In 2009, there were nearly 19 million federally funded community health center patients, whereas by 2022, there were 30.5 million patients in the United States. This statistic depicts the total number of health center patients in the U.S. from 2009 to 2022.

In 2010, there were 77 million federally funded community health center patient visits, whereas by 2022, there were 127 million such patient visits in the United States. This includes roughly 105.9 million clinic visits and 21 million virtual visits. This statistic depicts the total number of health center patient visits in the U.S. from 2010 to 2022.

Germany Number of Patients data was reported at 17,202,131.000 Person in 2023. This records an increase from the previous number of 16,802,693.000 Person for 2022. Germany Number of Patients data is updated yearly, averaging 17,202,131.000 Person from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 19,532,779.000 Person in 2016 and a record low of 14,576,613.000 Person in 1991. Germany Number of Patients data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.G057: Health Care Statistics.

This table shows the total number of patients in each of the Department of Veterans Affairs� healthcare enrollment priority group categories.

GPA04 - Number of Patients. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Number of Patients...

The dataset contains data on first aid activities from 2007 to 2013 collected in the health facilities of the municipality of Milan divided into hospitals, scientific institutes and accredited nursing homes. The data concern the number of hospitalizations/non-hospitalisations, deaths and the total number of services provided. NOTE: in 2010 the Maggiore Policlinico Foundation took on the current name of the IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation. In 2008 the Casa di Cura S. Rita took on the name of Istituto Clinico Città Studi. The path to use to find the original dataset on sisi.comune.milano.it is: sisi.comune.milano.it - ​​Services - Healthcare - Hospitals, Scientific Institutes and Nursing Homes - Emergency Room

Number of Veteran Patients by Healthcare Priority Group: FY2000 to FY2018

This dataset provides the number of patients treated by paramedics in the government health sector in the State of Qatar, categorized by nationality: Qatari, Non-Qatari, and Unknown. It allows for an analysis of how emergency medical services are utilized by residents and non-residents, contributing to healthcare planning and policy formulation related to national health needs.

This dataset presents the number of patients treated by paramedics in the government health sector in the State of Qatar, disaggregated by gender: male, female, and unknown. The data supports analysis of gender-based utilization of emergency medical services and contributes to planning and policy-making in healthcare delivery.

This dataset shows the annual number of patients attended by paramedics in the government health sector in the State of Qatar. The data is categorized by age group: children (0–14), adults (15+), and cases with unknown age. This dataset provides insights into demand for emergency medical services across different age demographics, supporting strategic planning and resource allocation in pre-hospital care.

This group expresses the numbers of hepatitis patients in the Kingdom distributed by governorate, age group and gender for the 2016/2017 year

This group expresses the numbers of suspected mumps patients by governorate, age group and gender for the 2016/2017-2018 year

In 2024, the number of foreign patients in Thailand was estimated to reach 3.07 million. Thailand is one of the leading medical tourism hubs in Southeast Asia, offering various medical treatments with top-quality medical care at more affordable prices compared to developed countries.

Number of patients served overall and by service type. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0256908

Number of Patients: Probable: Indonesia data was reported at 2.000 Person in 07 Aug 2003. This stayed constant from the previous number of 2.000 Person for 31 Jul 2003. Number of Patients: Probable: Indonesia data is updated daily, averaging 2.000 Person from Apr 2003 (Median) to 07 Aug 2003, with 74 observations. The data reached an all-time high of 2.000 Person in 07 Aug 2003 and a record low of 1.000 Person in 29 Apr 2003. Number of Patients: Probable: Indonesia data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D001: World Health Orgainzation: No of SARS Patients.

United States Number of Patients: Oregon data was reported at 2.000 Person in 15 Jul 2003. This stayed constant from the previous number of 2.000 Person for 07 Jul 2003. United States Number of Patients: Oregon data is updated daily, averaging 1.000 Person from Apr 2003 (Median) to 15 Jul 2003, with 45 observations. The data reached an all-time high of 2.000 Person in 15 Jul 2003 and a record low of 1.000 Person in 10 Jun 2003. United States Number of Patients: Oregon data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under High Frequency Database’s Disease Outbreaks – Table US.D001: Centers for Disease Control and Prevention: No of SARS Patients.

United States Number of Patients: Probable: Massachusetts data was reported at 2.000 Person in 15 Jul 2003. This stayed constant from the previous number of 2.000 Person for 07 Jul 2003. United States Number of Patients: Probable: Massachusetts data is updated daily, averaging 2.000 Person from Apr 2003 (Median) to 15 Jul 2003, with 45 observations. The data reached an all-time high of 3.000 Person in 05 May 2003 and a record low of 1.000 Person in 28 Apr 2003. United States Number of Patients: Probable: Massachusetts data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under High Frequency Database’s Disease Outbreaks – Table US.D001: Centers for Disease Control and Prevention: No of SARS Patients.

Department of State Hospitals (DSH)-wide Violence Data Annual Rates of Assault from 2010-2020 for the following groups: Patient Assault (A2), Staff Assault (A4). A2 - Patient physical assaults are committed by another patient. Formally defined as “Aggressive Act to Another Patient - Physical: Hitting, pushing, kicking or similar acts directed against another individual to cause potential or actual injury.” This does not include verbal assault, which is coded as “A1.” A4 – Staff physical assaults are committed by a patient. Formally defined as “Aggressive Act to Staff - Physical: Hitting, pushing, kicking, or similar acts directed against a staff person that could cause potential or actual injury.” This does not include verbal assault, which is coded as “A3.” Please Note: 1.Please note that it is an update to the previously published dataset with additional datasets. 2.Violence Rates value (in previous publication) can be calculated as a number per 1000 Patient Days. This number is easily interpreted and enables more accurate comparisons across time. 3.Prior to January 1, 2016 DSH-Atascadero coded an assault as Patient on Staff (A4) only when physical contact was made between patient and staff. All other Department of State Hospitals (DSH)- facilities code an assault as Patient on Staff (A4) either when physical contact was made or when physical contact was attempted. On January 1, 2016 Department of State Hospitals (DSH)--Atascadero began coding assaults in the same manner as all other Department of State Hospitals (DSH)- facilities. 4.Prior to January 1, 2016 Violence incidents were not captured specifically as Physical Contact made or Physical Contact Attempted.

Number of Registered Patients Covid-19

Note: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, hospital capacity, or occupancy data to HHS through CDC’s National Healthcare Safety Network (NHSN). The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.

This dataset represents weekly COVID-19 hospitalization data and metrics aggregated to national, state/territory, and regional levels. COVID-19 hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to COVID-19 hospital admissions, and inpatient and ICU bed capacity occupancy.

Reporting information:

• As of December 15, 2022, COVID-19 hospital data are required to be reported to NHSN, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN represent aggregated counts and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and admissions. Prior to December 15, 2022, hospitals reported data directly to the U.S. Department of Health and Human Services (HHS) or via a state submission for collection in the HHS Unified Hospital Data Surveillance System (UHDSS).
• While CDC reviews these data for errors and corrects those found, some reporting errors might still exist within the data. To minimize errors and inconsistencies in data reported, CDC removes outliers before calculating the metrics. CDC and partners work with reporters to correct these errors and update the data in subsequent weeks.
• Many hospital subtypes, including acute care and critical access hospitals, as well as Veterans Administration, Defense Health Agency, and Indian Health Service hospitals, are included in the metric calculations provided in this report. Psychiatric, rehabilitation, and religious non-medical hospital types are excluded from calculations.
• Data are aggregated and displayed for hospitals with the same Centers for Medicare and Medicaid Services (CMS) Certification Number (CCN), which are assigned by CMS to counties based on the CMS Provider of Services files.
• Full details on COVID-19 hospital data reporting guidance can be found here: https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf

Metric details:

• Time Period: timeseries data will update weekly on Mondays as soon as they are reviewed and verified, usually before 8 pm ET. Updates will occur the following day when reporting coincides with a federal holiday. Note: Weekly updates might be delayed due to delays in reporting. All data are provisional. Because these provisional counts are subject to change, including updates to data reported previously, adjustments can occur. Data may be updated since original publication due to delays in reporting (to account for data received after a given Thursday publication) or data quality corrections.
• New COVID-19 Hospital Admissions (count): Number of new admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction.
• New COVID-19 Hospital Admissions (7-Day Average): 7-day average of new admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction.
• Cumulative COVID-19 Hospital Admissions: Cumulative total number of admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction since August 1, 2020.
• Cumulative COVID-19 Hospital Admissions Rate: Cumulative total number of admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction since August 1, 2020 divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000.
• New COVID-19 Hospital Admissions Rate (7-day average) percent change from prior week: Percent change in the 7-day average new admissions of patients with laboratory-confirmed COVID-19 per 100,000 population compared with the prior week.
• New COVID-19 Hospital Admissions (7-Day Total): 7-day total number of new admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction.
• New COVID-19 Hospital Admissions Rate (7-Day Total): 7-day total number of new admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) for the entire jurisdiction divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000.
• Total Hospitalized COVID-19 Patients: 7-day total number of patients currently hospitalized with laboratory-confirmed COVID-19 (including both adult and pediatric patients) for the entire jurisdiction.
• Total Hospitalized COVID-19 Patients (7-Day Average): 7-day average of the number of patients currently hospitalized with laboratory-confirmed COVID-19 (including both adult and pediatric patients) for the entire jurisdiction.
• COVID-19 Inpatient Bed Occupancy (7-Day Average): Percentage of all staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 (including both adult and pediatric patients) within the entire jurisdiction is calculated as an average of valid daily values within the past 7 days (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (patients hospitalized with confirmed COVID-19) and denominators (staffed inpatient beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 Inpatient Bed Occupancy absolute change from prior week: The absolute change in the percent of staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the 7-day average occupancy of patients with confirmed COVID-19 in staffed inpatient beds in the past 7 days, compared with the prior week, in the entire jurisdiction.
• COVID-19 ICU Bed Occupancy (7-Day Average): Percentage of all staffed inpatient beds occupied by adult patients with confirmed COVID-19 within the entire jurisdiction is calculated as a 7-day average of valid daily values within the past 7 days (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (adult patients hospitalized with confirmed COVID-19) and denominators (staffed adult ICU beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 ICU Bed Occupancy absolute change from prior week: The absolute change in the percent of staffed ICU beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the average occupancy of patients with confirmed COVID-19 in staffed adult ICU beds for the past 7 days, compared with the prior week, in the in the entire jurisdiction.

Note: October 27, 2023: Due to a data processing error, reported values for avg_percent_inpatient_beds_occupied_covid_confirmed will appear lower than previously reported values by an average difference of less than 1%. Therefore, previously reported values for avg_percent_inpatient_beds_occupied_covid_confirmed may have been overestimated and should be interpreted with caution.

October 27, 2023: Due to a data processing error, reported values for abs_chg_avg_percent_inpatient_beds_occupied_covid_confirmed will differ from previously reported values by an average absolute difference of less than 1%. Therefore, previously reported values for abs_chg_avg_percent_inpatient_beds_occupied_covid_confirmed should be interpreted with caution.

December 29, 2023: Hospitalization data reported to CDC’s National Healthcare Safety Network (NHSN) through December 23, 2023, should be interpreted with caution due to potential reporting delays that are impacted by Christmas and New Years holidays. As a result, metrics including new hospital admissions for COVID-19 and influenza and hospital occupancy may be underestimated for the week ending December 23, 2023.

January 5, 2024: Hospitalization data reported to CDC’s National Healthcare Safety Network (NHSN) through December 30, 2023 should be interpreted with caution due to potential reporting delays that are impacted by Christmas and New Years holidays. As a result, metrics including new hospital admissions for COVID-19 and influenza and hospital occupancy may be underestimated for the week ending December 30, 2023.