56 National Inpatient Sample (NIS)

56.1 Organization

Agency for Healthcare Research and Quality (AHRQ), HHS

56.3 Description

  • Largest publicly available all-payer inpatient health care database in the US
  • Allows for national estimates of hospital inpatient stays
  • Used to make national estimates of health care utilization, access, charges, quality, and outcomes and explore trends over time
  • Topics promoted include utilization of health services by special populations, hospital stays for rare conditions, variations in medical practice, health care cost inflation, regional and national analyses, quality of care and patient safety, impact of health policy changes, and access to care

56.4 Vintage/Release Frequency

Annually since 1988

56.5 Observational Unit

Hospital inpatient admission

56.6 Collection Methodology

  • Twenty percent stratified sample of all discharges form US community hospitals (excludes rehabilitation and long-term acute care hospitals)
  • Most recently includes 46 states and DC (started with 8 states in first year)
  • Includes all patients regardless of payer (Medicare, Medicaid, private, uninsured)
  • Sampled from the State Inpatient Databases (SID) – now a sample of discharge records from all HCUP-participating hospitals
  • Four files: inpatient core file (e.g. age, total charges, expected primary payer); diagnosis and procedure groups file (ICD-9 and ICD-10 codes for diagnosis and procedure); disease severity measures file (ICD-9 and ICD-10 codes for disease severity); hospital weights file (hospital characteristics)

56.9 Cost

Cost varies by year

56.10 Proposal or Application required?

Application form required

56.11 DUA required?

Yes

56.12 Special Notes

  • In 2015, the diagnosis and procedure groups file as well as the disease severity measures file are split into two files (January – September for ICD-9 codes and October – December for ICD-10 codes)
  • There was a change in design in 2012; read documentation describing changes in methodology over time if conducting longitudinal data analyses.
  • Data Use Training must be completed and must sign Data Use Agreement
  • Before publishing with any HCUP database, ensure manuscript follows requirements of the HCUP DUA and includes the appropriate citation (see https://www.hcup- us.ahrq.gov/db/publishing.jsp)