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.

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.

Health professionals, especially primary care physicians, are in high demand in many parts of the U.S. Some areas are experiencing health professional shortages. This map shows the ratio of population to primary care physicians in the U.S. Areas in dark red show where there are less primary care physicians per person.The data comes from County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. The layer used in the map comes from ArcGIS Living Atlas of the World, and the full documentation for the layer can be found here.County data are suppressed if, for both years of available data, the population reported by agencies is less than 50% of the population reported in Census or less than 80% of agencies measuring crimes reported data.

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According to a survey carried out in the United States in 2023, more than ** percent of respondents said that one of the reasons why they were interested in sharing data from their personal device with healthcare providers was to take a more active role in their health. Another motivation for sharing data from a wearable device for over ************** of respondents was to improve their health outcomes.

Graph and download economic data for All Employees: Education and Health Services: Offices of Physicians in Michigan (SMU26000006562110001SA) from Jan 2001 to May 2025 about physicians, health, MI, services, employment, and USA.

This dataset comprises physician-level entries from the 1906 American Medical Directory, the first in a series of semi-annual directories of all practicing physicians published by the American Medical Association [1]. Physicians are consistently listed by city, county, and state. Most records also include details about the place and date of medical training. From 1906-1940, Directories also identified the race of black physicians [2].This dataset comprises physician entries for a subset of US states and the District of Columbia, including all of the South and several adjacent states (Alabama, Arkansas, Delaware, Florida, Georgia, Kansas, Kentucky, Louisiana, Maryland, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia). Records were extracted via manual double-entry by professional data management company [3], and place names were matched to latitude/longitude coordinates. The main source for geolocating physician entries was the US Census. Historical Census records were sourced from IPUMS National Historical Geographic Information System [4]. Additionally, a public database of historical US Post Office locations was used to match locations that could not be found using Census records [5]. Fuzzy matching algorithms were also used to match misspelled place or county names [6].The source of geocoding match is described in the “match.source” field (Type of spatial match (census_YEAR = match to NHGIS census place-county-state for given year; census_fuzzy_YEAR = matched to NHGIS place-county-state with fuzzy matching algorithm; dc = matched to centroid for Washington, DC; post_places = place-county-state matched to Blevins & Helbock's post office dataset; post_fuzzy = matched to post office dataset with fuzzy matching algorithm; post_simp = place/state matched to post office dataset; post_confimed_missing = post office dataset confirms place and county, but could not find coordinates; osm = matched using Open Street Map geocoder; hand-match = matched by research assistants reviewing web archival sources; unmatched/hand_match_missing = place coordinates could not be found). For records where place names could not be matched, but county names could, coordinates for county centroids were used. Overall, 40,964 records were matched to places (match.type=place_point) and 931 to county centroids ( match.type=county_centroid); 76 records could not be matched (match.type=NA).Most records include information about the physician’s medical training, including the year of graduation and a code linking to a school. A key to these codes is given on Directory pages 26-27, and at the beginning of each state’s section [1]. The OSM geocoder was used to assign coordinates to each school by its listed location. Straight-line distances between physicians’ place of training and practice were calculated using the sf package in R [7], and are given in the “school.dist.km” field. Additionally, the Directory identified a handful of schools that were “fraudulent” (school.fraudulent=1), and institutions set up to train black physicians (school.black=1).AMA identified black physicians in the directory with the signifier “(col.)” following the physician’s name (race.black=1). Additionally, a number of physicians attended schools identified by AMA as serving black students, but were not otherwise identified as black; thus an expanded racial identifier was generated to identify black physicians (race.black.prob=1), including physicians who attended these schools and those directly identified (race.black=1).Approximately 10% of dataset entries were audited by trained research assistants, in addition to 100% of black physician entries. These audits demonstrated a high degree of accuracy between the original Directory and extracted records. Still, given the complexity of matching across multiple archival sources, it is possible that some errors remain; any identified errors will be periodically rectified in the dataset, with a log kept of these updates.For further information about this dataset, or to report errors, please contact Dr Ben Chrisinger (Benjamin.Chrisinger@tufts.edu). Future updates to this dataset, including additional states and Directory years, will be posted here: https://dataverse.harvard.edu/dataverse/amd.References:1. American Medical Association, 1906. American Medical Directory. American Medical Association, Chicago. Retrieved from: https://catalog.hathitrust.org/Record/000543547.2. Baker, Robert B., Harriet A. Washington, Ololade Olakanmi, Todd L. Savitt, Elizabeth A. Jacobs, Eddie Hoover, and Matthew K. Wynia. "African American physicians and organized medicine, 1846-1968: origins of a racial divide." JAMA 300, no. 3 (2008): 306-313. doi:10.1001/jama.300.3.306.3. GABS Research Consult Limited Company, https://www.gabsrcl.com.4. Steven Manson, Jonathan Schroeder, David Van Riper, Tracy Kugler, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 17.0 [GNIS, TIGER/Line & Census Maps for US Places and Counties: 1900, 1910, 1920, 1930, 1940, 1950; 1910_cPHA: ds37]. Minneapolis, MN: IPUMS. 2022. http://doi.org/10.18128/D050.V17.05. Blevins, Cameron; Helbock, Richard W., 2021, "US Post Offices", https://doi.org/10.7910/DVN/NUKCNA, Harvard Dataverse, V1, UNF:6:8ROmiI5/4qA8jHrt62PpyA== [fileUNF]6. fedmatch: Fast, Flexible, and User-Friendly Record Linkage Methods. https://cran.r-project.org/web/packages/fedmatch/index.html7. sf: Simple Features for R. https://cran.r-project.org/web/packages/sf/index.html

Indonesia BioNER Dataset

This dataset taken from online health consultation platform Alodokter.com which has been annotated by two medical doctors. Data were annotated using IOB in CoNLL format. Dataset contains 2600 medical answers by doctors from 2017-2020. Two medical experts were assigned to annotate the data into two entity types: DISORDERS and ANATOMY. The topics of answers are: diarrhea, HIV-AIDS, nephrolithiasis and TBC, which marked as high-risk dataset from WHO. This… See the full description on the dataset page: https://huggingface.co/datasets/abid/indonesia-bioner-dataset.

The MedDialog dataset (English) contains conversations (in English) between doctors and patients.It has 0.26 million dialogues. The data is continuously growing and more dialogues will be added. The raw dialogues are from healthcaremagic.com and icliniq.com. All copyrights of the data belong to healthcaremagic.com and icliniq.com.

About this Dataset

Search Criteria- - Search as a guest - What type of care are you searching for? - Medical - What state do you want to search with? First we need CA, NY, NJ, PA, MA, Washington DC, and MD. Please give us this as a field so that we know which doctor is in what state - What type of plan do you want to search with? Please do Medical Networks on-Exchange, Medical (Individuals & Families), and Medical (Employer-Sponsored) - Plan/Network -ONLY ONE- Anthem Gold Advantage PPO - Need to search by COUNTIES of that States - Search by Care Provider - Behavioral Health REMARK THIS ONE- When you conduct the search I've already identified, it brings back a list of providers. Then there are additional filters at the top. From the "specialty" filter, Need to exclude these, and only include the remaining? • Applied Behavioral Analysis • Medication Assisted Treatment • Methadone • NP/Nurses • VA • Behavioral Health Facility
Fields- Plan Type, Plan Network, Name, Specialty, Full Address, State, Website, Email, Phone, Area of expertise

Category

Health & Medicine

Keywords

US Medicine,medical,doctors,California Doctors,california

Row Count

1860

Price

$30.00

Dataset Card for Prescription-based prediction

  Dataset Summary

This is the dataset used in the Roam blog post Prescription-based prediction. It is derived from a variety of US open health datasets, but the bulk of the data points come from the Medicare Part D dataset and the National Provider Identifier dataset. The prescription vector for each doctor tells a rich story about that doctor's attributes, including specialty, gender, age, and region. There are 239,930 doctors… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/prescriptionbasedprediction.

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:

Graph and download economic data for All Employees, Offices of Physicians (CES6562110001) from Jan 1972 to Jun 2025 about physicians, health, establishment survey, education, services, employment, and USA.

According to a survey carried out in the United States in 2023, willingness to share health data dropped when compared to the same survey question asked in 2020 and 2022. In 2023, ** percent of adults would share health data with a doctor or clinician, while in 2020, ** percent of respondents were willing to share health data with doctors or clinicians.

About this Dataset

Carefully curated list of “Surgeon / Doctor / Dentist” in New Jersey. We strive to keep our customers satisfied, so they no longer have to worry about finding quality leads. Which is why we offer a 100% data guarantee. If there is any information missing or incorrect we will replace it for you. Contact us immediately. What you will find below: - Contact Name - Company - Email - Contact no. & more

Category

Health & Medicine

Keywords

New Jersey Surgeon,New Jersey Doctors,New Jersey Dentist,US Surgeons,US Doctor

Row Count

1662

Price

$299.00

About this Dataset

Carefully curated list of “Surgeon / Doctor / Dentist” in USA. We strive to keep our customers satisfied, so they no longer have to worry about finding quality leads. Which is why we offer a 100% data guarantee. If there is any information missing or incorrect we will replace it for you. Contact us immediately. What you will find below: - Contact Name - Company - Email - Contact no. & more

Category

Health & Medicine

Keywords

USA Surgeon,USA Doctors,US Surgeons,US Doctors,US Dentist

Row Count

8768

Price

$4999.00

1. Overview This dataset is a collection of multimodal high quality image sets of medical data that are ready to use for optimizing the accuracy of computer vision models. All of the contents are sourced from Pixta AI's partner network with high quality & full data compliance.

2. Data subject The datasets consist of various models

3. X-ray datasets

4. CT datasets

5. MRI datasets

6. Mammography datasets

7. Segmentation datasets

8. Classification datasets

9. Regression datasets

10. Use case The dataset could be used for various Healthcare & Medical models:

11. Medical Image Analysis

12. Remote Diagnosis

13. Medical Record Keeping ... Each data set is supported by both AI and expert doctors review process to ensure labelling consistency and accuracy. Contact us for more custom datasets.

14. About PIXTA PIXTASTOCK is the largest Asian-featured stock platform providing data, contents, tools and services since 2005. PIXTA experiences 15 years of integrating advanced AI technology in managing, curating, processing over 100M visual materials and serving global leading brands for their creative and data demands. Visit us at https://www.pixta.ai/ or contact via our email admin.bi@pixta.co.jp.

About 33 percent of U.S. physicians spent 17-24 minutes with their patients, according to a survey conducted in 2018. Physicians are often constrained in their time directly working with patients, which could have an impact on patient care outcomes. Studies found out that physicians spend almost half of their time in office on data entry and other desk work. More sophisticated, network-enabled EHR (electronic health records) systems for physicians could probably be a step towards more time directly with patients.

U.S. physicians

Physicians work in a variety of fields and across direct patient care and research. Within the last 50 years, the total number of active physicians has increased dramatically throughout the United States. Among all U.S. states, including the District of Columbia, the District of Columbia had the highest rate of all U.S. states of active physicians.

Physician time

In a recent study, physicians were asked about the time they spend with their patients. According to the results, a majority of physicians said that they felt their time with patients was limited. In 2018, most physicians saw 11-20 patients per day. Some reports have estimated that for every hour of direct patient contact, physicians spend an additional 2 hours working on reporting and desk work. Recent physician surveys have also indicated that one of the primary reasons for physician burn-out is having too many bureaucratic tasks.

Medical doctors (%)

  Dataset Description

This dataset provides information on 'Medical doctors' for countries in the WHO African Region. The data is disaggregated by the 'Sex' dimension, allowing for analysis of health inequalities across different population subgroups. Units: %

  Dimensions and Subgroups

Dimension: Sex Available Subgroups: Female, Male

  Data Structure

The dataset is in a wide format.

Index: Year (formatted as YYYY-01-01) Columns:… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/medical-doctorsby-sex-for-african-countries.

At a glance - NHANES is the National Health and Nutrition Examination Survey. - NHANES is a national survey that measures the health and nutrition of adults and children in the United States. The National Health and Nutrition Examination Survey (NHANES) collects data about the health of adults and children in the United States. We also collect data about what participants eat, drink, and take as supplements to determine how many nutrients are in their diet. These dietary interviews and blood tests help us measure the nutritional status of U.S. adults and children. CDC's National Center for Health Statistics (NCHS) conducts NHANES. NHANES is the only national health survey that includes health exams, laboratory tests, and dietary interviews for participants of all ages. NHANES data can help improve the health of Americans. Survey data have driven changes in how doctors treat patients and how public policy supports good health. The NHANES program began in the early 1960s. It started as a series of surveys that focused on different population groups and health topics. Since 1999, NCHS has conducted NHANES without interruption—what we call continuous NHANES. Now, NHANES can focus on different health and nutrition measurements to meet changing information needs. Each year, about 5,000 adults and children in communities across the United States participate in NHANES. We use a random, scientific process to select the people we invite to participate. This process ensures that this group of people can accurately represent the health and nutritional status of everyone in our diverse nation. To collect data about a wide range of health and nutrition topics, NHANES includes— - Interviews about health, diet, and personal, social, and economic characteristics - Visits to our mobile exam center for dental exams and health and body measurements - Laboratory tests by highly trained medical professionals (Text above quoted from https://www.cdc.gov/nchs/nhanes/about/ on 2025-03-23)