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Introduction to the HCUP Nationwide Emergency Department Sample (NEDS), 2020

 

HEALTHCARE COST AND UTILIZATION PROJECT – HCUP
A FEDERAL-STATE-INDUSTRY PARTNERSHIP IN HEALTH DATA

Sponsored by the Agency for Healthcare Research and Quality

 

 

INTRODUCTION TO

THE HCUP NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)

2020

 

 

Please read all documentation carefully.

THE NEDS CONTAINS A FULL YEAR OF INTERNATIONAL CLASSIFICATION OF DISEASES, TENTH REVISION, CLINICAL MODIFICATION/PROCEDURE CODING SYSTEM (ICD-10-CM/PCS) CODES BEGINNING WITH DATA YEAR 2016.






These pages provide an introduction to the 2020 NEDS.

For full documentation and notification of changes, visit the HCUP User Support (HCUP-US) website at www.hcup-us.ahrq.gov.

 

Issued September 2022

Agency for Healthcare Research and Quality
Healthcare Cost and Utilization Project (HCUP)

 

NEDS Data and Documentation Distributed through the
HCUP Central Distributor
Phone: (866) 290-4287 (toll-free)
Fax: (805) 979-3787
Email: HCUP@ahrq.gov



Table of Contents

Index of Tables

Index of Figures



HCUP NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)
SUMMARY OF DATA USE LIMITATIONS

***** REMINDER *****


All users of the NEDS must take the online HCUP Data Use Agreement (DUA) Training Course as well as read and sign a DUA. Details and links may be found on the following page.

Authorized users of HCUP data agree to the following restrictions:a

  • Will not use the data for any purpose other than research, analysis and aggregate statistical reporting.

  • Will not rerelease any data to unauthorized users.

  • Will not redistribute HCUP data by posting on any website or publishing in any other publicly accessible online repository. If a journal or publication requests access to data or analytic files, will cite restrictions on data sharing in the DUA and direct them to AHRQ HCUP User Support (HCUP-US) website (www.hcup-us.ahrq.gov) for more information on accessing HCUP data.

  • Will not identify or attempt to identify any individual, including by the use of vulnerability analysis or penetration testing. Methods that could be used to identify individuals directly or indirectly shall not be disclosed or published.

  • Will not report any statistics where the number of observations (i.e., individual discharge records) in any given cell of tabulated data is less than or equal to 10 (<10).

  • Will not publish information that could identify individual establishments (e.g., hospitals) and will not contact establishments.

  • Will not use the data concerning individual establishments for commercial or competitive purposes affecting establishments, or to determine rights, benefits, or privileges of individual establishments.

  • Will not use the data for criminal and civil litigation, including expert witness testimony or for law enforcement activities.

  • Will acknowledge in reports that data from the "Healthcare Cost and Utilization Project (HCUP)" were used, including names of the specific databases used for analysis.b

Any violation of the limitations in the DUA is punishable under Federal law by a fine, and up to 5 years in prison, or both. Violations may also be subject to penalties under State statutes.

a This is a summary of key terms of the DUA for Nationwide Databases; please refer to the DUA for full terms and conditions.
b Suggested citations for the HCUP databases are provided in the Requirements for Publishing With HCUP Data page of the HCUP-US website.



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HCUP DATA USE AGREEMENT REQUIREMENTS

All HCUP data users, including data purchasers and collaborators, must complete the online HCUP Data Use Agreement (DUA) Training Course and read and sign the HCUP DUA. Proof of training completion and signed DUAs must be submitted to the HCUP Central Distributor.

Data purchasers will be required to provide their DUA training completion code and will execute their DUAs electronically as a part of the online ordering process. The DUAs and training certificates for collaborators and others with access to HCUP data should be submitted directly to the HCUP Central Distributor using the contact information below.

The online DUA Training Course is available at: www.hcup-us.ahrq.gov/tech_assist/dua.jsp.

The HCUP Nationwide DUA is available on the HCUP-US website at: www.hcup-us.ahrq.gov/team/NationwideDUA.pdf

HCUP CONTACT INFORMATION

HCUP Central Distributor and HCUP User Support

Information about the content of the HCUP databases is available on the HCUP User Support (HCUP-US) website (www.hcup-us.ahrq.gov).

If you have questions, please review the HCUP Frequently Asked Questions located at www.hcup-us.ahrq.gov/tech_assist/faq.jsp.

If you need further technical assistance, please contact the HCUP Central Distributor and User Support team at:

Phone: (866) 290-HCUP (4287) (toll free)
Email: HCUP@AHRQ.gov
Fax: (866) 792-5313 (toll free in the United States)

Mailing address:
HCUP Central Distributor
IBM
5425 Hollister Avenue, Suite 140
Santa Barbara, CA 93111

 

WHAT IS THE NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)?

 

  • The Nationwide Emergency Department Sample (NEDS) tracks information about emergency department (ED) visits across the country. Information includes geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, acute and chronic conditions, and injuries).

  • The NEDS was constructed using the Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID). The SEDD capture discharge information on ED visits that do not result in an admission (e.g., treat-and-release visits and transfers to another hospital). The SID contain information on patients initially seen in the emergency room and then admitted to the same hospital.

  • There are 41 HCUP Partner organizations that contributed to SID and SEDD from which the 2020 NEDS was built: Alaska, Arkansas, Arizona, California, Colorado, Connecticut, the District of Columbia, Florida, Georgia, Hawaii, Iowa, Illinois, Indiana, Kansas, Kentucky, Massachusetts, Maryland, Maine, Michigan, Minnesota, Missouri, Mississippi, Montana, North Carolina, North Dakota, Nebraska, New Hampshire, New Jersey, Nevada, New York, Ohio, Oregon, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Wisconsin, and Wyoming. These States are geographically dispersed and account for 85.0 percent of the total U.S. resident population and 84.0 percent of all U.S. ED visits.

  • Unweighted, the NEDS contains data from 28 million ED visits in 2020. Weighted, the 2020 NEDS describes 123 million ED visits. One of the most distinctive features of the NEDS is its large sample size, which allows for analysis across hospital types and the study of relatively uncommon disorders and procedures. The NEDS is an exceptional resource for conducting research on high-profile emergent health delivery issues.

  • The NEDS is a publicly available database that can be purchased through the HCUP Central Distributor. Annual data files are available for 2006-2020.

  • Users must complete the HCUP Data Use Agreement Training Course prior to receiving the data.

 

WHAT'S NEW IN THE 2020 NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)?

 

  • The overall number of ED visits for data year 2020 decreased by over 15 percent from 2019. The largest decrease was in the second quarter, which had almost 31 percent fewer discharges than the prior year. Further, the percentage of records in which the patient was admitted to the same hospital increased from 14 percent in 2019 to 16 percent in 2020.

  • Beginning with data year 2020, COVID-19-related ED visits may be identified by any-listed ICD-10-CM diagnosis code of "U071" (2019 novel coronavirus disease) on the record. Per coding guidelines, the use of diagnosis code "U071" is based on documentation by the provider or documentation of a positive COVID-19 test result. The ICD-10-CM diagnosis code for COVID-19 was implemented beginning April 1, 2020. There may be other ICD-10-CM codes that reflect conditions related to COVID-19 ED visits.

 

UNDERSTANDING THE NEDS

 

  • This document, Introduction to the NEDS, 2020, summarizes the content of the NEDS and describes the development of the 2020 NEDS sample and weights.

  • Important considerations for data analysis are provided along with references to detailed reports.

  • In-depth documentation for the NEDS is available on the HCUP-US website (www.hcup-us.ahrq.gov/db/nation/neds/nedsdbdocumentation.jsp). Please refer to the detailed documentation before using the data.

  • The coding system used to report diagnoses and inpatient procedures has changed over time (whereas the coding of emergency department procedures continues to use CPT codes):

    • Beginning with data year 2016, the NEDS includes a full calendar year of data with diagnosis and inpatient procedure codes reported using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM/PCS) coding system.

    • In data year 2015, the first 9 months of the NEDS contain ICD-9-CM codes and the last 3 months contain ICD-10-CM/PCS codes.

    • In data year 2014 and prior years, the NEDS contains ICD-9-CM diagnosis and procedure codes.

  • The HCUP-US website has an ICD-10-CM/PCS Resources section that summarizes key issues for researchers using HCUP and other administrative databases that include ICD-10-CM/PCS and ICD-9-CM coding. The web page provides general guidance to users analyzing outcomes that may be affected by the transition to the ICD-10-CM/PCS coding system and lists other related web resources.

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HEALTHCARE COST AND UTILIZATION PROJECT — HCUP
A FEDERAL-STATE-INDUSTRY PARTNERSHIP IN HEALTH DATA

Sponsored by the Agency for Healthcare Research and Quality


HCUP NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)

ABSTRACT

The Nationwide Emergency Department Sample (NEDS) is part of the Healthcare Cost and Utilization Project (HCUP) sponsored by the Agency for Healthcare Research and Quality (AHRQ). The NEDS was created to enable analyses of emergency department (ED) utilization patterns and to support researchers, public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. The ED serves a dual role in the U.S. healthcare system infrastructure—as a point of entry for approximately 50 percent of inpatient hospital admissions and as a setting for treat-and-release outpatient visits.1 The NEDS has many research applications, because it contains information about geographic, hospital, and patient characteristics as well as descriptions of the nature of the visits (e.g., common reasons for ED visits, including injuries).

The NEDS is the largest all-payer ED database that is publicly available in the United States, containing information from 28 million ED visits at 995 sampled hospital-owned EDs in the U.S. Weights are provided to calculate national estimates representing about 123 million ED visits in the United States in 2020.

The NEDS is made possible by the voluntary participation of statewide data organizations that provide HCUP with data from ED visits that may or may not have resulted in a hospital admission. Forty-one HCUP Partner organizations participated in the 2020 NEDS. See Appendix A, Table A1 for a list of HCUP Partner organizations participating in the NEDS.

By stratifying on important hospital characteristics, the NEDS sample is designed to represent all U.S. hospital-owned EDs. The stratified sample design is based on the following five hospital characteristics:

  1. Geographic region (Northeast, Midwest, South, and West)
  2. Trauma center designation (trauma level I, II, III, and nontrauma)
  3. Urban-rural location of the hospital (large metropolitan, small metropolitan, micropolitan, and nonurban residual)
  4. Teaching status (teaching or non-teacing)
  5. Hospital ownership or control (public, for-profit, and not-for-profit).

Because the ICD-10-CM/PCS coding system was introduced on October 1, 2015, trends that rely on diagnoses and procedures may be interrupted. Analyses that do not rely on diagnosis and procedure coding should not be affected.

Access to the NEDS is open to users who sign a Data Use Agreement. Uses are limited to research and aggregate statistical reporting.

For more information on the NEDS, visit the AHRQ-sponsored HCUP User Support (HCUP-US) website at www.hcup-us.ahrq.gov/db/nation/neds/nedsdbdocumentation.jsp.

Return to Introduction

 

INTRODUCTION TO THE NATIONWIDE EMERGENCY DEPARTMENT SAMPLE (NEDS)

 

Overview of NEDS Data

The Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) was created to enable analyses of emergency department (ED) utilization patterns and to support researchers, public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. The ED serves a dual role in the U.S. healthcare system infrastructure, as a point of entry for approximately 50 percent of inpatient hospital admissions and as a setting for treat-and-release outpatient visits.2 The NEDS supports many research applications, because it contains detailed information about geographic, hospital, and patient characteristics as well as the nature of visits (e.g., common reasons for ED visits, acute and chronic conditions, and injuries).

NEDS Data Sources, Hospitals, and ED Visits

The number of States, hospital-owned EDs, and ED visits included in the NEDS varies by year (Table 1). The names of the HCUP Partner organizations that contribute to the NEDS are in Appendix A, Table A1.

Table 1. Number of States, Hospital-Owned Emergency Departments, and Records in the NEDS by Year

Data Year Number of HCUP States in the NEDS HCUP States in the NEDS Number of Hospital-Owned EDs Sampled Number of ED Visits in Sample (Unweighted) Number of ED Visits, Weighted for National Estimates
2020 41 AK, AR, AZ, CA, CO, CT, DC, FL, GA, HI, IA, IL, IN, KS, KY, MA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NJ, NV, NY, OH, OR, RI, SC, SD, TN, TX, UT, VT, WI, and WY 995 28,037,034 123,278,165
2019 41 AK, AR, AZ, CA, CO, CT, DC, FL, GA, HI, IA, IL, IN, KS, KY, MA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NJ, NV, NY, OH, OR, RI, SC, SD, TN, TX, UT, VT, WI, and WY (Added AK, HI, NH, and UT) 989 33,147,251 143,432,284
2018 37 AR, AZ, CA, CO, CT, DC, FL, GA, IA, IL, IN, KS, KY, MA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NJ, NV, NY, OH, OR, RI, SC, SD, TN, TX, VT, WI, and WY (Added MI; UT data were not available) 990 35,807,950 143,454,430
2017 37 AR, AZ, CA, CO, CT, DC, FL, GA, IA, IL, IN, KS, KY, MA, MD, ME, MN, MO, MS, MT, NC, ND, NE, NJ, NV, NY, OH, OR, RI, SC, SD, TN, TX, UT, VT, WI, and WY (Added CO; HI data were not available) 984 33,506,645 144,814,803
2016 37 AR, AZ, CA, CT, DC, FL, GA, HI, IA, IL, IN, KS, KY, MA, MD, ME, MN, MO, MS, MT, NC, ND, NE, NJ, NV, NY, OH, OR, RI, SC, SD, TN, TX, UT, VT, WI, and WY (Added OR and MS) 953 32,680,232 144,842,742
2015 35 AR, AZ, CA, CT, DC, FL, GA, HI, IA, IL, IN, KS, KY, MA, MD, ME, MN, MO, MT, NC, ND, NE, NJ, NV, NY, OH, RI, SC, SD, TN, TX, UT, VT, WI, and WY (Added TX) 953 31,465,407 143,469,670
2014 34 AR, AZ, CA, CT, DC, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, ME, MN, MO, MT, NC, ND, NE, NJ, NV, NY, OH, RI, SC, SD, TN, UT, VT, WI, and WY (Added DC, MT, and WY) 945 31,026,417 137,807,901
2013 30 AR, AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, MN, MO, NC, ND, NE, NJ, NV, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added AR; ME data were not available) 947 29,581,718 134,869,015
2012 30 AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, ME, MN, MO, NC, ND, NE, NJ, NV, NY, OH, RI, SC, SD, TN, UT, VT, and WI 950 31,091,029 134,399,179
2011 30 AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, ME, MN, MO, NC, ND, NE, NJ, NV, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added ND; NH data were not available) 951 29,421,411 131,048,605
2010 28 AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, MN, MO, NC, NE, NJ, NV, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added NV; ME and NH data were not available) 961 28,584,301 128,970,364
2009 29 AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, IL, MA, MD, ME, MN, MO, NC, NE, NH, NJ, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added IL) 964 28,861,047 128,885,040
2008 28 AZ, CA, CT, FL, GA, HI, IA, IN, KS, KY, MA, MD, ME, MN, MO, NC, NE, NH, NJ, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added KY) 980 28,447,148 124,945,264
2007 27 AZ, CA, CT, FL, GA, HI, IA, IN, KS, MA, MD, ME, MN, MO, NC, NE, NH, NJ, NY, OH, RI, SC, SD, TN, UT, VT, and WI (Added NC, NY, RI) 966 26,627,923 122,331,739
2006 24 AZ, CA, CT, FL, GA, HI, IA, IN, KS, MA, MD, ME, MN, MO, NE, NH, NJ, OH, SC, SD, TN, UT, VT, and WI 955 25,702,597 120,033,570
Abbreviations: ED, emergency department; HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample.

Appendix A, Figure A1 represents the geographic distribution of the 41 HCUP Partner organizations participating in the 2020 NEDS. Based on U.S. Census Bureau data, the HCUP NEDS States (with the District of Columbia) account for 85.0 percent of the U.S. population in 2020. The 41 Partner organizations account for 84.0 percent of the ED visits reported in the 2020 American Hospital Association (AHA) Annual Survey Database. Details on the percentage of population and ED visits by region are provided in Appendix A, Table A2.

Identification of HCUP Records With Emergency Department Services

Records for ED visits are contained in two existing HCUP databases:

Both of these HCUP databases contain a core set of clinical and nonclinical data elements defined in a uniform scheme for all patients, regardless of payer. This scheme makes it possible to combine records across databases.

Selection of ED records from the SEDD and SID for the NEDS is based on evidence of ED services reported on the record. HCUP Partner organizations use differing methods to identify ED records. The HCUP criterion for identifying an ED record (i.e., a discharge record for a patient with an ED visit) is that it meets at least one of the following conditions:

Of the 41 HCUP Partner organizations contributing to the 2020 NEDS, 12 (Arkansas, Arizona, California, Connecticut, Florida, Massachusetts, Mississippi, Montana, New Hampshire, Nevada, Orgeon, and Utah) provided a source file that contained only ED treat-and-release records. Because the data source provided a dedicated outpatient ED file, all of the SEDD records were considered ED records, even though information may not have been available to determine whether HCUP criteria were met.


Partner-Specific Restrictions

Some HCUP Partner organizations that contributed data to the NEDS imposed restrictions on the release of certain data elements or on the number and types of hospitals that could be included in the database. In addition, because of confidentiality laws, some data sources were prohibited from providing HCUP with discharge records that indicated specific medical conditions, such as HIV/AIDS or behavioral health conditions. Detailed information on these Partner-specific restrictions is available in Appendix B, Table B1

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ICD-10-CM/PCS Started October 1, 2015 at the Beginning of Fiscal Year 2016

On October 1, 2015, the United States transitioned from using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the Tenth Revision (ICD-10-CM/Procedure Coding System [PCS])code sets for reporting medical diagnoses and inpatient procedures. ICD-10-CM/PCS consists of two parts:

The HCUP User Support (HCUP-US) website has an ICD-10-CM/PCS Resources section that summarizes key issues for researchers using HCUP and other administrative databases that include ICD-9-CM and ICD-10-CM/PCS coding. The web page provides general guidance and forewarning to users analyzing outcomes that may be affected by the transition to the ICD-10-CM/PCS coding system and lists other related web resources.

Return to Introduction

 

File Structure of the NEDS

Because of the size of the NEDS and the difference in information collected on records for patients admitted into the hospital directly from the ED (SID records) and for ED patients that are not admitted (SEDD records), the NEDS is divided into five types of files:

File Structure of the NEDS in all years except 2015. The NEDS is an annual, calendar year file based on discharge date. Prior to 2015, the NEDS includes ICD-9-CM diagnosis and procedure codes. Starting in 2016, the NEDS includes ICD-10-CM/PCS codes.

File structure of the 2015 NEDS. The introduction of ICD-10-CM/PCS in the United States on October 1, 2015, means that the 2015 NEDS includes a combination of codes:

To alert users to this change in the ICD coding scheme, the file structure of the 2015 NEDS differs from the annual files for other data years in three primary ways:

More information about the file structure of the 2015 NEDS is available in the Introduction to the Nationwide Emergency Department Sample (NEDS), 2015, and on the NEDS Database Documentation page of the HCUP-US website.

NEDS Data Elements

The coding of data elements in the NEDS is consistent with other HCUP databases. The following three objectives guided the definition of data elements in all HCUP databases:

More information on the coding of HCUP data elements is available on the HCUP Coding Practices page of the HCUP-US website.

After analyzing the availability of information from the HCUP Partner organizations, a set of common fields to be available in the NEDS was created. The NEDS contains more than 100 clinical and nonclinical variables provided in a hospital discharge abstract, such as the following:

Appendix C identifies the data elements in each NEDS file:

The tables in Appendix C provide summary documentation for the data. Please refer to the NEDS Description of Data Elements page on the HCUP-US website for more comprehensive information about data elements.

Getting Started

The HCUP NEDS is distributed as comma-separated values (CSV) files delivered via secure digital download from the online HCUP Central Distributor. The files are compressed and encrypted with SecureZIP® from PKWARE®.

The NEDS product is downloaded in a single zipped file for each year that contains several data-related files and accompanying documentation. The five compressed data-related files are as follows:

  1. Core File (NEDS_2020_Core.zip)
  2. Supplemental ED File (NEDS_2020_ED.zip)
  3. Supplemental Inpatient File (NEDS_2020_IP.zip)
  4. Hospital Weights File (NEDS_2020_Hospital.zip)
  5. Diagnosis and Procedure Groups File (NEDS_2020_DX_PR_GRPS.zip)
To load and analyze the NEDS data on a computer, users will need the following:

The total size of the CSV version of the NEDS is 45 GB. The NEDS files loaded into SAS are about 11 GB. In SAS, the largest use of space typically occurs during PROC SORT, which requires workspace about three times the size of the file. Thus, the NEDS files would require at least 40 GB of available workspace to perform a sort procedure. Most SAS data steps will require twice the storage of the file, so that both the input and output files can coexist. The NEDS files loaded into SPSS are about 27 GB. Because Stata loads the entire file into memory, it may not be possible to load every data element in the NEDS Core file into Stata. Stata users will need to maximize memory and use the "_skip" option to select a subset of data elements. More details are provided in the Stata load programs.

With a file of this size and without careful planning, space could easily become a problem in a multistep program. It is not common to produce several versions of a file during data preparation, as well as further multiple versions for analysis. Therefore, the amount of space required could escalate rapidly.

Decompressing the NEDS Files

To extract the data files from the compressed download file, follow these steps:

  1. Create a directory for the NEDS on your hard drive.
  2. Unzip the compressed NEDS product file into the new directory using a third-party zip utility. This will place four compressed, encrypted data-related files in the new directory. You will be prompted to enter the encryption password (sent separately by email) to decrypt the file.

    Please note that attempts to unzip encrypted files using the built-in zip utility in Windows® (Windows Explorer) or Macintosh® (Archive Utility) will produce an error message warning of incorrect password and/or file or folder errors. The solution is to use a third-party zip utility.

    Third-party zip utilities are available from the following reputable vendors on their official websites.

    • ZIP Reader (Windows) (free download offered by the PKWARE corporation)
    • SecureZIP for Mac or Windows (free evaluation and licensed/fee software offered by the PKWARE corporation)
    • WinZip (Windows) (evaluation and fee versions offered by the WinZip corporation)
    • Stuffit Expander® (Mac) (free evaluation and licensed/fee software offered by Smith Micro corporation)

  3. Unzip each of the compressed, encrypted data-related files using the same password and third-party zip utility method. This will place the data-related CSV files in this same directory by default.

Downloading and Running the Load Programs

Programs to load the data into SAS, SPSS, or Stata, are available on the HCUP-US website. To download and run the load programs, follow these steps:

  1. Go to the NEDS Database Documentation page on the HCUP-US website.
  2. Go to the File Specifications and Load Programs" section on this page.
  3. Click on "Nationwide SAS Load Programs", "Nationwide SPSS Load Programs", or "Nationwide Stata Load Programs" to go to the corresponding Load Programs page.
  4. Select the data year and the database ("NEDS") from the drop down lists on this page. Or you may select "NEDS Load All Years" to obtain a zipped file with all load programs for multiple years at once.
  5. Select and save the load programs you need. The load programs are specific to the data year and data-related file. For example, the load program for the 2020 NEDS Core file is found under the link "SAS NEDS 2020 Core file" in the list generated by selecting "2020" and "NEDS." Save the load programs into the same directory as the NEDS CSV files on your computer.
  6. Edit and run the load programs as appropriate for your computing environment to create the analysis files. For example, modify the directory paths to point to the location of your input and output files.

NEDS Documentation

Comprehensive documentation for the NEDS files is available on the NEDS Database Documentation page of the HCUP-US website. Users of the NEDS can access complete file documentation, including variable notes, file layouts, summary statistics, and related technical reports. Data users can also download SAS, SPSS, and Stata load programs. These important resources help the user understand the structure and content of the NEDS and aid in using the database. Appendix A, Table A3 details the comprehensive NEDS documentation available on HCUP-US.

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HCUP Online Tutorials

For additional assistance, AHRQ has created the HCUP Online Tutorial Series, a series of free, interactive courses that provide information on using HCUP data and tools and training on technical methods for conducting research with HCUP data. Topics include an HCUP Overview Course and these tutorials:

New tutorials are added periodically. The tutorials can be found on the HCUP Online Tutorial Series page of the HCUP-US website.

SAMPLING DESIGN OF THE NEDS

The NEDS is built using a 20-percent stratified sample of hospital-owned EDs in the United States. The main objective of a stratified sample is to ensure that it is representative of the target universe. By stratifying on important hospital characteristics, the NEDS represents a "microcosm" of EDs in the United States. For example, by including trauma center designation in the sampling strategy, the NEDS has the same percentage of trauma hospitals as the entire United States. The NEDS contains all of the ED visits that occurred at the hospital-owned EDs in the sample.

Universe of Hospital-Owned Emergency Departments

A feasibility study performed in 2008 assessed several possible data sources comprising the universe of hospital-owned EDs in the United States: the American Hospital Association (AHA) Annual Survey Database (Health Forum, LLC © 2007), Verispan, LLC databases (now called IMS Health, Inc.), and the Centers for Medicare & Medicaid Services Hospital Cost Reports. The AHA Annual Survey Database was chosen, for two main reasons. First, the AHA data provide the necessary hospital characteristics, such as ownership type and teaching status, and also report total ED visits for hospitals. Second, the crosswalk linkage from the HCUP databases to the AHA data is already established. The universe of hospital-owned EDs is therefore defined as the AHA community, nonrehabilitation hospitals that reported total ED visits. The AHA defines community hospitals as "all non-Federal, short-term, general, and other specialty hospitals open to the public."4 Included among community hospitals are pediatric institutions, public hospitals, and academic medical centers.

Sampling Frame of the NEDS

The sampling frame of the NEDS does not cover the entire target universe. The target universe consists of all the hospital-owned EDs in the U.S. (including the District of Columbia). The coverage of the sampling frame is limited because HCUP ED data (SID and SEDD) are not available in all States, the identification of HCUP hospitals in the AHA is imperfect, and the AHA data is incomplete. The sampling frame, a set of hospital-owned EDs, consists of AHA community, nonrehabilitation hospitals that report total ED visits and that could be accurately matched to the ED data provided to HCUP. If an ED in the AHA survey could not be matched to the ED data provided by the HCUP data source, it was eliminated from the sampling frame (but not from the target universe).

Stratification Variables

The following hospital characteristics were used for sample stratification: U.S. census region, trauma center designation, urban-rural location of the hospital, ownership, and teaching status. ED bed size was not used because no data source for this information could be identified. A number of data sources report the bed size of the hospital, but no source distinguishes between inpatient and ED beds.

The NEDS stratification variables are described below and detailed in Appendix A, Table A4.

U.S. Census Region

The four Census regions–Northeast, Midwest, South, and West–were used to stratify EDs by geographic location because practice patterns may vary substantially by region. Appendix A, Figure A1 shows the NEDS States by region.

Trauma Centers

A trauma center is a hospital equipped to provide comprehensive emergency medical services 24 hours a day, 365 days a year to patients with traumatic injuries. In 1976, the American College of Surgeons Committee on Trauma (ACS/COT) defined five levels of trauma centers:5

The ACS/COT verifies hospitals as trauma level I, II, or III.6 It is important to note that although all level I, II, and III trauma centers offer a high level of trauma care, there may be differences in the specific services and resources offered by hospitals between the different levels. Trauma levels IV and V are designated at the State level (and not by ACS/COT) with varying criteria applied across States.

The level of the trauma centers in the NEDS was identified using the Trauma Information Exchange Program (TIEP) database, a national inventory of trauma centers in the United States collected by the American Trauma Society (ATS).7 The TIEP database identifies all U.S. trauma centers that are level I, II, or III that treat both adults and children. TIEP includes some information on trauma centers within children's hospitals, but this is not the focus. To ensure that all trauma centers are identified for the NEDS, ATS reviews the ACS/COT list of trauma centers and all State-specific websites on emergency services to identify any additional trauma centers within children's hospitals and their associated trauma levels.

The stratum for trauma center in the NEDS was limited to trauma levels I, II, and III. The distinction between Level IV and V centers was not incorporated because the criteria for these designations varied across States. For hospital confidentiality purposes, a collapsed stratification was necessary if the stratum size in the universe or the frame was fewer than two hospitals. In such situations, the collapsed categories varied by data year:

The change between the 2010 and 2011 NEDS was prompted by differences between injury-related services provided by level I and II trauma centers versus injury-related services provided by level III trauma centers. Services at level III trauma centers were more similar to non-trauma hospitals.

Urban-Rural Location of the ED

The urban-rural location of hospital-owned EDs was determined by the county in which the hospital was located. The categorization is based on Urban Influence Codes (UIC).8 Starting in the 2014 NEDS, the categorization is a simplified adaptation of the 2013 version of the UIC. Prior to 2014, the categorization is a simplified adaptation of the 2003 version of the UIC. The 12 detailed UIC categories are combined into 4 broader categories:

If the stratum size in the universe or frame was fewer than two hospitals, a collapsed stratification of metropolitan (large and small), nonmetropolitan (micropolitan and nonurban residual), small metropolitan and micropolitan, 9 or all areas10 was necessary.

Teaching Status

A hospital-owned ED is considered a teaching hospital if it has one or more Accreditation Council for Graduate Medical Education (ACGME)-approved residency program, is a member of the Council of Teaching Hospitals, or has a ratio of full-time equivalent interns and residents to beds of 0.25 or higher. Beginning with the 2014 NEDS, there is an increase in the number of hospitals identified as teaching facilities because the AHA Annual Survey reported an increase in facilities with approved residency programs. About this time, the ACGME became the primary organization for residency training approval. Because there are very few teaching hospitals in micropolitan and rural areas, teaching status was only used to stratify EDs in metropolitan areas.

Hospital Ownership

Hospital ownership or control was categorized according to information reported in the AHA Annual Survey Database. The ownership categories include (1) public (government, non-Federal), (2) voluntary (private, not for profit), and (3) proprietary (private, investor owned/for profit).

When there were enough hospitals of each type, EDs were stratified into public, voluntary, and proprietary categories. If necessary, because of small stratum size in the universe, a collapsed stratification of public versus private was used; that is, the voluntary, nonprofit, and proprietary/for-profit hospitals were combined to form a single "private" category. Stratification based on ownership or control was not implemented in some regions (e.g., Northeast) because of the dominance of one hospital type.

Return to Introduction

 

Sample Weights

To enable nationwide estimates, weights were developed using the AHA universe as the standard. Two weights were developed to allow analysis of two distinct units of observation: facilities (hospital-owned EDs) and ED visits. Hospital-level weights expand the NEDS sample of EDs to represent the universe of hospital-owned EDs. Similarly, discharge-level weights expand the ED visits in the NEDS sample to represent the universe of ED visits.

Hospital Weights

Hospital weights were calculated by stratum. Hospital-owned EDs were stratified on the same variables that were used for sampling: geographic region, trauma center designation, urban-rural location, teaching status, and ownership or control. The strata that were collapsed for sampling were also collapsed for sample weight calculations. Within each stratum, s, each ED in the NEDS sample received a weight:

where Ws(universe) was the ED universe weight, and Ns(universe) and Ns(sample) were the number of hospital-owned EDs within stratum s in the universe and sample, respectively. Thus, each hospital's universe weight (HOSPWT) is equal to the number of universe hospitals it represents during that year. Because 20 percent of the hospitals in each stratum were sampled when possible, the ED weights were usually near a value of 5.

Discharge Weights

Discharge weights were also calculated by stratum. Hospital-owned EDs were stratified in a manner similar to that for universe hospital-weight calculations. Within stratum s for hospital i, the universe weight for each visit in the NEDS sample was calculated as follows:

where DWis(universe) was the discharge weight; DNs(universe) is the number of ED visits from community, non-rehabilitation hospitals in the universe within stratum s; ADNs(sample) ) is the number of adjusted ED visits from sample hospitals selected for the NEDS; and Qi represents the number of quarters of ED visits contributed by hospital i to the NEDS (usually Qi = 4). Thus, each discharge's weight (DISCWT) is equal to the number of universe ED visits it represents in stratum s during that year.

Final NEDS Sample

The target universe for the NEDS was: (1) community, non-rehabilitation hospital-owned EDs in the United States that were included in the 2020 AHA Annual Survey Database, and (2) reported total ED visits. Excluded were 47 nonrural hospitals that reported fewer than 10 ED visits in data year 2020.

The NEDS sampling frame included hospital-owned ED visits from community, non-rehabilitation hospitals in the 41 HCUP Partner organizations that provided discharge abstracts on patients admitted to the hospital through the ED and on patients treated and released or transferred to another hospital from the ED. The HCUP hospitals were required to be represented in the AHA data and have no more than 90 percent of their ED visits resulting in admission. Appendix A, Table A5 lists the number of EDs and ED visits in the target universe, the sampling frame, and the sample.

The NEDS is a stratified probability sample of hospital-owned EDs in the frame. Sampling probabilities were calculated to select 20 percent of the universe contained in each stratum, which was defined by region, trauma designation, urban-rural location, teaching status, and hospital ownership or control. A sample size of 20 percent was based on previous experience with similar research databases. A larger sample would be cumbersome for data users, given that a 20-percent sample contains about 30 million records. A 20-percent sample also enables an analyst to split the NEDS into two 10-percent subsamples for estimation and validation of models.

Using the universe of U.S. hospital-owned EDs, strata were defined by region, trauma designation, urban-rural location, teaching status, and hospital ownership or control. Strata with fewer than two hospitals in the universe and frame were collapsed with adjacent strata on the dimensions of urban-rural location, trauma designation, or ownership or control. Prior to sampling, the list of frame hospitals within each stratum is sorted as follows to ensure geographic representation within strata: (1) sorted by the first three digits of the hospital's ZIP Code and (2) sorted by a random number within the three-digit ZIP Code 11 After stratifying and sorting the frame hospitals, a random sample of up to 20 percent of the total number of hospital-owned EDs in the United States was selected within each stratum. A stratum with a shortfall was defined as having an insufficient number of EDs in the frame to meet the threshold of 20 percent of the universe for that stratum. In strata with shortfalls, the sampling rate from the universe was less than 20 percent and all possible EDs in the frame were selected for the NEDS. In contrast, the sampling rate is larger than 20 percent in some strata because protecting hospital confidentiality required a minimum of two sampled EDs in each stratum.

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HOW TO USE THE NEDS FOR DATA ANALYSIS

This section provides a brief synopsis of special considerations for analyzing NEDS data. For more details, refer to the comprehensive documentation on the NEDS Database Documentation page of the HCUP-US website.

Data Use Agreement

Anyone accessing the NEDS (whether or not they are the original recipient of the data) must complete the online HCUP Data Use Agreement Training available on the HCUP-US website and then read and sign a Data Use Agreement. A copy of the signed Data Use Agreements must be sent to the HCUP Central Distributor.

Limitations of the NEDS

The NEDS contains about 28 million ED records and more than 100 clinical and nonclinical data elements. A multitude of research studies can be conducted with the data, but there are some limitations.

Identifying Different Types of ED Events

The HCUP data element ED event distinguishes among the different types of ED visits: Appendix A, Table A6 provides the number and percentage of records in the 2020 NEDS for each of the five ED event types.

Calculating National Estimates

To produce national estimates, weights MUST be applied to the sample.

Because the NEDS is a stratified sample, proper statistical techniques must be used to calculate standard errors and confidence intervals. For detailed instructions, refer to the HCUP Methods Series report #2003-02 Calculating Nationwide Inpatient Sample (NIS) Variances for Data Years 2011 and Earlier on the HCUP-US website. The NEDS uses a stratified sampling design similar to the HCUP NIS prior to 2012, so techniques appropriate for the NIS prior to 2012 are also appropriate for the NEDS.

When creating national estimates, it is advisable to check results against other data sources, if available. Summary independent benchmarks for NEDS estimates are in Appendix D. Other ED data sources include, for example, the National Hospital Ambulatory Medical Care Survey which has an ED component and publishes national health statistics annually.

To ensure that weights are applied appropriately and estimates and variances are calculated accurately, researchers can also access HCUPnet the free online query system. HCUPnet is a web-based query tool for identifying, tracking, analyzing, and comparing statistics on hospitals at the national, regional, and State levels. HCUPnet offers easy access to national statistics and trends as well as selected State statistics about hospital stays, ED visits, and ambulatory surgeries. This tool provides step-by-step guidance, helping researchers quickly obtain the statistics they need. HCUPnet generates statistics from the HCUP databases.

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Choosing Data Elements for Analysis

For any data element of interest, the analyst should first examine descriptive statistics such as the range of values and the number of missing values. Summary statistics are also available on the NEDS Summary Statistics page of the HCUP-US website. When anomalies (e.g., a large amount of missing values) are detected, descriptive statistics by region or by hospital (HOSP_ED) may be informative.

ICD-9-CM and ICD-10-CM/PCS Diagnosis and Procedure Codes and CPT Procedure Codes


Missing Values

Missing data values can compromise the quality of estimates. For example, if the outcome for ED visits with missing values differs from the outcome for ED visits with valid values, then estimates for that outcome will be biased and inaccurately represent the ED utilization patterns. Several techniques are available to help overcome this bias. One strategy is to use imputation to replace missing values with acceptable values. Another strategy is to use sample weight adjustments to compensate for missing values. Descriptions of such data preparation and adjustment are outside the scope of this report; however, it is recommended that researchers evaluate and adjust for missing data, if necessary.

Alternatively, if the cases with and without missing values are assumed to be similar with respect to their outcomes, no adjustment may be necessary for estimates of means and rates because the nonmissing cases would be representative of the missing cases. However, some adjustment may still be necessary for the estimates of totals. Sums of data elements (e.g., aggregate ED charges) containing missing values would be incomplete because cases with missing values would be omitted from the calculations. Estimates of the sum of charges can be calculated as the product of the number of cases times the average charge to account for records with missing information.

Variance Calculations

It may be important for researchers to calculate a measure of precision for some estimates based on the NEDS sample data. Variance estimates must account for both the sampling design and the form of the statistic. The sampling design consisted of a stratified, single-stage cluster sample. A stratified random sample of hospital-owned EDs (clusters) was drawn, and then all ED visits were included from each selected hospital. To accurately calculate variances from the NEDS, appropriate statistical software and techniques must be used. For detailed instructions, refer to the HCUP Methods Series report #2003-02 Calculating Nationwide Inpatient Sample (NIS) Variances for Data Years 2011 and Earlier. Prior to 2012, the NIS used a stratified sample design similar to the NEDS, so techniques appropriate for the NIS prior to 2012 are also appropriate for the NEDS.

A multitude of statistics can be estimated from the NEDS data. Several computer programs that calculate statistics and their variances from sample survey data are listed in the next section. Some of these programs use general methods of variance calculations (e.g., the jackknife and balanced half-sample replications) that account for the sampling design. However, it may be desirable to calculate variances using formulas specifically developed for certain statistics.

Variance calculations that factor in the cluster and strata are based on finite-sample theory, which is an appropriate method for obtaining cross-sectional, nationwide estimates of outcomes. According to finite-sample theory, the intent of the estimation process is to obtain estimates that are precise representations of the nationwide population at a specific point in time. In the context of the NEDS, any estimates that attempt to accurately describe characteristics and interrelationships among hospitals and ED visits during a specific year should be governed by finite-sample theory. Examples would be estimates of expenditure and utilization patterns.

Alternatively, in the study of hypothetical population outcomes not limited to a specific point in time, the concept of a "superpopulation" may be useful. Analysts may be less interested in specific characteristics of the finite population (and period) from which the sample was drawn than they are in hypothetical characteristics of a conceptual superpopulation from which any particular finite population in a given year might have been drawn. According to this superpopulation model, the nationwide population in a given year is only a snapshot in time of the possible interrelationships between hospital, market, and discharge characteristics. In a given year, all possible interactions between such characteristics may not have been observed, but analysts may wish to predict or simulate interrelationships that may occur in the future.

Under the finite-population model, the variances of estimates approach zero as the sampling fraction approaches one. This is the case because the population is defined at that point in time and because the estimate is for a characteristic as it existed when sampled. The superpopulation model, in contrast, adopts a stochastic viewpoint rather than a deterministic viewpoint. That is, the nationwide population in a particular year is viewed as a random sample of some underlying superpopulation over time. Different methods are used for calculating variances under the two sample theories. The choice of an appropriate method for calculating variances for nationwide estimates depends on the type of measure and the intent of the estimation process.

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Computer Software for Applying Weights and Calculating Variance

The hospital weights produce hospital-level statistics for analysis at the hospital-owned ED unit of analysis. In contrast, the discharge weights produce visit-level statistics for analysis that centers on the ED visit as the unit of analysis.

In most cases, computer programs are readily available to perform both types of calculations. Several statistical programming packages allow weighted analyses.12 For example, nearly all SAS procedures can incorporate weights. In addition, several statistical analysis programs have been developed to specifically calculate statistics and their standard errors from survey data. Version 8 or later of SAS contains procedures (PROC SURVEYMEANS and PROC SURVEYREG) for calculating statistics from complex sampling designs. Stata and SUDAAN® are two other common statistical software packages that perform calculations for numerous statistics arising from the stratified, single-stage cluster sampling design. Examples of the use of SAS, SUDAAN, and Stata to calculate NIS variances are presented in the special report Calculating Nationwide Inpatient Sample (NIS) Variances for Data Years 2011 and Earlier. Although the examples using the NIS also apply to the NEDS, it should be noted that the NEDS is a much larger dataset. Please consult the documentation for the different software packages concerning the use of large databases. For a review of programs to calculate statistics from survey data, visit the Summary of Survey Analysis Software page on the Harvard Medical School website.

The NEDS includes a Hospital Weights File with variables required by these programs to calculate finite-population statistics. The file includes hospital identifiers (Primary Sampling Units), stratification variables, and stratum-specific totals for the number of ED visits and hospitals so that finite-population corrections can be applied to variance estimates.

In addition to these subroutines, standard errors can be estimated by validation and cross-validation techniques. Given that a very large number of observations will be available for most NEDS analyses, it may be feasible to set aside a part of the data for validation purposes. Standard errors and confidence intervals then can be calculated from the validation data.

If the analytic file is too small to set aside a large validation sample, cross-validation techniques may be used. For example, 10-fold cross-validation would split the data into 10 subsets of equal size. The estimation would take place in 10 iterations. In each iteration, the outcome of interest is predicted for one-tenth of the observations by an estimate based on a model that is fit to the other nine-tenths of the observations. Unbiased estimates of error variance are then obtained by comparing the actual values to the predicted values obtained in this manner.

COMPARABLE ED DATA SOURCES

To aid in understanding the NEDS, analysts can compare national estimates from the NEDS to other available data sources (Table 2). Each of the ED data sources in Table 2 has potential for use in research addressing ED utilization and policy.

Table 2. Sources of Emergency Department (ED) Data by Type

Type of ED Data ED Data Source Description
National inventories of EDs AHA Annual Survey Data Database containing characteristics and descriptions of hospitals in the United States reported by hospitals via survey. Owned by Health Forum.
National Emergency Department Inventory — USA Inventory of ED locations in the United States and annual ED visit volume that integrates information from the AHA Annual Survey Database, the Hospital Market Profiling Solution© internet searches, and direct communication with hospital staff. Created by the Emergency Medicine Network.
ED visit information from a sample of EDs HCUP Nationwide Emergency Department Sample Nationwide sample drawn from the HCUP SID and SEDD, stratified and weighted to be nationally representative of ED visits and facilities. Sponsored by AHRQ.
National Hospital Ambulatory Medical Care Survey National probability sample survey of utilization and provision of ambulatory services in hospital emergency and outpatient departments. Sponsored by the National Center for Health Statistics of the CDC.
National Electronic Injury Surveillance System - All Injury Program National probability sample providing counts of injuries seen in the ED. Sponsored by the National Center for Injury Prevention and Control of the CDC and the U.S. Consumer Product Safety Commission.
ED visit information from a sample of patients National Health Interview Survey A comprehensive survey of the civilian noninstitutionalized population residing in the United States at the time of the interview. Sponsored by the National Center for Health Statistics of the CDC.
Abbreviations: AHA, American Hospital Association; AHRQ, Agency for Healthcare Research and Quality; CDC, the Centers for Disease Control and Prevention; HCUP, Healthcare Cost and Utilization Project; SEDD, State Emergency Department Databases; SID, State Inpatient Databases.

Information on total ED visits in 2020 for the United States was available from four data sources (AHA, NEDS, National Health Interview Survey, and National Hospital Ambulatory Medical Care Survey)13. Appendix D, Figure D1, displays the range of aggregate ED visits; Appendix D, Table D1 lists the total ED visits in the United States by census region. The total U.S. ED visit counts are relatively consistent across the data sources. The South consistently had the highest number of ED visits.

Estimates of the number of hospital-owned EDs by ED visit volume are available from two data sources (NEDS and AHA) and are displayed in Appendix D, Table D2.

Estimates of the number of ED visits related to nonfatal ED visits are available from two data sources (NEDS and National Electronic Injury Surveillance System - All Injury Program) and are displayed in Appendix D, Table D3.

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Appendix A: NEDS States, Sampling Strata and Rates, and Website Resources

 

Table A1. States Data Organizations Providing SID and SEDD and Participating in the 2020 NEDS

State Data Organization
AK Alaska Department of Health and Social Services
AR Arkansas Department of Health
AZ Arizona Department of Health Services
CA California Office of Statewide Health Planning & Development
CO Colorado Hospital Association
CT Connecticut Hospital Association
DC District of Columbia Hospital Association
FL Florida Agency for Health Care Administration
GA Georgia Hospital Association
HI Hawaii Laulima Data Alliance
IA Iowa Hospital Association
IL Illinois Department of Public Health
IN Indiana Hospital Association
KS Kansas Hospital Association
KY Kentucky Cabinet for Health and Family Services
MA Massachusetts Center for Health Information and Analysis
MD Maryland Health Services Cost Review Commission
ME Maine Health Data Organization
MI Michigan Health and Hospital Association
MN Minnesota Hospital Association
MO Missouri Hospital Industry Data Institute
MS Mississippi State Department of Health
MT Montana Hospital Association
NC North Carolina Department of Health and Human Services
ND North Dakota (data provided by the Minnesota Hospital Association)
NE Nebraska Hospital Association
NJ New Jersey Department of Health
NV Nevada Department of Health and Human Services
NH New Hampshire Department of Health & Human Services
NY New York State Department of Health
OH Ohio Hospital Association
OR Oregon Association of Hospitals and Health Systems Oregon Office of Health Analytics
RI Rhode Island Department of Health
SC South Carolina Revenue and Fiscal Affairs Office
SD South Dakota Association of Healthcare Organizations
TN Tennessee Hospital Association
TX Texas Health Care Information Collection
UT Utah Department of Health
VT Vermont Association of Hospitals and Health Systems
WI Wisconsin Department of Health Services
WY Wyoming Hospital Association
Abbreviation: NEDS, Nationwide Emergency Department Sample.


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Figure A1. Map of States Providing SID and SEDD to HCUP and Participating in the 2020 NEDS

Figure A.1. displays a US map illustrating states in the NEDS by Region. In the Western region, AK, AZ, CA, CO, HI, MT, NV, OR, UT, WY are in the HCUP NEDS. The following states are not in the NEDS in this region - ID, NM, WA. In the Midwestern region, IA, IN, IL, KS, MN, MO, ND, NE, OH, SD, WI are in the HCUP NEDS. In the Northeastern region, CT, MA, ME, NH, NJ, NY, RI, VT are in the HCUP NEDS. The following state is not in the NEDS in this region - PA. In the Southern region, AR, DC, FL, GA, KY, MD, MS, NC, SC, TN, TX are in the HCUP NEDS. The following states are not in the NEDS in this region - AL, DE, LA, OK, VA, WV

Abbreviations: HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample.

The above graphic outlines 2020 states in the NEDS by Region. In the Western region, AK, AZ, CA, CO, HI, MT, NV, OR, UT, WY are in the HCUP NEDS. The following states are not in the NEDS in this region - ID, NM, WA. In the Midwestern region, IA, IN, IL, KS, MN, MO, ND, NE, OH, SD, WI are in the HCUP NEDS. In the Northeastern region, CT, MA, ME, NH, NJ, NY, RI, VT are in the HCUP NEDS. The following state is not in the NEDS in this region - PA. In the Southern region, AR, DC, FL, GA, KY, MD, MS, NC, SC, TN, TX are in the HCUP NEDS. The following states are not in the NEDS in this region - AL, DE, LA, OK, VA, WV.



Table A2. Coverage of the U.S. Population and AHA ED Visits by the 41 NEDS States, 2020

Region Population, 2020 Population Residing in NEDS States Percent of Population Residing in NEDS States Number of AHA ED Visits, 2020 Number of ED Visits in NEDS States Percent of ED Visits in NEDS States
Northeast 57,525,633 44,536,008 77.4 21,881,692 16,416,486 75.0
Midwest 68,935,174 68,935,174 100.0 27,542,194 27,542,194 100.0
South 126,409,007 101,357,242 80.2 50,376,080 39,970,382 79.3
West 78,631,266 66,947,143 85.1 23,478,199 19,676,691 83.8
U.S. 331,501,080 281,775,567 85.0 123,278,165 103,605,753 84.0
Abbreviations: AHA, American Hospital Association; ED, emergency department; HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample.
Source: Population counts from the U.S. Census Bureau, Annual Estimates of the Population for the United States, Regions, States, and Puerto Rico: April 1, 2010 to July 1, 2021 (NST-EST2021-01, released December 2021). AHA ED visit counts from the American Hospital Association Annual Survey of Hospitals, 2020. ED visit counts for NEDS States from the HCUP SID and SEDD.


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Table A3. NEDS-Related Reports and Database Documentation Available on the HCUP-US Website

Description of the NEDS Database
  • NEDS Overview
    • HCUP Partners in the NEDS
  • Introduction to the NEDS, 2019 (this document) and prior years
  • NEDS Related Reports

Restrictions on Use
  • HCUP Data Use Agreement Training
  • Data Use Agreement for the HCUP Nationwide Databases
  • Requirements for Publishing With HCUP data

File Specifications and Load Programs

  • NEDS File Specifications - details data file names, number of records, record length, and record layout
  • Nationwide SAS Load Programs
  • Nationwide SPSS Load Programs
  • Nationwide Stata Load Programs

Data Elements
  • NEDS Description of Data Elements - details uniform coding and State-specific idiosyncrasies
  • Summary Statistics - lists means and frequencies on nearly all data elements
  • Frequencies by Diagnosis and Procedure Codes, NEDS, 2016-2020 - includes frequency distributions for ICD-10-CM/PCS codes (individually and by the CCSR categories).

Additional Resources for NEDS Data Elements
  • HCUP Quality Control Procedures - describes procedures used to assess data quality
  • HCUP Coding Practices - describes how HCUP data elements are coded
  • HCUP Hospital Identifiers - explains data elements that characterize individual hospitals
  ICD-10-CM/PCS Data Included in the NEDS Starting With 2015

  • NEDS Changes Beginning Data Year 2016
  • Caution: 2015 NEDS includes ICD-9-CM and ICD-10-CM/PCS
    • 2015 NEDS Revised File Structure and New Data Elements
  • Additional ICD-10-CM/PCS Resources - contains documentation to assist with the transition to ICD-10-CM/PCS
  • HCUP Software Tools Tutorial

Known Data Issues

  • 2011
  • 2006 AND 2007

HCUP Tools: Labels and Formats

  • Clinical Classifications Software
  • Format Programs - to create value labels
    • DRG formats
    • HCUP formats
    • HCUP Diagnoses and Procedure Groups, Formats, including Clinical Classifications Software categories
    • ICD-9-CM formats
    • ICD-10-CM formats

Obtaining HCUP Data

  • Purchase HCUP Data from the HCUP Central Distributor

Abbreviations: DRG, diagnosis-related group; HCUP, Healthcare Cost and Utilization Project; HCUP-US, Healthcare Cost and Utilization Project User Support; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; ICD-10-CM, International Classification of Diseases, Tenth Revision, Clinical Modification; NEDS, Nationwide Emergency Department Sample.


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Table A4. NEDS Sampling Stratifiers

Stratifier Values
Region 1: Northeast
2: Midwest
3: South
4: West
Trauma 0: Not a trauma center
1: Trauma center level I
2: Trauma center level II
3: Trauma center level III

Collapsed categories used for strata with small sample sizes
4: Nontrauma or trauma center level III (beginning in the 2011 NEDS)
7: Trauma center level II or III (beginning in the 2018 NEDS)
8: Trauma center level I or II (in all years of the NEDS)
9: Trauma center level I, II or III (only in the 2006-2010 NEDS)
Urban-Rural 1: Large metropolitan
2: Small metropolitan
3: Micropolitan
4: Non-urban residual

Collapsed categories used for strata with small sample sizes
6: Any urban-rural location (used in the South in 2014)
7: Small metropolitan and micropolitan (used in the South in 2011-2015)
8: Metropolitan (large and small)
9: Nonmetropolitan (micropolitan and nonurban location)
Teaching 0: Metropolitan nonteaching
1: Metropolitan teaching
2: Nonmetropolitan teaching and nonteaching
Control 0: All (used for combining public, voluntary, and private)
1: Public – government, non-Federal
2: Voluntary – private, nonprofit
3: Proprietary – private, investor-owned/for-profit
4: Private (used for combining private voluntary and proprietary)
Abbreviation: NEDS, Nationwide Emergency Department Sample


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Table A5. Size of NEDS Target Universe, Sampling Frame, and Sample, 2020

Category Description Number of Hospital-Owned EDs, 2020 Number of ED Events, 2020
Target Universe EDs in community, nonrehabilitation U.S. hospitals that reported total ED visits in the AHA Annual Survey Database 4,590 123,278,165
Sampling Frame EDs in the 40 States and the District of Columbia that provide information on ED visits that result and do not result in admission 3,531 95,910,831
2020 NEDS 20 percent sample of target universe drawn from the sampling frame 995 28,037,034
Abbreviations: ED, emergency department; NEDS, Nationwide Emergency Department Sample.
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2020.


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Table A6. Number and Percent of ED Visits by Discharge Status, 2020

Type of ED Visit Based on Discharge Status from the ED Number of ED Visits ED Visits, %
ED visit in which the patient was treated and released 100,523,389 81.5
ED visit in which the patient was admitted to the same hospital 20,091,310 16.3
ED visit in which the patient was transferred to another short-term hospital 2,359,079 1.9
ED visit in which the patient died in the ED 231,626 0.2
ED visit in which patient was not admitted to the same hospital, destination unknown 71,500 0.1
ED visit in which the patient was discharged alive, destination unknown (but not admitted) 1,263 0.0
Abbreviation: ED, emergency department; NEDS, Nationwide Emergency Department Sample.
Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2020.


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Appendix B: Partner-Specific Restrictions

 

Table B1 enumerates the types of restrictions applied to the 2020 Nationwide Emergency Department Sample. Restrictions include the following types:

Table B1. Partner-Specific Restrictions

Confidentiality of Hospitals
Limitations on sampling to ensure hospital confidentiality:
  • For a subset of Partners:
    • Prior to collapsing strata: If there is a "unique" hospital in the State, it is excluded from sampling. Unique is defined as the only hospital in the State universe for a stratum. For example, if there is only one rural, nonteaching, trauma level III hospital in a State, then it is excluded from the sampling frame.
    • After sampling: Stratifier data elements are set to missing if the stratum had fewer than two hospitals in the universe of the State's hospitals.

 

Confidentiality of Records
Limitations on selected data elements to ensure patient confidentiality:
  • Age (AGE) values greater than 90 are set to 90 for all NEDS records.
  • At least one Partner requires that ages in years (AGE) be set to the midpoints of age ranges.
  • At least one Partner requires that admission month (AMONTH) be set to missing on all records.

 

Limited Reporting of Diagnosis Codes for Medical Misadventures and Adverse Effects
  • At least one Partner removes diagnosis codes for medical misadventures and adverse effects from the data files supplied to HCUP.

 

Missing Information for Specific Populations of Patients
  • HIV
    • At least one Partner excludes records for HIV patients from the files provided to HCUP. Therefore, these records are not included in the NEDS.
    • Alternatively, at least one Partner includes records for HIV patients in the data provided to HCUP but removes the diagnosis codes identifying HIV.
  • At least one Partner removes diagnosis codes from the records of children aged 18 years or younger for the following conditions: mental, behavioral, and neurodevelopmental disorders (including those related to pregnancy and childbirth and excluding those due to psychoactive substances), symptoms and signs involving emotional state (including suicide attempt), and poisoning and adverse effect of drugs and other biological substances.
  • At least one Partner excludes records for patients treated in two types of alternate level of care units: skilled nursing and swing bed. Therefore, these records are not included in the NEDS.
  • At least one Partner masks the type of abortion (e.g., spontaneous, legally induced) by setting all abortion-specific diagnosis and procedure codes to "unspecified" abortions.

 

Abbreviations: HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample.


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Appendix C: NEDS Data Elements and Codes

Table C1. Data Elements in the 2020 NEDS Core File

Core File
Type of Data Element HCUP Data Element Coding Notes
Admission timing AWEEKEND Admission on weekend: (0) admission on Monday through Friday, (1) admission on Saturday or Sunday
AMONTH Admission month coded from (1) January to (12) December
Age at admission AGE Age in years coded 0-90 years. Any ages greater than 90 were set to 90.
Diagnosis information I10_DX1 - I10_DX35 ICD-10-CM diagnoses, with external cause of morbidity codes at the end of the array
I10_NDX Number of diagnoses coded on the original record received from Partner organizations
I10_INJURY ICD-10-CM initial injury diagnosisa reported: (0) no injury diagnoses reported, (1) injury is reported in first-listed diagnosis, (2) injury is reported in a diagnosis other than the first-listed diagnosis
I10_MULTINJURY Multiple ICD-10-CM initial injury diagnosesa reported: (0) one or no injury diagnosis reported, (1) more than one injury diagnoses reported, regardless of position
I10_INJURY_CUT External cause of morbidity codes indicating injury by cutting or piercing: (0) no injury by cutting or piercing, (1) injury by cutting or piercing
I10_INJURY_DROWN External cause of morbidity codes indicating injury by drowning or submersion: (0) no injury by drowning or submersion, (1) injury by drowning or submersion
I10_INJURY_FALL External cause of morbidity codes indicating injury by falling: (0) no injury by falling, (1) injury by falling
I10_INJURY_FIRE External cause of morbidity codes indicating injury by fire, flame, or hot object: (0) no injury by fire, flame, or hot object, (1) injury by fire, flame, or hot object
I10_INJURY_FIREARM External cause of morbidity codes indicating injury by firearm: (0) no injury by firearm, (1) injury by firearm
I10_INJURY_MACHINERY External cause of morbidity codes indicating injury by machinery: (0) no injury by machinery, (1) injury by machinery
I10_INJURY_MVT External cause of morbidity codes indicating injury involving motor vehicle traffic, including the occupant of a car, motorcyclist, pedal cyclist, pedestrian, or unspecified person: (0) no injury involving motor vehicle traffic, (1) injury involving motor vehicle traffic
I10_INJURY_NATURE External cause of morbidity codes indicating injury involving natural or environmental causes, including bites and stings: (0) no injury involving natural or environmental causes, (1) injury involving natural or environmental causes
I10_INJURY_OVEREXERTION External cause of morbidity codes indicating injury by overexertion: (0) no injury by overexertion, (1) injury by overexertion
I10_INJURY_POISON External cause of morbidity codes indicating injury by poisoning: (0) no injury by poisoning, (1) injury by poisoning
I10_INJURY_STRUCK External cause of morbidity codes indicating injury involving being struck by or against something: (0) no injury involving being struck by or against, (1) injury involving being struck by or against
I10_INJURY_SUFFOCATION External cause of morbidity codes indicating injury by suffocation: (0) no injury by suffocation, (1) injury by suffocation
I10_INTENT_ASSAULT External cause of morbidity codes indicating injury by assault: (0) no injury by assault, (1) injury by assault
I10_INTENT_SELF_HARM External cause of morbidity codes indicating intended self harm: (0) not intended self harm, (1) intended self harm
I10_INTENT_UNINTENTIONAL External cause of morbidity codes indicating injury was unintentional: (0) no unintentional injury, (1) unintentional injury
Discharge timing DQTR Discharge quarter coded: (1) January - March, (2) April - June, (3) July - September, (4) October - December
YEAR Calendar year of ED visits
Disposition of patient from the ED DISP_ED Disposition from ED: (1) routine; (2) transfer to short-term hospital; (5) other transfers, including skilled nursing facility, intermediate care, and another type of facility; (6) home health care; (7) against medical advice; (9) admitted as an inpatient to this hospital; (20) died in ED; (21) discharged/transferred to court/law enforcement; (98) not admitted, destination unknown; (99) discharged alive, destination unknown (but not admitted)
DIED_VISIT Died in ED: (0) did not die (1) died in the ED, (2) died in the hospital
ED event EDevent Type of ED visit: (1) ED visit in which the patient is treated and released, (2) ED visit in which the patient is admitted to the same hospital, (3) ED visit in which the patient is transferred to another short-term hospital, (9) ED visit in which the patient died in the ED, (98) ED visits in which patient was not admitted, destination unknown, (99) ED visit in which patient was discharged alive, destination unknown (but not admitted)
Sex of patient FEMALE Indicates sex: (0) male, (1) female
Race and ethnicity of patient RACE Race, uniform coding: (1) White, (2) Black, (3) Hispanic, (4) Asian or Pacific Islander, (5) Native American, (6) Other. (For 2020, RACE contains missing values on just 2.2 percent of the records.)
Urban-rural location of the patient’s residence PL_NCHS Urban—rural designation for patient's county of residence: (1) large central metropolitan, (2) large fringe metropolitan, (3) medium metropolitan, (4) small metropolitan, (5) micropolitan, (6) not metropolitan or micropolitan
National quartile for median household income of patient's ZIP Code ZIPINC_QRTL Median household income quartiles for patient's ZIP Code. For 2020, the median income quartiles are defined as: (1) $1-$49,999; (2) $50,000- $64,999; (3) $65,000-$85,999; and (4) $86,000 or more
Payer information PAY1 Expected primary payer, uniform: (1) Medicare, (2) Medicaid, (3) private including HMO, (4) self-pay, (5) no charge, (6) other
PAY2 Expected secondary payer, uniform: (1) Medicare, (2) Medicaid, (3) private including HMO, (4) self-pay, (5) no charge, (6) other
Total ED charges TOTCHG_ED Total charges for ED services, edited
HCUP source file HCUPFILE Source of HCUP record: (SEDD) from SEDD file, (SID) from SID file
Discharge weight DISCWT Discharge weight used to calculate national estimates. Weights ED visits to AHA universe.
NEDS hospital identifier, synthetic HOSP_ED Unique HCUP NEDS hospital number — links to NEDS Hospital weights file, but not to other HCUP databases
NEDS stratum NEDS_STRATUM Stratum used to sample hospitals, based on geographic region, trauma, location/teaching status, and control. Stratum information is also contained in the Hospital Weights File.
Record identifier, synthetic KEY_ED Unique HCUP NEDS record number - links to NEDS Supplemental Files, but not to other HCUP databases
Abbreviations: ED, emergency department; HCUP, Healthcare Cost and Utilization Project; HMO, health maintenance organization; ICD-10-CM, International Classification of Diseases, Tenth Revision, Clinical Modification; NEDS, Nationwide Emergency Department Sample; SEDD, State Emergency Department Databases; SID, State Inpatient Databases.
Notes: For data years prior to 2020, refer to the NEDS Description of Data Elements page on the HCUP-US website or to previous versions of the Introduction to the NEDS.
a Injuries are identified by diagnosis codes in the Clinical Classifications Software Refined for ICD-10-CM categories of INJ001-INJ027 and INJ032. Injuries are limited to the initial encounter with a 7th character of A, B, C, or missing.


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Table C2. Data Elements in the 2020 NEDS Supplemental ED File

Type of Data Element HCUP Data Element Coding Notes
CPT procedure information CPT1 — CPT35 CPT procedures performed in the ED
CPTCCS1 — CPTCCS35 Clinical Classifications Software category for all CPT procedures
NCPT Number of procedures coded on the original record. A maximum of 35 CPT codes are retained on the NEDS.
NEDS hospital identifier, synthetic HOSP_ED Unique HCUP NEDS hospital number — links to NEDS Hospital Weights File, but not to other HCUP databases
Record identifier, synthetic KEY_ED Unique HCUP NEDS record number — links to NEDS Supplemental Files, but not to other HCUP databases
Abbreviations: CPT, Current Procedural Terminology; ED, emergency department; HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample.
Notes: For data years prior to 2020, refer to the NEDS Description of Data Elements page on the HCUP-US website or to previous versions of the Introduction to the NEDS.


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Table C3.Data Elements in the 2020 NEDS Supplemental Inpatient File

Type of Data Element HCUP Data Element Coding Notes
Disposition of patient from the hospital DISP_IP Disposition from hospital admission: (1) routine, (2) transfer to short-term hospital, (5) other transfers, including skilled nursing facility, intermediate care, and another type of facility, (6) home health care, (7) against medical advice, (20) died in hospital, (99) discharged alive, destination unknown
Diagnosis related group (DRG) DRG DRG in use on discharge date
DRG_NoPOA DRG assignment made without the use of the present on admission flags for the diagnoses
DRGVER Grouper version in use on discharge date
MDC Major diagnosis category (MDC) in use on discharge date
MDC_NoPOA MDC in use on discharge date, calculated without the use of the present on admission flags for the diagnoses
Length of hospital inpatient stay LOS_IP Length of stay, edited
Total charges for inpatient stay TOTCHG_IP Total charges for ED and inpatient services, edited
ICD-10-PCS procedure information I10_PR_IP1 - I10_PRI_IP15 ICD-10-PCS procedures coded on ED admissions. Procedure may have been performed in the ED or during the hospital stay.
I10_NPR_IP Number of procedures coded on the original record.
Data elements derived from the HCUP Software Tools for ICD-10-PCS PCLASSn1 Procedure Classes Refined for ICD-10-PCS procedure codes
PCLASS_VERSION Version of the Procedure Classes Refined for ICD-10-PCS procedure codes
PRCCSR_aaannn2 Indication that at least one ICD-10-CM diagnosis on the record is included in the Clinical Classification Software Refined (CCSR) aaannn
PRCCSR_VERSION Version of CCSR for ICD-10-PCS procedure codes
NEDS hospital identifier, synthetic HOSP_ED Unique HCUP NEDS hospital number - links to NEDS Hospital Weights File, but not to other HCUP databases
Record identifier, synthetic KEY_ED Unique HCUP NEDS record number - links to NEDS Supplemental Files, but not to other HCUP databases
Abbreviations: ED, emergency department; HCUP, Healthcare Cost and Utilization Project; ICD-10-PCS, International Classification of Diseases, Tenth Revision, Procedure Coding System; NEDS, Nationwide Emergency Department Sample
Notes: For data years prior to 2020, refer to the NEDS Description of Data Elements page on the HCUP-US website or to previous versions of the Introduction to the NEDS.
1 PCLASS_IPn was available on the NEDS through quarter 3 of data year 2015 and was specific to the coding of ICD-9-CM procedures.
2 Where aaa denotes the clinical domain and nnn denotes the CCSR number within the clinical domain.


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Table C4. Data Elements in the 2020 NEDS Hospital Weights File

Type of Data Element HCUP Data Element Coding Notes
Discharge counts N_DISC_U Number of AHA universe ED visits in the stratum
S_DISC_U Number of sampled ED visits in the sampling stratum
TOTAL_EDvisits Total number of ED visits for this hospital in the NEDS
Weights DISCWT Discharge weight used to calculate national estimates. Weights ED visits to AHA universe.
HOSPWT Weight to hospital-owned EDs in AHA universe (i.e., total U.S.)
Discharge year YEAR Discharge year
Hospital counts N_HOSP_U Number of AHA universe hospital-owned EDs in the stratum
S_HOSP_U Number of sampled hospital-owned EDs in the stratum
NEDS hospital identifier, synthetic HOSP_ED Unique HCUP NEDS hospital number — links to NEDS Hospital Weights file, but not to other HCUP databases
Hospital characteristics HOSP_URCAT4 Hospital urban-rural location: (1) large metropolitan areas with at least 1 million residents; (2) small metropolitan areas with less than 1 million residents; (3) micropolitan areas; (4) not metropolitan or micropolitan; (6) collapsed category of any urban-rural location; (7) collapsed category of small metropolitan and micropolitan; (8) metropolitan, collapsed category of large and small metropolitan; (9) nonmetropolitan, collapsed category of micropolitan and rural
HOSP_CONTROL Control/ownership of hospital: (0) government or private, collapsed category, (1) government, non-federal, public, (2) private, nonprofit, voluntary, (3) private, invest-own, (4) private, collapsed category
HOSP_REGION Region of hospital: (1) Northeast, (2) Midwest, (3) South, (4) West
HOSP_TRAUMA Trauma center level: (0) nontrauma center, (1) trauma level I, (2) trauma level II (3) trauma level III, (4) nontrauma or trauma level III, collapsed category beginning in the 2011 NEDS, (8) trauma level I or II, collapsed category, (9) trauma level I, II, or III, collapsed category in the 2006-2010 NEDS. Children's hospitals with trauma centers are classified with adult/pediatric trauma centers.
HOSP_UR_TEACH Teaching status of hospital: (0) metropolitan nonteaching, (1) metropolitan teaching, (2) nonmetropolitan
NEDS_STRATUM Stratum used to sample EDs, includes geographic region, trauma, location/teaching status, and control
Abbreviations: AHA, American Hospital Association; ED, emergency department; HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample
Notes: For data years prior to 2020, refer to the NEDS Description of Data Elements page on the HCUP-US website or to previous versions of the Introduction to the NEDS.


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Table C5. Data Elements in the 2020 NEDS Diagnosis and Procedure Groups File

Type of Data Element HCUP Data Element Coding Notes
Clinical Classifications Software Refined (CCSR) for ICD-10-CM diagnoses DXCCSR_aaannn3 Indication that at least one ICD-10-CM diagnosis on the record is included in CCSR AAAnnn
DXCCSR_Default_DX1 Default CCSR for principal/first-listed ICD-10-CM diagnosis
DXCCSR_VERSION Version of CCSR for ICD-10-CM diagnoses
Elixhauser Comorbidity Software Refined for ICD-10-CM CMR_aaa4 Comorbidity measures (aaa) identified by the AHRQ Elixhauser Comorbidity Software Refined for ICD-10-CM diagnosis codes
CMR_VERSION Version of the Elixhauser Comorbidity Measure Refined for ICD-10-CM
NEDS identifiers, synthetic HOSP_ED Unique HCUP NEDS hospital number—links to NEDS Hospital Weights File but not to other HCUP databases
KEY_ED Unique HCUP NEDS record number—links to NEDS Core and Supplemental Files but not to other HCUP databases
Abbreviations: AHA, American Hospital Association; ED, emergency department; HCUP, Healthcare Cost and Utilization Project; NEDS, Nationwide Emergency Department Sample
Notes: For data years prior to 2020, refer to the NEDS Description of Data Elements page on the HCUP-US website or to previous versions of the Introduction to the NEDS.
3 Where aaa denotes the body system and nnn denotes the CCSR number within the body system.
4 Where aaa denotes the specific comorbidity measure.


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Appendix D: Comparisons of the NEDS With Other Sources of ED Data

 

Figure D1. Number of Emergency Department (ED) Visits in the U.S., by Data Source, 2020

Figure D.1. is a bar chart displaying the number of emergency department visits in the United States in 2020. For 2020 it is estimated to be 123,278,165 according to the HCUP Nationwide Emergency Department Sample (NEDS); 123,278,165 according to the American Hospital Association Annual Survey Database (AHA); 89,019,742 according to the National Health Interview Survey (NHIS); and 131,296,603 according to the National Hospital Ambulatory Medical Care Survey (NHAMCS).

Abbreviations: NEDS, Nationwide Emergency Department Sample; AHA, American Hospital Association Annual Survey Database; NHIS, National Health Interview Survey; NHAMCS, National Hospital Ambulatory Medical Care Survey.

The above graphic outlines the number of emergency department visits in the United States in 2020. For 2020 it is estimated to be 123,278,165 according to the HCUP Nationwide Emergency Department Sample (NEDS); 123,278,165 according to the American Hospital Association Annual Survey Database (AHA); 89,019,742 according to the National Health Interview Survey (NHIS); and 131,296,603 according to the National Hospital Ambulatory Medical Care Survey (NHAMCS).

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Table D1. Number and Percent of Emergency Department (ED) Visits in the U.S., by Census Region and Data Source, 2020

Region NEDSa AHA NHISb NHAMCS
Number of Visits (weighted) % Number of Visits % Number of Visits % Number of Visits %
Northeast 21,881,692 18.0 21,881,692 18.0 13,964,456 16.0 22,916,693 17.0
Midwest 27,542,194 22.0 27,542,194 22.0 18,022,544 20.0 27,052,357 21.0
South 50,376,080 41.0 50,376,080 41.0 38,309,895 43.0 49,818,891 38.0
West 23,478,199 19.0 23,478,199 19.0 18,722,847 21.0 31,508,662 24.0
Total U.S. 123,278,165 100.0 123,278,165 100.0 89,019,742 100.0 131,296,603 100.0
Abbreviations: NEDS, Nationwide Emergency Department Sample; AHA, American Hospital Association Annual Survey Database; NHIS, National Health Interview Survey; NHAMCS, National Hospital Ambulatory Medical Care Survey.
a NEDS weighted counts by geographic region exactly match the AHA counts because the AHA data were used as control totals for the NEDS discharge weights.
b NHIS estimates were calculated using the values provided in the survey (0, 1, 3, 4+). For the upper range of visits in the survey (4 or more ED visits), 4 ED visits were used for the estimate.


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Table D2. Distribution of Hospital-Owned Emergency Departments (ED) by Number of Visits, NEDS and AHA, 2020

Volume of ED Visits NEDS AHA
Number of EDs % Number of EDs %
<10,000 visits 1,595 34.7 1,791 39.0
10,000-19,999 visits 713 15.5 762 16.6
20,000-29,999 664 14.5 540 11.8
30,000-39,999 433 9.4 426 9.3
40,000-49,999 351 7.7 286 6.2
50,000 or more visits 834 18.2 785 17.1
All hospital-owned EDs 4,590 100.0 4,590 100.0
Abbreviations: NEDS, Nationwide Emergency Department Sample; AHA, American Hospital Association Annual Survey Database.


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Table D3. Number and Percent of Emergency Department (ED) Visits Resulting in Inpatient Admission in the U.S., by Census Region, NEDS and NHAMCS, 2020

Region NEDS NHAMCS
Number of ED Visits (weighted) Number of ED Visits Resulting in Admission (weighted) Percent of ED Visits Resulting in Admission Number of ED Visits Number of ED Visits Resulting in Admission Percent of ED Visits Resulting in Admission
Northeast 21,881,692 4,220,024 19.3 22,916,693 3,483,537 15.2
Midwest 27,542,194 4,166,906 15.1 27,052,357 3,937,548 14.6
South 50,376,080 8,266,980 16.4 49,818,891 5,563,840 11.2
West 23,478,199 3,437,400 14.6 31,508,662 5,608,297 17.8
Total U.S. 123,278,165 20,091,310 16.3 131,296,603 18,593,221 14.2
Abbreviations: NEDS, Nationwide Emergency Department Sample; NHAMCS, National Hospital Ambulatory Medical Care Survey.


Table D4. Number of Injuries by Type of Injury-Related ED Visit, NEDS and NEISS-AIP, 2020

Type of Injury-Related ED Visit NEDS (All Injuries)a NEDS (Initial Encounter for Injurya NEISS-AIPb
Number of Visits (weighted) 95% CI Number of Visits (weighted) 95% CI Number of Visits (weighted) 95% CI
Total number of visits for nonfatal injuries 23,863,455 (22,918,770, 24,808,141) 23,207,872 (22,287,327, 24,128,418) 22,887,137 (18,528,409, 27,245,864)
Treated and released from ED 20,510,853 (19,680,723, 21,340,983) 19,992,744 (19,182,070, 20,803,417) 18,531,421 (15,100,489, 21,962,353)
Admitted to the same hospital 2,625,810 (2,481,234, 2,770,386) 2,500,313 (2,361,697, 2,638,929) 2,888,143 (2,084,335, 3,691,950)
Transferred 501,720 (476,040, 527,401) 495,632 (470,239, 521,024) 641,240 (480,505, 801,975)
Otherc 225,072 (208,354, 241,790) 219,184 (202,971, 235,397) NAd NAd
Abbreviations: NEDS, Nationwide Emergency Department Sample; NEISS-AIP, National Electronic Injury Surveillance System All-Injury Program; CI, confidence interval.
a Injuries are identified by diagnosis codes in the Clinical Classifications Software Refined for ICD-10-CM categories of INJ001-INJ027 and INJ032. Initial encounters are limited to diagnoses with a 7th character of A, B, C, or missing.
Counts for all injuries allowed any 7th character for the injury diagnosis code; counts for the initial encounter limited injury diagnosis codes to those with a 7th character of A, B, C, or missing.
b Data from the Web-based Injury Statistics Query and Reporting System (WISQARS™) (https://webappa.cdc.gov/sasweb/ncipc/nfirates.html). Includes nonfatal, all-cause injuries for all ages and sexes. Patients who died on arrival to the ED or during treatment in the ED are excluded. Queried September 7, 2022.
c For the NEISS-AIP, other includes left against medical advice, sent for observations, and unknown destination. For the NEDS, other include left against medical advice. Patients who are treated in the ED and then observed cannot be identified. If they were discharged home from observation, they are counted under "treated and released from the ED"; if they were admitted to the hospital from observation, they are counted under "admitted to the same hospital".
d The estimate for other in 2020 was not shown in the WISQARS Query System because it was unstable due to small sample size and/or a coefficient of variation >30 percent.


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1 Merrill CT, Owens PL. Hospital Admissions That Began in the Emergency Department for Children and Adolescents, 2004. HCUP Statistical Brief #32. Rockville, MD: Agency for Healthcare Research and Quality; June 2007. www.hcup-us.ahrq.gov/reports/statbriefs/sb32.pdf.
2 Merrill CT, Owens PL. Hospital Admissions That Began in the Emergency Department for Children and Adolescents, 2004. HCUP Statistical Brief #32. Rockville, MD: Agency for Healthcare Research and Quality; June 2007. www.hcup-us.ahrq.gov/reports/statbriefs/sb32.pdf.
3 Users interested in applying HCUP software tools to the NEDS to produce data elements not available for a certain data year may do so by downloading the respective tool(s) from the HCUP Research Tools section of the HCUP-US website. Further, users may wish to review the HCUP Software Tools Tutorial, which provides instructions on how to apply the HCUP software tools to HCUP or other administrative databases.
4 More of the AHA "community hospital designation" is available at www.ahadataviewer.com/glossary. Exit Disclaimer
5 MacKenzie EJ, Hoyt DB, Sacra JC, et al. National inventory of hospital trauma centers. JAMA. 2003;289:1515-1522.
6 American College of Surgeons Committee on Trauma, Verification, Review, and Consultation Program for Hospitals. Verification, Review, and Consultation (VRC) Program. www.facs.org/quality-programs/trauma/tqp/center-programs/vrc. Exit Disclaimer Accessed September 2018.
7 American Trauma Society. Trauma Information Exchange Program. www.amtrauma.org/page/TIEP. Exit Disclaimer Accessed December 2019.
8 U.S. Department of Agriculture Economic Research Service. Urban Influence Codes. Last updated October 23, 2019. www.ers.usda.gov/data-products/urban-influence-codes.aspx. Accessed June 26, 2020.
9 The collapsing of small metropolitan and micropolitan areas was required in the South in 2011-2015.
10 The collapsing of all areas was required in the South in 2014.
11The ZIP Code of the hospital is not included in the NEDS data files.
12 Carlson BL, Johnson AE, Cohen SB. An evaluation of the use of personal computers for variance estimation with complex survey data. J Of Statistics. 1993;9(4):795-814.
13 At the time this document was created, the 2020 National Emergency Department Inventory was not available for developing comparative estimates.

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Internet Citation: 2020 Introduction to the NEDS. Healthcare Cost and Utilization Project (HCUP). October 2022. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/db/nation/neds/NEDS_Introduction_2020.jsp.
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