In 2022, there were over 33.7 million hospital admissions in the United States. The number of hospitals in the U.S. has decreased in recent years, although the country faces an increasing elder population. Predictably, the elderly account for the largest share of hospital admissions in the U.S.

Hospital stays

Stays in hospitals are more common among females than males, with around 7.2 percent of females reporting one or more hospital stays in the past year, compared to 4.8 percent of males. Furthermore, 16.6 percent of those aged 65 years and older had a hospitalization in the past year, compared to just 6.6 percent of those aged 18 to 44 years. The average length of a stay in a U.S. hospital is 5.7 days.

Hospital beds

In 2022, there were 916,752 hospital beds in the U.S. In the past few years, there has been a decrease in the number of hospital beds available. This is unsurprising given the decrease in the number of overall hospitals. In 2021, the occupancy rate of hospitals in the U.S. was 65 percent.

In 2022, there were around 125 hospital admissions per 1,000 population in the state of West Virginia. In comparison, Wyoming had just 65 hospital admissions per 1,000 population in the same year. This statistic shows hospital admission rates in the United States in 2022, by state.

Number of admissions to non-psychiatric/non-obstetric hospitals in Scotland.

Singapore Hospital Admissions: Total data was reported at 47,639.000 Number in Sep 2018. This records a decrease from the previous number of 49,048.000 Number for Aug 2018. Singapore Hospital Admissions: Total data is updated monthly, averaging 32,545.000 Number from Jan 1987 (Median) to Sep 2018, with 381 observations. The data reached an all-time high of 50,497.000 Number in Mar 2018 and a record low of 23,041.000 Number in Jan 1987. Singapore Hospital Admissions: Total data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G075: Health Statistics.

The number of admissions has increased year-on-year from 2000 to 2020. Due to the COVID-19 pandemic, hospital admission dropped in 2020/21. In 2023/24 there were around 17.6 million admissions* to NHS hospitals in England, showing that admission numbers have reached and exceeded pre-pandemic levels.

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.

Note: May 3,2024: Due to incomplete or missing hospital data received for the April 21,2024 through April 27, 2024 reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on May 3, 2024.

This dataset represents COVID-19 hospitalization data and metrics aggregated to county or county-equivalent, for all counties or county-equivalents (including territories) in the United States as of the initial date of reporting for each weekly metric. 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

• County-level hospital data are derived using calculations performed at the Health Service Area (HSA) level. An HSA is defined by CDC’s National Center for Health Statistics as a geographic area containing at least one county which is self-contained with respect to the population’s provision of routine hospital care. Every county in the United States is assigned to an HSA, and each HSA must contain at least one hospital. Therefore, use of HSAs in the calculation of local hospital metrics allows for more accurate characterization of the relationship between health care utilization and health status at the local level.
• Data presented at the county-level represent admissions, hosp

Directly age and sex standardised admission rate for emergency admissions for acute conditions that should not usually require hospital admission per 100,000 registered patients, 95% confidence intervals (CI). March 2022 - The coronavirus (COVID-19) pandemic began to have an impact on Hospital Episode Statistics (HES) data late in the 2019-20 financial year, which continued into the 2020-21 financial year. This means we are seeing different patterns in the submitted data, for example, fewer patients being admitted to hospital, and therefore statistics which contain data from this period should be interpreted with care. Further information is available in the annual HES publication: https://digital.nhs.uk/data-and-information/publications/statistical/hospital-admitted-patient-care-activity/2020-21/covid-19-impact As of the October 2020 release, the CCG OIS is now published on an annual basis, as a result provisional data periods will no longer be published. The annual update will be based on finalised data for the April to March reporting period each year. As of the March 2020 release, the data included in the December 2019 publication for the 2018/19, July 2018 to June 2019 (Provisional) and October 2018 to September 2019 (Provisional) data periods has been revised. This is due to a revision of a large proportion of records for East Sussex Healthcare NHS Trust (RXC) which had missing information for the condition the patient was in hospital for and other conditions the patients suffer from. The revised data for these reporting periods also differs from that originally published in December 2019 in that the HES database is routinely updated (overwritten) on a monthly basis for the year in progress. Data for the two provisional periods remain provisional, but is now more complete than it was when the December 2019 publication was released. This effect cannot be readily separated from the effect of the East Sussex Healthcare NHS Trust (RXC) resubmission which also took place after processing for the December 2019 publication. Legacy unique identifier: P01844

This dataset provides counts of Finished Admission Episodes (FAE) at MSOA level and higher geographies. The information covers the following specified diagnosis, cause and operative procedures: 1) Coronary Heart Disease; 2) Cerbrovascular Disease (including Stroke); 3) Cancer (excluding non-melanoma skin cancer); 4) Falls (basic accidental falls); 5) Coronary Artery Bypass Graft (CABG) and Percutaneous Transluminal Coronary Angioplasty (PTCA) (Heart); 6) Hip Replacement; 7) Knee Replacement; 8) Cataracts. Source: The Information Centre for health and social care (IC) Publisher: Neighbourhood Statistics Geographies: Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England Time coverage: 2004/05 to 2007/08 Type of data: Administrative data

Emergency hospital admission rates for all conditions and all ages. Data is available from Health and Social Care Information Centre Indicator Portal and Hospital episode statistics legacy website containing content from the London Health Observatory].

Indirectly age and sex standardised rates.

Data on hospital admission, average length of stay, outpatient visits, and outpatient surgery in the United States, by type of ownership and size of hospital. Data are from Health, United States. SOURCE: American Hospital Association (AHA) Annual Survey of Hospitals, Hospital Statistics. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

This dataset contains annual hospital inpatient summary data based upon the Patient’s County of Residence. The summary data includes discharge disposition, expected payer, sex, Medicare Severity-Diagnosis Related Group (MS-DRG), Major Diagnostic Categories (MDC), race group, admission source, and type of care.

Indicators in the Child and maternal health profiles have been updated. The profiles give data at a local, regional and national level to inform the development and provision of health improvement and prevention activities and acute hospital services for children and families.

This release updates indicators relating to:

• emergency admissions:
  • to hospital for children under 18 years by different age groups
  • to hospital for children aged 0 to 4 years for falls; falls from furniture; exposure to animate mechanical force; inanimate mechanical forces; and heat and hot substances – and emergency admissions for accidental poisoning; poisoning from medicines, due to inhalation of food or vomit; hot tap water scalds; and burns from food and hot fluids
  • for children and young people up to age 24 following road traffic accidents for pedestrians, cyclists, motorcyclists and car occupants
• hospital admissions:
  • for gastroenteritis and respiratory tract infections for babies and young children
  • for asthma, diabetes and epilepsy for children under 19 years by different age groups
• A&E attendance for different age groups
• subsets of road traffic accidents

After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.

The following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Sunday to Saturday). These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities.

The hospital population includes all hospitals registered with Centers for Medicare & Medicaid Services (CMS) as of June 1, 2020. It includes non-CMS hospitals that have reported since July 15, 2020. It does not include psychiatric, rehabilitation, Indian Health Service (IHS) facilities, U.S. Department of Veterans Affairs (VA) facilities, Defense Health Agency (DHA) facilities, and religious non-medical facilities.

For a given entry, the term “collection_week” signifies the start of the period that is aggregated. For example, a “collection_week” of 2020-11-15 means the average/sum/coverage of the elements captured from that given facility starting and including Sunday, November 15, 2020, and ending and including reports for Saturday, November 21, 2020.

Reported elements include an append of either “_coverage”, “_sum”, or “_avg”.

• A “_coverage” append denotes how many times the facility reported that element during that collection week.
• A “_sum” append denotes the sum of the reports provided for that facility for that element during that collection week.
• A “_avg” append is the average of the reports provided for that facility for that element during that collection week.

The file will be updated weekly. No statistical analysis is applied to impute non-response. For averages, calculations are based on the number of values collected for a given hospital in that collection week. Suppression is applied to the file for sums and averages less than four (4). In these cases, the field will be replaced with “-999,999”.

A story page was created to display both corrected and raw datasets and can be accessed at this link: https://healthdata.gov/stories/s/nhgk-5gpv

This data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020.

Sometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect.

For influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied.

For recent updates to the dataset, scroll to the bottom of the dataset description.

On May 3, 2021, the following fields have been added to this data set.

• hhs_ids
• previous_day_admission_adult_covid_confirmed_7_day_coverage
• previous_day_admission_pediatric_covid_confirmed_7_day_coverage
• previous_day_admission_adult_covid_suspected_7_day_coverage
• previous_day_admission_pediatric_covid_suspected_7_day_coverage
• previous_week_personnel_covid_vaccinated_doses_administered_7_day_sum
• total_personnel_covid_vaccinated_doses_none_7_day_sum
• total_personnel_covid_vaccinated_doses_one_7_day_sum
• total_personnel_covid_vaccinated_doses_all_7_day_sum
• previous_week_patients_covid_vaccinated_doses_one_7_day_sum
• previous_week_patients_covid_vaccinated_doses_all_7_day_sum

On May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added.

On May 13, 2021 Changed vaccination fields from sum to max or min fields. This reflects the maximum or minimum number reported for that metric in a given week.

On June 7, 2021 Changed vaccination fields from max or min fields to Wednesday reported only. This reflects that the number reported for that metric is only reported on Wednesdays in a given week.

On September 20, 2021, the following has been updated: The use of analytic dataset as a source.

On January 19, 2022, the following fields have been added to this dataset:

• inpatient_beds_used_covid_7_day_avg
• inpatient_beds_used_covid_7_day_sum
• inpatient_beds_used_covid_7_day_coverage

On April 28, 2022, the following pediatric fields have been added to this dataset:

• all_pediatric_inpatient_bed_occupied_7_day_avg
• all_pediatric_inpatient_bed_occupied_7_day_coverage
• all_pediatric_inpatient_bed_occupied_7_day_sum
• all_pediatric_inpatient_beds_7_day_avg
• all_pediatric_inpatient_beds_7_day_coverage
• all_pediatric_inpatient_beds_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_0_4_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_12_17_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_5_11_7_day_sum
• previous_day_admission_pediatric_covid_confirmed_unknown_7_day_sum
• staffed_icu_pediatric_patients_confirmed_covid_7_day_avg
• staffed_icu_pediatric_patients_confirmed_covid_7_day_coverage
• staffed_icu_pediatric_patients_confirmed_covid_7_day_sum
• staffed_pediatric_icu_bed_occupancy_7_day_avg
• staffed_pediatric_icu_bed_occupancy_7_day_coverage
• staffed_pediatric_icu_bed_occupancy_7_day_sum
• total_staffed_pediatric_icu_beds_7_day_avg
• total_staffed_pediatric_icu_beds_7_day_coverage
• total_staffed_pediatric_icu_beds_7_day_sum

On October 24, 2022, the data includes more analytical calculations in efforts to provide a cleaner dataset. For a raw version of this dataset, please follow this link: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb

Due to changes in reporting requirements, after June 19, 2023, a collection week is defined as starting on a Sunday and ending on the next Saturday.

Legacy unique identifier: P02177

BackgroundAir pollution is considered one of the risk factors for stroke prevalence in the long term and incidence in the short term. Tabriz is one of the most important industrial cities in Iran. Hence, air pollution has always been one of the main concerns in environmental health in the region.MethodThe patient data were retrieved from electronic health records of the primary tertiary hospital of the city (Imam Reza Hospital). Air pollution data was obtained from the Environmental Protection Agency and is generated by 8 sensor stations spread across the city. Average daily values were calculated for CO, NO, NO, NOx, O3, SO2, PM2.5, and PM10 from hourly measurement data. Autoregressive integrated moving average (ARIMA-X) model with 3 lag days was developed to assess the correlation.ResultsAir pollutants and hospital admission data were collected for 1821 day and includes 4865 stroke cases. our analysis showed no statistically significant association between the daily concentrations of CO (p = 0.41), NOx (p = 0.96), O3 (p = 0.65), SO2 (p = 0.91), PM2.5 (p = 0.44), and PM10 (p = 0.36). Only the binary COVID variable which was used to distinguish between COVID-19 era and other days, was significant (p value = 0.042). The goodness of fit measures, Root Mean Squared Error (RMSE), and Median Absolute Error (MAE) were 1.81 and 1.19, respectively.ConclusionIn contrast to previous reports on the subject, we did not find any pollutant significantly associated with an increased number of stroke patients.

Singapore Hospital Admissions: PS: Khoo Teck Puat Hospital data was reported at 3,650.000 Number in Sep 2018. This records a decrease from the previous number of 3,899.000 Number for Aug 2018. Singapore Hospital Admissions: PS: Khoo Teck Puat Hospital data is updated monthly, averaging 2,990.000 Number from Jun 2010 (Median) to Sep 2018, with 100 observations. The data reached an all-time high of 4,109.000 Number in Mar 2018 and a record low of 19.000 Number in Jun 2010. Singapore Hospital Admissions: PS: Khoo Teck Puat Hospital data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G075: Health Statistics.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Fillmore County, NE (DISCONTINUED) (DMPCRATE031059) from 2008 to 2015 about Fillmore County, NE; preventable; admissions; hospitals; NE; 5-year; rate; and USA.

This statistic displays the rate of mental health hospital admissions per 100,000 population worldwide as of 2020, by WHO region. There were about about 32.2 such hospital admissions per 100,000 population in the Eastern Mediterranean region that year.

In 2022, a total of approximately one million hospital admissions were recorded in Italy. This statistic breaks this figure down by macro region where the hospitals were located. According to the data, the Northern part of Italy registered the highest number of hospitalizations.

We use an event study approach to examine the economic consequences of hospital admissions for adults in two datasets: survey data from the Health and Retirement Study, and hospitalization data linked to credit reports. For non-elderly adults with health insurance, hospital admissions increase out-of-pocket medical spending, unpaid medical bills, and bankruptcy, and reduce earnings, income, access to credit, and consumer borrowing. The earnings decline is substantial compared to the out-of-pocket spending increase, and is minimally insured prior to age-eligibility for Social Security Retirement Income. Relative to the insured non-elderly, the uninsured non-elderly experience much larger increases in unpaid medical bills and bankruptcy rates following a hospital admission. Hospital admissions trigger fewer than 5 percent of all bankruptcies in our sample.