Prior template for requested daily data reports on testing, capacity and utilization, and patient flows to facilitate the public health response to the 2019 Novel Coronavirus (COVID-19).

Prior template for requested daily data reports on testing, capacity and utilization, and patient flows to facilitate the public health response to the 2019 Novel Coronavirus (COVID-19).

This shows the facilities details

This file has explanatory information for the template, including field numberings to match the FAQ.

The following dataset provides state-aggregated data for hospital utilization in a timeseries format dating back to January 1, 2020. These are derived from reports with facility-level granularity across three main sources: (1) HHS TeleTracking, (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities and (3) National Healthcare Safety Network (before July 15).

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.

COVID-19 Reported Patient Impact and Hospital Capacity by State Data Dictionary

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials t

The National Hospital Discharge Survey (NHDS), conducted from 1965 to 2010, was a national probability survey designed to meet the need for information on characteristics of inpatients discharged from non-Federal short-stay hospitals in the United States. From 1988-2007 the NHDS collected data from a sample of approximately 270,000 inpatient records acquired from a national sample of about 500 hospitals. From 2008 to 2010 the sample size was reduced to 239. Only hospitals with an average length of stay of fewer than 30 days for all patients, general hospitals, or children’s general hospitals are included in the survey. Federal, military, and Department of Veterans Affairs hospitals, as well as hospital units of institutions (such as prison hospitals), and hospitals with fewer than six beds staffed for patient use, are excluded.
Beginning in 1988, two data collection procedures have been used in the survey. The medical abstract form and the automated data tapes contain items that relate to the personal characteristics of the patient. These items include age, sex, race, ethnicity, marital status, and expected sources of payment. Administrative items such as admission and discharge dates (which allow calculation of length of stay), as well as discharge status are also included. Medical information about patients includes diagnoses and procedures coded to the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM).

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels.

Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time.

The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., gender, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals.

Restricted access data files are available with a data use agreement and brief online security training.

Data on initial injury-related visits to hospital emergency departments, by sex, age, and intent and mechanism of injury. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. Due to a change in national medical data coding standards in 2015, from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to the ICD-10-CM, the definition for injuries and injury subcategories changed for the 2017 reporting period and beyond. Results from 2017 and subsequent years should not be compared with previous reporting periods. Any observed changes in trends across this transition period should not be considered. Data for 2016 are not included. Additional information regarding injury definitions and categorization of injuries by mechanism and intent of injury is available at: https://www.cdc.gov/nchs/injury/injury_tools.htm. Note that the data file available here has more recent years of data than what is shown in the PDF or Excel version.

SOURCE: NCHS, National Hospital Ambulatory Medical Care Survey. For more information on the National Hospital Ambulatory Medical Care Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus17_appendix.pdf.

HCUPnet is an online data tool based on data from the Healthcare Cost and Utilization Project (HCUP).

The data tool provides healthcare statistics and information for hospital inpatient and emergency department settings, as well as population-based healthcare data on counties. Users are able to query HCUP data to access detailed or summary statistics on inpatient stays and emergency department visits by patient, hospital, and encounter characteristics. Users are also able to generate tables and graphs on national and regional statistics and trends for community hospitals in the United States.