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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Health care Cost & Utilization Project (HCUP): Kids' Inpatient Database (KID) (HCUP-KID)

Basic Information
Dataset Full Name Health care Cost & Utilization Project (HCUP): Kids' Inpatient Database (KID)
Dataset Acronym HCUP-KID
Summary The HCUP- KID is a database of hospital inpatient stays for children ages 20 and under, designed to permit researchers to study a broad range of conditions and procedures related to child health issues. It allows researchers to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The KID is one of the databases and software tools developed as part of the Healthcare Cost and Utilization Project (HCUP) to inform decision making at the national, state, and community levels.
Key Terms Utilization and Cost of Hospital Services, Health Care Cost, Comparative Effectiveness Research, Access and Quality of Care, Newborns, Children, Adolescents
Study Design Cross-Sectional
Data Type(s) Administrative
Sponsoring Agency/Entity

Department of Health and Human Services (HHS)

Agency for Healthcare Research and Quality (AHRQ)

Health Conditions/Disability Measures
Health Condition(s)

Arthritis, Blood disorder, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Depression, Diabetes, ICD-9/10 diagnostic codes, Infectious diseases, Kidney/renal condition, Neurological conditions, Partial or total paralysis, Pulmonary disorders, Thyroid disease

Disability Measures NA
Measures/Outcomes of Interest
Topics Primary diagnosis, Secondary diagnosis, Primary procedure, Secondary procedure, Admission status, Discharge status, Patient demographics (e.g., gender, age, race, median income for ZIP Code), Expected payment source, Total charges, Length of stay, Hospital characteristics (e.g., ownership, size, teaching status), Hospital services, Newborns, Children, Adolescents, Congenital anomalies, Economic burden, Adolescent pregnancy, Pediatric conditions, Outcomes, Death in hospital
Sample
Sample Population All hospital inpatient children: 20 years and younger; the 1997 KID contains data on children 18 years of age and younger
Sample Size/Notes 2012: 4,179 hospitals from 44 states containing 3,195,782 pediatric discharges
Unit of Observation Individual/Patient
Continent(s) North America
Countries

United States

Geographic Coverage National* (44 states in 2012)
Geographic Specificity Varies by state
Special Population(s)

Children/Youth

Data Collection
Data Collection Mode Administrative
Years Collected 1997, 2000, 2003, 2006, 2009, 2012, 2016 (the 2015 data contained blended ICD-9/10 coding, so 2016 data will be released instead)
Data Collection Frequency Every three years
Strengths and Limitations
Strengths Unique and powerful database of hospital inpatient stays for children, specifically designed to permit researchers to study a broad range of conditions and procedures related to child health issues. Researchers and policymakers can use the KID to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. Data is weighted to determine national estimates. Patient severity adjustment is available. Large sample allows for examination of incidence of uncommon conditions. Comprehensive documentation and training available through AHRQ. Data can be linked with other datasets like American Hospital Association (AHA) survey, and Area Resource File (ARF).
Limitations Information is limited to inpatient stays. Clinical details are limited (e.g., intensity of rehabilitation intervention). Not all states or hospitals participate. Not all data elements are uniformly coded or available across states. Different states have different rules regarding confidentiality resulting in missing values, cases, or hospitals. Coding of certain variables has changed over time.
Data Details
Primary Website https://www.hcup-us.ahrq.gov/kidoverview.jsp
Data Access

https://www.hcup-us.ahrq.gov/tech_assist/centdist.jsp  

Data Access Requirements Data Use agreement, $ Cost
Summary Tables/Reports https://www.hcup-us.ahrq.gov/db/nation/kid/kidrelatedreports.jsp
Data Components
  • Inpatient Core File: Contains pediatric discharge information including elements for data linkage, demographics, clinical and payment information (unit of observation is an inpatient stay record).
  • Hospital File: The hospital-level file (unit of observation is the hospital)
  • Disease Severity Measures File: To be used in conjunction with the Inpatient Core File (unit of observation is an inpatient stay record)
  • Diagnosis and Procedure Groups Files: to facilitate the use of the ICD-9/10 diagnostic and procedure information in the HCUP databases, to be used in conjunction with the Inpatient Core File (unit of observation is an inpatient stay record)
Similar/Related Dataset(s)

Nationwide Readmission Database (NRD)


Health care Cost & Utilization Project (HCUP): Nationwide Inpatient Sample (NIS) 


Health care Cost & Utilization Project (HCUP): State Inpatient Database (SID)

Selected Papers
Other Papers NA
Technical

Documentation:

https://www.hcup-us.ahrq.gov/db/nation/kid/kiddbdocumentation.jsp 


Introduction to 2012 HCUP-KID:

https://www.hcup-us.ahrq.gov/db/nation/kid/KID_2012_Introduction.pdf

Related Repositories
Repositories

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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