This statistic depicts the average daily census in registered hospitals in the United States in 2019, categorized by the number of beds. During this year, the average daily census totaled ****** people for hospitals with ** to ** beds.

The acute-care pathway (from the emergency department (ED) through acute medical units or ambulatory care and on to wards) is the most visible aspect of the hospital health-care system to most patients. Acute hospital admissions are increasing yearly and overcrowded emergency departments and high bed occupancy rates are associated with a range of adverse patient outcomes. Predicted growth in demand for acute care driven by an ageing population and increasing multimorbidity is likely to exacerbate these problems in the absence of innovation to improve the processes of care.

Key targets for Emergency Medicine services are changing, moving away from previous 4-hour targets. This will likely impact the assessment of patients admitted to hospital through Emergency Departments.

This data set provides highly granular patient level information, showing the day-to-day variation in case mix and acuity. The data includes detailed demography, co-morbidity, symptoms, longitudinal acuity scores, physiology and laboratory results, all investigations, prescriptions, diagnoses and outcomes. It could be used to develop new pathways or understand the prevalence or severity of specific disease presentations.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

Electronic Health Record: University Hospital Birmingham 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 & an expanded 250 ITU bed capacity during COVID. 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”.

Scope: All patients with a medical emergency admitted to hospital, flowing through the acute medical unit. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes patient demographics, co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (timings, admissions, wards and readmissions), physiology readings (NEWS2 score and clinical frailty scale), Charlson comorbidity index and time dimensions.

Available supplementary data: Matched controls; ambulance data, OMOP data, synthetic data.

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.

The average daily change in percentage of inpatient beds occupied by COVID-19 patients in a state was estimated using statistical regression methods. The percentage of inpatient beds occupied by COVID-19 patients on a given date was based on a 3-day moving average, to minimize random fluctuations in bed counts.State estimates of change in percentage, with 95% confidence intervals that reflect sampling errors, were based on data submitted by acute care hospitals to the NHSN COVID-19 Module.Estimates obtained from regression models were adjusted for hospital size, facility type, and the percentage of facilities participating daily in NHSN COVID-19 Module.

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.

Number of Bed: Central Sulawesi: Banggai Regency data was reported at 469.000 Unit in 09 Oct 2022. This stayed constant from the previous number of 469.000 Unit for 08 Oct 2022. Number of Bed: Central Sulawesi: Banggai Regency data is updated daily, averaging 442.000 Unit from Aug 2021 (Median) to 09 Oct 2022, with 370 observations. The data reached an all-time high of 471.000 Unit in 18 Aug 2021 and a record low of 345.000 Unit in 30 Aug 2021. Number of Bed: Central Sulawesi: Banggai Regency data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Indonesia Premium Database’s Health Sector – Table ID.HLA010: Number of Hospital Bed: by Regency/Municipality (Discontinued).

The point map shows the availability of nursing home beds by the location of the nursing home facility. The color grading of the points represent the relevancy of the bed availability data. The sizes of the points represent the number of beds available. Flyouts will display specific data for the nursing home selected. If multiple nursing homes are located close together in such a way that the map cannot easily distinguish between them, the points may appear on top of each other. To view a nursing home that is displayed in this way, click the next button at the bottom of the flyout for the nursing home.

For more information, check out http://nursinghomes.nyhealth.gov/. The "About" tab contains additional details concerning this dataset.

Sector: 03. Ensuring health and well-being for all and for all ages Algorithm: Beds in ordinary day care in nursing homes Territorial comparisons: South Tyrol, Italy

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, 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.

• Time period: data for the previous MMWR week (Sunday-Saturday) 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 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”.

Notes: June 15, 2023: Due to incomplete or missing hospital data received for the June 4, 2023, through June 10, 2023, reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and AS and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on June 15, 2023.

July 10, 2023: Due to incomplete or missing hospital data received for the June 25, 2023, through July 1, 2023, reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and AS and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on July 10, 2023.

July 17, 2023: Due to incomplete or missing hospital data received for the July 2, 2023, through July 8, 2023, reporting

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 LOG9/12/2024 -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.

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, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.

This dataset represents daily 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 laborat

The Federal Railroad Administration (FRA) sponsored a study of the work schedules and sleep patterns of railroad employees. The purpose of the study was to understand work-schedule related fatigue that affects various categories of railroad employees by documenting a group's work/rest schedules and sleep patterns to ascertain their impact on the level of fatigue/alertness.Employees surveyed include: signalmen, maintenance of way (MOW) workers, dispatchers, and train & engine service workers (in both freight and passenger train service)

Number of Bed: Covid-19: Used: Riau Islands data was reported at 19.000 Unit in 09 Oct 2022. This records an increase from the previous number of 18.000 Unit for 08 Oct 2022. Number of Bed: Covid-19: Used: Riau Islands data is updated daily, averaging 27.000 Unit from Aug 2021 (Median) to 09 Oct 2022, with 370 observations. The data reached an all-time high of 763.000 Unit in 06 Aug 2021 and a record low of 5.000 Unit in 18 Jul 2022. Number of Bed: Covid-19: Used: Riau Islands data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Indonesia Premium Database’s Health Sector – Table ID.HLA015: Number of Used Hospital Bed: Covid-19: by Province (Discontinued).

In 2022, the Chinese mental healthcare enterprise Wenzhou Kangning Hospital's total average inpatient spending per bed-day was almost *** yuan, increasing slightly from the previous year. The average inpatient expenditure per bed-day stood above *** yuan in 2018.

This data set was prepared to verify the core relation between intertidal morphodynamics and BSS distribution as descripted by the Dynamic Equilibrium Theory (DET). Hydrodynamic and bed-level change data were monitored daily for one year on two tidal flats with contrasting wave exposures. Notably, the bed-level change data were provided by SED-sensors (surface elevation dynamic sensors). The data sets presented here includes the bed-level data, wave data, water depths and current velocity.

9.704 (Number) in 2014. Equipped beds at end year

This dataset compiles daily counts of patients (both COVID-related and non-COVID-related) in adult and pediatric ICU beds and the number of adult and pediatric ICU beds that are unoccupied. **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 ** Data includes: * date * number of adults in ICU for COVID-related critical illness (CRCI)_**_ * number of adults in ICU for non-CRCI reasons * number of adult ICU beds that are unoccupied * total number of adults in ICU for any reason * number of patients in pediatric ICU for COVID-related critical illness (CRCI)_**_ * number of patients in pediatric ICU beds for non-CRCI reasons * number of pediatric ICU beds that are unoccupied * total number of patients in pediatric ICU beds for any reason **These results may not match the CRCI cases in ICU reported elsewhere (on Ontario.ca) as they are restricted to either adults only or pediatric patients only and do not include cases in other ICU bed types. * ICU data includes patients in levels 2 and 3 adult or pediatric ICU beds. The reported numbers reflect the previous day’s values. Patients are counted at a single point in time (11:59 pm) to ensure that each person is only counted once, and their COVID status is updated at 6 am, prior to posting. This may vary slightly from similar sources who update at different times. * COVID-related critical illness (CRCI) includes patients currently testing positive for COVID and patients in ICU due to COVID who are no longer testing positive for COVID. * Since the start of the pandemic, the province has invested in “incremental” ICU beds to accommodate potential surges in ICU demand due to COVID. These beds were added at various points in time (i.e., October 2020, February 2021, April 2021) to ensure system preparedness and meet operational needs. Aligned with the decline of Wave 3 and COVID-related pressures and at the direction of Ontario Health, a number of these beds were brought offline in July 2021. These events account for the sudden increases and/or decreases in ICU beds seen in the data. The number of ICU beds continues to fluctuate slightly as beds are brought on and offline to meet localized demands/need. ##Modifications to this data Data for the period of October 24, 2023 to March 24, 2024 excludes hospitals in the West region who were experiencing data availability issues. Daily adult, pediatric, and neonatal patient ICU census data were impacted by technical issues between September 9 and October 20, 2023. As a result, when public reporting resumes on November 16, 2023, historical ICU data for this time period will be excluded. January 18, 2022: Information on pediatric ICU beds was added to the file for the period of May 2020 to present. January 7, 2022: Due to some methodology changes, historical data were impacted during the following timeframes: * May 1, 2020 to October 22, 2020. * February 19, 2021 to July 26, 2021. ###How the data was impacted To ensure system preparedness throughout the pandemic, hospitals were asked to identify the number of beds (i.e., non-ICU beds) and related resources that could be made available within 24 hours for use as an ICU bed in case of a surge in COVID patients. These beds were considered expanded ICU capacity and were not used to calculate hospitals’ ICU occupancy. These beds were previously included in this data. The current numbers include only funded ICU beds based on data from the Critical Care Information System (CCIS).

Bed Occupancy Rate: Emergency Department: East Java: Bondowoso Regency data was reported at 0.000 % in 09 Oct 2022. This stayed constant from the previous number of 0.000 % for 08 Oct 2022. Bed Occupancy Rate: Emergency Department: East Java: Bondowoso Regency data is updated daily, averaging 0.000 % from Aug 2021 (Median) to 09 Oct 2022, with 370 observations. The data reached an all-time high of 78.125 % in 10 Aug 2021 and a record low of 0.000 % in 09 Oct 2022. Bed Occupancy Rate: Emergency Department: East Java: Bondowoso Regency data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Indonesia Premium Database’s Health Sector – Table ID.HLA020: Hospital Bed Occupancy Rate: Emergency Department: by Regency/Municipality (Discontinued).

Bed Occupancy Rate: Emergency Department: Central Java: Kudus Regency data was reported at 0.000 % in 09 Oct 2022. This stayed constant from the previous number of 0.000 % for 08 Oct 2022. Bed Occupancy Rate: Emergency Department: Central Java: Kudus Regency data is updated daily, averaging 0.000 % from Aug 2021 (Median) to 09 Oct 2022, with 361 observations. The data reached an all-time high of 3.922 % in 25 Feb 2022 and a record low of 0.000 % in 09 Oct 2022. Bed Occupancy Rate: Emergency Department: Central Java: Kudus Regency data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Indonesia Premium Database’s Health Sector – Table ID.HLA020: Hospital Bed Occupancy Rate: Emergency Department: by Regency/Municipality (Discontinued).

Updated daily between 3:00 pm to 5:00 pm Data are updated daily in the early afternoon and reflect laboratory results reported to the Washington State Department of Health as of midnight the day before. Data for previous dates will be updated as new results are entered, interviews are conducted, and data errors are corrected.

Many people test positive but do not require hospitalization. The counts of positive cases do not necessarily indicate levels of demand at local hospitals.

Reporting of test results to the Washington State Department of Health may be delayed by several days and will be updated when data are available. Only positive or negative test results are reflected in the counts and exclude tests where results are pending, inconclusive or were not performed.

Adult day health care services in the U.S. cost a national median of 100 U.S. dollars per day in 2024. This is an increase of 5 percent from 95 U.S. dollars in 2023. Long-term health care can be provided in various environments. Adult day health care (ADC) provides social support in a community setting through socialization, supervision, and structured activities. Personal care, transportation, meals, and other related services may also be provided.