In 2023, Singapore dominated the ranking of the world's health and health systems, followed by Japan and South Korea. The health index score is calculated by evaluating various indicators that assess the health of the population, and access to the services required to sustain good health, including health outcomes, health systems, sickness and risk factors, and mortality rates. The health and health system index score of the top ten countries with the best healthcare system in the world ranged between 82 and 86.9, measured on a scale of zero to 100.

Global Health Security Index  Numerous health and health system indexes have been developed to assess various attributes and aspects of a nation's healthcare system. One such measure is the Global Health Security (GHS) index. This index evaluates the ability of 195 nations to identify, assess, and mitigate biological hazards in addition to political and socioeconomic concerns, the quality of their healthcare systems, and their compliance with international finance and standards. In 2021, the United States was ranked at the top of the GHS index, but due to multiple reasons, the U.S. government failed to effectively manage the COVID-19 pandemic. The GHS Index evaluates capability and identifies preparation gaps; nevertheless, it cannot predict a nation's resource allocation in case of a public health emergency.

Universal Health Coverage Index  Another health index that is used globally by the members of the United Nations (UN) is the universal health care (UHC) service coverage index. The UHC index monitors the country's progress related to the sustainable developmental goal (SDG) number three. The UHC service coverage index tracks 14 indicators related to reproductive, maternal, newborn, and child health, infectious diseases, non-communicable diseases, service capacity, and access to care. The main target of universal health coverage is to ensure that no one is denied access to essential medical services due to financial hardships. In 2021, the UHC index scores ranged from as low as 21 to a high score of 91 across 194 countries. 

In 2023, the health care system in Finland ranked first with a care index score of ****, followed by Belgium and Japan. Care systems index score is measured using multiple indicators from various public databases, it evaluates the capacity of a health system to treat and cure diseases and illnesses, once it is detected in the population This statistic shows the care systems ranking of countries worldwide in 2023, by their index score.

According to a 2021 health care systems ranking among selected high-income countries, the United States came last in the overall ranking of its health care system performance. The overall ranking was based on five performance categories, including access to care, care process, administrative efficiency, equity, and health care outcomes. For the category care process, which measures preventive care, safe and coordinated care among others, the U.S. was ranked second, while New Zealand took first place. This statistic illustrates the health care process rankings of the United States' health care system compared to ten other high-income countries in 2021.

The average for 2020 based on 36 countries was 4.44 hospital beds. The highest value was in South Korea: 12.65 hospital beds and the lowest value was in Mexico: 0.99 hospital beds. The indicator is available from 1960 to 2021. Below is a chart for all countries where data are available.

In 2023, Norway ranked first with a health index score of 83, followed by Iceland and Sweden. The health index score is calculated by evaluating various indicators that assess the health of the population, and access to the services required to sustain good health, including health outcomes, health systems, sickness and risk factors, and mortality rates. The statistic shows the health and health systems ranking of European countries in 2023, by their health index score.

Data on the top universities for Medical and Health in 2025, including disciplines such as Medicine and Dentistry, and Other Health Subjects.

The average for 2021 based on 181 countries was 7.21 percent. The highest value was in Afghanistan: 21.83 percent and the lowest value was in Brunei: 2.2 percent. The indicator is available from 2000 to 2022. Below is a chart for all countries where data are available.

Full ranking of countries’ healthcare capacity response capacity and resilience.

Ranking results of the countries based on their healthcare resources.

According to a survey from *************, Taiwan was ranked as the best country for expat healthcare, followed by South Korea and Qatar. This statistic represents the ranking of top ten countries with best healthcare for expats worldwide in 2023.

According to a survey conducted in a selection of Latin American countries in 2024, Argentina was by far the country with the highest share of satisfied health patients, with ** percent of respondents assessing healthcare quality as good or very good, whereas only ** percent of respondents in Peru claimed to receive good healthcare. Hospitals in Latin America Hospital Israelita Albert Einstein in São Paulo, Brazil was considered the hospital with the highest care quality in Latin America in 2022. The first three leading hospitals in hosting patients were also located in Brazil, ranking high along other healthcare facilities in Argentina, Colombia and Chile. In 2024, Brazil was the country with the highest number of hospitals in the region, with approximately ***** establishments, followed by Mexico and Colombia. Hospital equipment in Latin America As of 2023, more than ** percent of hospitals in Latin America were equipped with electrocardiogram (EKG) machines. That year, ultrasound machines could be found in ** percent of hospitals, while a fourth of these establishments in the region had computed tomography (CT) scanners. In that year, Brazil had the most ultrasound machines installed in hospitals in Latin America, with over ******, followed by Mexico and Argentina.

In 2023, there were 5,177 hospital organizations operating in Russia, reflecting a slight increase from the previous year. This marks a decrease of 1,131 hospitals compared to 2010, highlighting a continuous decline from the peak of 6,343 hospitals in 2011. The number of hospitals has fluctuated over the years, with the lowest count recorded in 2021 at 5,072. Hospital bed density in Russia The density of hospital beds in Russia, measured as the number of beds per 10,000 population, saw a decrease in recent years and reached 77.5 in 2023. In fact, Russia has one of the highest hospital bed densities worldwide, ranking above other Central and Eastern European (CEE) countries. Russian health care in a global context In 2024, Russia ranked 14th among the countries with the best medical infrastructure and healthcare professionals (HCPs) with an index score exceeding that of Germany and Canada. Moreover, Russia ranked 14th in terms of medicine affordability and availability.

The average for 2021 based on 10 countries was 46.11 index points. The highest value was in Singapore: 130.04 index points and the lowest value was in Laos: 21.7 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

In 2025, South Africa had the highest health care index in Africa with a score of 63.8, followed by Kenya with 62 points. These scores, for both countries, are considered to be reasonably high. The health care index takes into account factors such as the overall quality of the health care system, health care professionals, equipment, staff, doctors, and cost.

This statistic shows the 2024 ranking of the global top 10 health care equipment and services companies based on revenue. The values were taken from the Financial Times equity screener database. U.S. health care provider Thermo Fisher Scientific was ranked first, with a total revenue of almost 42.5 billion U.S. dollars.

Official ranking of 173 global cities based on stability, healthcare, culture, education, and infrastructure by the Economist Intelligence Unit

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

The average for 2021 based on 51 countries was 136.99 U.S. dollars. The highest value was in the Seychelles: 718.49 U.S. dollars and the lowest value was in Madagascar: 17.64 U.S. dollars. The indicator is available from 2000 to 2022. Below is a chart for all countries where data are available.

Context

Movehub city ranking as published on http://www.movehub.com/city-rankings

Content

movehubqualityoflife.csv

Cities ranked by
Movehub Rating: A combination of all scores for an overall rating for a city or country.
Purchase Power: This compares the average cost of living with the average local wage.
Health Care: Compiled from how citizens feel about their access to healthcare, and its quality.
Pollution: Low is good. A score of how polluted people find a city, includes air, water and noise pollution.
Quality of Life: A balance of healthcare, pollution, purchase power, crime rate to give an overall quality of life score.
Crime Rating: Low is good. The lower the score the safer people feel in this city.

movehubcostofliving.csv

Unit: GBP
City
Cappuccino
Cinema
Wine
Gasoline
Avg Rent
Avg Disposable Income

cities.csv

Cities to countries as parsed from Wikipedia https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A (A-Z)

Acknowledgements

Movehub

http://www.movehub.com/city-rankings

Wikipedia

https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A

BackgroundAs new interventions to reduce childhood mortality are identified, careful consideration must be given to identifying populations that could benefit most from them. Promising reductions in childhood mortality reported in a large cluster randomized trial of mass drug administration (MDA) of azithromycin (AZM) prompted the development of visually compelling, easy-to-use tools that synthesize country-specific data on factors that would influence both potential AZM benefit and MDA implementation success.Methodology/Principal FindingsWe assessed the opportunity to reduce mortality and the feasibility of implementing such a program, creating Opportunity and Feasibility Indices, respectively. Countries with high childhood mortality were included. A Country Ranking Index combined key variables from the previous two Indices and applied a scoring system to identify high-priority countries. We compared four scenarios with varying weights given to each variable.Twenty-five countries met inclusion criteria. We created easily visualized tools to display the results of the Opportunity and Feasibility Indices. The Opportunity Index revealed substantial variation in the opportunity for an MDA of AZM program to reduce mortality, even among countries with high overall childhood mortality. The Feasibility Index demonstrated that implementing such a program would be most challenging in the countries that could see greatest benefit. Based on the Country Ranking Index, Equatorial Guinea would benefit the most from the MZA of AZM in three of the four scenarios we tested.Conclusions/SignificanceThese visually accessible tools can be adapted or refined to include other metrics deemed important by stakeholders, and provide a quantitative approach to prioritization for intervention implementation. The need to explicitly state metrics and their weighting encourages thoughtful and transparent decision making. The objective and data-driven approach promoted by the three Indices may foster more efficient use of resources.