Top 100 Countries by Hospital Beds per 1,000 People, Latest World Bank/WHO Data
Hospital Bed Density by Country and Economy: Latest World Bank / WHO Snapshot
Monaco ranks first in this table, with 21.99 hospital beds per 1,000 people. The figure is the latest value published for Monaco in World Bank WDI, with source year 2014, so it should be read as a historical latest entry rather than as current hospital capacity.
Thank you for reading this post, don't forget to subscribe!The metric is hospital beds per 1,000 people from World Bank indicator SH.MED.BEDS.ZS, sourced from WHO data supplemented by country data. Higher values rank higher because they show more reported inpatient bed capacity per resident.
World Bank World Development Indicators is the primary source for the numbers. DataHub and NationStat are listed only as access and cross-check pages for the same indicator.
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Open rankingMonaco ranks first, using its latest World Bank / WHO entry from 2014.
Saudi Arabia is the 100th entry, with 2.41 beds per 1,000 people in 2023.
The table covers World Bank reporting countries and economies with a usable value; regional aggregates are excluded.
This is a mixed-year latest-data snapshot, not one common survey year.
Overview: what hospital beds per 1,000 people measures
Hospital beds per 1,000 people is a health-system capacity measure. It counts reported inpatient beds in public, private, general and specialized hospitals and rehabilitation centers, with acute and chronic care beds included in the broad World Bank definition.
The metric helps compare hospital infrastructure density, but it is not a quality score. It does not show whether beds are staffed, equipped, occupied, affordable, geographically accessible or suitable for emergency and intensive care.
Each economy is represented by its latest available World Bank WDI value. This keeps the table source-based, but it also means older observations remain visible when the indicator has not been updated for a country or territory.
Why countries differ in hospital-bed density
High hospital-bed density often reflects a hospital-centered care model, long-stay and chronic-care capacity, older infrastructure patterns, aging populations, specialized facilities or reporting rules that count a wider range of beds.
A lower value is not automatically a sign of weak healthcare. Some systems use more primary care, outpatient treatment, day surgery, home care, shorter stays and stronger triage, which can reduce the number of inpatient beds needed per resident.
Small economies and territories need extra caution. A single specialized facility, a small resident population or an old source year can push a bed-density value far above the levels seen in large national systems.
Top 10 hospital-bed densities in the latest World Bank WDI entries
The top ten combine small economies, older source years and high-capacity hospital systems. The rank is calculated from beds per 1,000 people, while the note shows the source year that explains how current each entry is.
Top 10 countries and economies by hospital beds per 1,000 people
| Rank | Entity | Value | Region · year · source |
|---|---|---|---|
| 1 | Monaco | 21.99 | Europe & Central Asia · 2014 · World Bank/WHO · published |
| 2 | Virgin Islands (U.S.) | 18.68 | Latin America & Caribbean · 1996 · World Bank/WHO · published |
| 3 | Greenland | 14.35 | Europe & Central Asia · 1970 · World Bank/WHO · published |
| 4 | Korea, Rep. | 12.81 | East Asia & Pacific · 2022 · World Bank/WHO · published |
| 5 | Korea, Dem. People's Rep. | 12.80 | East Asia & Pacific · 2018 · World Bank/WHO · published |
| 6 | Japan | 12.59 | East Asia & Pacific · 2022 · World Bank/WHO · published |
| 7 | Channel Islands | 10.60 | Europe & Central Asia · 1981 · World Bank/WHO · published |
| 8 | Belarus | 9.77 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 9 | Mongolia | 8.58 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 10 | Bulgaria | 8.20 | Europe & Central Asia · 2023 · World Bank/WHO · published |
Values are beds per 1,000 people. Always read the year badge: this table combines the latest available WDI year for each economy.
How to read older top entries: Greenland, Channel Islands and Virgin Islands
Some high-ranking entries are source-backed but old observations. Greenland appears with a 1970 value, the Channel Islands with a 1981 value and the U.S. Virgin Islands with a 1996 value.
Those entries should not be read as current 2026 hospital capacity. They remain in the table because the ranking follows the World Bank reporting universe and uses the latest available value for each economy.
For current policy analysis, give more weight to recent-year entries and treat older small-territory values as data-availability signals rather than direct evidence of present-day bed supply.
Chart: Top 20 hospital beds per 1,000 people
The chart uses the same values as the ranking table. It highlights the gap between the highest reported entries and the rest of the Top 20; the table should still be used for source years and interpretation.
Methodology
The metric is hospital beds per 1,000 people. The source indicator is World Bank SH.MED.BEDS.ZS, with WHO data supplemented by country data. The ranking orders the published WDI values from higher to lower.
Metric and unit
Metric: hospital beds per 1,000 people. Display values are shown with two decimals where needed.
Year logic
Each economy uses its latest available WDI year. The page is a latest-data snapshot, not a same-year global survey.
Source hierarchy
World Bank WDI is the source for values and years. DataHub and NationStat are listed only to make access and checking easier.
Coverage and exclusions
The table includes 100 countries and economies with usable WDI values. Regional and income-group aggregates are excluded.
Entries without a WDI value are excluded. When display values look equal after rounding, the underlying numeric value and the existing table order determine placement.
Limits are important. World Bank metadata treats hospital beds as a rough capacity indicator because definitions are not fully consistent across countries. This is not an ICU-bed count, not a hospital-quality score, not a staffing measure and not a real-time capacity tracker.
The metric also does not measure bed occupancy, emergency readiness, equipment, regional access, affordability, waiting times, health outcomes or the strength of outpatient and primary-care systems.
Main ranking: Top 100 countries and economies by hospital beds per 1,000 people
Use the controls to search by entity, filter by region or source type, change sort order or switch between Top 10, Top 20 and the full Top 100.
Top 100 countries and economies by hospital beds per 1,000 people
| Rank | Entity | Value | Region · year · source |
|---|---|---|---|
| 1 | Monaco | 21.99 | Europe & Central Asia · 2014 · World Bank/WHO · published |
| 2 | Virgin Islands (U.S.) | 18.68 | Latin America & Caribbean · 1996 · World Bank/WHO · published |
| 3 | Greenland | 14.35 | Europe & Central Asia · 1970 · World Bank/WHO · published |
| 4 | Korea, Rep. | 12.81 | East Asia & Pacific · 2022 · World Bank/WHO · published |
| 5 | Korea, Dem. People's Rep. | 12.80 | East Asia & Pacific · 2018 · World Bank/WHO · published |
| 6 | Japan | 12.59 | East Asia & Pacific · 2022 · World Bank/WHO · published |
| 7 | Channel Islands | 10.60 | Europe & Central Asia · 1981 · World Bank/WHO · published |
| 8 | Belarus | 9.77 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 9 | Mongolia | 8.58 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 10 | Bulgaria | 8.20 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 11 | Germany | 7.55 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 12 | Romania | 7.23 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 13 | Russian Federation | 6.81 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 14 | Austria | 6.70 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 15 | Hungary | 6.63 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 16 | Czechia | 6.54 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 17 | Kazakhstan | 6.54 | Europe & Central Asia · 2020 · World Bank/WHO · published |
| 18 | Barbados | 6.40 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 19 | Bermuda | 6.30 | Latin America & Caribbean · 1996 · World Bank/WHO · published |
| 20 | Ukraine | 6.14 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 21 | Poland | 6.04 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 22 | Serbia | 5.78 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 23 | Lithuania | 5.71 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 24 | France | 5.65 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 25 | China | 5.63 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 26 | Croatia | 5.60 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 27 | Slovak Republic | 5.57 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 28 | Moldova | 5.54 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 29 | Belgium | 5.42 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 30 | Macao SAR, China | 5.30 | East Asia & Pacific · 1970 · World Bank/WHO · published |
| 31 | Nauru | 4.97 | East Asia & Pacific · 2010 · World Bank/WHO · published |
| 32 | Latvia | 4.95 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 33 | Haiti | 4.90 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 34 | Hong Kong SAR, China | 4.89 | East Asia & Pacific · 1985 · World Bank/WHO · published |
| 35 | Uzbekistan | 4.89 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 36 | North Macedonia | 4.74 | Europe & Central Asia · 2021 · World Bank/WHO · published |
| 37 | Maldives | 4.56 | South Asia · 2021 · World Bank/WHO · published |
| 38 | Switzerland | 4.38 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 39 | Palau | 4.34 | East Asia & Pacific · 2010 · World Bank/WHO · published |
| 40 | Cuba | 4.33 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 41 | Greece | 4.27 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 42 | Armenia | 4.24 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 43 | Tuvalu | 4.16 | East Asia & Pacific · 2001 · World Bank/WHO · published |
| 44 | Estonia | 4.13 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 45 | Slovenia | 4.11 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 46 | Malta | 4.09 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 47 | Georgia | 4.04 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 48 | Tajikistan | 4.04 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 49 | St. Kitts and Nevis | 3.98 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 50 | Dominica | 3.97 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 51 | Luxembourg | 3.95 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 52 | Sri Lanka | 3.93 | South Asia · 2023 · World Bank/WHO · published |
| 53 | Australia | 3.82 | East Asia & Pacific · 2016 · World Bank/WHO · published |
| 54 | Montenegro | 3.82 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 55 | Mauritius | 3.80 | Sub-Saharan Africa · 2023 · World Bank/WHO · published |
| 56 | Kyrgyz Republic | 3.73 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 57 | Azerbaijan | 3.68 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 58 | Turkmenistan | 3.60 | Europe & Central Asia · 2021 · World Bank/WHO · published |
| 59 | Brunei Darussalam | 3.58 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 60 | Libya | 3.50 | Middle East & North Africa · 2022 · World Bank/WHO · published |
| 61 | Portugal | 3.48 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 62 | Antigua and Barbuda | 3.42 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 63 | Argentina | 3.36 | Latin America & Caribbean · 2022 · World Bank/WHO · published |
| 64 | San Marino | 3.35 | Europe & Central Asia · 2014 · World Bank/WHO · published |
| 65 | Puerto Rico | 3.32 | Latin America & Caribbean · 1996 · World Bank/WHO · published |
| 66 | Norway | 3.30 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 67 | Guyana | 3.24 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 68 | Micronesia, Fed. Sts. | 3.22 | East Asia & Pacific · 2009 · World Bank/WHO · published |
| 69 | St. Vincent and the Grenadines | 3.21 | Latin America & Caribbean · 2022 · World Bank/WHO · published |
| 70 | Israel | 3.14 | Middle East & North Africa · 2023 · World Bank/WHO · published |
| 71 | Italy | 3.06 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 72 | Turkiye | 3.05 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 73 | Grenada | 3.01 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 74 | Cayman Islands | 3.00 | Latin America & Caribbean · 1990 · World Bank/WHO · published |
| 75 | Ireland | 2.96 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 76 | Spain | 2.91 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 77 | Sao Tome and Principe | 2.91 | Sub-Saharan Africa · 2019 · World Bank/WHO · published |
| 78 | Albania | 2.90 | Europe & Central Asia · 2020 · World Bank/WHO · published |
| 79 | Suriname | 2.87 | Latin America & Caribbean · 2022 · World Bank/WHO · published |
| 80 | Iceland | 2.83 | Europe & Central Asia · 2020 · World Bank/WHO · published |
| 81 | Singapore | 2.81 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 82 | Marshall Islands | 2.80 | East Asia & Pacific · 2010 · World Bank/WHO · published |
| 83 | Solomon Islands | 2.75 | East Asia & Pacific · 1992 · World Bank/WHO · published |
| 84 | Lebanon | 2.73 | Middle East & North Africa · 2021 · World Bank/WHO · published |
| 85 | Namibia | 2.70 | Sub-Saharan Africa · 2009 · World Bank/WHO · published |
| 86 | United States | 2.68 | North America · 2022 · World Bank/WHO · published |
| 87 | Cameroon | 2.65 | Sub-Saharan Africa · 2016 · World Bank/WHO · published |
| 88 | Seychelles | 2.63 | Sub-Saharan Africa · 2023 · World Bank/WHO · published |
| 89 | Finland | 2.61 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 90 | Andorra | 2.56 | Europe & Central Asia · 2008 · World Bank/WHO · published |
| 91 | Canada | 2.54 | North America · 2022 · World Bank/WHO · published |
| 92 | Brazil | 2.52 | Latin America & Caribbean · 2021 · World Bank/WHO · published |
| 93 | Viet Nam | 2.52 | East Asia & Pacific · 2017 · World Bank/WHO · published |
| 94 | New Zealand | 2.51 | East Asia & Pacific · 2023 · World Bank/WHO · published |
| 95 | Tonga | 2.48 | East Asia & Pacific · 2010 · World Bank/WHO · published |
| 96 | Uruguay | 2.44 | Latin America & Caribbean · 2023 · World Bank/WHO · published |
| 97 | Denmark | 2.43 | Europe & Central Asia · 2023 · World Bank/WHO · published |
| 98 | United Kingdom | 2.42 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 99 | Netherlands | 2.42 | Europe & Central Asia · 2022 · World Bank/WHO · published |
| 100 | Saudi Arabia | 2.41 | Middle East & North Africa · 2023 · World Bank/WHO · published |
Primary source: World Bank WDI indicator SH.MED.BEDS.ZS, WHO data supplemented by country data. DataHub and NationStat are listed as secondary access and checking pages. Values are rounded for display after ranking.
Insights from the hospital-bed density ranking
Key insight
The top of the ranking is strongly affected by small-economy effects and older source years. The year badge is therefore part of the result, not a footnote.
Notable pattern
Several European and post-Soviet health systems remain high in the table, including Belarus, Bulgaria, Germany, Romania, the Russian Federation, Austria and Hungary.
Regional concentration
Europe & Central Asia accounts for 51 of the 100 entries, while East Asia & Pacific contributes 19. The result reflects both hospital-system design and the economies covered by the World Bank indicator.
Outlier
Monaco ranks first at 21.99 beds per 1,000 people, but its source year is 2014. It is a published World Bank value, not a claim about current operating capacity.
What this ranking means for readers
This ranking helps compare reported inpatient bed density across countries and economies. It is useful for discussions about healthcare infrastructure, hospital-system capacity and long-run differences in care models.
A latest WDI value is not the same as a current operating-capacity count. Some entries have older source years, especially small territories and economies with infrequent reporting.
Hospital beds are only one part of readiness. A system with fewer beds can still perform well if it has strong primary care, outpatient capacity, staffing, financing, triage and short average stays. A system with many beds may still face shortages if staff, equipment or regional access are constrained.
FAQ
Which country or economy has the most hospital beds per 1,000 people?
Monaco ranks first in this table with 21.99 hospital beds per 1,000 people, using its latest World Bank / WHO value from 2014.
Are these 2026 hospital bed numbers?
No. This is a 2026 snapshot based on the latest available WDI values. It is not a same-year 2026 ranking; source years range from 1970 to 2023.
Why are Greenland, Channel Islands and the U.S. Virgin Islands so high?
They have older latest WDI values: Greenland 1970, Channel Islands 1981 and Virgin Islands 1996. Their ranks should be read as source-backed historical latest values, not current hospital-capacity claims.
Why are territories and economies included?
The World Bank indicator is published for countries and economies. This page follows that reporting universe and excludes regional aggregates, but it does not limit the table only to sovereign states.
Does a higher value mean a better healthcare system?
No. More beds per 1,000 people can indicate greater inpatient capacity, but quality, staffing, access, equipment, outcomes and efficiency are separate questions.
Does the metric include ICU beds?
The indicator is broader than ICU capacity. It covers reported inpatient hospital beds across several types of hospitals and care settings; it is not an ICU-only measure.
Why do some countries have fewer beds but strong healthcare systems?
Some systems rely more on outpatient care, primary care, home care, day surgery and shorter hospital stays. That can reduce beds per resident without necessarily reducing quality.
How is the rank calculated?
Entries are ordered from the highest to the lowest beds-per-1,000-people value. The value column is the ranking metric, while the note column shows region, year and source.
Sources
World Bank Data — Hospital beds per 1,000 people
Primary source for SH.MED.BEDS.ZS values, source years and country/economy coverage.
World Bank DataBank Metadata Glossary
Definition and limitation source for interpreting hospital beds per 1,000 people in World Development Indicators.
https://databank.worldbank.org/metadataglossary/world-development-indicators/series/SH.MED.BEDS.ZS
DataHub WDI package — SH.MED.BEDS.ZS
Secondary access page for the World Development Indicators CSV package and field structure.
https://datahub.io/world-development-indicators/sh.med.beds.zs
NationStat — World Bank WDI ranking view
Secondary access view used to check ordering against WDI values; World Bank WDI remains the source for the table.
https://nationstat.com/de/indicator/hospital-beds-per-1000-people
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