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.

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.

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

• Description of NIS Database
• Restrictions on Use

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• 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

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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

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NIS Areas of Research and HCUP Publications

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.

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.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all payers and the uninsured. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in health care data - the lack of nationally representative information on hospital readmissions for all ages. Outcomes of interest include national readmission rates, reasons for returning to the hospital for care, and the hospital costs for discharges with and without readmissions. Unweighted, the NRD contains data from approximately 18 million discharges each year. Weighted, it estimates roughly 35 million discharges. 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 NRD is drawn from HCUP State Inpatient Databases (SID) containing verified patient linkage numbers that can be used to track a person across hospitals within a State, while adhering to strict privacy guidelines. The NRD is not designed to support regional, State-, or hospital-specific readmission analyses.

The NRD contains more than 100 clinical and non-clinical data elements provided in a hospital discharge abstract. Data elements include but are not limited to: diagnoses, procedures, patient demographics (e.g., sex, age), expected source of payer, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge, discharge month, quarter, and year, total charges, length of stay, and data elements essential to readmission analyses. 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.

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.

National Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

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.

National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent by demographics.

Following collection of August 2021 survey data, an error in data processing led to incorrect categorization of some survey respondents; some respondents who should have been categorized as MSA: Principal City instead were categorized as MSA: Non-Principal City. Data downloaded during the period September 12, 2021 through September 30, 2021 may have incorrect estimates by MSA status, SVI of county of residence, and political leaning of county of residence.

National Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine uptake and confidence. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

Aims: We aimed to assess diabetes outcomes in heart failure (HF) patients with hypertrophic cardiomyopathy (HCM).Methods: The National Inpatient Sample database was analyzed to identify records from 2005 to 2015 of patients hospitalized for HF with concomitant HCM. We examined the prevalence of diabetes in those patients, assessed the temporal trend of in-hospital mortality, ventricular fibrillation, atrial fibrillation, and cardiogenic shock and compared diabetes patients to their non-diabetes counterparts.Results: Among patients with HF, 0.26% had HCM, of whom 29.3% had diabetes. Diabetes prevalence increased from 24.8% in 2005 to 32.7% in 2015. The mean age of patients with diabetes decreased from 71 ± 13 to 67.6 ± 14.2 (p < 0.01), but the prevalence of cardiovascular risk factors significantly increased. In-hospital mortality decreased from 4.3% to 3.2% between 2005 and 2015. Interestingly, cardiogenic shock, VF, and AF followed an upward trend. Age (OR = 1.04 [1.03–1.05]), female gender (OR = 1.50 [0.72–0.88]), and cardiovascular risk factors were associated with a higher in-hospital mortality risk in diabetes. Compared to non-diabetes patients, the ones with diabetes were younger and had more comorbidities. Unexpectedly, the adjusted risks of in-hospital mortality (aOR = 0.88 [0.76–0.91]), ventricular fibrillation (aOR = 0.79 [0.71–0.88]) and atrial fibrillation (aOR 0.80 [0.76–0.85]) were lower in patients with diabetes, but not cardiogenic shock (aOR 1.01 [0.80–1.27]). However, the length of stay was higher in patients with diabetes, and so were the total charges per stay.Conclusion: In total, we observed a temporal increase in diabetes prevalence among patients with HF and HCM. However, diabetes was paradoxically associated with lower in-hospital mortality and arrhythmias.

This dataset includes breastfeeding data from the National Immunization Survey (NIS). This data is used for DNPAO's Data, Trends, and Maps database, which provides national and state specific data on obesity, nutrition, physical activity, and breastfeeding. For more information about breastfeeding and NIS visit https://www.cdc.gov/breastfeeding/data/nis_data/index.htm.

ObjectThe potential imbalance between malpractice liability cost and quality of care has been an issue of debate. We investigated the association of malpractice liability with unfavorable outcomes and increased hospitalization charges in cranial neurosurgery.MethodsWe performed a retrospective cohort study involving patients who underwent cranial neurosurgical procedures from 2005-2010, and were registered in the National Inpatient Sample (NIS) database. We used data from the National Practitioner Data Bank (NPDB) from 2005 to 2010 to create measures of volume and size of malpractice claim payments. The association of the latter with the state-level mortality, length of stay (LOS), unfavorable discharge, and hospitalization charges for cranial neurosurgery was investigated.ResultsDuring the study period, there were 189,103 patients (mean age 46.4 years, with 48.3% females) who underwent cranial neurosurgical procedures, and were registered in NIS. In a multivariable regression, higher number of claims per physician in a state was associated with increased ln-transformed hospitalization charges (beta 0.18; 95% CI, 0.17 to 0.19). On the contrary, there was no association with mortality (OR 1.00; 95% CI, 0.94 to 1.06). We observed a small association with unfavorable discharge (OR 1.09; 95% CI, 1.06 to 1.13), and LOS (beta 0.01; 95% CI, 0.002 to 0.03). The size of the awarded claims demonstrated similar relationships. The average claims payment size (ln-transformed) (Pearson’s rho=0.435, P=0.01) demonstrated a positive correlation with the risk-adjusted hospitalization charges but did not demonstrate a correlation with mortality, unfavorable discharge, or LOS.ConclusionsIn the present national study, aggressive malpractice environment was not correlated with mortality but was associated with higher hospitalization charges after cranial neurosurgery. In view of the association of malpractice with the economics of healthcare, further research on its impact is necessary.

This data set contains the NEAR infrared spectrometer (NIS) data for the CRUISE4 phase. The data set begins on 1998-12-24T00:00:00.000 and ends 2000-01-10T23:59:59.999 . The data are raw telemetry data, provided in engineering units, that have been reformatted into FITS file format (NASA Office of Science and Technology (NOST), 100-1.0). In addition to the raw spectrometer data, a calibration file and algorithm are available. This data set is archived as a set of CDROM images as a part of the NEAR EDR volume set.

This composition appears in the Ni-S region of phase space. It's relative stability is shown in the Ni-S phase diagram (left). The relative stability of all other phases at this composition (and the combination of other stable phases, if no compound at this composition is stable) is shown in the relative stability plot (right)

This data set contains the NEAR infrared spectrometer (NIS) data for the CRUISE1 phase. The data set begins on 1996-02-20T00:00:00.000 and ends 1997-06-24T23:59:59.999 . The data are raw telemetry data, provided in engineering units, that have been reformatted into FITS file format (NASA Office of Science and Technology (NOST), 100-1.0). In addition to the raw spectrometer data, a calibration file and algorithm are available. This data set is archived as a set of CDROM images as a part of the NEAR EDR volume set.

NiS is Millerite structured and crystallizes in the trigonal R3m space group. The structure is three-dimensional. Ni2+ is bonded to five equivalent S2- atoms to form a mixture of distorted corner and edge-sharing NiS5 trigonal bipyramids. There are a spread of Ni–S bond distances ranging from 2.25–2.36 Å. S2- is bonded in a 5-coordinate geometry to five equivalent Ni2+ atoms.

Data obtained from computational DFT calculations on Monoclinic NiS is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

Data obtained from computational DFT calculations on Orthorhombic NiS is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files. This structure was obtained from ICSD (Collection code = NiS)

Analysis of ‘National Immunization Survey Child COVID Module (NIS-CCM): COVIDVaxViews| Data | Centers for Disease Control and Prevention (cdc.gov)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f6e5b821-c6f6-4b99-9764-9a09fdd66950 on 11 February 2022.

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

National Immunization Survey Child COVID Module (NIS-CCM): National Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

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