====== National Inpatient Sample database ====== The National [[Inpatient]] Sample [[database]] is one of the largest all-payer inpatient [[healthcare database]]s in the [[United States]]. It's a part of the [[Healthcare Cost and Utilization Project]] (HCUP), which is sponsored by the Agency for Healthcare Research and Quality (AHRQ). The NIS captures data from over 7 million hospital stays each year, representing more than 35 million hospitalizations nationally. Key features of the NIS database include: Large Sample Size: The database includes data from a large number of hospital stays across the United States, making it valuable for analyzing trends and patterns in healthcare. All-Payer Data: It includes information from patients with different types of insurance coverage (including Medicare, Medicaid, private insurance, and uninsured) as well as those covered by other payers, providing a comprehensive view of inpatient care across various payer types. Geographic and Hospital Diversity: The database covers a wide range of geographic regions and includes data from various types of hospitals, including academic medical centers, community hospitals, and others. Diagnosis and Procedure Information: The NIS contains detailed information on diagnoses and procedures performed during hospital stays, coded using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding systems. Utilization and Cost Data: It provides data on hospital utilization, including length of stay, discharge status, total charges, and other metrics related to healthcare utilization and costs. Researchers often use the NIS database for a wide range of purposes, including health services research, epidemiological studies, outcomes research, and policy analysis. Its large sample size and comprehensive data make it a valuable resource for understanding trends and disparities in healthcare delivery and outcomes across different populations and settings.