The Medicare Physician & Other Practitioners by Provider dataset provides information on use, payments, submitted charges and beneficiary demographic and health characteristics organized by National Provider Identifier (NPI). Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.
ONC uses the SK&A Office-based Provider Database to calculate the counts of medical doctors, doctors of osteopathy, nurse practitioners, and physician assistants at the state and count level from 2011 through 2013. These counts are grouped as a total, as well as segmented by each provider type and separately as counts of primary care providers.
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The Physician and Physician Practice Research Database (3P-RD) captures characteristics of physicians and physician practices in 13 states. The database describes the supply of physician services available across selected states for data year 2019-2020.
The Medicare Physician & Other Practitioners by Provider and Service dataset provides information on use, payments, and submitted charges organized by National Provider Identifier (NPI), Healthcare Common Procedure Coding System (HCPCS) code, and place of service. Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.
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Physicians (per 1,000 people) in United States was reported at 3.608 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
This data package contains the Physician Quality Reporting System (PQRS), Performance Rates for Individual Eligible Professionals (EP) PQRS, Consumer Assessment of Healthcare Providers and Systems (CAHPS) and Group Practice.
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Electronic health records (EHRs) are a rich source of information for medical research and public health monitoring. Information systems based on EHR data could also assist in patient care and hospital management. However, much of the data in EHRs is in the form of unstructured text, which is difficult to process for analysis. Natural language processing (NLP), a form of artificial intelligence, has the potential to enable automatic extraction of information from EHRs and several NLP tools adapted to the style of clinical writing have been developed for English and other major languages. In contrast, the development of NLP tools for less widely spoken languages such as Swedish has lagged behind. A major bottleneck in the development of NLP tools is the restricted access to EHRs due to legitimate patient privacy concerns. To overcome this issue we have generated a citizen science platform for collecting artificial Swedish EHRs with the help of Swedish physicians and medical students. These artificial EHRs describe imagined but plausible emergency care patients in a style that closely resembles EHRs used in emergency departments in Sweden. In the pilot phase, we collected a first batch of 50 artificial EHRs, which has passed review by an experienced Swedish emergency care physician. We make this dataset publicly available as OpenChart-SE corpus (version 1) under an open-source license for the NLP research community. The project is now open for general participation and Swedish physicians and medical students are invited to submit EHRs on the project website (https://github.com/Aitslab/openchart-se), where additional batches of quality-controlled EHRs will be released periodically.
Dataset content
OpenChart-SE, version 1 corpus (txt files and and dataset.csv)
The OpenChart-SE corpus, version 1, contains 50 artificial EHRs (note that the numbering starts with 5 as 1-4 were test cases that were not suitable for publication). The EHRs are available in two formats, structured as a .csv file and as separate textfiles for annotation. Note that flaws in the data were not cleaned up so that it simulates what could be encountered when working with data from different EHR systems. All charts have been checked for medical validity by a resident in Emergency Medicine at a Swedish hospital before publication.
Codebook.xlsx
The codebook contain information about each variable used. It is in XLSForm-format, which can be re-used in several different applications for data collection.
suppl_data_1_openchart-se_form.pdf
OpenChart-SE mock emergency care EHR form.
suppl_data_3_openchart-se_dataexploration.ipynb
This jupyter notebook contains the code and results from the analysis of the OpenChart-SE corpus.
More details about the project and information on the upcoming preprint accompanying the dataset can be found on the project website (https://github.com/Aitslab/openchart-se).
Comprehensive dataset of 5,999 Occupational medical physicians in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.
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Turkmenistan TM: Physicians: per 1000 People data was reported at 2.291 Ratio in 2014. This records an increase from the previous number of 2.266 Ratio for 2013. Turkmenistan TM: Physicians: per 1000 People data is updated yearly, averaging 3.263 Ratio from Dec 1980 (Median) to 2014, with 22 observations. The data reached an all-time high of 4.355 Ratio in 2002 and a record low of 2.266 Ratio in 2013. Turkmenistan TM: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkmenistan – Table TM.World Bank: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;
Comprehensive dataset of 142 Occupational medical physicians in Wisconsin, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.
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Croatia HR: Physicians: per 1000 People data was reported at 3.610 Ratio in 2021. This records a decrease from the previous number of 6.959 Ratio for 2020. Croatia HR: Physicians: per 1000 People data is updated yearly, averaging 2.425 Ratio from Dec 1980 (Median) to 2021, with 37 observations. The data reached an all-time high of 6.959 Ratio in 2020 and a record low of 1.673 Ratio in 1980. Croatia HR: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Croatia – Table HR.World Bank.WDI: Social: Health Statistics. Physicians include generalist and specialist medical practitioners.;World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.;Weighted average;This is the Sustainable Development Goal indicator 3.c.1 [https://unstats.un.org/sdgs/metadata/].
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affordable
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Physicians (per 1,000 people) in Mexico was reported at 2.559 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mexico - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
Comprehensive dataset of 15 Men's health physicians in Connecticut, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.
Healthcare Provider/Professional Data contains the data of individual providers and facilities, including their information about opening hours, insurance networks, specialties, NPI, etcetera. In addition to discovering data sources, merging data, running analytics, and receiving decision-making guidance, the bigger problem is responding to marketplace business and patient care demands in a timely manner. Pharmacy contains the location details of pharmacies and has attributes such as addresses, opening hours, facilities, etcetera.
A. Usecase/Applications possible with the data:
a. Provider network data systems (PNDS) - The primary goal of the PNDS is to collect data needed to evaluate provider networks, which include physicians, hospitals, labs, home health agencies, durable medical equipment providers, and so on, for all types of Health Insurers. Such information can be used to:
b. Find health care providers in my network - Use this directory to easily find other providers in my network.
c. Comprehensive services assessment - Determine whether insurers have contracted with a sufficient number of primary care practitioners, clinical specialists, and service facilities (hospitals, labs, etc.) within the insurer's service area.
d. Capacity analysis - Calculate the potential capacity of a managed care plan’s primary care providers.
e. Locate pharmacies in your local areas.
f. Support Employee Benefits Decisions - Having access to network data can help you make better decisions about which providers to use for Employee Medical Benefits.
g. Know about the facilities available across different pharmacies.
How does it work?
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Samoa WS: Physicians: per 1000 People data was reported at 0.344 Ratio in 2010. This records a decrease from the previous number of 0.463 Ratio for 2008. Samoa WS: Physicians: per 1000 People data is updated yearly, averaging 0.347 Ratio from Dec 1960 (Median) to 2010, with 14 observations. The data reached an all-time high of 0.691 Ratio in 1999 and a record low of 0.207 Ratio in 1989. Samoa WS: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Samoa – Table WS.World Bank.WDI: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;
This data package shows the Physician and Other Healthcare Information like Business Wire Healthcare Press Release Distribution List, Health Professional Shortage Area Mental and Dental Health, Physician Evaluation and Management Medicare Service Events and Physicians Malpractice Payments.
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Tanzania TZ: Physicians: per 1000 People data was reported at 0.022 Ratio in 2014. This records a decrease from the previous number of 0.030 Ratio for 2012. Tanzania TZ: Physicians: per 1000 People data is updated yearly, averaging 0.040 Ratio from Dec 1960 (Median) to 2014, with 14 observations. The data reached an all-time high of 0.055 Ratio in 1960 and a record low of 0.008 Ratio in 2010. Tanzania TZ: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;
Comprehensive dataset of 18 Occupational medical physicians in New Hampshire, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.
The Medicare Physician & Other Practitioners by Provider dataset provides information on use, payments, submitted charges and beneficiary demographic and health characteristics organized by National Provider Identifier (NPI). Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.