NOTE: This dataset is historical-only as of 5/10/2023. All data currently in the dataset will remain, but new data will not be added. The recommended alternative dataset for similar data beyond that date is  https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u. (This is not a City of Chicago site. Please direct any questions or comments through the contact information on the site.)

During the COVID-19 pandemic, the Chicago Department of Public Health (CDPH) required EMS Region XI (Chicago area) hospitals to report hospital capacity and patient impact metrics related to COVID-19 to CDPH through the statewide EMResource system. This requirement has been lifted as of May 9, 2023, in alignment with the expiration of the national and statewide COVID-19 public health emergency declarations on May 11, 2023. However, all hospitals will still be required by the U.S. Department of Health and Human Services (HHS) to report COVID-19 hospital capacity and utilization metrics into the HHS Protect system through the CDC’s National Healthcare Safety Network until April 30, 2024. Facility-level data from the HHS Protect system can be found at healthdata.gov.

Until May 9, 2023, all Chicago (EMS Region XI) hospitals (n=28) were required to report bed and ventilator capacity, availability, and occupancy to the Chicago Department of Public Health (CDPH) daily. A list of reporting hospitals is included below. All data represent hospital status as of 11:59 pm for that calendar day. Counts include Chicago residents and non-residents.

ICU bed counts include both adult and pediatric ICU beds. Neonatal ICU beds are not included. Capacity refers to all staffed adult and pediatric ICU beds. Availability refers to all available/vacant adult and pediatric ICU beds. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases in ICU on 03/19/2020. Hospitals began reporting ICU surge capacity as part of total capacity on 5/18/2020.

Acute non-ICU bed counts include burn unit, emergency department, medical/surgery (ward), other, pediatrics (pediatric ward) and psychiatry beds. Burn beds include those approved by the American Burn Association or self-designated. Capacity refers to all staffed acute non-ICU beds. An additional 500 acute/non-ICU beds were added at the McCormick Place Treatment Facility on 4/15/2020. These beds are not included in the total capacity count. The McCormick Place Treatment Facility closed on 05/08/2020. Availability refers to all available/vacant acute non-ICU beds. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases in acute non-ICU beds on 04/03/2020.

Ventilator counts prior to 04/24/2020 include all full-functioning mechanical ventilators, with ventilators with bilevel positive airway pressure (BiPAP), anesthesia machines, and portable/transport ventilators counted as surge. Beginning 04/24/2020, ventilator counts include all full-functioning mechanical ventilators, BiPAP, anesthesia machines and portable/transport ventilators. Ventilators are counted regardless of ability to staff. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases on ventilators on 03/19/2020. CDPH has access to additional ventilators from the EAMC (Emergency Asset Management Center) cache. These ventilators are included in the total capacity count.

Chicago (EMS Region 11) hospitals: Advocate Illinois Masonic Medical Center, Advocate Trinity Hospital, AMITA Resurrection Medical Center Chicago, AMITA Saint Joseph Hospital Chicago, AMITA Saints Mary & Elizabeth Medical Center, Ann & Robert H Lurie Children's Hospital, Comer Children's Hospital, Community First Medical Center, Holy Cross Hospital, Jackson Park Hospital & Medical Center, John H. Stroger Jr. Hospital of Cook County, Loretto Hospital, Mercy Hospital and Medical Center, , Mount Sinai Hospital, Northwestern Memorial Hospital, Norwegian American Hospital, Roseland Community Hospital, Rush University M

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 state-aggregated data for hospital utilization. These are derived from reports with facility-level granularity across three main sources: (1) National Healthcare Safety Network (NHSN) (after December 15, 2022) (2) HHS TeleTracking (before December 15, 2022), (3) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities, and (4) historical NHSN timeseries data (before July 15, 2020). Data in this file have undergone routine data quality review of key variables of interest by subject matter experts to identify and correct obvious data entry errors. The file will be updated regularly and provides the latest values reported by each facility within the last four days for all time. This allows for a more comprehensive picture of the hospital utilization within a state by ensuring a hospital is represented, even if they miss a single day of reporting. No statistical analysis is applied to account for non-response and/or to account for missing data. The below table displays one value for each field (i.e., column). Sometimes, reports for a given facility will be provided to more than one reporting source: HHS TeleTracking, NHSN, and HHS Protect. When this occurs, to ensure that there are not duplicate reports, prioritization is applied to the numbers for each facility. This file contains data that have been corrected based on additional data quality checks applied to select data elements. The resulting dataset allows various data consumers to use for their analyses a high-quality dataset with consistent standards of data processing and cleaning applied. The following fields in this dataset are derived from data elements included in these data quality checks: inpatient_beds inpatient_beds_used total_staffed_adult_icu_beds adult_icu_bed_utilization adult_icu_bed_utilization_numerator adult_icu_bed_utilization_denominator adult_icu_bed_covid_utilization_numerator adult_icu_bed_covid_utilization_denominator adult_icu_bed_covid_utilization total_adult_patients_hospitalized_confirmed_covid total_pediatric_patients_hospitalized_confirmed_covid

In 2023, there were, on average, 2.32 hospital beds per 1,000 population in the United States. Hospital bed density varied widely between the states, with District of Columbia having 4.87 beds per thousand population, while there were just 1.57 hospital beds per thousand population available in Washington.

The "COVID-19 Reported Patient Impact and Hospital Capacity by Facility" dataset from the U.S. Department of Health & Human Services, filtered for Connecticut. View the full dataset and detailed metadata here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u The following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Friday to Thursday). 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 2020-11-20 means the average/sum/coverage of the elements captured from that given facility starting and including Friday, November 20, 2020, and ending and including reports for Thursday, November 26, 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”. 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. 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. To see the numbers as reported by the facilities, go to: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb On May 13, 2021 Changed vaccination fields from sum to max or min fields. This reflects the maximum or minimum number report

Context

This data-set is regarding the current pandemic COVID-19. It contains the total number of beds available in hospital in each and every state. The rows contains the state names and columns contains the "Number of hospital beds in public sector", "Number of hospital beds in private sector", "Total number of beds (private + public)". The data for Ladakh state is not available since it is not available on the govt. sites. This data-set is taken from the pdf available on the below link. This pdf is provided by the CDDEP (THE CENTRE FOR DISEASE DYNAMICS, ECONOMICS AND POLICY) and PRINCETON UNIVERSITY. They have done the study and research on the data of COVID-19 and publish their conclusions and findings namely in " INDIA : STATE-WISE ESTIMATES OF CURRENT HOSPITAL BEDS, ICU BEDS, AND VENTILATORS ".

Link: https://cddep.org/wp-content/uploads/2020/04/State-wise-estimates-of-current-beds-and-ventilators_5Apr2020-AN_gk.pdf

Acknowledgements

Thanks to these people for their valuable contribution. Geetanjali Kapoor, Aditi Sriram, Jyoti Joshi, Ramanan Laxminarayan

If anyone found anything wrong in this data-set, please feel free to let me know or any kind of feedback anyone wants to share I'm open to that also. Since, I'm a newbie in this field I would love to resolve any problem. Thanks.

The total hospital bed capacity in the National Capital Region (NCR) in the Philippines reached over ****** beds in 2022, the highest among all regions. In contrast, the Bangsamoro Autonomous Region in Muslim Mindanao (BARMM) had the lowest hospital bed capacity.

The highest number of hospital beds in Norway in 2024 was in the health region of South-East Norway, with ***** beds. The health region West had the second-highest number of beds, which was *****.

The dataset provides state-aggregated data for estimated patient impact and hospital utilization. The source data is gotten 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 files in the dataset are representative estimates for each state and are updated weekly. Data files include: Estimated Inpatient Beds Occupied by State Timeseries; Estimated Inpatient Beds Occupied by COVID-19 Patients by State Timeseries; and Estimated ICU Beds Occupied by State Timeseries.

In 2024, there were approximately ******* private hospital beds in Brazil, out of which nearly ** percent, or about ******* beds, were concentrated in the Southeast region of Brazil. Similarly, that year, approximately ** percent of private hospitals in the country were located in the Southeast region, while the North was the region with fewer private hospitals and hospital beds, which amounted to about ****** thousand units in 2024.

This dataset provides values for HOSPITAL BEDS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This scatter chart displays female population (people) against hospital beds (per 1,000 people). The data is about regions.

In FY 2024, there were a total of ******* staffed beds in U.S. hospitals. California recorded the highest number of staffed beds, with over **** thousand hospital beds, while the number stood at only *** beds in Vermont. This statistic presents the number of staffed beds in U.S. hospitals in FY 2024, by state.

Deprecated report. This report was created early in the response to the COVID-19 pandemic. Increased reporting and quality in hospital data have rendered the estimated datasets obsolete.

The following dataset provides state-aggregated data for estimated patient impact and hospital utilization.

The source data for estimation is 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.

Estimates Basis: These files are representative estimates for each state and are updated weekly. These projections are based on the information we have from those who reported. As more hospitals report more frequently our projections become more accurate. The actual data for these data points are updated every day, once a day on healthdata.gov and these are the downloadable data sets.

Laos Number of Hospital Beds: Regional Hospitals data was reported at 665.000 Person in 2017. This records a decrease from the previous number of 767.000 Person for 2016. Laos Number of Hospital Beds: Regional Hospitals data is updated yearly, averaging 740.000 Person from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 1,299.000 Person in 2011 and a record low of 632.000 Person in 2006. Laos Number of Hospital Beds: Regional Hospitals data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.G018: Health Statistics.

In 2023, there were approximately ****** hospital beds in the region of Riyadh in Saudi Arabia. This was more than double the number of beds in the Eastern region, which had the second-highest number of beds at around *****. The total number of beds in the country increased by roughly **** over the previous year.

This collection of synthetic hospital datasets is designed to simulate real-world operations for a medium-sized hospital, focusing on staffing, patient admissions, and bed allocation among services. The data allows for exploration and analysis of hospital resource distribution, including personnel deployment, patient demand, and service-level performance.

The dataset consists of four CSV files:

• hospital_staff.csv – List of hospital staff
• hospital_patients.csv – Patient records
• hospital_service_weekly.csv – Weekly service-level data
• hospital_staff_schedule.csv – Weekly schedule

*** Note: This is synthetic data generated for educational and analytical purposes. It does not represent real patients or real hospital staff.

As of 2021, the region with the highest number of hospital beds for all types of inpatient care in Italy is Lombardy. As the graph shows, Lombardy counted a total of nearly ** thousand hospital beds, private and public combined. By contrast, the region of Aosta Valley counted the lowest number of hospital beds for inpatient care, with ***. This, however, should not come as a surprise as Lombardy and Aosta Valley are the most and least populous regions in the country, respectively. This statistic displays the number of inpatient care hospital beds in Italy in 2021, by region.

Data on community hospital beds in the United States, by state. 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 a wide range of health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

DISCLAIMER

Dataset consists of historical data of pre-pandemic period and doesn’t represent the current reality which may have changed due to the spikes in demand. This dataset has been generated in collaboration of efforts within CoronaWhy community.

Context

Last updated: April 26th 2020 Updates: April 14th 2020 - Added missing population data April 15th 2020 - Added Brazil statewise ICU hospital beds dataset April 21th 2020 - Added Italy, Spain statewise ICU hospital beds dataset, India statewise TOTAL hospital beds dataset April 26th 2020 - Added Sweden ICU(2019) and TOTAL(2018) beds datasets

Purpose of the dataset

I am trying to produce a dataset that will provide a foundation for policymakers to understand the realistic capacity of healthcare providers being able to deal with the spikes in demand for intensive care. As a way to help, I’ve prepared a dataset of beds across countries and states. Work in progress dataset that should and will be updated as more data becomes available and public on weekly basis.

Importance

This dataset is intended to be used as a baseline for understanding the typical bed capacity and coverage globally. This information is critical for understanding the impact of a high utilization event, like COVID-19.

Current challenges

Datasets are scattered across the web and are very hard to normalize, I did my best but help would be much appreciated.

Data sources / Acknowledgments

arcgis (USA) - https://services1.arcgis.com/Hp6G80Pky0om7QvQ/arcgis/rest/services/Hospitals_1/FeatureServer/0 KHN (USA) - https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/ datahub.io (World) - https://datahub.io/world-bank/sh.med.beds.zs eurostat - https://data.europa.eu/euodp/en/data/dataset/vswUL3c6yKoyahrvIRyew OECD - https://data.oecd.org/healtheqt/hospital-beds.htm WDI (World) - https://data.worldbank.org/indicator/SH.MED.BEDS.ZS NHP(India) - http://www.cbhidghs.nic.in/showfile.php?lid=1147 data.gov.sg (Singapore) - https://data.gov.sg/dataset/health-facilities?view_id=91b4feed-dcb9-4720-8cb0-ac2f04b7efd0&resource_id=dee5ccce-4dfb-467f-bcb4-dc025b56b977 dati.salute.gov.it (Italy)- http://www.dati.salute.gov.it/dati/dettaglioDataset.jsp?menu=dati&idPag=96 portal.icuregswe.org (Sweden) - https://portal.icuregswe.org/seiva/en/Rapport publications: Intensive Care Medicine Journal (Europe) - https://link.springer.com/article/10.1007/s00134-012-2627-8 Critical Care Medicine Journal (Asia) - https://www.researchgate.net/figure/Number-of-critical-care-beds-per-100-000-population_fig1_338520008 Medicina Intensiva (Spain) - https://www.medintensiva.org/en-pdf-S2173572713000878 news: https://lanuovaferrara.gelocal.it/italia-mondo/cronaca/2020/03/19/news/dietro-la-corsa-a-nuovi-posti-in-terapia-intensiva-gli-errori-del-passato-1.38611596 kaggle: germany - https://www.kaggle.com/manuelblechschmidt/icu-beds-in-germany brazil (IBGE) - https://www.kaggle.com/thiagobodruk/brazilianstates Manual population data search from wiki

Data columns

country,state,county,lat,lng,type,measure,beds,population,year,source,source_url - country - country of origin, if present - state - more granular location, if present - lat - latitude - lng - longtitude - type - [TOTAL, ICU, ACUTE(some data could include ICU beds too), PSYCHIATRIC, OTHER(merged ‘SPECIAL’, ‘CHRONIC DISEASE’, ‘CHILDREN’, ‘LONG TERM CARE’, ‘REHABILITATION’, ‘WOMEN’, ‘MILITARY’] - measure - type of measure (per 1000 inhabitants) - beds - number of beds per 1000 - population - population of location based on multiple sources and wikipedia - year - source year for beds and population data - source - source of data - source_url - URL of the original source

Files

for each of datasource: hospital_beds_per_source.csv

US only: US arcgis + khn (state/county granularity): hospital_beds_USA.csv

Global (state(region)/county granularity): hospital_beds_global_regional.csv

Global (country granularity): hospital_beds_global_v1.csv

Contributors

Igor Kiulian - extracting/normalizing/formatting/merging data Artur Kiulian - helped with Kaggle setup Augaly S. Kiedi - helped with country population data Kristoffer Jan Zieba - found Swedish data sources

Possible Improvements

Find and megre more detailed (state/county wise) or newer datasource

This scatter chart displays hospital beds (per 1,000 people) against population (people). The data is about regions.