Useful Datasets

Useful Datasets

It may be useful to get an idea of what data is available in other datasets to help formulate research questions and develop a list of variables you want to include. Below

Healthcare Cost and Utilization Project (HCUP)
HCUP (pronounced "H-Cup") is a family of health care databases and related software tools and products developed through a Federal-State-Industry partnership and sponsored by the Agency for Healthcare Research and Quality. HCUP is based on statewide data collected by individual data organizations across the United States and provided to AHRQ through the HCUP partnership. HCUP would not be possible without statewide data collection projects. HCUP includes the largest collection of longitudinal hospital care data in the United States, encompassing all-payer, discharge-level information.

HCUP data are used for research on hospital utilization, access, charges, quality and outcomes. The data are used to describe patterns of care for uncommon as well as common diseases, to analyze hospital procedures, including those that are performed infrequently, and to study the care of population sub-groups such as minorities, children, women, and the uninsured. Researchers and policymakers use HCUP data to identify, track, analyze and compare hospital statistics at the national, regional and State levels.

  • The Nationwide Inpatient Sample (NIS) with inpatient data from a national sample of over 1,000 hospitals.
    • The Kids' Inpatient Database (KID) is a nationwide sample of pediatric inpatient discharges. 
    • The Nationwide Emergency Department Sample (NEDS) is a database that yields national estimates of emergency department (ED) visits. 
    • The State Inpatient Databases (SID)contain the universe of inpatient discharge abstracts from participating states. 
    • The State Ambulatory Surgery Databases (SASD) contain data from ambulatory care encounters from hospital-affiliated and sometimes freestanding ambulatory surgery sites. 
    • The State Emergency Department Databases (SEDD) contain data from hospital-affiliated emergency departments for visits that do not result in hospitalizations. 
    • Many of the HCUP databases are available for purchase through the HCUP Central Distributor.

Please refer to the fact sheet for more information:

Statewide Planning and Research Cooperative System (SPARCS)

SPARCS is a comprehensive data reporting system established in 1979 as a result between the health care industry and government. The database collects patient-level detail on patient characteristics, diagnoses and treatments, services, and charges for every hospital discharge, ambulatory surgery patient, and emergency department admission in New York State. SPARCS data feeds into the HCUP national database.

SPARCS data is available for inpatient discharges and outpatient visits. Inpatient data contains information on all discharges from Article 28 hospitals located in New York State. Data is not collected from Federal hospitals. Outpatient data consists of visits from Ambulatory Surgery (AS) and Emergency Department (ED) that do not result in a hospital admission. ED visits for patients who were subsequently admitted to a hospital inpatient service are contained in the SPARCS inpatient data.
Inpatient discharge data is available in two forms: Master and Abbreviated. The Master Inpatient file contains all data elements listed in the SPARCS Inpatient Output Data Dictionary and includes multiple records per discharge (continuation records).
Outpatient data files are available in three forms: Master Outpatient (AS and ED), Ambulatory Surgery Only, and Emergency Department Only. All three forms contain all elements listed in the SPARCS Outpatient Output Data Dictionary and include multiple records per discharge (continuation records).
An All-Visits Emergency Department data file is available and provides a complete data set on Emergency Department visits. This data contains all ED records in both the Inpatient and Outpatient data files and comprises approximately 7.2 million records.
Please refer to the SPARCS website for more information.

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