Data on visits to physician offices, hospital outpatient departments and hospital emergency departments by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. Note that the data file available here has more recent years of data than what is shown in the PDF or Excel version. Data for 2017 physician office visits are not available.

SOURCE: NCHS, National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. For more information on the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey, see the corresponding Appendix entries at https://www.cdc.gov/nchs/data/hus/hus17_appendix.pdf.

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).

Visits to physician offices, hospital outpatient departments, and hospital emergency departments, by age, sex, and race: United States

  Description

Data on visits to physician offices, hospital outpatient departments and hospital emergency departments by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/visits-to-physician-offices-hospital-outpatient-de.

This dataset presents statistics on the healthcare workforce in the State of Qatar for the year 2024. It categorizes health professionals by type (physicians, dentists, nurses) and sector (government and private), and provides metrics such as rate per 1,000 population, total number of professionals, and population per professional.These statistics are vital for assessing the availability, distribution, and adequacy of human resources in the healthcare sector. They support health system planning, workforce allocation, and policy development to ensure equitable access to medical services.

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

Analysis of ‘MSSA Detail 2010c1 public’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b0ad8a2d-468b-47bf-8c4e-270779b1d841 on 12 February 2022.

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

Medical Service Study Areas - Census Detail, 2010

Medical Service Study Areas (MSSAs) are sub-city and sub-county geographical units used to organize and display population, demographic and physician data. MSSAs were developed in 1976 by the California Healthcare Workforce Policy Commission (formerly California Health Manpower Policy Commission) to respond to legislative mandates requiring it to determine "areas of unmet priority need for primary care family physicians" (Song-Brown Act of 1973) and "geographical rural areas where unmet priority need for medical services exist" (Garamendi Rural Health Services Act of 1976).

MSSAs are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions' Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas (HPSAs), and Medically Underserved Areas and Medically Underserved Populations (MUAs/MUPs).

The MSSAs incorporate the U.S. Census total population, socioeconomic and demographic data and are updated with each decadal census. Office of Statewide Health Planning and Development provides updated data for each County's MSSAs to the County and Communities, and will schedule meetings for areas of significant population change. Community meetings will be scheduled throughout the State as needed.

Adopted by the California Healthcare Workforce Policy Commission on May 15, 2002.

Each MSSA is composed of one or more complete census tracts. MSSAs will not cross county lines. All population centers within the MSSA are within 30 minutes travel time to the largest population center.

Urban MSSA - Population range 75,000 to 125,000. Reflect recognized community and neighborhood boundaries. Similar demographic and socio-economic characteristics.

Rural MSSA - Population density of less than 250 persons per square mile. No population center exceeds 50,000.

Frontier MSSA - Population density of less than 11 persons per square mile.

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

This dataset merges 1972 data on social and military expenditures in 132 nations selected from WORLD MILITARY AND SOCIAL EXPENDITURES, 1974 (see Data Source) with information on demographic attributes of the same nations in 1972 obtained from WORLD POPULATION, 1973 (ICPSR 5032), collected by the United States Bureau of the Census. Military expenditures as well as international peacekeeping, public education, public health, and foreign economic aid expenditures are presented as both raw and per capita measures. Other information includes number of teachers, school age population per teacher, illiteracy rates, number of qualified physicians, population per physician, infant mortality rates, and population per soldier.

Abstract

Nigeria has one of the largest stocks of human resources for health (HRH) in Africa. However, great disparities in health status and access to health care exist among the six geo-political zones, and between rural and urban areas. This assessment measures the size, skills mix, distribution, and growth rate of HRH in the public health sector in Nigeria. The assessment also quantifies the increase in HRH requirements in the public health sector necessary for reaching key PEPFAR targets and the health Millennium Development Goals. The findings are based on a survey conducted in April-May 2006 in 290 public health facilities representing all levels of care (primary, secondary, and tertiary). The study data enabled us to estimate the total number of doctors, nurses, midwives, lab and pharmacy staff, and community health workers currently employed in the public sector. The distribution of health workers by level of care, and HRH availability in rural and urban areas was also quantified.Staff attrition rates, measuring the number of those leaving the public sector as percent of total staff, were determined among all staff categories. The annual growth in HRH in the public sector from new graduates was also measured.

Geographic coverage

National

Analysis unit

Public Health Facilities

Universe

The survey focused on public health facilities representing all levels of care (primary, secondary, and tertiary).

Kind of data

Sample survey data [ssd]

Sampling procedure

Two-Stage Stratified Random Sample A survey was conducted in 290 public health facilities representing all levels of care (primary, secondary, and tertiary). The facilities were selected using two-stage stratified sampling. First, two states were selected from each of the six geo-political zones in Nigeria, with probability of selection of each state proportional to its population size. In addition, the Federal Capital Territory of Abuja (FCT) was added to the two states selected in the North Central zone. The selected states in each zone cover between 32 and 50 percent of the zone's population and in total, the 13 states included in the sample account for 40 percent of Nigeria's population. In the second stage of sampling, a sample of facilities at each level of care was chosen in each selected state. All Federal Medical Centers and teaching hospitals in the sampled states were selected with certainty. All other facilities were selected using systematic random sampling. A higher proportion of hospitals, compared to smaller facilities, were included in the sample in order to increase the number of facilities that have most of the data being collected. Primary care facilities include health centers, health clinics, maternities, and dispensaries. There was non-response from two facilities selected with certainty.

Mode of data collection

Face-to-face [f2f]

Research instrument

Data collection instrument In each of the selected facilities, a questionnaire was administered to eligible facility managers and health staff. These were staff in charge of the services included in the survey – for example, information regarding immunizations in a hospital was obtained from the nurse in charge at the hospital’s child health clinic. The questionnaire collected information on: 1. Number of staff employed in 2004, 2005, and at the time of survey (April 2006); 2. Number of incoming and outgoing staff in 2005 by reason for leaving or starting work at the facility; 3. Types of services provided at the facility for HIV/AIDS, TB, malaria, maternal and child health, and family planning; 4. Number of patients seen at the facility in the three months preceding the survey for each of these services; 5. Which types of health staff provide each service; 6. Average time spent per patient-visit for each of the services related to the five focus areas.

Cleaning operations

Data from the survey questionnaires was entered electronically using an EpiInfo database, and all data analysis was performed using Stata v.8 software.