In 2023, there were over 34.4 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.

As of 9/12/2024, we have resumed reporting on COVID-19 hospitalization data using a San Francisco specific dataset. These new data differ slightly from previous hospitalization data sources but the overall patterns and trends in hospitalizations remain consistent. You can access the previous data here.

A. SUMMARY This dataset includes information on COVID+ hospital admissions for San Francisco residents into San Francisco hospitals. Specifically, the dataset includes the count and rate of COVID+ hospital admissions per 100,000. The data are reported by week.

B. HOW THE DATASET IS CREATED Hospital admission data is reported to the San Francisco Department of Public Health (SFDPH) via the COVID Hospital Data Repository (CHDR), a system created via health officer order C19-16. The data includes all San Francisco hospitals except for the San Francisco VA Medical Center.

San Francisco population estimates are pulled from a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

C. UPDATE PROCESS Data updates weekly on Wednesday with data for the past Wednesday-Tuesday (one week lag). Data may change as more current information becomes available.

D. HOW TO USE THIS DATASET New admissions are the count of COVID+ hospital admissions among San Francisco residents to San Francisco hospitals by week.

The admission rate per 100,000 is calculated by multiplying the count of admissions each week by 100,000 and dividing by the population estimate.

E. CHANGE LOG

In 2023, there were around *** hospital admissions per 1,000 population in the state of West Virginia. In comparison, Alaska had just ** hospital admissions per 1,000 population in the same year. Hospital admission rates in the United States have been decreasing in the last decades before dropping at the start of the pandemic.

This dataset details the percentage of COVID-19 positive patients in hospitals and ICUs for COVID-19 related reasons, and for reasons other than COVID-19. Data includes: * reporting date * percentage of COVID-19 positive patients in hospital admitted for COVID-19 * percentage of COVID-19 positive patients in hospital admitted for other reasons * percentage of COVID-19 positive patients in ICU admitted for COVID-19 * percentage of COVID-19 positive patients in ICU admitted for other reasons **Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool ** Due to incomplete weekend and holiday reporting, data for hospital and ICU admissions are not updated on Sundays, Mondays and the day after holidays. This dataset is subject to change.

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.

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 labo

In 2023, there were around ** hospital admissions per 1,000 population in the United States in 2023. Hospital admission rates have generally declined since 1999, where *** admissions per 1,000 population were recorded. Hospital admission rates further dropped during the pandemic and still show no signs of returning to pre-pandemic levels.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Orange County, NY (DISCONTINUED) (DMPCRATE036071) from 2008 to 2015 about Orange County, NY; Poughkeepsie; preventable; admissions; hospitals; NY; 5-year; rate; and USA.

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 publication reports on Admitted Patient Care activity in England for the financial year 2022-23. This report includes but is not limited to analysis of hospital episodes by patient demographics, diagnoses, external causes/injuries, operations, bed days, admission method, time waited, specialty, provider level analysis and Adult Critical Care (ACC). It describes NHS Admitted Patient Care Activity, Adult Critical Care activity and performance in hospitals in England. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care and may also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. The data sources for this publication are Hospital Episode Statistics (HES). It contains final data and replaces the provisional data that are released each month. HES contains records of all admissions, appointments and attendances for patients at NHS hospitals in England. The HES data used in this publication are called 'Finished Consultant Episodes', and each episode relates to a period of care for a patient under a single consultant at a single hospital. Therefore, this report counts the number of episodes of care for admitted patients rather than the number of patients. This publication shows the number of episodes during the period, with breakdowns including by patient's age, gender, diagnosis, procedure involved and by provider. Please send queries or feedback via email to enquiries@nhsdigital.nhs.uk. Author: Secondary Care Open Data and Publications, NHS England. Lead Analyst: Emily Michelmore

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Allen County, OH (DISCONTINUED) (DMPCRATE039003) from 2008 to 2015 about Allen County, OH; Lima; preventable; admissions; hospitals; OH; 5-year; rate; and USA.

In 2024, there were approximately 13.2 million hospital admissions in Brazil. The highest number of hospitalizations was due to pregnancy, childbirth, and puerperium, amounting to over two million. Meanwhile, there were more than 1.4 million hospital admissions related to injuries, poisonings and other consequences of external causes. The year prior, circulatory system diseases were the leading cause of death in the country.

Legacy unique identifier: P02177

Analysis of ‘Hospital Admissions Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ashishsahani/hospital-admissions-data on 13 February 2022.

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

This dataset is being provided under creative commons License (Attribution-Non-Commercial-Share Alike 4.0 International (CC BY-NC-SA 4.0)) https://creativecommons.org/licenses/by-nc-sa/4.0/

Context

This data was collected from patients admitted over a period of two years (1 April 2017 to 31 March 2019) at Hero DMC Heart Institute, Unit of Dayanand Medical College and Hospital, Ludhiana, Punjab, India. This is a tertiary care medical college and hospital. During the study period, the cardiology unit had 14,845 admissions corresponding to 12,238 patients. 1921 patients who had multiple admissions.

Specifically, data were related to patients ; date of admission; date of discharge; demographics, such as age, sex, locality (rural or urban); type of admission (emergency or outpatient); patient history, including smoking, alcohol, diabetes mellitus (DM), hypertension (HTN), prior coronary artery disease (CAD), prior cardiomyopathy (CMP), and chronic kidney disease (CKD); and lab parameters corresponding to hemoglobin (HB), total lymphocyte count (TLC), platelets, glucose, urea, creatinine, brain natriuretic peptide (BNP), raised cardiac enzymes (RCE) and ejection fraction (EF). Other comorbidities and features (28 features), including heart failure, STEMI, and pulmonary embolism, were recorded and analyzed.

Shock was defined as systolic blood pressure < 90 mmHg, and when the cause for shock was any reason other than cardiac. Patients in shock due to cardiac reasons were classified into cardiogenic shock. Patients in shock due to multifactorial pathophysiology (cardiac and non-cardiac) were considered for both categories. The outcomes indicating whether the patient was discharged or expired in the hospital were also recorded.

Further details about this dataset can be found here: https://doi.org/10.3390/diagnostics12020241

If you use this dataset in academic research all publications arising out of it must cite the following paper: Bollepalli, S.C.; Sahani, A.K.; Aslam, N.; Mohan, B.; Kulkarni, K.; Goyal, A.; Singh, B.; Singh, G.; Mittal, A.; Tandon, R.; Chhabra, S.T.; Wander, G.S.; Armoundas, A.A. An Optimized Machine Learning Model Accurately Predicts In-Hospital Outcomes at Admission to a Cardiac Unit. Diagnostics 2022, 12, 241. https://doi.org/10.3390/diagnostics12020241

If you intend to use this data for commercial purpose explicit written permission is required from data providers.

Content

table_headings.csv has explanatory names of all columns.

Acknowledgements

Data was collected from Hero Dayanand Medical College Heart Institute Unit of Dayanand Medical College and Hospital, Ludhiana, Punjab, India.

Inspiration

For any questions about the data or collaborations please contact ashish.sahani@iitrpr.ac.in

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

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.

Graph and download economic data for Rate of Preventable Hospital Admissions (5-year estimate) in Haywood County, NC (DISCONTINUED) (DMPCRATE037087) from 2008 to 2015 about Haywood County, NC; Asheville; preventable; admissions; hospitals; NC; 5-year; rate; and USA.

Hospital Admissions

In 2023, the average number of inpatient hospital admissions per person in Saudi Arabia witnessed an increase compared to the previous year, reaching around 11.3 admissions per 100 people. Approximately 46.5 percent of admissions were made at private healthcare facilities.

The number of finished and unfinished continuous inpatient spells (CIPS) for patients of all ages with an emergency method of admission and with any of the following primary diagnoses - Ear, nose and throat infections, Kidney / urinary tract infections, Heart failure Source: Hospital Episode Statistics (HES), Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2002/03 to 2007/08 Type of data: Administrative data

Legacy unique identifier: P02173