Brief version

The 2022 version of the index compares 26 European OECD members. It follows 23 indicators, starting with general ones (like life expectancy) and going to more specific aspects (hospital admissions with diabetes, 5-year leukemia survival rates, etc.). See the rankings for a more specific description of the indicators. Most of the data comes from OECD and Eurostat, but other sources are also used.

The data was indexed on a 0-1 scale with the best country result valued at 1 and the worst at 0. The results from individual indicators (Perinatal mortality + Neonatal mortality + Infant mortality and Ischemic stroke mortality + Hemorrhagic stroke mortality are grouped and averaged into two groups) are summed.

There are three sets of results:

  • Nominal - no weights applied
  • Expenditure weighted - nominal results weighted by healthcare expenditure share on the country's GDP
  • "Health for money" - nominal results weighted by nominal expenditure per capita on healthcare, modified with wage level in the country

Complete methodology


The Health for Money (HFM) Index 2022 consists of 25 main indicators:

  • AMI mortality
  • Antibiotics consumption
  • Citations per document
  • Covid deaths per million
  • Healthy life years 65
  • Hemorrhagic stroke mortality
  • Hospital length of stay
  • Hypertension hospitalization
  • Death due to cancer per 100 000
  • Diabetes hospital admission
  • Disability per population
  • Graduates per 100 000
  • Incidence measles
  • Infant mortality
  • Ischemic stroke mortality
  • Life expectancy
  • Maternal mortality
  • Health & Social workers
  • Health expenditure GDP
  • Health expenditure per capita
  • Morbidity perceived health
  • Neonatal mortality
  • Perinatal mortality
  • Potential life years lost
  • Top Universities

These are the indicators on the basis of which the basic index is calculated. Two of them (Top universities, Covid deaths per million) are calculated on the basis of auxiliary indicators. The Health expenditure GDP and Health expenditure per capita indicators are used to weigh the base index.

In addition, the index includes two indicators created by calculating the average of multiple related variables. Firstly, the “Average – mortalities” indicator comprises Infant mortality, Neonatal mortality, and Perinatal mortality. Secondly, the “Average stroke mortality” comprises Ischemic stroke mortality and Hemorrhagic stroke mortality.

Auxiliary indicators

The following 3 auxiliary indicators were also used in the preparation of the main variables (or their indexation):

  • Population World Bank data
  • Global covid data
  • Average wage

Their use is described in the sections "Calculating indicators" and "Indexing indicators."

Outdated (discarded) indicators

Previous versions of the index also included 3 indicators which were subsequently removed due to their obsolescence[1]:

  • Breast cancer survival
  • Colon cancer survival
  • Leukemia survival

These indicators have been replaced by the indicator Death due to cancer per 100 000.

Calculating indicators

Data for most indicators are exported from external datasets and directly incorporated into the HFM index calculations. However, three indicators are prepared in a different way:

  • Top universities index

The Top Universities Index indicates the number of medical schools in a country that are among the top 500 in the world. No such dataset currently exists, so the Top universities indicator is based on the QS Ranking by subject (medicine). The medical faculties among the top 500 in the world are counted and then weighted by the population of the country. For this purpose, the Population World Bank data dataset is used.

  • Covid deaths per million

The Our World in Data portal publishes (and regularly updates) an Excel file on its website that contains day-by-day covid data from the start of the pandemic, for each country in the world. Data processed in this way allows the number of deaths for a particular year to be calculated, and then (based on the Population World Bank dataset) the number of deaths from covid per million inhabitants for a particular year to be calculated.

  • Incidence measles

The measles incidence indicator is prone to significant variation for countries that experience (local) measles outbreaks. Given the way the indicators are indexed, and the final index calculated, such a deviation could significantly skew a country's results.

For this reason, this indicator is calculated as the average measles incidence over the last 5 years. This means that, for example, the 2019 figure is the average of the years 2015-2019. The result of such a calculation will be affected by a possible measles outbreak, but without unduly distorting the final index for the country in question.

Indexing indicators

Most indicators are indexed in the same way - the highest and lowest value in a given year is identified, and then the difference between the two values (the range) is calculated. An index is then calculated for each country, reflecting where the country is on the scale of values.

For indicators where higher values indicate better performance (e.g. life expectancy), a country's position on the scale (index) is calculated using the following formula:

Index = (Country value - lowest value) / Range

For indicators where higher values imply worse performance (e.g. maternal mortality in childbirth), a country's position on the scale is calculated using the following formula:

Index = 1 - (Country value - lowest value) / Range


In some cases, the nature of the indicator requires (for various reasons) a different approach to indexation. These cases are described in this section:

  • Average wage index

The auxiliary indicator Average Wage Index measures the average wage in a given country in relation to the European Union (EU) average wage. It is calculated using the following formula:

Average wage index = Country average / EU average wage

This calculation measures the "distance" between a country's average wage and the EU average wage. Unlike other indices, it can therefore exceed 1 (in cases where the country's wage is higher than the EU average). The Average Wage Index is used in the preparation of the Health expenditure per capita Index.

  • Health expenditure per capita Index

The Health expenditure per capita (HEpC) indicator is calculated on the basis of the average per capita government expenditure on health and the Average wage Index. The calculation is based on the assumption that 60% of health expenditure is used for wages. The final equation is as follows:

HEpC index = (HEpC x 0,4) + (HEpC x 0,6) / Average wage index



For most indicators, the data used come from the OECD database (subcategory Health). In some cases, however, OECD data are missing, in which case one of two scenarios occurs:

  1. Data from another source is used (e.g. Eurostat, the statistical office of the country, etc.)
  2. The given value is estimated (see Missing data section)

The HFM Index also includes some specific indicators that are compiled by institutions focusing on specific areas (e.g. Quacquarelli Symonds (QS), a UK-based company ranking the world's best universities, or the European Centre for Disease Prevention and Control (ECDC), which monitors the incidence of measles).

Data timeliness

For each version of the HFM index, t-1 data are used (e.g. the 2022 index is based on 2021 data). Where data for a given year is missing, data from the next available year backward are used. Data from the following year are used only if the following year is the first year for which data are collected.

Missing data

In some cases, it is not possible to find a source that provides the necessary data. In such cases, the values are estimated on the basis of values for other countries. In order to make the estimates as accurate as possible, the countries have been divided into two groups:

  1. Countries that joined the EU in 2004 (except Malta and Cyprus)
    • Czech Republic, Estonia, Latvia, Poland, Slovakia, Slovenia, Hungary, Lithuania
  2. EU15 countries (except Greece)
    • Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom

We assume that the states in each group have similar economic characteristics and, as a result, have less dispersion in health system performance (compared to the dispersion of all states). Thus, an estimate for a country is based on the values of the other countries in its group.

[1] The most recent data for these indicators are from the 2010-2014 period (the indicators are measured at 5-year intervals)

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