The number of hospitals in the United States has steadily declined over the past five decades, dropping from ***** in 1975 to ***** in 2022. This significant reduction reflects broader changes in the healthcare landscape, including consolidation, technological advancements, and shifts in patient care delivery models. Hospital types and ownership As of 2023, the U.S. healthcare system comprises ***** community hospitals, which are primarily non-profit institutions. For-profit hospitals make up about ** percent of these facilities, and their numbers have increased over the past two decades. The healthcare landscape also includes *** federal hospitals and ***** nonfederal hospitals. This diversity in ownership and management structures reflects the complex nature of the U.S. healthcare system and its various funding sources. Hospital capacity and utilization The decline in hospital numbers has been accompanied by a reduction in available hospital beds, decreasing from about *** million in 1975 to ******* in 2023. Despite this reduction, hospital admissions have remained relatively stable, with over **** million admissions recorded in 2023. Interestingly, hospital occupancy rates have generally decreased compared to 1975, although recent figures are showing signs of increase again.

About this dataset

Looking for a dataset on hospitals in the United States? Look no further! This dataset contains information on all of the hospitals registered with Medicare in the US, including their addresses, phone numbers, hospital type, and more. With such a large amount of data, this dataset is perfect for anyone interested in studying the US healthcare system.

This dataset can also be used to study hospital ownership, emergency services

How to use the dataset

If you want to study the US healthcare system, this dataset is perfect for you. It contains information on all of the hospitals registered with Medicare, including their addresses, phone numbers, hospital type, and more. With such a large amount of data, this dataset is perfect for anyone interested in studying the US healthcare system.

This dataset can also be used to study hospital ownership, emergency services, and EHR usage. In addition, the hospital overall rating and various comparisons are included for safety of care, readmission rates

Research Ideas

1. Predicting readmission rates for different hospital conditions
2. Analyzing relationships between hospital ownership and quality of care
3. Studying the relationship between hospital type and patient experience

Acknowledgements

This dataset was originally published by Centers for Medicare and Medicaid Services and has been modified for this project

Columns

File: Hospital_General_Information.csv | Column name | Description | |:-------------------------------------------------------|:----------------------------------------------------------------------------------------------------------| | Hospital Name | The name of the hospital. (String) | | Hospital Name | The name of the hospital. (String) | | Address | The address of the hospital. (String) | | Address | The address of the hospital. (String) | | City | The city in which the hospital is located. (String) | | City | The city in which the hospital is located. (String) | | State | The state in which the hospital is located. (String) | | State | The state in which the hospital is located. (String) | | ZIP Code | The ZIP code of the hospital. (Integer) | | ZIP Code | The ZIP code of the hospital. (Integer) | | County Name | The county in which the hospital is located. (String) | | County Name | The county in which the hospital is located. (String) | | Phone Number | The phone number of the hospital. (String) | | Phone Number | The phone number of the hospital. (String) | | Hospital Type | The type of hospital. (String) | | Hospital Type | The type of hospital. (String) | | Hospital Ownership | The ownership of the hospital. (String) | | Hospital Ownership | The ownership of the hospital. (String) | | Emergency Services | Whether or not the...

The number of hospitals in the United States was forecast to continuously decrease between 2024 and 2029 by in total 13 hospitals (-0.23 percent). According to this forecast, in 2029, the number of hospitals will have decreased for the twelfth consecutive year to 5,548 hospitals. Depicted is the number of hospitals in the country or region at hand. As the OECD states, the rules according to which an institution can be registered as a hospital vary across countries.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 up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of hospitals in countries like Canada and Mexico.

Trends indicate that the overall number of hospital beds in the U.S. is decreasing. In 1975, there were about *** million hospital beds in the country. Despite fluctuations, by 2023 there were just ******* hospital beds in the U.S. There is a growing trend towards consumer use of outpatient services, which tend to be less costly for patients. This may be only one reason why hospital bed numbers are decreasing in the United States. Hospital occupancy Despite seeing a decrease in the number of hospital beds in the U.S., hospital occupancy rate has also generally decreased compared to 1975. The number of hospital admissions, on the other hand, has been fluctuating. Hospital costs Costs also may be an important factor in the reduction of number of hospital beds in the U.S., however, costs do not appear to be on the decline. Inpatient stays in U.S. community hospitals has been steadily increasing. In fact, the United States has the highest daily hospital costs in the world. While hospital costs depend heavily on the condition that is being treated, the U.S. had consistently the highest costs for inpatient treatments such as a hip replacement, or a coronary bypass surgery.

In 2023, there were over **** 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 *** percent of females reporting one or more hospital stays in the past year, compared to *** percent of males. Furthermore, **** percent of those aged 65 years and older had a hospitalization in the past year, compared to just *** percent of those aged 18 to 44 years. The average length of a stay in a U.S. hospital is *** days. Hospital beds In 2022, there were ******* 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 ** percent.

Note - this is not real-time status information, the data represents bed utilization based on annual estimates of how many beds are used versus available.Definitive Healthcare is the leading provider of data, intelligence, and analytics on healthcare organizations and practitioners. In this service, Definitive Healthcare provides intelligence on the numbers of licensed beds, staffed beds, ICU beds, and the bed utilization rate for the hospitals in the United States. Please see the following for more details about each metric, data was last updated on 17 March 2020:

Number of Licensed beds: is the maximum number of beds for which a hospital holds a license to operate; however, many hospitals do not operate all the beds for which they are licensed. This number is obtained through DHC Primary Research. Licensed beds for Health Systems are equal to the total number of licensed beds of individual Hospitals within a given Health System.

Number of Staffed Bed: is defined as an "adult bed, pediatric bed, birthing room, or newborn ICU bed (excluding newborn bassinets) maintained in a patient care area for lodging patients in acute, long term, or domiciliary areas of the hospital." Beds in labor room, birthing room, post-anesthesia, postoperative recovery rooms, outpatient areas, emergency rooms, ancillary departments, nurses and other staff residences, and other such areas which are regularly maintained and utilized for only a portion of the stay of patients (primarily for special procedures or not for inpatient lodging) are not termed a bed for these purposes. Definitive Healthcare sources Staffed Bed data from the Medicare Cost Report or Proprietary Research as needed. As with all Medicare Cost Report metrics, this number is self-reported by providers. Staffed beds for Health Systems are equal to the total number of staffed beds of individual Hospitals within a given Health System. Total number of staffed beds in the US should exclude Hospital Systems to avoid double counting. ICU beds are likely to follow the same logic as a subset of Staffed beds.

Number of ICU Beds - ICU (Intensive Care Unit) Beds: are qualified based on definitions by CMS, Section 2202.7, 22-8.2. These beds include ICU beds, burn ICU beds, surgical ICU beds, premature ICU beds, neonatal ICU beds, pediatric ICU beds, psychiatric ICU beds, trauma ICU beds, and Detox ICU beds.

Bed Utilization Rate: is calculated based on metrics from the Medicare Cost Report: Bed Utilization Rate = Total Patient Days (excluding nursery days)/Bed Days Available

Potential Increase in Bed Capacity: This metric is computed by subtracting “Number of Staffed Beds from Number of Licensed beds” (Licensed Beds – Staffed Beds). This would provide insights into scenario planning for when staff can be shifted around to increase available bed capacity as needed.

Hospital Definition: Definitive Healthcare defines a hospital as a healthcare institution providing inpatient, therapeutic, or rehabilitation services under the supervision of physicians. In order for a facility to be considered a hospital it must provide inpatient care.

Hospital types are defined by the last four digits of the hospital’s Medicare Provider Number. If the hospital does not have a Medicare Provider Number, Definitive Healthcare determines the Hospital type by proprietary research.

Hospital Types:

·
Short Term Acute Care Hospital (STAC)

o
Provides inpatient care and other services for surgery, acute medical conditions, or injuries

o
Patients care can be provided overnight, and average length of stay is less than 25 days

·
Critical Access Hospital (CAH)

o
25 or fewer acute care inpatient beds

o
Located more than 35 miles from another hospital

o
Annual average length of stay is 96 hours or less for acute care patients

o
Must provide 24/7 emergency care services

o
Designation by CMS to reduce financial vulnerability of rural hospitals and improve access to healthcare

·
Religious Non-Medical Health Care Institutions

o
Provide nonmedical health care items and services to people who need hospital or skilled nursing facility care, but for whom that care would be inconsistent with their religious beliefs

·
Long Term Acute Care Hospitals

o
Average length of stay is more than 25 days

o
Patients are receiving acute care - services often include respiratory therapy, head trauma treatment, and pain management

·
Rehabilitation Hospitals

o
Specializes in improving or restoring patients' functional abilities through therapies

·
Children’s Hospitals

o
Majority of inpatients under 18 years old

·
Psychiatric Hospitals

o
Provides inpatient services for diagnosis and treatment of mental illness 24/7

o
Under the supervision of a physician

·
Veteran's Affairs (VA) Hospital

o
Responsible for the care of war veterans and other retired military personnel

o
Administered by the U.S. VA, and funded by the federal government

·
Department of Defense (DoD) Hospital

o
Provides care for military service people (Army, Navy, Air Force, Marines, and Coast Guard), their dependents, and retirees (not all military service retirees are eligible for VA services)

Forecast: Number of Hospital Beds in Publicly Owned Hospitals in the US 2023 - 2027 Discover more data with ReportLinker!

As of 2025, New York-Presbyterian hospital is the largest hospital in the United States with its eight campuses based in New York City. This was followed by AdventHealth Orlando in Florida stands as the second largest hospital in the United States, boasting an impressive 2,787 beds. Evolving landscape of U.S. hospitals Despite the decline in the total number of hospitals since 1980, the healthcare sector continues to grow in other ways. U.S. hospitals now employ about 7.5 million workers and generate a gross output of around 1,263 billion U.S. dollars. The Hospital Corporation of America, based in Nashville, Tennessee, leads the pack as the largest health system in the country, operating 222 hospitals as of February 2025. This reflects a trend towards consolidation and the rise of for-profit hospital chains, which gained prominence in the 1990s. Specialization and emergency care While bed count is one measure of hospital size, institutions also distinguish themselves through specialization and emergency care capabilities. For instance, the University of California at Los Angeles Medical Center performed 22,287 organ transplants between January 1988 and March 2025, making it the leading transplant center in the nation. In terms of emergency care, Parkland Health and Hospital System in Dallas recorded the highest number of emergency department visits in 2024, with 235,893 patients seeking urgent care.

From the Web site: The American Hospital Directory® provides data, statistics, and analytics about more than 7,000 hospitals nationwide. AHD.com® hospital information includes both public and private sources such as Medicare claims data, hospital cost reports, and commercial licensors. AHD® is not affiliated with the American Hospital Association (AHA) and is not a source for AHA Data. Our data are evidence-based and derived from the most definitive sources.

Description:

This dataset encapsulates ten years (1999-2008) of clinical care data from 130 US hospitals and integrated delivery networks. Each row pertains to hospital records of diabetic patients who received laboratory tests and medications and had hospital stays of up to 14 days. The primary goal is to predict early readmission of patients within 30 days of discharge. This task is crucial due to the significant impact on healthcare costs and patient outcomes, as many diabetic patients do not receive adequate preventive and therapeutic interventions during hospitalization, leading to poor glycemic control and increased readmissions.

Dataset Characteristics: - Type: Multivariate - Subject Area: Health and Medicine - Associated Tasks: Classification, Clustering - Feature Types: Categorical, Integer - Number of Instances: 101,766 - Number of Features: 47 - Missing Values: Yes

Instance Representation: Instances represent hospital records of patients diagnosed with diabetes.

Data Splits: There are no specific recommendations for data splitting. Standard train-test or three-way holdout splits (train-validation-test) can be used for model selection.

Sensitivity: The dataset includes sensitive information such as age, gender, and race of the patients.

Dataset Details: The dataset includes over 50 features related to patient and hospital outcomes. Data was extracted based on the following criteria: 1. Inpatient encounters (hospital admissions). 2. Diabetic encounters (any type of diabetes diagnosis). 3. Length of stay between 1 and 14 days. 4. Laboratory tests conducted during the encounter. 5. Medications administered during the encounter.

Attributes: - encounter_id: Unique identifier for each encounter. - patient_nbr: Unique identifier for each patient. - race: Race of the patient (e.g., Caucasian, Asian, African American, Hispanic, other). - gender: Gender of the patient (e.g., male, female, unknown/invalid). - age: Age grouped in 10-year intervals (e.g., [0, 10), [10, 20), ..., [90, 100)). - weight: Weight in pounds (contains missing values). - admission_type_id: Integer identifier for admission type (e.g., emergency, urgent, elective, newborn, not available). - discharge_disposition_id: Integer identifier for discharge disposition (e.g., discharged to home, expired, not available). - admission_source_id: Integer identifier for admission source (e.g., physician referral, emergency room, transfer from another hospital). - time_in_hospital: Number of days between admission and discharge.

Additional Information: For a detailed description of all attributes, refer to Table 1 in the paper titled "Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records" by Beata Strack, Jonathan DeShazo, Chris Gennings, Juan Olmo, Sebastian Ventura, Krzysztof Cios, and John Clore, published in BioMed Research International, vol. 2014.

Link to Paper: Impact of HbA1c Measurement on Hospital Readmission Rates

Forecast: Number of Hospital in the US 2022 - 2026 Discover more data with ReportLinker!

Forecast: Number of Hospital Beds in for Profit Privately Owned Hospitals in the US 2022 - 2026 Discover more data with ReportLinker!

Hospitals play a critical role in healthcare, offering specialized treatments and emergency services essential for public health, regardless of economic fluctuations or individuals' financial situations. Rising incomes and broader access to insurance have fueled demand for care in recent years, supporting hospitals' post-pandemic recovery initiated by federal policies and funding. The recovery for many hospitals was also promoted by mergers that lessened financial strains, especially in rural hospitals. This trend toward consolidation has resulted in fewer enterprises relative to establishments, enhancing hospitals' bargaining power regarding input costs and insurance reimbursements. With this improved position, hospitals are expected to see revenue climb at a CAGR of 2.0%, reaching $1.5 trillion by 2025, with a 3.2% increase in 2025 alone. Competition, economic conditions and regulatory changes will impact hospitals based on size and location. Smaller hospitals, particularly rural ones, may encounter more significant obstacles as the industry transitions from fee-based to value-based care. Independent hospitals face wage inflation, staffing shortages and drug supply costs. Although state and federal policies aim to support small rural hospitals in addressing hospital deserts, uncertainties linger over federal Medicare funding and Medicaid reimbursements, which account for nearly half of hospital care spending. Even so, increasing per capita disposable income and increasing the number of individuals with private insurance will boost revenues from private insurers and out-of-pocket payments for all hospitals, big and small. Hospitals will continue incorporating technological advancements in AI, telemedicine and wearables to enhance their services and reduce cost. These technologies aid hospital systems in strategically expanding outpatient services, mitigating the increasing competitive pressures from Ambulatory Surgery Centers (ASCs) and capitalizing on the increased needs of an aging adult population and shifts in healthcare delivery preferences. As the consolidation trend advances and technology adoption further leverages economies of scale, industry revenue is expected to strengthen at a CAGR of 2.4%, reaching $1.7 trillion by 2030, with steady profit over the period.

NAPSG Foundation simply changed the symbology based on bed utilization and filter set to Hospital Type is not 'Psychiatric Hospital'. NAPSG Foundation is not the host of this dataset, see notes below for more details.Also - it is not clear how often the bed utilization rate updates, but it is now presumed to be 4x per year. THIS IS NOT A REAL-TIME DATASET.Definitive Healthcare is the leading provider of data, intelligence, and analytics on healthcare organizations and practitioners. In this service, Definitive Healthcare provides intelligence on the numbers of licensed beds, staffed beds, ICU beds, and the bed utilization rate for the hospitals in the United States. Please see the following for more details about each metric, data was last updated on 17 March 2020:Number of Licensed beds: is the maximum number of beds for which a hospital holds a license to operate; however, many hospitals do not operate all the beds for which they are licensed. This number is obtained through DHC Primary Research. Licensed beds for Health Systems are equal to the total number of licensed beds of individual Hospitals within a given Health System. Number of Staffed Bed: is defined as an "adult bed, pediatric bed, birthing room, or newborn ICU bed (excluding newborn bassinets) maintained in a patient care area for lodging patients in acute, long term, or domiciliary areas of the hospital." Beds in labor room, birthing room, post-anesthesia, postoperative recovery rooms, outpatient areas, emergency rooms, ancillary departments, nurses and other staff residences, and other such areas which are regularly maintained and utilized for only a portion of the stay of patients (primarily for special procedures or not for inpatient lodging) are not termed a bed for these purposes. Definitive Healthcare sources Staffed Bed data from the Medicare Cost Report or Proprietary Research as needed. As with all Medicare Cost Report metrics, this number is self-reported by providers. Staffed beds for Health Systems are equal to the total number of staffed beds of individual Hospitals within a given Health System. Total number of staffed beds in the US should exclude Hospital Systems to avoid double counting. ICU beds are likely to follow the same logic as a subset of Staffed beds. Number of ICU Beds - ICU (Intensive Care Unit) Beds: are qualified based on definitions by CMS, Section 2202.7, 22-8.2. These beds include ICU beds, burn ICU beds, surgical ICU beds, premature ICU beds, neonatal ICU beds, pediatric ICU beds, psychiatric ICU beds, trauma ICU beds, and Detox ICU beds. Bed Utilization Rate: is calculated based on metrics from the Medicare Cost Report: Bed Utilization Rate = Total Patient Days (excluding nursery days)/Bed Days AvailablePotential Increase in Bed Capacity: This metric is computed by subtracting “Number of Staffed Beds from Number of Licensed beds” (Licensed Beds – Staffed Beds). This would provide insights into scenario planning for when staff can be shifted around to increase available bed capacity as needed. Hospital Definition: Definitive Healthcare defines a hospital as a healthcare institution providing inpatient, therapeutic, or rehabilitation services under the supervision of physicians. In order for a facility to be considered a hospital it must provide inpatient care. Hospital types are defined by the last four digits of the hospital’s Medicare Provider Number. If the hospital does not have a Medicare Provider Number, Definitive Healthcare determines the Hospital type by proprietary research. Hospital Types:· Short Term Acute Care Hospital (STAC)o Provides inpatient care and other services for surgery, acute medical conditions, or injurieso Patients care can be provided overnight, and average length of stay is less than 25 days· Critical Access Hospital (CAH)o 25 or fewer acute care inpatient bedso Located more than 35 miles from another hospitalo Annual average length of stay is 96 hours or less for acute care patientso Must provide 24/7 emergency care serviceso Designation by CMS to reduce financial vulnerability of rural hospitals and improve access to healthcare· Religious Non-Medical Health Care Institutionso Provide nonmedical health care items and services to people who need hospital or skilled nursing facility care, but for whom that care would be inconsistent with their religious beliefs· Long Term Acute Care Hospitalso Average length of stay is more than 25 dayso Patients are receiving acute care - services often include respiratory therapy, head trauma treatment, and pain management· Rehabilitation Hospitalso Specializes in improving or restoring patients' functional abilities through therapies· Children’s Hospitalso Majority of inpatients under 18 years old· Psychiatric Hospitalso Provides inpatient services for diagnosis and treatment of mental illness 24/7o Under the supervision of a physician· Veteran's Affairs (VA) Hospital o Responsible for the care of war veterans and other retired military personnelo Administered by the U.S. VA, and funded by the federal government· Department of Defense (DoD) Hospitalo Provides care for military service people (Army, Navy, Air Force, Marines, and Coast Guard), their dependents, and retirees (not all military service retirees are eligible for VA services) For more information please visit - https://www.definitivehc.com/ - or contact sales@definitivehc.com

Forecast: Number of Hospital Beds in the US 2023 - 2027 Discover more data with ReportLinker!

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.

This dataset is used in the map tooltip documentation to explain different ways to enhance information in a map.This database represents locations of Hospitals for 50 states and Washington D.C. , Puerto Rico and US territories. The dataset only includes hospital facilities and does not include nursing homes. Data for all the states was acquired from respective states departments or their open source websites and then geocoded and converted into a spatial database. After geocoding the exact spatial location of each point was moved to rooftops wherever possible and points which have been physically verified have been labelled "Geocode", "Imagery", "Imagery with other" and "Unverified" depending on the methodology used to move the points. "Unverified" data points have still not been physically examined even though each of the points has been street geocoded as mentioned above. Missing records are denoted by 'Not Available' or NULL values. Not Available denotes information that was either missing in the source data or data that has not been populated current version. This dataset has been developed to represent Hospitals for inclusion in the HSIP datasets.

In the 2024fiscal year, a total of **** million discharges were recorded in U.S. hospitals. Californian hospitals alone made nearly *** million discharges, while there were *** million discharges in Texas.

Graph and download economic data for All Employees, Hospitals (CES6562200001) from Jan 1990 to Sep 2025 about hospitals, health, establishment survey, education, services, employment, and USA.

Accounting for under 5.0% of US hospitals, children's specialty hospitals are key to pediatric healthcare. And despite pandemic disruptions, industry revenue is expected to climb at a CAGR of 2.9% through 2025 to total $54.7 billion, with minimal growth of 0.1% in 2025. Several factors drive this growth, which outpaces the expected growth for the hospital sector overall. The closure of pediatric units in some general hospitals led some individuals to seek treatment at specialty hospitals. The rapid adoption of telemedicine, AI-aided diagnostics and monitoring also brought cost savings and expanded markets that contribute to revenue growth. Half of the revenue for children's hospitals comes from private insurance and increases in the number of people with private insurance have contributed to industry performance. However, two-fifths of industry revenue stems from government insurance. In April 2025, ten states remained Medicaid non-expansion states, affecting children's access to health services. Over half of uninsured children reside in non-expansion states, leaving a market segment underserved and a source of future revenue. Children's specialty hospitals' cost challenges are impacted by location. Some rural regions face persistent shortages of physicians and nurses, which leads to wage inflation and impacts service availability. Meanwhile, urban hospitals deal with increased and challenging occupancy rates. While consolidations can ease financial pressure and create economies of scale, advancements in telemedicine and innovations in wearables and medical devices could shift services from smaller rural hospitals to larger urban ones, worsening the imbalance. Looking forward, budget cuts at the National Institutes of Health (NIH), federal agency consolidations and spending cuts from the One Big Beautiful Bill Act (OBBBA) threaten children's specialty hospitals by undermining pediatric research, potentially stalling advancements in therapies for conditions like childhood cancers and rare diseases. Hospital financial stability and the risk of service reductions will vary by state and require proactive policy advocacy and alternative revenue strategies. Despite funding challenges, demand for services from children's specialty hospitals is expected to remain strong because of the increasing prevalence of conditions like asthma, obesity, diabetes and congenital anomalies in those under 18. Industry revenue will strengthen at a CAGR of 2.6% through the end of 2030, reaching $62.3 billion, with profit as a share of revenue expected to strengthen and surpass pre-pandemic levels.