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Accessing the National Inpatient Sample (NIS) Database

A guide on accessing the National Inpatient Sample (NIS) and an overview of the qualities of the data set.

What is the National Inpatient Sample?

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.  The NIS is the largest 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 it enables analyses of rare conditions, uncommon treatments, and special populations. 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.

The NIS does NOT track the same patients year to year, therefore it is not suitable for research on hospital readmissions, patient progress, etc. 

Potential Research Uses

The National Inpatient Sample (NIS) can be used to apply more than 100 clinical and nonclinical variables to your research, including:

  • Primary and secondary diagnoses and procedures
  • Patient demographic characteristics
  • Hospital characteristics
  • Total charges
  • Expected payer
  • Discharge status
  • Length of stay
  • Severity and comorbidity measures

The National Inpatient Sample (NIS) can be used for research on a variety of topics, including:

  • Access to care
  • Quality of care and patient safety
  • Use and cost of hospital services
  • Variations in medical practice
  • Health care cost inflation
  • Medical treatment effectiveness
  • Impact of health policy changes
  • Diffusion of medical technology
  • Regional and national analyses
  • Utilization of health services by special populations


Which years does NYMC provide access to?

The Capozzi Library provides access to the following years of data:

  • 2015
  • 2016
  • 2017
  • 2018
  • 2019