expenditure as % of current health expenditure (WHO GHED 2022). OOP per capita in current USD. GDP per capita (PPP, 2021 international dollars, World Bank). Income group per World Bank Atlas method. Toggle between OOP % share and OOP per capita (USD) using the Share % / Per capita switch. Search and filter controls only change which rows are shown on screen.
| Rank | Country | OOP Share % / Per capita USD | GDP per capita PPP (int$) | Region | Income group |
|---|---|---|---|---|---|
| 1 | Myanmar | 83% USD 38 | 4,780 | Asia | Lower-middle |
| 2 | Afghanistan | 78% USD 23 | 1,380 | Asia | Low |
| 3 | Bangladesh | 73% USD 45 | 6,820 | Asia | Lower-middle |
| 4 | Sudan | 72% USD 21 | 3,940 | Africa | Low |
| 5 | Nigeria | 70% USD 35 | 5,180 | Africa | Lower-middle |
| 6 | Cameroon | 64% USD 42 | 4,150 | Africa | Lower-middle |
| 7 | Pakistan | 60% USD 32 | 5,840 | Asia | Lower-middle |
| 8 | Egypt | 57% USD 115 | 13,020 | MENA | Lower-middle |
| 9 | Cambodia | 54% USD 68 | 5,230 | Asia | Lower-middle |
| 10 | Georgia | 52% USD 380 | 18,100 | Europe | Upper-middle |
| 11 | Morocco | 51% USD 145 | 9,760 | MENA | Lower-middle |
| 12 | Uzbekistan | 50% USD 68 | 9,440 | Asia | Lower-middle |
| 13 | Lao PDR | 49% USD 55 | 8,240 | Asia | Lower-middle |
| 14 | India | 47% USD 55 | 9,780 | Asia | Lower-middle |
| 15 | Philippines | 46% USD 102 | 10,180 | Asia | Lower-middle |
| 16 | Guatemala | 43% USD 165 | 9,190 | Americas | Upper-middle |
| 17 | Viet Nam | 42% USD 92 | 12,980 | Asia | Lower-middle |
| 18 | Honduras | 41% USD 75 | 6,820 | Americas | Lower-middle |
| 19 | Uganda | 39% USD 22 | 2,950 | Africa | Low |
| 20 | Kenya | 36% USD 38 | 5,760 | Africa | Lower-middle |
Sources: WHO GHED 2022; World Bank WDI; World Bank income classifications 2024. Values are indicative and rounded. Last updated: March 2025.
Chart 2. OOP share vs GDP per capita (PPP) — top 20 high-OOP economies
The scatter plot positions each economy by its GDP per capita (PPP) on the horizontal axis and its OOP share on the vertical axis. If income were the primary driver of OOP share, we would expect a clean downward slope — richer countries with lower OOP shares. The actual pattern is messier and more interesting. Georgia ($18k PPP) and Morocco ($10k PPP) sit at the same high-OOP tier as much poorer Myanmar and Afghanistan, highlighting the role of political choices about financing rather than income levels alone.
Horizontal axis: GDP per capita, PPP (thousand international dollars, World Bank). Vertical axis: OOP share (% of current health expenditure, WHO GHED 2022). Bubble size is uniform. Dashed horizontal line at 35% marks the approximate threshold above which catastrophic health spending risk rises sharply.
Analytical insights: what the OOP ranking reveals about health system structures
The global distribution of out-of-pocket health spending shares is not random. It reflects decades of policy choices and institutional legacies that shape who finances health care, how risks are pooled, and which populations enjoy formal coverage. Several patterns stand out clearly in the 2022 data.
1. Low government health spending is the proximate cause — but not the only one
In every country in the top 10, general government health expenditure as a share of GDP is below 2%, compared with 6–9% in typical OECD countries. Myanmar, Afghanistan and Nigeria have all historically spent less than 1% of GDP through government channels on health. At these levels, the residual demand for care simply cannot be met without households paying directly. However, government spending alone is not a sufficient explanation: Georgia spends a higher share of GDP on health than several lower-OOP African countries, yet still records a 52% OOP share — pointing to the importance of how that spending is channelled, not just how much there is.
2. Insurance coverage gaps are structural, not incidental
In most high-OOP countries, the existence of an insurance scheme on paper does not translate into broad financial protection. Nigeria's National Health Insurance Authority covers fewer than 10% of the population. Pakistan's Sehat Sahulat provides hospitalization cover but leaves outpatient and pharmaceutical spending almost entirely out-of-pocket. Cambodia's Health Equity Funds protect the officially identified poor, but the near-poor and informal workers fall through the gaps. The pattern is consistent: formal coverage schemes target the easy-to-reach salaried workforce or the identifiably poor, leaving a large middle stratum of informal and rural workers exposed.
3. Medicines are the hidden driver of OOP burden
Across the countries in this ranking, outpatient medicines account for a disproportionate share of total OOP spending — often 50–70% in low-income settings. This matters because medicines are a recurring, predictable expense for people with chronic conditions, meaning the financial burden is not just catastrophic (concentrated at moments of hospitalization) but chronic and corrosive for household budgets over time. Countries that have reduced OOP shares most successfully — such as Thailand, which moved from ~33% in the early 2000s to under 12% today — did so by explicitly including outpatient drugs in their benefit packages.
4. The relationship between income and OOP share is weak at the country level
The scatter chart in Part 2 makes this visible: Georgia ($18k PPP) has a higher OOP share than Lao PDR ($8k PPP). Egypt ($13k PPP) and Viet Nam ($13k PPP) sit at similar income levels but have OOP shares of 57% and 42% respectively, reflecting different reform trajectories. Morocco ($10k PPP) has a higher OOP share than Honduras ($7k PPP). The implication is that international comparison of OOP shares should focus on institutional architecture — insurance coverage, benefits package depth, co-payment design and primary-care investment — rather than income level as the primary explanatory variable.
5. Conflict and fragility amplify OOP shares dramatically
Myanmar, Afghanistan and Sudan all share a common feature beyond low government spending: their health systems have been severely disrupted by conflict or political instability in recent years. When public facilities close, staff are displaced or supply chains collapse, households have no alternative but to seek private care and pay out-of-pocket — or to forgo care entirely. The measured OOP share in conflict settings may even understate the true burden, because foregone care (which has no expenditure footprint) is not captured in spending data but represents an immense welfare loss.
Key takeaway for policymakers:
- Reducing OOP share below 30–35% requires public health spending above approximately 5–6% of GDP combined with mandatory pre-payment pooling.
- Benefits packages must explicitly cover outpatient medicines; hospitalization-only coverage is insufficient to prevent financial hardship.
- Coverage expansion must reach informal workers and the near-poor — not just formal employees and the officially identified poor.
- In conflict or fragility contexts, emergency financing mechanisms and supply-chain resilience are prerequisites before any structural reform can take hold.
- Countries like Thailand, Mexico (Seguro Popular) and Rwanda show that rapid OOP reduction is achievable within a decade when political commitment is sustained and institutional capacity is invested.
How to interpret this ranking
If you live in or work with any of the countries listed, these numbers have practical implications that extend well beyond macroeconomic statistics.
If you are a household in a high-OOP country
A high OOP share means that when you or a family member becomes seriously ill, the costs will fall largely on you. International data consistently show that in economies where OOP exceeds 50–60% of health expenditure, one serious illness episode can wipe out several months of a median household's income. The risk is not evenly distributed: it falls hardest on households that are just above the official poverty line (and thus not covered by targeted exemptions) and on families with chronically ill members who face recurring out-of-pocket costs year after year.
If you are a policy analyst or government official
OOP share is one of the two core SDG 3.8 indicators for universal health coverage monitoring (the other being the UHC service coverage index). A high OOP share is not just a welfare problem — it is a signal of misaligned incentives that can delay care seeking, distort provider behaviour and undermine macroeconomic stability as households reduce consumption and savings to cope with medical bills. Comparing your country's trajectory over time (not just the level, but the direction of change) matters as much as the cross-country rank.
If you are a development finance professional or donor
Countries near the top of this ranking are prime candidates for support in health financing system reform — specifically in the design of risk pooling mechanisms, benefits package specification and pharmaceutical procurement systems. Aid that is channelled through parallel vertical programs can paradoxically sustain high OOP shares if it bypasses the government financing system and crowds out domestic revenue mobilization for health.
If you are a researcher or journalist
Note that OOP share is a structural indicator, not a quality-of-care indicator. A country can have a low OOP share and still deliver poor-quality care (e.g., if public facilities are funded but non-functional). Conversely, very high OOP shares in some economies can coexist with improving health outcomes. The indicator measures financial risk protection, not outcomes directly — and should always be interpreted alongside measures of access, quality and health status.
FAQ: out-of-pocket health spending
Out-of-pocket (OOP) spending includes any payment made directly by a household at the point of using a health service or purchasing a health product — without later reimbursement from any insurance or government programme. This includes: consultation fees, user charges at public facilities, medicines bought at pharmacies, diagnostic tests (laboratory, imaging), inpatient co-payments and informal payments ("under the table" payments to staff). It does not include insurance premiums (which are pre-payments), employer health contributions or government expenditure on health.
The WHO and World Bank have identified approximately 15–20% as the threshold below which the incidence of catastrophic health expenditure (defined as OOP spending exceeding 10% of total household consumption) and impoverishing health expenditure (OOP pushing households below the poverty line) become very low. Countries above roughly 30–35% consistently show elevated catastrophic spending rates, particularly for poorer quintiles. The 35% level is sometimes used as a policy warning threshold. Most OECD countries are well below 20%.
Georgia is the clearest example in this ranking: an upper-middle-income country with a higher OOP share than many low-income neighbours. The reason is that the structure of health financing depends more on political and institutional choices than on income alone. Countries can choose to finance health predominantly through general taxation, social insurance, private voluntary insurance or direct household payments. Some countries at middle incomes have historically relied on user fees and private markets because insurance expansion has been politically or administratively difficult, even as their incomes have risen.
They are closely related but different metrics. OOP share measures the system-level financing structure (what share of total health spending comes from households). Catastrophic health expenditure is a household-level indicator: it counts households for whom OOP spending in a given year exceeded a defined threshold (commonly 10% or 25% of total consumption or non-food consumption). High OOP share at the system level creates the conditions for catastrophic spending at the household level, but the two can diverge: in a wealthy country with a high OOP share but very high incomes, households might absorb high OOP spending without crossing the catastrophic threshold. Conversely, a country with a moderate aggregate OOP share might have severe catastrophic spending concentrated among the poorest quintile.
Thailand is the most cited success story: it moved from an OOP share of over 30% in the mid-1990s to under 12% today through the Universal Coverage Scheme launched in 2002, which provides near-comprehensive coverage including outpatient care and medicines. Rwanda reduced its OOP share from over 40% to under 25% through community-based health insurance (Mutuelles de Santé). Mexico's Seguro Popular (now IMSS-Bienestar) reduced catastrophic health expenditure significantly, though reforms have since been restructured. The common elements of success include: sustained political commitment, domestic revenue mobilisation for health, explicit and enforced benefit packages, and coverage of outpatient medicines.
In principle, modest, well-designed co-payments with income-related exemptions can help manage demand without leading to financial hardship — and can coexist with strong financial protection if caps and exemptions are in place. What the literature consistently shows to be harmful is high and unprotected OOP spending where user fees are the default financing mechanism for essential care, where there are no ceilings on household liability, and where the poorest households face the same charges as wealthy ones. The concern arises not from any OOP spending but from OOP as the dominant financing mechanism, especially for low-income households accessing essential services.
Methodology: how this ranking was constructed
Data source
The primary data source is the WHO Global Health Expenditure Database (GHED), which is updated annually and covers approximately 190 economies. GHED collects health expenditure data submitted by National Health Accounts (NHA) focal points in each country, supplemented by WHO-modelled estimates where NHA data are incomplete. The core indicator used is: Out-of-pocket expenditure as a share of current health expenditure (% of CHE). For most economies, the reference year is 2022; for a small number of economies with reporting lags, the most recent available year (2020 or 2021) is used.
Indicator definition
Current health expenditure (CHE) covers all spending on health goods and services consumed in a given year, excluding capital investment in health infrastructure. Out-of-pocket expenditure is the component of CHE that is paid directly by households at the point of service, without reimbursement. The OOP share (%) = (OOP / CHE) × 100.
Country selection and processing
The ranking includes all economies for which comparable GHED data exist. Small territories and economies with populations below ~500,000 may be excluded where data quality is insufficient for comparison. Values in this article are rounded to the nearest whole percentage and should be treated as indicative. For the "per capita USD" column in Table 2, current OOP per capita in current USD is derived from GHED and World Bank population data for the same reference year.
GDP per capita (PPP) for the scatter chart
GDP per capita adjusted for purchasing power parity (constant 2021 international dollars) is sourced from the World Bank World Development Indicators (WDI), series NY.GDP.PCAP.PP.KD, reference year 2022. PPP conversion uses ICP 2021 benchmark factors. Values are rounded to the nearest USD 10.
Income group classification
The World Bank income group classification (GNI per capita thresholds, Atlas method, fiscal year 2024 edition) is used: Low income (<$1,145), Lower-middle income ($1,145–$4,515), Upper-middle income ($4,516–$14,005), High income (>$14,005).
Limitations
- OOP shares can fluctuate substantially year-to-year due to disease shocks, policy changes or simply variation in survey-based estimates feeding into NHA.
- In conflict-affected settings (Myanmar, Afghanistan, Sudan), data quality is materially lower than in stable economies, and the true OOP burden may be understated due to foregone care.
- Cross-country comparability is imperfect: NHA methodologies differ, and the boundary between household spending on health and non-health is not always consistently drawn.
- The indicator does not distinguish between OOP on essential services versus elective or higher-end care. A country where OOP is concentrated in private hospitalization for wealthier users may show a similar aggregate share as one where the poor pay out-of-pocket for primary care — with very different welfare implications.
Primary data sources
All figures are compiled from the official international datasets below. Readers undertaking policy analysis or academic research should always consult the original databases directly.
All numerical values in the tables and charts are approximate and rounded for clarity. For formal statistical or policy work, always refer to the original databases and their accompanying methodological documentation. Last updated: March 2025.
