The current healthcare spending in Argentina was forecast to continuously increase between 2024 and 2029 by in total 9.2 billion U.S. dollars (+16.13 percent). After the fourth consecutive increasing year, the spending is estimated to reach 66.5 billion U.S. dollars and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. The spending refers to current spending of both governments and consumers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending in countries like Chile and Paraguay.

The current health expenditure as a share of the GDP in Argentina was forecast to continuously decrease between 2024 and 2029 by in total 0.2 percentage points. After the ninth consecutive decreasing year, the share is estimated to reach 9.32 percent and therefore a new minimum in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Paraguay and Uruguay.

The current healthcare spending per capita in Argentina was forecast to continuously increase between 2024 and 2029 by in total 178.8 U.S. dollars (+14.26 percent). According to this forecast, in 2029, the spending will have increased for the fourth consecutive year to 1,432.6 U.S. dollars. Depicted here is the average per capita spending, in a given country or region, with regards to healthcare. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending per capita in countries like Chile and Uruguay.

The number of physicians in Argentina was forecast to continuously increase between 2024 and 2029 by in total 1.5 thousand physicians (+0.86 percent). According to this forecast, in 2029, the number of physicians will have increased for the sixth consecutive year to 176.63 thousand physicians. Depicted here is the estimated number of physicians in the geographical unit at hand. Thereby physicians include medical specialists as well as general practitioners.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of physicians in countries like Paraguay and Uruguay.

The smoking prevalence in Argentina was forecast to continuously decrease between 2024 and 2029 by in total 0.4 percentage points. After the twenty-eighth consecutive decreasing year, the smoking prevalence is estimated to reach 23.11 percent and therefore a new minimum in 2029. Shown is the estimated share of the adult population (15 years or older) in a given region or country, that smoke on a daily basis. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smoking prevalence in countries like Uruguay and Paraguay.

According to this forecast, the number of hospitals will stay nearly the same over the forecast period. Depicted is the number of hospitals in the country or region at hand. As the OECD states, the rules according to which an institution can be registered as a hospital vary across countries.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospitals in countries like Chile and Uruguay.

Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.

The share of the population with overweight in Argentina was forecast to continuously increase between 2024 and 2029 by in total two percentage points. After the fifteenth consecutive increasing year, the overweight population share is estimated to reach 72.14 percent and therefore a new peak in 2029. Notably, the share of the population with overweight of was continuously increasing over the past years.Overweight is defined as a body mass index (BMI) of more than 25.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the share of the population with overweight in countries like Chile and Uruguay.

The alcohol consumption per capita in Argentina was forecast to continuously decrease between 2024 and 2029 by in total 0.04 liters (-0.5 percent). The per capita consumption is estimated to amount to 7.9 liters in 2029. Depicted is the estimated alcohol consumption in the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the alcohol consumption per capita in countries like Paraguay and Uruguay.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Improving health is central to the Millennium Development Goals, and the public sector is the main provider of health care in developing countries. To reduce inequities, many countries have emphasized primary health care, including immunization, sanitation, access to safe drinking water, and safe motherhood initiatives. Data here cover health systems, disease prevention, reproductive health, nutrition, and population dynamics. Data are from the United Nations Population Division, World Health Organization, United Nations Children's Fund, the Joint United Nations Programme on HIV/AIDS, and various other sources.

The average number of hospital beds available per 1,000 people in Argentina was forecast to continuously decrease between 2024 and 2029 by in total 0.2 beds (-6.56 percent). After the eighth consecutive decreasing year, the number of available beds per 1,000 people is estimated to reach 2.85 beds and therefore a new minimum in 2029. Depicted is the number of hospital beds per capita in the country or region at hand. As defined by World Bank this includes inpatient beds in general, specialized, public and private hospitals as well as rehabilitation centers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the average number of hospital beds available per 1,000 people in countries like Paraguay and Uruguay.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was a stratified random multi-stage sample representative of all inhabitants of Argentina aged 18 +. At the first stage of sampling, using the stratification as per geographical criteria, the country was divided into six regions. The sampling selection criteria adopted for Argentina was as follows:

a) Buenos Aires The official cartography provided by the National Census was used for the sample frame. The procedure consisted in stratifying the census ratio according to two criteria: • Geographical location; • And social class, defined by the educational level of the head of the household. Using this stratification, the census ratio was selected and within each one, a block was randomly selected.

b) Rest of the Country Within each locality selected (representing the first stage sampling unit), the census ratio (second stage unit) was ordered by social class and a sample within them was chosen using a random start. In each census ratio that was selected, the same criteria used for Buenos Aires area was applied to get to the final unit sample. (the respondent).

c) General Sampling Aspects: Over 250 different sampling points were selected on a mathematically random basis from within localities. In each sampling point, four interviews were conducted. Only one person per household was interviewed. If the person who opened the door matched the quota requirements (sex and age), this person was interviewed. If not, the correct target was looked for in the household.

Final Sample Size=1,555

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

Response rate

36%

Forecast: Risk of Catastrophic Health Expenditure Due to Surgical Care in Argentina 2024 - 2028 Discover more data with ReportLinker!

Argentina AR: Health Expenditure: Public: % of Government Expenditure data was reported at 6.917 % in 2014. This records a decrease from the previous number of 7.723 % for 2013. Argentina AR: Health Expenditure: Public: % of Government Expenditure data is updated yearly, averaging 17.022 % from Dec 1995 (Median) to 2014, with 20 observations. The data reached an all-time high of 19.429 % in 1995 and a record low of 6.917 % in 2014. Argentina AR: Health Expenditure: Public: % of Government Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Social: Health Statistics. Public health expenditure consists of recurrent and capital spending from government (central and local) budgets, external borrowings and grants (including donations from international agencies and nongovernmental organizations), and social (or compulsory) health insurance funds.; ; World Health Organization Global Health Expenditure database (see http://apps.who.int/nha/database for the most recent updates).; Weighted average;

Argentina Consumer Price Index (CPI): GBA: Medical Care & Health Preservation data was reported at 178.880 1999=100 in 2007. This records an increase from the previous number of 166.880 1999=100 for 2006. Argentina Consumer Price Index (CPI): GBA: Medical Care & Health Preservation data is updated yearly, averaging 113.380 1999=100 from Dec 1996 (Median) to 2007, with 12 observations. The data reached an all-time high of 178.880 1999=100 in 2007 and a record low of 98.115 1999=100 in 1996. Argentina Consumer Price Index (CPI): GBA: Medical Care & Health Preservation data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.I019: Consumer Price Index: Greater Buenos Aires: 1999=100: Annual.

This dataset contains data from WHO's data portal covering the following categories:

Adolescent, Ageing, Air pollution, Assistive technology, Child, Child mortality, Cross-cutting, Dementia diagnosis, treatment and care, Environment and health, Foodborne Diseases Estimates, Global Dementia Observatory (GDO), Global Health Estimates: Life expectancy and leading causes of death and disability, Global Information System on Alcohol and Health, Global Patient Safety Observatory, Global strategy, HIV, Health financing, Health systems, Health taxes, Health workforce, Hepatitis, Immunization coverage and vaccine-preventable diseases, Malaria, Maternal and newborn, Maternal and reproductive health, Mental health, Neglected tropical diseases, Noncommunicable diseases, Nutrition, Oral Health, Priority health technologies, Resources for Substance Use Disorders, Road Safety, SDG Target 3.8 | Achieve universal health coverage (UHC), Sexually Transmitted Infections, Tobacco control, Tuberculosis, Vaccine-preventable communicable diseases, Violence prevention, Water, sanitation and hygiene (WASH), World Health Statistics.

For links to individual indicator metadata, see resource descriptions.

Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Health Services data was reported at 124.000 4Q2013=100 in Sep 2014. This records an increase from the previous number of 121.990 4Q2013=100 for Aug 2014. Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Health Services data is updated monthly, averaging 112.680 4Q2013=100 from Dec 2013 (Median) to Sep 2014, with 10 observations. The data reached an all-time high of 124.000 4Q2013=100 in Sep 2014 and a record low of 100.910 4Q2013=100 in Dec 2013. Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Health Services data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.I007: Consumer Price Index: Urban: Q42013=100.

UNICEF's country profile for Argentina, including under-five mortality rates, child health, education and sanitation data.

187,237 (Thousand Pesos) in 2004.

Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Medicinal Products & Therapeutic Accessories: Medicinal Products data was reported at 124.630 4Q2013=100 in Sep 2014. This records an increase from the previous number of 123.050 4Q2013=100 for Aug 2014. Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Medicinal Products & Therapeutic Accessories: Medicinal Products data is updated monthly, averaging 122.885 4Q2013=100 from Dec 2013 (Median) to Sep 2014, with 10 observations. The data reached an all-time high of 125.920 4Q2013=100 in Jun 2014 and a record low of 101.360 4Q2013=100 in Dec 2013. Argentina Consumer Price Index (CPI): Urban: Medical Care & Health Preservation: Medicinal Products & Therapeutic Accessories: Medicinal Products data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.I007: Consumer Price Index: Urban: Q42013=100.