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Health expenditure per capita - Total

See all data and research on:
Healthcare Spending

What you should know about this indicator

The data is measured in international-$ at 2020 prices – this adjusts for inflation and for differences in the cost of living between countries.

Health expenditure per capita - Total
Health expenditure in total divided by population.
Source
OECD (2025) – with minor processing by Our World in Data
Last updated
December 11, 2025
Next expected update
December 2026
Date range
1970–2024
Unit
international-$ in 2020 prices

Related research and writing

A dark blue background with a lighter blue world map superimposed over it. Yellow text that says Financing Healthcare by Our World in Data

Healthcare Spending

Esteban Ortiz-Ospina, Pablo Arriagada, and Max Roser

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Sources and processing

This data is based on the following sources

OECD – OECD Health Expenditure and Financing Database

A System of Health Accounts 2011 provides an updated and systematic description of the financial flows related to the consumption of healthcare goods and services. As demands for information increase and more countries implement and institutionalise health accounts according to the system, the data produced are expected to be more comparable, more detailed and more policy relevant.

It builds on the original OECD Manual, published in 2000 to create a single global framework for producing health expenditure accounts that can help track resource flows from sources to uses.

It is the result of a collaborative effort between the OECD, WHO and the European Commission, and sets out in more detail the boundaries, the definitions and the concepts – responding to healthcare systems around the globe – from the simplest to the more complicated. The accounting framework is organised around a tri-axial system for the recording of healthcare expenditure, namely classifications of the functions of healthcare (ICHA-HC), healthcare provision (ICHA-HP), and financing schemes (ICHA-HF).

Retrieved on
December 11, 2025
Retrieved from
https://data-explorer.oecd.org/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD (2025), Health Expenditure and Financing Database, https://data-explorer.oecd.org/

A System of Health Accounts 2011 provides an updated and systematic description of the financial flows related to the consumption of healthcare goods and services. As demands for information increase and more countries implement and institutionalise health accounts according to the system, the data produced are expected to be more comparable, more detailed and more policy relevant.

It builds on the original OECD Manual, published in 2000 to create a single global framework for producing health expenditure accounts that can help track resource flows from sources to uses.

It is the result of a collaborative effort between the OECD, WHO and the European Commission, and sets out in more detail the boundaries, the definitions and the concepts – responding to healthcare systems around the globe – from the simplest to the more complicated. The accounting framework is organised around a tri-axial system for the recording of healthcare expenditure, namely classifications of the functions of healthcare (ICHA-HC), healthcare provision (ICHA-HP), and financing schemes (ICHA-HF).

Retrieved on
December 11, 2025
Retrieved from
https://data-explorer.oecd.org/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD (2025), Health Expenditure and Financing Database, https://data-explorer.oecd.org/

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Health expenditure per capita - Total”, part of the following publication: Esteban Ortiz-Ospina, Pablo Arriagada, and Max Roser (2017) - “Healthcare Spending”. Data adapted from OECD. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/health-expenditure-and-financing-per-capita.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

OECD (2025) – with minor processing by Our World in Data

Full citation

OECD (2025) – with minor processing by Our World in Data. “Health expenditure per capita - Total” [dataset]. OECD, “OECD Health Expenditure and Financing Database” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/health-expenditure-and-financing-per-capita.html (archived on March 4, 2026).

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/health-expenditure-and-financing-per-capita.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear