66 datasets found
  1. National Inpatient Sample (NIS) - Restricted Access Files

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Feb 22, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). National Inpatient Sample (NIS) - Restricted Access Files [Dataset]. https://catalog.data.gov/dataset/hcup-national-nationwide-inpatient-sample-nis-restricted-access-file
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    Dataset updated
    Feb 22, 2025
    Description

    The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

  2. NIS_2016

    • redivis.com
    application/jsonl +7
    Updated Jan 27, 2025
    + more versions
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    Center for Surgery and Public Health (2025). NIS_2016 [Dataset]. https://redivis.com/datasets/e4ms-4dp8mape8
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    avro, sas, parquet, csv, arrow, stata, spss, application/jsonlAvailable download formats
    Dataset updated
    Jan 27, 2025
    Dataset provided by
    Redivis Inc.
    Authors
    Center for Surgery and Public Health
    Description

    Usage

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

  3. HCUP National Inpatient Database

    • redivis.com
    application/jsonl +7
    Updated May 11, 2024
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    Stanford Center for Population Health Sciences (2024). HCUP National Inpatient Database [Dataset]. http://doi.org/10.57761/d67b-fz41
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    application/jsonl, csv, avro, arrow, parquet, stata, sas, spssAvailable download formats
    Dataset updated
    May 11, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 2000 - Dec 31, 2021
    Description

    Abstract

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

    Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, uncommon treatments, and special populations.

    Usage

    IMPORTANT NOTE: Some records are missing from the Severity Measures table for 2017 & 2018, but none are missing from any of the other 2012-2020 data. We are in the process of trying to recover the missing records, and will update this note when we have done so.

    Also %3Cu%3EDO NOT%3C/u%3E

    use this data without referring to the NIS Database Documentation, which includes:

    • Description of NIS Database
    • Restrictions on Use

    %3C!-- --%3E

    • Data Elements
    • Additional Resources for Data Elements
    • ICD-10-CM/PCS Data Included in the NIS Starting with 2015 (More details about this transition available here.)
    • Known Data Issues
    • NIS Supplemental Files
    • HCUP Tools: Labels and Formats
    • Obtaining HCUP Data

    %3C!-- --%3E

    Before Manuscript Submission

    All manuscripts (and other items you'd like to publish) must be submitted to

    phsdatacore@stanford.edu for approval prior to journal submission.

    We will check your cell sizes and citations.

    For more information about how to cite PHS and PHS datasets, please visit:

    https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

    HCUP Online Tutorials

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

    • The HCUP Sampling Design tutorial is designed to help users learn how to account for sample design in their work with HCUP national (nationwide) databases. • The Producing National HCUP Estimates tutorial is designed to help users understand how the three national (nationwide) databases – the NIS, Nationwide Emergency Department Sample (NEDS), and Kids' Inpatient Database (KID) – can be used to produce national and regional estimates. HCUP 2020 NIS (8/22/22) 14 Introduction • The Calculating Standard Errors tutorial shows how to accurately determine the precision of the estimates produced from the HCUP nationwide databases. Users will learn two methods for calculating standard errors for estimates produced from the HCUP national (nationwide) databases. • The HCUP Multi-year Analysis tutorial presents solutions that may be necessary when conducting analyses that span multiple years of HCUP data. • The HCUP Software Tools Tutorial provides instructions on how to apply the AHRQ software tools to HCUP or other administrative databases.

    New tutorials are added periodically, and existing tutorials are updated when necessary. The Online Tutorial Series is located on the HCUP-US website at www.hcupus.ahrq.gov/tech_assist/tutorials.jsp.

    Important notes about the 2015 data

    In 2015, AHRQ restructured the data as described here:

    https://hcup-us.ahrq.gov/db/nation/nis/2015HCUPNationalInpatientSample.pdf

    Some key points:

    • For the 2015 data, all diagnosis and procedure data elements, including any data elements derived from diagnoses and procedures, were moved out of the Core File and into the Diagnosis and Procedure Groups Files.
    • Prior to 2015, and for Q1-3 of 2015, the DX1-30 and PR1-15 variables (which use ICD-9 codes) variables were used, but starting in Q4 of 2015, the I10_DX1-30 and I10_PR1-I10-15 (which use ICD-10 codes) were used. The best way to identify discharges for quarter 1-3 or quarter 4 is based on the value of the diagnosis version (DXVER); For quarters 1-3, DXVER has a value of 9; while for quarter 4, DXVER has a value of 10.
    • Some other variables also transitioned in Q4 of 2015. Please refer to the link above for more details.
    • Starting in 2016, the diagnosis and procedure information returned to the Core file. Additional details about the data in 2016 are available here: https://hcup-us.ahrq.gov/db/nation/nis/NISChangesBeginningDataYr2016.pdf

    %3C!-- --%3E

    NIS Areas of Research and HCUP Publications

  4. The National (Nationwide) Inpatient Sample

    • datacatalog.library.wayne.edu
    Updated Jun 16, 2020
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    U.S. Agency for Healthcare Research and Quality (AHRQ) (2020). The National (Nationwide) Inpatient Sample [Dataset]. https://datacatalog.library.wayne.edu/dataset/the-national-nationwide-inpatient-sample
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    Dataset updated
    Jun 16, 2020
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Description

    The National (Nationwide) Inpatient Sample (NIS) is a large publicly available all-payer inpatient care database in the United States, containing data on more than seven million hospital stays. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, uncommon treatments, and special populations.

  5. H

    Nationwide Inpatient Sample (NIS)

    • dataverse.harvard.edu
    Updated Aug 5, 2011
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    Harvard Dataverse (2011). Nationwide Inpatient Sample (NIS) [Dataset]. http://doi.org/10.7910/DVN/UXHCOW
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 5, 2011
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The Nationwide Inpatient Sample (NIS) is a database focused on hospital stay information. Users are able to use the NIS to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. Background The Nationwide Inpatient Sample (NIS) is maintained by the Healthcare Cost and Utilization Project. The NIS is the largest all-payer inpatient care database in the United States. It contains data from approximately 8 million hospital stays each year. The 2009 NIS contains all discharge data from 1,050 hospitals located in 44 States, approximating a 20-percent stratified sample of U.S. community hospitals. The sampling frame for the 2009 NIS is a sample of hospitals that comprises approximately 95 percent of all hospital discharges in the United States. The NIS is the only national hospital database containing charge information on all patients, regardless of payer, including persons covered by Medicare, Medicaid, private insurance, and the uninsured. User functionality Users must pay to access the database. NIS releases for data years 1988-2009 are available from the HCUP Central Distributor. The 2009 NIS may be purchased for $50 for students and $350 for all others on a single DVD-ROM with accompanying documentation. . Data Notes NIS data are available from 1988 to 2009. The number of states in the NIS has grown from 8 in the first year to 44 at present. Beginning with the 2002 NIS, severity adjustment data elements including APR-DRGs, APS-DRGs, Disease Staging, and AHRQ Comorbidity Indicators, are available. Begi nning with the 2005 NIS, Diagnosis and Procedure Groups Files containing data elements from AHRQ software tools designed to facilitate the use of the ICD-9-CM diagnostic and procedure information are available. Beginning with the 2007 NIS, data elements describing hospital structural characteristics and provision of outpatient services are available in the Hospital Weights file. NIS Release 1 includes data from 8-11 States and spans the years 1988 to 1992. NIS Releases 2 and 3 contain data from 17 States for 1993 and 1994, respectively. NIS Releases 4 and 5 contain data from 19 States for 1995 and 1996. NIS Release 6 contains data from 22 States for 1997. NIS 1998 contains data from 22 States. NIS 1999 contains data from 24 States. NIS 2000 contains data from 28 States. NIS 2001 contains data from 33 States. NIS 2002 contains data from 35 States. NIS 2003 contains data from 37 States. NIS 2004 contains data from 37 States. NIS 2005 contains data from 37 States. NIS 2006 contains data from 38 States. NIS 2007 contains data from 40 States. NIS 2008 contains data from 42 States.

  6. r

    NIS Core

    • redivis.com
    Updated Jan 11, 2022
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    Stanford Center for Population Health Sciences (2022). NIS Core [Dataset]. https://redivis.com/datasets/2g37-7mghj1wyb
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    Dataset updated
    Jan 11, 2022
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2012 - 2021
    Description

    Inpatient core file showing all discharges from the sample of hospitals in participating states. Unit of observation: discharge-level

  7. A

    ‘Healthcare Cost and Utilization Project (HCUP) - National Inpatient Sample’...

    • analyst-2.ai
    Updated Jan 27, 2022
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Healthcare Cost and Utilization Project (HCUP) - National Inpatient Sample’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-healthcare-cost-and-utilization-project-hcup-national-inpatient-sample-6aba/latest
    Explore at:
    Dataset updated
    Jan 27, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Healthcare Cost and Utilization Project (HCUP) - National Inpatient Sample’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/5fd2d275-4019-407f-af21-58e453bc8caa on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    2001 forward. The National (Nationwide) Inpatient Sample (NIS) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). The NIS is the largest publicly available all-payer inpatient health care database in the United States, yielding national estimates of hospital inpatient stays. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Indicators from this data source have been computed by personnel in CDC's Division for Heart Disease and Stroke Prevention (DHDSP). This is one of the datasets provided by the National Cardiovascular Disease Surveillance System. The system is designed to integrate multiple indicators from many data sources to provide a comprehensive picture of the public health burden of CVDs and associated risk factors in the United States. The data are organized by indicator, and they include CVDs (e.g., heart failure). The data can be plotted as trends and stratified by age group, sex, and race/ethnicity.

    --- Original source retains full ownership of the source dataset ---

  8. r

    NIS Severity

    • redivis.com
    Updated Jan 11, 2022
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    Stanford Center for Population Health Sciences (2022). NIS Severity [Dataset]. https://redivis.com/datasets/2g37-7mghj1wyb
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    Dataset updated
    Jan 11, 2022
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2012 - 2021
    Description

    Disease severity measures file showing disease severity measures linkable to Inpatient Core File. Unit of observation: discharge-level.

  9. Database Creation Description and Data Dictionaries

    • figshare.com
    txt
    Updated Aug 11, 2016
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    Jordan Kempker; John David Ike (2016). Database Creation Description and Data Dictionaries [Dataset]. http://doi.org/10.6084/m9.figshare.3569067.v3
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    txtAvailable download formats
    Dataset updated
    Aug 11, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Jordan Kempker; John David Ike
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    There are several Microsoft Word documents here detailing data creation methods and with various dictionaries describing the included and derived variables.The Database Creation Description is meant to walk a user through some of the steps detailed in the SAS code with this project.The alphabetical list of variables is intended for users as sometimes this makes some coding steps easier to copy and paste from this list instead of retyping.The NIS Data Dictionary contains some general dataset description as well as each variable's responses.

  10. n

    Hospital Admission Data from the Agency for HealthCare Research and Quality...

    • cmr.earthdata.nasa.gov
    Updated Apr 20, 2017
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    (2017). Hospital Admission Data from the Agency for HealthCare Research and Quality (AHRQ) [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1214136020-SCIOPS
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    Dataset updated
    Apr 20, 2017
    Time period covered
    Jan 1, 1970 - Present
    Description

    The Agency for Healthcare Research and Quality (AHRQ, formerly the Agency for Health Care Policy and Research) maintains the Healthcare Cost and Utilization Project (HCUP). HCUP is a Federal-State-industry partnership to build a standardized, multi-State health data system. AHRQ has taken the lead in developing HCUP databases, Web-based products, and software tools and making them available for restricted access public release.

    HCUP comprises a family of administrative longitudinal databases-including State-specific hospital-discharge databases and a national sample of discharges from community hospitals.

    HCUP databases contain patient-level information compiled in a uniform format with privacy protections in place. * The Nationwide Inpatient Sample (NIS) includes inpatient data from a national sample (about 20% of U.S. community hospitals) including roughly 7 million discharges from about 1,000 hospitals. It is the largest all-payer inpatient database in the U.S.; data are now available from 1988-1998. The NIS is ideal for developing national estimates, for analyzing national trends, and for research that requires a large sample size. * The State Inpatient Databases (SID) cover individual data sets in community hospitals from 22 participating States that represent more than half of all U.S. hospital discharges. The data have been translated into a uniform format to facilitate cross-State comparisons. The SID are particularly well-suited for policy inquiries unique to a specific State, studies comparing two or more States, market area research, and small area variation analyses.

    • The State Ambulatory Surgery Databases (SASD) contain data from ambulatory care encounters in 9 participating States. The SASD capture surgeries performed on the same day in which patients are admitted and released form hospital- affiliated ambulatory surgery sites. The SASD are well suited for research that requires complete enumeration of hospital-based ambulatory surgeries within market areas and States.
    • The project's newest restricted access public release is the Kids' Inpatient Database (KID), containing hospital inpatient stays for children 18 years of age and younger. Researchers and policymakers can use the KID to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The KID is the only all-payer inpatient care database for children in the U.S. It contains data from approximately 1.9 million hospital discharges for children. The data are drawn from 22 HCUP 1997 State Inpatient Databases and include a sample of pediatric general discharges from over 2,500 U.S. community hospitals (defined as short-term, non-Federal, general and specialty hospitals, excluding hospital units of other institutions). A key strength of the KID is that the large sample size enables analyses of both common and rare conditions; uncommon treatments, and organ transplantation. The KID also includes charge information on all patients, regardless of payer, including children covered by Medicaid, private insurance, and the uninsured.

      HCUP also contains powerful, user-friendly software that can be used with both HCUP data and with other administrative databases. The AHRQ has developed three powerful software tools Quality Indicators (QIs), Clinical Classification Software (CCS) and HCUPnet. See more on the agency's webpages.

  11. AHRQ Healthcare Cost and Utilization Project

    • openicpsr.org
    Updated Feb 21, 2025
    + more versions
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    AHRQ (2025). AHRQ Healthcare Cost and Utilization Project [Dataset]. http://doi.org/10.3886/E220328V2
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    Dataset updated
    Feb 21, 2025
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Authors
    AHRQ
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary Trend TablesThe HCUP Summary Trend Tables include information on hospital utilization derived from the HCUP State Inpatient Databases (SID), State Emergency Department Databases (SEDD), National Inpatient Sample (NIS), and Nationwide Emergency Department Sample (NEDS). State statistics are displayed by discharge month and national and regional statistics are displayed by discharge quarter. Information on emergency department (ED) utilization is dependent on availability of HCUP data; not all HCUP Partners participate in the SEDD.The HCUP Summary Trend Tables include downloadable Microsoft® Excel tables with information on the following topics:Overview of trends in inpatient and emergency department utilizationAll inpatient encounter typesInpatient encounter typeNormal newbornsDeliveriesNon-elective inpatient stays, admitted through the EDNon-elective inpatient stays, not admitted through the EDElective inpatient staysInpatient service lineMaternal and neonatal conditionsMental health and substance use disordersInjuriesSurgeriesOther medical conditionsED treat-and-release visitsDescription of the data source, methodology, and clinical criteria (Excel file, 43 KB)Change log (Excel file, 65 KB)For each type of inpatient stay, there is an Excel file for the number of discharges, the percent of discharges, the average length of stay, the in-hospital mortality rate per 100 discharges,1 and the population-based rate per 100,000 population.2 Each Excel file contains State-specific, region-specific, and national statistics. For most files, trends begin in January 2017. Also included in each Excel file is a description of the HCUP databases and methodology.

  12. HCUP National Kid Inpatient Database

    • redivis.com
    application/jsonl +7
    Updated Jan 23, 2019
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    Stanford Center for Population Health Sciences (2019). HCUP National Kid Inpatient Database [Dataset]. http://doi.org/10.57761/tscn-6451
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    parquet, arrow, csv, sas, application/jsonl, avro, stata, spssAvailable download formats
    Dataset updated
    Jan 23, 2019
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 2003 - Dec 31, 2012
    Description

    Abstract

    The National (Nationwide) Kids' Inpatient Database (KID) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). Only years 2003, 2006, 2009, 2012 are available on the PHS Data Portal.

    The Kids' Inpatient Database (KID) is the largest publicly available all-payer pediatric inpatient care database in the United States, containing data from two to three million hospital stays. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, such as congenital anomalies, as well as uncommon treatments, such as organ transplantation. KID releases for data years 1997, 2000, 2003, 2006, 2009, 2012, 2016, and 2019 are available for purchase online through the Online HCUP Central Distributor. The KID was not produced for 2015 because of the transition from ICD-9-CM to ICD-10-CM/PCS coding.

    Usage

    KID Database Documentation includes:

    • Description of KID Database
    • Restrictions on Use
    • Files Specifications and Load Programs
    • Data Elements
    • Additional Resources for Data Elements
    • ICD-10-CM/PCS Included in 2016 KID
    • Information on Change to KID Design in 2000
    • Known Data Issues
    • KID Supplemental Files
    • HCUP Tools: Labels and Formats
    • Obtaining HCUP Data

    %3C!-- --%3E

    Documentation

    Please visit the HCUP National KID page for more information.

  13. f

    Specific injuries in patients seen in the ED with football injuries by...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Michael J. McGinity; Ramesh Grandhi; Joel E. Michalek; Jesse S. Rodriguez; Aron M. Trevino; Ashley C. McGinity; Ali Seifi (2023). Specific injuries in patients seen in the ED with football injuries by hospital admission (N = 819,000). [Dataset]. http://doi.org/10.1371/journal.pone.0195827.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Michael J. McGinity; Ramesh Grandhi; Joel E. Michalek; Jesse S. Rodriguez; Aron M. Trevino; Ashley C. McGinity; Ali Seifi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Specific injuries in patients seen in the ED with football injuries by hospital admission (N = 819,000).

  14. HCUP Nationwide Emergency Department Database (NEDS) Restricted Access File

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Jul 29, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2023). HCUP Nationwide Emergency Department Database (NEDS) Restricted Access File [Dataset]. https://catalog.data.gov/dataset/hcup-nationwide-emergency-department-database-neds-restricted-access-file
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    Dataset updated
    Jul 29, 2025
    Description

    The Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) is the largest all-payer emergency department (ED) database in the United States. yielding national estimates of hospital-owned ED visits. Unweighted, it contains data from over 30 million ED visits each year. Weighted, it estimates roughly 145 million ED visits nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. Sampled from the HCUP State Inpatient Databases (SID) and State Emergency Department Databases (SEDD), the HCUP NEDS can be used to create national and regional estimates of ED care. The SID contain information on patients initially seen in the ED and subsequently admitted to the same hospital. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NEDS contain information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 85% of patients, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.Restricted access data files are available with a data use agreement and brief online security training.

  15. HCUP Nationwide Emergency Department Database (NEDS)

    • catalog.data.gov
    • s.cnmilf.com
    Updated Mar 14, 2013
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    Agency for Healthcare Research and Quality (2013). HCUP Nationwide Emergency Department Database (NEDS) [Dataset]. https://catalog.data.gov/dataset/hcup-nationwide-emergency-department-database-neds
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    Dataset updated
    Mar 14, 2013
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Description

    The Nationwide Emergency Department Sample (NEDS) was created to enable analyses of emergency department (ED) utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. The NEDS can be weighted to produce national estimates. The NEDS is the largest all-payer ED database in the United States. It was constructed using records from both the HCUP State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID), both also described in healthdata.gov. The SEDD capture information on ED visits that do not result in an admission (i.e., 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. The NEDS contains 25-30 million (unweighted) records for ED visits for over 950 hospitals and approximates a 20-percent stratified sample of U.S. hospital-based EDs. The NEDS contains information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 75% of patients, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.

  16. HCUP Kids' Inpatient Database (KID) - Restricted Access File

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Jul 16, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). HCUP Kids' Inpatient Database (KID) - Restricted Access File [Dataset]. https://catalog.data.gov/dataset/hcup-kids-inpatient-database-kid-restricted-access-file
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    Dataset updated
    Jul 16, 2025
    Description

    The Healthcare Cost and Utilization Project (HCUP) Kids' Inpatient Database (KID) is the largest publicly available all-payer pediatric inpatient care database in the United States, containing data from two to three million hospital stays each year. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, such as congenital anomalies, as well as uncommon treatments, such as organ transplantation. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The KID is a sample of pediatric discharges from 4,000 U.S. hospitals in the HCUP State Inpatient Databases yielding approximately two to three million unweighted hospital discharges for newborns, children, and adolescents per year. About 10 percent of normal newborns and 80 percent of other neonatal and pediatric stays are selected from each hospital that is sampled for patients younger than 21 years of age. The KID contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes discharge status, diagnoses, procedures, patient demographics (e.g., sex, age), expected source of primary payment (e.g., Medicare, Medicaid, private insurance, self-pay, and other insurance types), and hospital charges and cost. Restricted access data files are available with a data use agreement and brief online security training.

  17. AHRQ Healthcare Cost and Utilization Project Summary Tables

    • datalumos.org
    Updated Feb 21, 2025
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    AHRQ (2025). AHRQ Healthcare Cost and Utilization Project Summary Tables [Dataset]. http://doi.org/10.3886/E220328V1
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    Dataset updated
    Feb 21, 2025
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Authors
    AHRQ
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary Trend TablesThe HCUP Summary Trend Tables include information on hospital utilization derived from the HCUP State Inpatient Databases (SID), State Emergency Department Databases (SEDD), National Inpatient Sample (NIS), and Nationwide Emergency Department Sample (NEDS). State statistics are displayed by discharge month and national and regional statistics are displayed by discharge quarter. Information on emergency department (ED) utilization is dependent on availability of HCUP data; not all HCUP Partners participate in the SEDD.The HCUP Summary Trend Tables include downloadable Microsoft® Excel tables with information on the following topics:Overview of trends in inpatient and emergency department utilizationAll inpatient encounter typesInpatient encounter typeNormal newbornsDeliveriesNon-elective inpatient stays, admitted through the EDNon-elective inpatient stays, not admitted through the EDElective inpatient staysInpatient service lineMaternal and neonatal conditionsMental health and substance use disordersInjuriesSurgeriesOther medical conditionsED treat-and-release visitsDescription of the data source, methodology, and clinical criteria (Excel file, 43 KB)Change log (Excel file, 65 KB)For each type of inpatient stay, there is an Excel file for the number of discharges, the percent of discharges, the average length of stay, the in-hospital mortality rate per 100 discharges,1 and the population-based rate per 100,000 population.2 Each Excel file contains State-specific, region-specific, and national statistics. For most files, trends begin in January 2017. Also included in each Excel file is a description of the HCUP databases and methodology.

  18. f

    In-hospital mortality rate and annual change in rate for specific infection...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee (2023). In-hospital mortality rate and annual change in rate for specific infection site among patients with sepsis. [Dataset]. http://doi.org/10.1371/journal.pone.0227752.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In-hospital mortality rate and annual change in rate for specific infection site among patients with sepsis.

  19. f

    Incidence, trends, and outcomes of infection sites among hospitalizations of...

    • plos.figshare.com
    tiff
    Updated Jun 2, 2023
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    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee (2023). Incidence, trends, and outcomes of infection sites among hospitalizations of sepsis: A nationwide study [Dataset]. http://doi.org/10.1371/journal.pone.0227752
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    tiffAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    PurposeTo determine the trends of infection sites and outcome of sepsis using a national population-based database.Materials and methodsUsing the Nationwide Inpatient Sample database of the US, adult sepsis hospitalizations and infection sites were identified using a validated approach that selects admissions with explicit ICD-9-CM codes for sepsis and diagnosis/procedure codes for acute organ dysfunctions. The primary outcome was the trend of incidence and in-hospital mortality of specific infection sites in sepsis patients. The secondary outcome was the impact of specific infection sites on in-hospital mortality.ResultsDuring the 9-year period, we identified 7,860,687 admissions of adult sepsis. Genitourinary tract infection (36.7%), lower respiratory tract infection (36.6%), and systemic fungal infection (9.2%) were the leading three sites of infection in patients with sepsis. Intra-abdominal infection (30.7%), lower respiratory tract infection (27.7%), and biliary tract infection (25.5%) were associated with highest mortality rate. The incidences of all sites of infections were trending upward. Musculoskeletal infection (annual increase: 34.2%) and skin and skin structure infection (annual increase: 23.0%) had the steepest increase. Mortality from all sites of infection has decreased significantly (trend p

  20. f

    Characteristics of study cohort, stratified by three periods between 2006...

    • figshare.com
    • plos.figshare.com
    xls
    Updated May 30, 2023
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    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee (2023). Characteristics of study cohort, stratified by three periods between 2006 and 2014. [Dataset]. http://doi.org/10.1371/journal.pone.0227752.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Eric H. Chou; Shaynna Mann; Tzu-Chun Hsu; Wan-Ting Hsu; Carolyn Chia-Yu Liu; Toral Bhakta; Dahlia M. Hassani; Chien-Chang Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Characteristics of study cohort, stratified by three periods between 2006 and 2014.

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Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). National Inpatient Sample (NIS) - Restricted Access Files [Dataset]. https://catalog.data.gov/dataset/hcup-national-nationwide-inpatient-sample-nis-restricted-access-file
Organization logoOrganization logo

National Inpatient Sample (NIS) - Restricted Access Files

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5 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Feb 22, 2025
Description

The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

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