5 datasets found
  1. T

    United States Medical Doctors

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Medical Doctors [Dataset]. https://tradingeconomics.com/united-states/medical-doctors
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1993 - Dec 31, 2019
    Area covered
    United States
    Description

    Medical Doctors in the United States increased to 2.77 per 1000 people in 2019 from 2.74 per 1000 people in 2018. This dataset includes a chart with historical data for the United States Medical Doctors.

  2. Physician density in Latin America and the Caribbean 2020, by country

    • statista.com
    Updated Feb 27, 2024
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    Statista Research Department (2024). Physician density in Latin America and the Caribbean 2020, by country [Dataset]. https://www.statista.com/topics/9865/health-in-latin-america/
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    Dataset updated
    Feb 27, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Latin America, Americas
    Description

    This statistic shows a ranking of the estimated average number of physicians per 1,000 inhabitants in 2020 in Latin America, differentiated by country.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 more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

  3. u

    Data from: Data Hospital Beds, Physicians, Nurses and Expenditure for 20...

    • investiga.upo.es
    • data.niaid.nih.gov
    Updated 2023
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    Matus-Lopez, Mauricio; Fernández Pérez, paloma; Matus-Lopez, Mauricio; Fernández Pérez, paloma (2023). Data Hospital Beds, Physicians, Nurses and Expenditure for 20 Latin American Countries from 1960 to 2022 [Dataset]. https://investiga.upo.es/documentos/668fc413b9e7c03b01bd3d22?lang=en
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    Dataset updated
    2023
    Authors
    Matus-Lopez, Mauricio; Fernández Pérez, paloma; Matus-Lopez, Mauricio; Fernández Pérez, paloma
    Area covered
    Latin America, Americas
    Description

    Long-term quantitative series for 20 Latin American countries, spanning from 1960 to 2020, on the number of hospital beds, physicians, nurses and healthcare expenditure. Matus-Lopez, M. and Fernández Pérez, P. 2023. "Transformations in Latin American Healthcare: A Retrospective Analysis of Hospital Beds, Medical Doctors, and Nurses from 1960 to 2022". Journal of Evolutionary Studies in Business. The information was extracted from official reports and cross-country databases. Official reports were available in digital format in the Institutional Repository for Information Sharing (IRIS) of Pan American Health Organization (PAHO). They were summary of four-year reports on Health Conditions in the Americas (PAHO 1962, 1966, 1970, 1974, 1978, 1982, 1986, 1990, 1994, 1998, 2002a), annual reports of Basic Indicators (PAHO 2002b, 2007, 2008, 2010, 2013), Health in South America (PAHO 2012) and Core Indicators (PAHO 2016). Databases were Open Data Portal of the Pan American Health Organization (PLISA) (PAHO 2023), Core Indicator Database provided directly by PAHO (PAHO 2022), Data Portal of National Health Workforce Accounts of the World Health Organization (NHWA) (WHO 2022), and the Global Health Expenditure Database of the World Health Organization (GHED) (WHO 2023). Serie 1. Hospital Beds per 1,000 inhabitants Serie 2. Physicians per 10,000 inhabitants Serie 3. Nurses per 10,000 inhabitants Serie 4. Government spending on health, per capita. Constant US dollars of 2020 Cite as:

  4. o

    National Neighborhood Data Archive (NaNDA): Health Care Services by Census...

    • openicpsr.org
    Updated Feb 25, 2020
    + more versions
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    Anam Khan; Mao Li; Jessica Finlay; Michael Esposito; Iris Gomez-Lopez; Philippa Clarke; Megan Chenoweth (2020). National Neighborhood Data Archive (NaNDA): Health Care Services by Census Tract, United States, 2003-2017 [Dataset]. http://doi.org/10.3886/E120907V3
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    Dataset updated
    Feb 25, 2020
    Dataset provided by
    University of Michigan. Institute for Social Research
    Authors
    Anam Khan; Mao Li; Jessica Finlay; Michael Esposito; Iris Gomez-Lopez; Philippa Clarke; Megan Chenoweth
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This dataset describes the number and density of health care services in each census tract in the United States. The data includes counts, per capita densities, and area densities per tract for many types of businesses in the health care sector, including doctors, dentists, mental health providers, nursing homes, and pharmacies.

  5. A

    ‘World Bank WDI 2.12 - Health Systems’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 21, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘World Bank WDI 2.12 - Health Systems’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-bank-wdi-2-12-health-systems-6537/c001b7a7/?iid=006-754&v=presentation
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    Dataset updated
    Nov 21, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘World Bank WDI 2.12 - Health Systems’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/danevans/world-bank-wdi-212-health-systems on 21 November 2021.

    --- Dataset description provided by original source is as follows ---

    World Bank - World Development Indicators: Health Systems

    This is a digest of the information described at http://wdi.worldbank.org/table/2.12# It describes various health spending per capita by Country, as well as doctors, nurses and midwives, and specialist surgical staff per capita

    Content

    Notes, explanations, etc. 1. There are countries/regions in the World Bank data not in the Covid-19 data, and countries/regions in the Covid-19 data with no World Bank data. This is unavoidable. 2. There were political decisions made in both datasets that may cause problems. I chose to go forward with the data as presented, and did not attempt to modify the decisions made by the dataset creators (e.g., the names of countries, what is and is not a country, etc.).

    Columns are as follows: 1. Country_Region: the region as used in Kaggle Covid-19 spread data challenges. 2. Province_State: the region as used in Kaggle Covid-19 spread data challenges. 3. World_Bank_Name: the name of the country used by the World Bank 4. Health_exp_pct_GDP_2016: Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.

    1. Health_exp_public_pct_2016: Share of current health expenditures funded from domestic public sources for health. Domestic public sources include domestic revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, non-profit institutions serving households (NPISH) or enterprise financing schemes as well as compulsory prepayment and social health insurance contributions. They do not include external resources spent by governments on health.

    2. Health_exp_out_of_pocket_pct_2016: Share of out-of-pocket payments of total current health expenditures. Out-of-pocket payments are spending on health directly out-of-pocket by households.

    3. Health_exp_per_capita_USD_2016: Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.

    4. per_capita_exp_PPP_2016: Current expenditures on health per capita expressed in international dollars at purchasing power parity (PPP).

    5. External_health_exp_pct_2016: Share of current health expenditures funded from external sources. External sources compose of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country. External sources either flow through the government scheme or are channeled through non-governmental organizations or other schemes.

    6. Physicians_per_1000_2009-18: Physicians include generalist and specialist medical practitioners.

    7. Nurse_midwife_per_1000_2009-18: Nurses and midwives include professional nurses, professional midwives, auxiliary nurses, auxiliary midwives, enrolled nurses, enrolled midwives and other associated personnel, such as dental nurses and primary care nurses.

    8. Specialist_surgical_per_1000_2008-18: Specialist surgical workforce is the number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100,000 population.

    9. Completeness_of_birth_reg_2009-18: Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.

    10. Completeness_of_death_reg_2008-16: Completeness of death registration is the estimated percentage of deaths that are registered with their cause of death information in the vital registration system of a country.

    What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

    Inspiration

    Does health spending levels (public or private), or hospital staff have any effect on the rate at which Covid-19 spreads in a country? Can we use this data to predict the rate at which Cases or Fatalities will grow?

    --- Original source retains full ownership of the source dataset ---

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TRADING ECONOMICS, United States Medical Doctors [Dataset]. https://tradingeconomics.com/united-states/medical-doctors

United States Medical Doctors

United States Medical Doctors - Historical Dataset (1993-12-31/2019-12-31)

Explore at:
31 scholarly articles cite this dataset (View in Google Scholar)
json, csv, excel, xmlAvailable download formats
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 31, 1993 - Dec 31, 2019
Area covered
United States
Description

Medical Doctors in the United States increased to 2.77 per 1000 people in 2019 from 2.74 per 1000 people in 2018. This dataset includes a chart with historical data for the United States Medical Doctors.

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