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

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.

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

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. This report shows a summary of the percent compliance by different hospital provider types. 6/17/23 - With the new 28-day compliance reporting period, CoP reports will be posted every 4 weeks. 9/12/2021 - To view other COVID-19 Hospital Data Coverage datasets, follow this link to view summary page: https://healthdata.gov/stories/s/ws49-ddj5

This dataset is not being updated as hospitals are no longer mandated to report COVID Hospitalizations to CDPH.

Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/

Note: Hospitalization counts include all patients diagnosed with COVID-19 during their stay. This does not necessarily mean they were hospitalized because of COVID-19 complications or that they experienced COVID-19 symptoms.

Note: Cumulative totals are not available due to the fact that hospitals report the total number of patients each day (as opposed to new patients).

The dataset contains information from a cohort of 799 patients admitted in the hospital for COVID-19, characterized with sociodemographic and clinical data. Retrospectively, from November 2020 to January 2021, data was collected from the medical records of all hospital admissions that occurred from March 1st, 2020, to December 31st, 2020. The analysis of these data can contribute to the definition of the clinical and sociodemographic profile of patients with COVID-19. Understanding these data can contribute to elucidating the sociodemographic profile, clinical variables and health conditions of patients hospitalized by COVID-19. To this end, this database contains a wide range of variables, such as: Month of hospitalization Gender Age group Ethnicity Marital status Paid work Admission to clinical ward Hospitalization in the Intensive Care Unit (ICU)COVID-19 diagnosisNumber of times hospitalized by COVID-19Hospitalization time in daysRisk Classification ProtocolData is presented as a single Excel XLSX file: dataset.xlsx of clinical and sociodemographic characteristics of hospital admissions by COVID-19: retrospective cohort of patients in two hospitals in the Southern of Brazil. Researchers interested in studying the data related to patients affected by COVID-19 can extensively explore the variables described here. Approved by the Research Ethics Committee (No. 4.323.917/2020) of the Federal University of Santa Catarina.

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. This report shows facilities currently in suspense regarding CoP requirements due to being in a work plan or other related reasons is shown if any facilities are currently in suspense. These CCNs will not be included in the tab listing all other hospitals or included in any summary counts while in suspense. 01/05/2024 – As of FAQ 6, the following optional fields have been added to this report: total_adult_patients_hospitalized_confirmed_influenza total_pediatric_patients_hospitalized_confirmed_influenza previous_day_admission_adult_influenza_confirmed previous_day_admission_pediatric_influenza_confirmed staffed_icu_adult_patients_confirmed_influenza staffed_icu_pediatric_patients_confirmed_influenza total_adult_patients_hospitalized_confirmed_rsv total_pediatric_patients_hospitalized_confirmed_rsv previous_day_admission_adult_rsv_confirmed previous_day_admission_pediatric_rsv_confirmed staffed_icu_adult_patients_confirmed_rsv staffed_icu_pediatric_patients_confirmed_rsv 6/17/2023 - With the new 28-day compliance reporting period, CoP reports will be posted every 4 weeks. 9/12/2021 - To view other COVID-19 Hospital Data Coverage datasets, follow this link to view summary page: https://healthdata.gov/stories/s/ws49-ddj5 As of FAQ3, the following field are federally inactive and will no longer be included in this report: previous_week_personnel_covid_vaccinated_doses_administered total_personnel_covid_vaccinated_doses_none total_personnel_covid_vaccinated_doses_one total_personnel_covid_vaccinated_doses_all total_personnel previous_week_patients_covid_vaccinated_doses_one previous_week_patients_covid_vaccinated_doses_all

Background: The COVID-19 pandemic disrupted hospital care, as hospitals had to deal with a highly infectious virus, while at the same time continuing to fulfill the ongoing health service needs of their communities. This study examines the direct effects of COVID-19 on the delivery of inpatient care in Croatia.Materials and Methods: The research is a retrospective, comparative analysis of the hospital admission rate across all Diagnosis Related Group (DRG) classes before and during the pandemic. It is based on DRG data from all non-specialized acute hospitals in Croatia, which account for 96% of national inpatient activity. The study also used COVID-19 data from the Croatian Institute of Public Health (CIPH).Results: The results show a 21% decrease in the total number of admissions [incident rate ratio (IRR) 0.8, p < 0.0001] across the hospital network during the pandemic in 2020, with the greatest drop occurring in April, when admissions plunged by 51%. The decrease in activity occurred in non-elective DRG classes such as cancers, stroke, major chest procedures, heart failure, and renal failure. Coinciding with this reduction however, there was a 37% increase (IRR 1.39, p < 0.0001) in case activity across six COVID-19 related DRG classes.Conclusions: The reduction in hospital inpatient activity during 2020, can be attributed to a number of factors such as lock-downs and quarantining, reorganization of hospital operations, the rationing of the medical workforce, and the reluctance of people to seek hospital care. Further research is needed to examine the consequences of disruption to hospital care in Croatia. Our recommendation is to invest multidisciplinary effort in reviewing response procedures to emergencies such as COVID-19 with the aim of minimizing their impact on other, and equally important community health care needs.

A dataset of hospital admissions of adults due to moderate to severe COVID-19 includes detailed information on more than 5,000 cases (approximately 350 variables). All ethical and data security principles have been applied following current standards of data protection and confidentiality. Individually identifiable data is not available. Data include detailed structtured records on the thousands of hospitalizations that occurred in HCFMUSP due to COVID-19 with the contribution of information automatically extracted from electronic medical records, and the cooperation of some research groups that agreed to share the data captured specifically for their studies. More information: https://sites.google.com/view/covid-19-hcfmusp

Note: This dataset has been limited to show metrics for Ramsey County, Minnesota.

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. 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

Calculation of county-level hospital metrics: 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, hospital inpatient and ICU bed capacity and occupancy among hospitals within the selected HSA. Therefore, admissions, capacity, and occupancy are not limited to residents of the selected HSA. For all county-level hospital metrics listed below the values are calculated first for the entire HSA, and then the HSA-level value is then applied to each county within the HSA. For all county-level hospital metrics listed below the values are calculated first for the entire HSA, and then the HSA-level value is then applied to each county within the HSA.

Metric details: Time period: data for the previous MMWR week (Sunday-Saturday) will update weekly on Thursdays 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 hospital admissions (count): Total number of admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction New Hospital Admissions Rate Value (Admissions per 100k): Total number of new admissions of patients with laboratory-confirmed COVID-19 in the past week (including both adult and pediatric admissions) for the entire jurisdiction divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000. (Note: This metric is used to determine each county’s COVID-19 Hospital Admissions Level for a given week). New COVID-19 Hospital Admissions Rate Level: qualitative value of new COVID-19 hospital admissions rate level [Low, Medium, High, Insufficient Data] New hospital admissions percent change from prior week: Percent change in the current weekly total new admissions of patients with laboratory-confirmed COVID-19 per 100,000 population compared with the prior week. New hospital admissions percent change from prior week level: Qualitative value of percent change in hospital admissions rate from prior week [Substantial decrease, Moderate decrease, Stable, Moderate increase, Substantial increase, Insufficient data] COVID-19 Inpatient Bed Occupancy Value: Percentage of all staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 (including both adult and pediatric patients) within the in the entire jurisdiction is calculated as an average of valid daily values within the past week (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 Level: Qualitative value of inpatient beds occupied by COVID-19 patients level [Minimal, Low, Moderate, Substantial, High, Insufficient data] COVID-19 Inpatient Bed Occupancy percent 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 average occupancy of patients with confirmed COVID-19 in staffed inpatient beds in the past week, compared with the prior week, in the entire jurisdiction. COVID-19 ICU Bed Occupancy Value: Percentage of all staffed inpatient beds occupied by adult patients with confirmed COVID-19 within the entire jurisdiction is calculated as an average of valid daily values within the past week (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 Level: Qualitative value of ICU beds occupied by COVID-19 patients level [Minimal, Low, Moderate, Substantial, High, Insufficient data] COVID-19 ICU Bed Occupancy percent 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 week, compared with the prior week, in the in the entire jurisdiction. For all metrics, if there are no data in the specified locality for a given week, the metric value is displayed as “insufficient data”.

The dataset contains information about hospitalization and Intensive Care Unit (ICU) admission rates and current occupancy for COVID-19 by date and Country.

It is based on data originally downloaded by the site https://www.ecdc.europa.eu/en/covid-19.

Raw data from ECDC, harmonization and homogenization of data from UNIPV - Laboratory of Geomatics

COVID-19 Reported Patient Impact and Hospital Capacity by State

  Description

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… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/covid-19-reported-patient-impact-and-hospital-capa.

This dataset shows the number of hospital admissions for influenza-like illness, pneumonia, or include ICD-10-CM code (U07.1) for 2019 novel coronavirus. Influenza-like illness is defined as a mention of either: fever and cough, fever and sore throat, fever and shortness of breath or difficulty breathing, or influenza. Patients whose ICD-10-CM code was subsequently assigned with only an ICD-10-CM code for influenza are excluded. Pneumonia is defined as mention or diagnosis of pneumonia. Baseline data represents the average number of people with COVID-19-like illness who are admitted to the hospital during this time of year based on historical counts. The average is based on the daily avg from the rolling same week (same day +/- 3 days) from the prior 3 years. Percent change data represents the change in count of people admitted compared to the previous day. Data sources include all hospital admissions from emergency department visits in NYC. Data are collected electronically and transmitted to the NYC Health Department hourly. This dataset is updated daily. All identifying health information is excluded from the dataset.

As of 9/12/2024, we will begin reporting on hospitalization data again using a new San Francisco specific dataset. Updated data can be accessed here.

On 5/1/2024, hospitalization data reporting will change from mandatory to optional for all hospitals nationwide. We will be pausing the refresh of the underlying data beginning 5/2/2024.

A. SUMMARY Count of COVID+ patients admitted to the hospital. Patients who are hospitalized and test positive for COVID-19 may be admitted to an acute care bed (a regular hospital bed), or an intensive care unit (ICU) bed. This data shows the daily total count of COVID+ patients in these two bed types, and the data reflects totals from all San Francisco Hospitals.

B. HOW THE DATASET IS CREATED Hospital information is based on admission data reported to the National Healthcare Safety Network (NHSN) and provided by the California Department of Public Health (CDPH).

C. UPDATE PROCESS Updates automatically every week.

D. HOW TO USE THIS DATASET Each record represents how many people were hospitalized on the date recorded in either an ICU bed or acute care bed (shown as Med/Surg under DPHCategory field).

The dataset shown here includes all San Francisco hospitals and updates weekly with data for the past Sunday-Saturday as information is collected and verified. Data may change as more current information becomes available.

E. CHANGE LOG

• 9/12/2024 -Hospitalization data are now being tracked through a new source and are available here.
• 5/1/2024 - hospitalization data reporting to the National Healthcare Safety Network (NHSN) changed from mandatory to optional for all hospitals nationwide. We will be pausing the refresh of the underlying data beginning 5/2/2024.
• 12/14/2023 – added column “hospitalreportingpct” to indicate the percentage of hospitals who submitted data on each report date.
• 8/7/2023 - In response to the end of the federal public health emergency on 5/11/2023 the California Hospital Association (CHA) stopped the collection and dissemination of COVID-19 hospitalization data. In alignment with the California Department of Public Health (CDPH), hospitalization data from 5/11/2023 onward are being pulled from the National Healthcare Safety Network (NHSN). The NHSN data is updated weekly and does not include information on COVID suspected (PUI) patients.
• 4/9/2021 - dataset updated daily with a four-day data lag.

Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. The COVID-19 pandemic has wider impacts on individuals' health, and their use of healthcare services, than those that occur as the direct result of infection. Reasons for this may include: * Individuals being reluctant to use health services because they do not want to burden the NHS or are anxious about the risk of infection. * The health service delaying preventative and non-urgent care such as some screening services and planned surgery. * Other indirect effects of interventions to control COVID-19, such as mental or physical consequences of distancing measures. This dataset provides information on trend data regarding the wider impact of the pandemic on hospital admissions. Data are shown by age group, sex, broad deprivation category and specialty groups. Information is also available at different levels of geographical breakdown such as Health Boards, Health and Social Care partnerships, and Scotland totals. This data is also available on the COVID-19 Wider Impact Dashboard. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications.

For English, see below This file contains: - the number of COVID-19 hospital and IC admissions per age group in the Netherlands, per week of hospital or IC admission and per week on which the data were reported to the NICE registry (https: //www.stichting-nice.nl). The numbers concern COVID-19 hospital and IC admissions since the first report in the Netherlands (27/02/2020) up to and including the most recent complete week of admission. The registration of the number of COVID-19 hospital and IC admissions may be lagging behind. This may result in the date of recording and the date of the report falling in a different calendar week. Hospital or ICU admissions from the most recent complete week of admission may have been reported in the current incomplete week and are therefore shown in this file. Hospital and ICU admissions from the most recent incomplete week are not included in this file but are censored with the value “NaN” (Not a number). The file is structured as follows: - One record per week of statistics for the Netherlands, even if there are no recordings or reports for the week in question. The numbers are then 0 (zero). -The stated date for statistics may relate to a hospital or IC admission date or the date on which the hospital reported a hospital or IC admission to the NICE registry. Description of the variables: Version: version number of the dataset. When the content of the dataset is structurally changed (so not the daily update or a correction at record level), the version number will be adjusted (+1) and also the corresponding metadata in RIVMdata (Https://data.rivm.nl) . Version 2 update (August 9, 2022): - From August 9, 2022, new admissions of persons with a SARS-CoV-2 infection who were also admitted during a previous COVID-19 episode have been added to this open data file. For this reason, the number of withdrawals with retroactive effect is higher than in our previous files. The underestimation of admissions since the start of the pandemic to August 9, 2022 is less than 1%. A recording is counted as a new recording when a person with a SARS-CoV-2 infection has a recording date that is more than 90 days after the previous recording. Version 3 update (September 1, 2022): - From September 1, 2022, the data will no longer be updated every Wednesday, but on Tuesdays. - As of September 1, 2022, this dataset is split into two parts. The first part contains the dates from the start of the pandemic to October 3, 2021 (week 39) and contains "tm" in the file name. This data will no longer be updated. The second part contains the data from October 4, 2021 (week 40) and is updated every Tuesday. Version 4 update (November 24, 2022): - From November 24, 2022, the age group 0-14 years will be split into age groups 0-4, 5-9 and 10-14 years. This will be retroactively updated for the entire pandemic. Version 5 update (April 4, 2023): - From April 4, 2023, this file will be updated weekly on Tuesdays. The data is retroactively updated for the other days. Date_of_report: Date and time on which the data file was created by RIVM. Date_of_statistics_week_start: The date of the Monday - first day of that week - for which the numbers per week are presented. Week of hospital admission (variable Hospital_admission), week of IC admission (variable IC_admission), the week on which the hospital admission (variable Hospital_admission_notification) or IC admission was reported (variable IC_admission_notification) to the NICE registry. Age_group: Age group in years of the admitted or reported patients. Five-year intervals are used with the exception of 90 years and above (90+). Patients with an unknown age are added to 'Unknown'. Hospital_admission_notification: The number of new COVID-19 patients admitted to the NICE registry per age group [Age_group] per week on which the hospital admission was reported [Date_of_statistics_week_start]. Hospital_admission: The number of new COVID-19 patients admitted to hospital per age group [Age_group] per hospital admission week [Date_of_statistics_week_start] reported to the NICE registry. IC_admission_notification: The number of new COVID-19 patients reported to the NICE registry who were admitted to the ICU per age group [Age_group] per week on which the ICU admission was reported [Date_of_statistics_week_start]. IC_admission: The number of new COVID-19 patients reported to the NICE registry who have been admitted to the ICU per age group [Age_group] per ICU admission week [Date_of_statistics_week_start]. A patient can be hospitalized or admitted to ICU multiple times (see version 2 update). RIVM and the NICE registry have aligned the method for determining the most relevant admission date in such cases as much as possible, but the numbers may differ slightly from the data as presented by the NICE registry. A patient admitted to the ICU also counts in the hospital admission figures. Despite the fact that hospitals are asked to register COVID-19 patients several times a day, the registration of the number of patients may lag. As a result, the numbers for the past calendar week may still be incomplete (https://www.stichting-nice.nl). Corrections made in reports in the source system of the NICE registration by employees of hospitals can also lead to corrections in this database. In that case, numbers published by RIVM in the past may deviate from the numbers in this database. At the time of creation and publication, this file therefore always contains the most up-to-date data according to the source system of the NICE registration after processing by RIVM. -------------------------------------------------- --------------------------------------------- Covid-19 hospital and intensive care unit (ICU) admissions in the Netherlands by age group by hospital and ICU admission week and reporting week (according to NICE registration) This file contains: - the number of COVID-19 hospital and ICU admissions by age group in the Netherlands, per week of hospitalization or ICU admission and per week on which the data were reported to the NICE registry (https://www.stichting-nice.nl). The numbers concern COVID-19 hospital and ICU admissions since the first report in the Netherlands (27/02/2020) up to and including the most recent complete week of admission. The registration of the number of COVID-19 hospital and ICU admissions may be lagging behind. This may result in the date of recording and the date of the report falling in a different calendar week. Hospital or ICU admissions from the most recent complete week of admission may have been reported in the current incomplete week and are therefore shown in this file. Hospital and ICU admissions from the most recent incomplete week are not included in this file but are censored with the value “NaN” (Not a Number). The file is structured as follows: - A record per week of statistics for the Netherlands, even if there are no recordings or reports on the week in question. The numbers are then 0 (zero). -The stated date for statistics may relate to a hospital or ICU admission date or the date on which the hospital reported a hospital or ICU admission to the NICE registry. Description of the variables: Version: version number of the dataset. When the content of the dataset is structurally changed (so not the daily update or a correction at record level), the version number will be adjusted (+1) and also the corresponding metadata in RIVMdata (Https://data.rivm.nl ). Version 2 update (August 9, 2022): - From August 9, 2022, new admissions of persons with a SARS-CoV-2 infection who were also admitted during a previous COVID-19 episode have been added to this open data file. For this reason, the number of withdrawals with retroactive effect is higher than in our previous files. The underestimation of admissions since the start of the pandemic to August 9, 2022 is less than 1%. A recording is counted as a new recording when a person with a SARS-CoV-2 infection has a recording date that is more than 90 days after the previous recording. Version 3 update (September 1, 2022): - From September 1, 2022, the data will no longer be updated every Wednesday, but on Tuesdays. - As of September 1, 2022, this dataset is split into two parts. The first part contains the dates from the start of the pandemic till October 3, 2021 (week 39) and contains "tm" in the file name. This data will no longer be updated. The second part contains the data from October 4, 2021 (week 40) and is updated every Tuesday. Version 4 update (November 24, 2022): - From November 24, 2022, the age group 0-14 years will be split into age groups 0-4, 5-9 and 10-14 years. This will be retroactively updated for the entire pandemic. Version 5 update (April 4, 2023): - From April 4, 2023, this file will be updated weekly on Tuesdays. The data has been retroactively updated for the other days. Date_of_report: Date and time on which the data file was created by the RIVM. Date_of_statistics_week_start: The date of the Monday - first day of that week - for which the numbers per week are presented. Week of hospital admission (variable Hospital_admission), week of ICU admission (variable IC_admission), the week on which the hospital admission (variable Hospital_admission_notification) or ICU admission was reported (variable IC_admission_notification) to the NICE registry. Age_group: Age group in years of the admitted or reported patients. Five-year intervals are used with the exception of 90 years and above (90+). Patients with an unknown age are added to 'Unknown'. Hospital_admission_notification: The number of new COVID-19 patients admitted to the NICE registry per age group [Age_group] per week on which the hospital admission was reported [Date_of_statistics_week_start]. Hospital_admission: The number of new COVID-19 patients admitted to hospital per age group [Age_group] per hospital admission week [Date_of_statistics_week_start] reported to the NICE registry. IC_admission_notification: The

OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 2.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases & more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) & death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID OMOP dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date. This is a subset of data in OMOP format.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – August 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data. Further OMOP data available as an additional service.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

COVID-19 Hospital Data Coverage Summary

  Description

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.

This report shows a summary of… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/covid-19-hospital-data-coverage-summary.

Multivariable negative binomial regression with daily number of medical and surgical hospital admissions per day as the outcome comparing March 16-September 23, 2020 (post COVID-19 public health measures) to March 16-September 23, 2019.

Data extracted from the pediatric infectious disease case registration system of the Negeri Sembilan state of Malaysia. These were secondary data that underwent data cleaning and preprocessing (anonymization, imputation of missing values, categorical variable encoding, and dimension reduction) for clinical research.a. dataset_pediatricCOVID19_cleanedData_1495rows.csv consists of clinical data collected between 1st February 2020 and 31st December 2021.b. dataset2_pediatricCOVID19_cleanedData_500rows.csv consists of clinical data collected between 1st January 2022 and 31st March 2022.Outcome variable: 1= requires ambulatory outpatient care, 2= requires hospital care