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. 

The healthcare ranking reflects the quality of health care and access to health services in different countries. The assessment includes various factors such as life expectancy, access to medical services, healthcare funding, and technologies.

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 2021 based on 186 countries was 1368.8 U.S. dollars. The highest value was in the USA: 11999.09 U.S. dollars and the lowest value was in Somalia: 14.63 U.S. dollars. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.

About the Dataset

This dataset contains Quality of Life indices for various countries around the globe, extracted from the Numbeo website. The data provides valuable metrics for comparing countries based on several aspects of living standards, which can assist in decisions such as choosing a place to live or analyzing global trends in quality of life.

OBS: The code to generate this dataset is presented on: https://www.kaggle.com/code/marcelobatalhah/web-scrapping-quality-of-life-index

Columns in the Dataset

1. Rank:
   The global rank of the country based on its Quality of Life Index according to Year (1 = highest quality of life).

2. Country:
   The name of the country.

3. Quality of Life Index:
   A composite index that evaluates the overall quality of life in a country by combining other indices, such as Safety, Purchasing Power, and Health Care.

4. Purchasing Power Index:
   Measures the relative purchasing power of the average consumer in a country compared to New York City (baseline = 100).

5. Safety Index:
   Indicates the safety level of a country. A higher score suggests a safer environment.

6. Health Care Index:
   Evaluates the quality and accessibility of healthcare in the country.

7. Cost of Living Index:
   Measures the relative cost of living in a country compared to New York City (baseline = 100).

8. Property Price to Income Ratio:
   Compares the affordability of real estate by dividing the average property price by the average income.

9. Traffic Commute Time Index:
   Reflects the average time spent commuting due to traffic.

10. Pollution Index:
    Rates the level of pollution in the country (air, water, etc.).

11. Climate Index:
    Rates the favorability of the climate in the country (higher = more favorable).

12. Year:
    Year when the metrics were extracted.

Key Insights from the Dataset

• The Quality of Life Index aggregates multiple indicators, making it a useful single metric to compare countries.
• Specific indices such as Safety Index or Health Care Index allow for focused analysis on areas like security or healthcare quality.
• Cost of Living Index and Purchasing Power Index can help determine the affordability of living in each country.

How the Data Was Collected

• The dataset was built using web scraping techniques in Python.
• The data was extracted from the "Quality of Life Rankings by Country" page on Numbeo.
• Libraries used:
  • requests for retrieving webpage content.
  • BeautifulSoup for parsing the HTML and extracting relevant information.
  • pandas for organizing and storing the data in a structured format.

Possible Applications

1. Relocation Decision Making:
   Use the dataset to compare countries and identify destinations with high quality of life, safety, and healthcare.

2. Global Analysis:
   Perform exploratory data analysis (EDA) to identify trends and correlations across quality of life metrics.

3. Visualization:
   Plot global maps, bar charts, or other visualizations to better understand the data.

4. Predictive Modeling:
   Use this dataset as a base for machine learning tasks, like predicting Quality of Life Index based on other metrics.

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

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.

BackgroundssssHealth system performance is a multifaceted concept that encompasses various dimensions of a nation’s healthcare infrastructure. This study aims to assess and rank the performance of health systems across different regions of the world.MethodologyWe employed the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method in 2023 to evaluate and rank the health system performance of 31 countries across six geographical regions. Our evaluation included six general categories and twelve indicators related to health, finance, and the COVID-19 pandemic. The final weights for these indicators were determined using the Three-scale method and the Entropy-weighting method. Additionally, we categorized health system performance into three groups: high, moderate, and low. Hierarchical clustering of health system performance scores was conducted using SPSS software (version 26).ResultsLuxembourg emerged as the only high-performing health system, while Qatar and the Netherlands fell into the moderate-performance group. Other countries exhibited low-performing health systems. Notably, within the low-performance group, the United States of America, Australia, Singapore, Canada, England, and Germany achieved relatively better rankings. Conversely, Yemen, Egypt, Afghanistan, and Bolivia ranked lowest in terms of health system performance.ConclusionContrary to the assumption that higher health spending guarantees improved performance, the experience of COVID-19 among high-income countries revealed mixed results. Strengthening resilience, investing in public health systems, and ensuring sustainable financial resources are crucial for enhancing health system performance.

Context:

Understanding and analyzing healthcare prices globally is essential for making informed decisions in healthcare policy, medical tourism, and personal healthcare choices. In this Kaggle dataset, we aim to shed light on healthcare prices in different countries in 2017. To get started, let's define the columns and features within the dataset and discuss how we can work with them effectively.

Content:

Introduction - Introduce the dataset and its importance in understanding global healthcare pricing. - Explain the objective of this analysis.

Columns:

a. Countries: This column contains the names of different countries.

b. Healthcare Prices, 2017: This column represents healthcare prices in the respective countries for the year 2017. It serves as the primary numerical feature of interest.

c. Global Rank: This column provides the global rank of each country based on its healthcare prices in 2017. It can be used for comparative analysis and benchmarking.

d. Available Data: This column likely indicates whether there is complete data available for each country in the dataset. It may be binary (e.g., 'Yes' or 'No').

Features: - Discuss what features are and how they relate to columns. Features are variables used in analysis, and in this dataset, the primary feature is "Healthcare Prices, 2017."

Data Preprocessing - Check for missing values in the dataset, especially in the "Healthcare Prices, 2017" column. - Deal with any outliers that may skew the analysis. - If the "Available Data" column contains relevant information, explain how it might be used or whether it needs preprocessing.

Exploratory Data Analysis (EDA) - Visualize the distribution of healthcare prices in 2017. - Explore any patterns or anomalies in the data. - Consider using statistical measures like mean, median, and standard deviation to summarize the data.

Feature Engineering - If necessary, discuss potential feature engineering techniques. For example, you might create new features like "Healthcare Prices Growth Rate" or "Healthcare Prices Quartiles."

Working with Missing Data (if applicable) - If there are missing data points in the "Available Data" column, discuss strategies for handling this missing information, such as imputation or exclusion.

Conclusion - Summarize the main points discussed in this document. - Emphasize the importance of understanding the dataset's columns and features before diving into a more detailed analysis.

The average for 2021 based on 186 countries was 7.09 percent. The highest value was in Afghanistan: 21.51 percent and the lowest value was in Brunei: 2.15 percent. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.

The average for 2021 based on 17 countries was 65.06 index points. The highest value was in Costa Rica: 128.98 index points and the lowest value was in Nicaragua: 28.86 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

Cost of Living - Country Rankings Dataset

Context:

The "Cost of Living - Country Rankings Dataset" provides comprehensive information on the cost of living in various countries around the world. Understanding the cost of living is crucial for individuals, businesses, and policymakers alike, as it impacts decisions related to travel, relocation, investment, and economic analysis. This dataset is intended to serve as a valuable resource for researchers, data analysts, and anyone interested in exploring and comparing the cost of living across different nations.

Content:

This dataset comprises four primary columns:

1. Countries: This column contains the names of various countries included in the dataset. Each country is identified by its official name.

2. Cost of Living: The "Cost of Living" column represents the cost of living index or score for each country. This index is typically calculated by considering various factors, such as housing, food, transportation, healthcare, and other essential expenses. A higher index value indicates a higher cost of living in that particular country, while a lower value suggests a more affordable cost of living.

3. 2017 Global Rank: This column provides the global ranking of each country's cost of living in the year 2017. The ranking is based on the cost of living index mentioned earlier. A lower rank indicates a lower cost of living relative to other countries, while a higher rank suggests a higher cost of living position.

4. Available Data: The "Available Data" column indicates whether or not data for a specific country and year is available.

This dataset is designed to support various data analysis and visualization tasks. Users can explore trends in the cost of living, identify countries with high or low cost of living, and analyze how rankings have changed over time. Researchers can use this dataset to conduct in-depth studies on the factors influencing the cost of living in different regions and the economic implications of such variations.

Please note that the dataset includes information for the year 2017, and users are encouraged to consider this when interpreting the data, as economic conditions and the cost of living may have changed since then. Additionally, this dataset aims to provide a snapshot of cost of living rankings for countries in 2017 and may not cover every country in the world.

Link: https://www.theglobaleconomy.com/rankings/cost_of_living_wb/

Disclaimer: The accuracy and completeness of the data provided in this dataset are subject to the source from which it was obtained. Users are advised to cross-reference this data with authoritative sources and exercise discretion when making decisions based on it. The dataset creator and Kaggle assume no responsibility for any actions taken based on the information provided herein.

Global health system performance rankings of the 31 countries.

This dataset provides a comparative analysis of education and health indicators across top countries, including Poland, Finland, Italy, and the USA etc... The data covers a range of indicators related to education, such as literacy rates, enrollment rates, and education spending, as well as health indicators such as life expectancy, infant mortality rates, and healthcare spending. The data is sourced from various official and publicly available data sources, including the World Bank, the United Nations, and country-specific government websites. Researchers, analysts, and educators can use this dataset to gain insights into the education and health outcomes of different countries, as well as to identify areas for improvement and best practices. The dataset is ideal for cross-country comparative analysis and can be used to inform policy-making, research, and educational programs.

The average for 2021 based on 19 countries was 3215.44 U.S. dollars. The highest value was in the USA: 11999.09 U.S. dollars and the lowest value was in India: 75.55 U.S. dollars. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.

Ranking of 31 countries (Out of Pocket Spending & Prepaid Private Spending Indices).

This table provides statistics on the Top 50 Health Service Codes for services provided to Alberta Residents in Other Countries (Except United States). This table is an Excel version of a table in the “Alberta Health Care Insurance Plan Statistical Supplement” report published annually by Alberta Health.

The national averages for critical quality measures of Home Health Agencies.

The average for 2021 based on 44 countries was 3554.27 U.S. dollars. The highest value was in Switzerland: 11262.23 U.S. dollars and the lowest value was in Ukraine: 369.9 U.S. dollars. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.