The National Hospital Ambulatory Medical Care Survey (NHAMCS), conducted by the National Center for Health Statistics (NCHS), collects annual data on visits to emergency departments to describe patterns of utilization and provision of ambulatory care delivery in the United States. Data are collected from nonfederal, general, and short-stay hospitals from all 50 U.S. states and the District of Columbia, and are used to develop nationally representative estimates. The data include counts and rates of emergency department visits from 2016-2022 for the 10 leading primary diagnoses and reasons for visit, stratified by selected patient and hospital characteristics. Rankings for the 10 leading categories were identified using weighted data from 2022 and were then assessed in prior years.

In 2023, there were, on average, 422 hospital emergency room (ER) visits per 1,000 population in the United States. ER visit rates had been steadily increasing from 365 visits per 1,000 population in 1999 till a peak of 445 visits in 2017. There was a drop in ER visit rates during the pandemic, but numbers are slowly increasing to pre-pandemic levels again.

This dataset contains counts and rates (per 10,000 residents) of asthma emergency department (ED) visits among Californians. The table “Asthma Emergency Department Visit Rates by County” contains statewide and county-level data stratified by age group (all ages, 0-17, 18+, 0-4, 5-17, 18-64, 65+) and race/ethnicity (white, black, Hispanic, Asian/Pacific Islander, American Indian/Alaskan Native). The table “Asthma Emergency Department Visit Rates by ZIP Code” contains zip-code level data stratified by age group (all ages, 0-17, 18+). The data are derived from the Department of Health Care Access and Information emergency department database. These data include emergency department visits from all licensed hospitals in California. These data are based only on primary discharge diagnosis codes. On October 1, 2015, diagnostic coding for asthma transitioned from ICD9-CM (493) to ICD10-CM (J45). Because of this change, CDPH and CDC do not recommend comparing data from 2015 (or earlier) to 2016 (or later). NOTE: Rates are calculated from the total number of asthma emergency department visits (not the unique number of individuals).

In 2022, there were over *** million hospital emergency department visits in the United States. While the number of ED visits has fluctuated in the past years, numbers have been steadily increasing since 2000. This statistic represents the number of hospital emergency department visits in the United States from 2000 to 2022.

This dataset provides the Emergency Department ratio of encounters and treatment stations to represent the ED Burden. Smaller ratios indicate fewer ED visits per available treatment station and less burden. Larger ratios of ED visits per available treatment station indicate greater burden. The encounters are broken down by health-related conditions: Active COVID-19, Asthma, Cancer, Cardiac, COPD, COVID-19 History, Diabetes, Homeless, Hypertension, Mental Health, Obesity, Pneumonia, Respiratory, Sepsis, Stroke, and Substance Abuse.

The data includes a broader range of geographic units of analysis than have previously been made available in HPD public reports, in addition to other measures. - Geography: County, Covered California Region, Public Health Region, California Assembly District, California Senate District, California Congressional District - Demographics: Age Band, Sex - Payer Type: Commercial, Medi-Cal, Medicare - Measures: Prevalence of 23 chronic conditions, total emergency department (ED) visits, avoidable ED visits

This dataset contains annual Excel pivot tables that display summaries of the patients treated in each Emergency Department (ED). The Emergency Department data is sourced from two databases, the ED Treat-and-Release Database and the Inpatient Database (i.e. patients treated in the ED and then formally admitted to the hospital). The summary data include number of visits, expected payer, discharge disposition, age groups, sex, preferred language spoken, race groups, principal diagnosis groups, and principal external cause of injury/morbidity groups. The data can also be summarized statewide or for a specific hospital county, ED service level, teaching/rural status, and/or type of control.

This dataset was inspired by real-world emergency room dynamics and healthcare industry reports to provide a realistic simulation of patient visits. The data reflects insights from studies on ER wait times, patient outcomes, and satisfaction metrics, incorporating key factors such as urgency levels, seasonal trends, and time-of-day variability.

Sources of inspiration include reports from the Agency for Healthcare Research and Quality, studies on nurse-to-patient ratios, and published statistics on average ER wait times across urban and rural regions. The dataset was designed using a Python-based simulation, with input from ChatGPT to ensure logical relationships between variables and alignment with domain knowledge.

While entirely simulated, the dataset serves as a practical tool for learning data analysis, visualization, and statistical modeling in the context of healthcare operations.

NSSP Emergency Department (ED) Visit Trajectories by State and Sub-State Regions- COVID-19, Flu, RSV, Combined. This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geographic part of the country that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). In addition, the trend over time is characterized as increasing, decreasing or no change, with exceptions for when there are no data available, the data are too sparse, or there are not enough data to compute a trend. These data are to provide awareness of how the weekly trend is changing for the given geographic region. 

Note that the reported sub-state trends are from Health Service Areas (HSA) and the data reported from the health care facilities located within the given HSA. Health Service Areas are regions of one or more counties that align to patterns of care seeking. The HSA level data are reported for each county in the HSA.

More information on HSAs is available here.

For the emergency department time series, trajectory classifications reported on for sub-state (HSA) emergency department time series, trajectory classifications are based on approximations of the first derivative (slope) of trends that are smoothed using generalized additive models (GAMs). To determine time intervals in which the slope is sufficiently changing (i.e., rate of change distinguishable from 0), 95% confidence intervals for the slope approximations are calculated and assessed. Weeks with a 95% confidence interval not containing 0 are classified as increasing if the slope estimate is positive and decreasing if the slope estimate is negative. Weeks with a 95% confidence interval containing 0 are classified as stable. In the scenario that an HSA's time series is determined to be too sparse (i.e., many weeks with percentages of 0%), a model is not fit, and the HSA is classified as “sparse”.

For additional information, please see: Companion Guide: NSSP Emergency Department Data on Respiratory Illness

Updated once per week on Fridays. 

In 2022, emergency department visit rate was highest among infants under the age of one. Adults 75 years and over had the second-highest ED visit rate, while the average for all ages was 47 visits per 100 people in 2022.

This dataset includes aggregated weekly data on the percent of emergency department visits and the percent of hospital inpatient admissions due to influenza-like illness (ILI), COVID-19, influenza, RSV, and acute respiratory illness. The Illinois Department of Public Health (IDPH) collects data for Emergency Department visits to all 185 acute care hospitals in Illinois. The data are submitted from IDPH to the CDC’s BioSense Platform for access and analysis by health departments via the ESSENCE system. The CDC National Syndromic Surveillance Program (NSSP) utilizes diagnostic codes and clinical terms to create definitions for diagnosed COVID-19, influenza, RSV, and acute respiratory illness. For more information on diagnostic codes and clinical terms used, visit: https://www.cdc.gov/nssp/php/onboarding-resources/companion-guide-ed-data-respiratory-illness.html The data is characterized by selected demographic groups including age group and race/ethnicity. The dataset also includes percent of weekly outpatient visits due to ILI as reported by several outpatient clinics throughout Chicago that participate in CDC’s Influenza-like Illness Surveillance Network (ILINet). For more information on ESSENCE, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance For more information on ILINet, see https://www.cdc.gov/fluview/overview/index.html#cdc_generic_section_3-outpatient-illness-surveillance All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

Data on visits to physician offices, hospital outpatient departments and hospital emergency departments by selected population characteristics. 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. Note that the data file available here has more recent years of data than what is shown in the PDF or Excel version. Data for 2017 physician office visits are not available. SOURCE: NCHS, National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. For more information on the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey, see the corresponding Appendix entries at https://www.cdc.gov/nchs/data/hus/hus17_appendix.pdf.

Emergency department visits in U.S. hospitals continue to surge, with *********************************** in Dallas leading the pack in 2024. The facility recorded ******* ED visits, followed closely by ******************************** in Florida with ******* visits. This trend highlights the growing demand for emergency medical services across the country, particularly in large urban centers. Evolving healthcare landscape While emergency departments are busier than ever, the overall number of hospitals in the U.S. has been decreasing since the 1970s. Meanwhile, there is a rise of large health systems. The Hospital Corporation of America, based in Nashville, Tennessee, stands as the largest health system in the country, operating *** hospitals as of February 2025. This consolidation trend reflects the changing dynamics of healthcare delivery and management in the United States. Specialization and capacity challenges As hospitals face increasing pressure on their emergency departments, many are also focusing on specialized services to meet diverse patient needs. For instance, the ****************************************************** performed ****** organ transplants between January 1988 and March 2025, making it the nation's ******* transplant center. Meanwhile, ******************** in Florida holds the title of the largest U.S. hospital with ***** beds.

To statistics of emergency room consultation rates - by gender and age group division

This dataset includes the number and percentage of emergency department (ED) visits for COVID-19, Influenza, and RSV by week and age group. This dataset corresponds to the data on https://www.vdh.virginia.gov/epidemiology/respiratory-diseases-in-virginia/data/.

Emergency Department Visits Related To Mental Health Conditions - This indicator shows the rate of emergency department visits related to mental health disorders (per 100,000 population). Mental health problems can place a heavy burden on the healthcare system, particularly when persons in crisis utilize emergency departments instead of other sources of care when available. In Maryland, there were 207,650 mental health disorder-related emergency department visits in 2014.Diagnoses include adjustment disorders, anxiety disorders, attention deficit disorders, disruptive behavior disorders, mood disorders, personality disorders, schizophrenia, and other psychotic disorders, suicide and intentional self-inflicted injury and miscellaneous mental disorders.

List of footnotes, notes, and source information for The National Hospital Ambulatory Medical Care Survey (NHAMCS). Each row of this dataset contains the accompanying text for a footnote found in NHAMCS dataset. The footnote lookup can be merged onto any NHAMCS dataset using, DATASET_SHORT_NAME, FN_ID, FN_TYPE, and FN_TEXT.

SOURCE: National Center for Health Statistics CDC, The National Hospital Ambulatory Medical Care Survey (NHAMCS)

In 2022, of the estimated *** million emergency department visits in the United States, **** percent were admitted, while *** percent were transferred to another hospital. Meanwhile, the majority (**********) were referred to physicians or clinics for follow-up.

These data include counts and rates of emergency department visits from 2016-2022 for selected primary diagnoses and reasons for visit, stratified by selected patient and hospital characteristics. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

From 2010 to 2016, 11.8 percent of emergency department visits for sports and recreational injuries for female patients aged 5 to 24 years were due to gymnastics or cheerleading. This statistic shows the distribution of emergency department visits for sport and recreational activity injuries for patients aged 5 to 24 years in the United States from 2010 to 2016, by gender and activity type.