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Rehabilitation Dataset Directory: Dataset Profile

Dataset: The National Survey of Children with Special Health Care Needs (NS-CSHCN)

Basic Information
Dataset Full Name The National Survey of Children with Special Health Care Needs
Dataset Acronym NS-CSHCN
Summary

The NS-CSHCN provides a consistent source of data for all fifty U.S. states, the District of Columbia, and the U.S. Virgin Islands on the size and characteristics of the population of CSHCN. This survey provides detailed information regarding the prevalence of CSHCN as well as the demographic characteristics of these children and their families, their physical, emotional and behavioral heath, the types of health and support services they and their families need, and their access to and satisfaction with the care they receive. Trends can be compared across the waves of data collected.

Note that for 2016-2017 and beyond, the content of the NS-CSHCN is incorporated into the National Survey of Children’s Health (NSCH). 
Key Terms Children, Child(ren) with Special Health Care Needs, State level
Study Design Cross-Sectional
Data Type(s) Survey
Sponsoring Agency/Entity Department of Health and Human Services (HHS) Health Resources and Services Administration (HRSA)
Maternal and Child Health Bureau (MCHB)
Health Conditions/Disability Measures
Health Condition(s)

ADD/ADHD, Allergies, Anxiety disorders, Arthritis, Autism spectrum disorders, Blood disorder, Body mass index (BMI)/obesity, Cardiovascular conditions, Cerebral palsy, Chronic pain, Depression, Diabetes, Down syndrome, Epilepsy or seizure disorder, Migraine or frequent headaches, Muscular dystrophy, Pulmonary disorders, Traumatic brain injury (TBI)
Disability Measures Ambulatory disability, Cognitive disability, Communication impairment, Developmental disabilities, Functional limitations (ADLs and/or IADLs), Hearing disability, Independent living disability, Intellectual disability, Mental health disability, Self-care disability, Special equipment use/assistive technology, Visual disability
Measures/Outcomes of Interest
Topics Prevalence and number of CSHCN in each state, Percent of households with children with CSHCN, Health and functional status, Family characteristics, Child demographics, Health care access, Satisfaction with healthcare, Unmet healthcare needs, Preventative medical and dental care, Health insurance and coverage adequacy, Access to community-based services, Transition to adulthood, Child's health impact on family
Sample
Sample Population Children ages 0-17 with Special Health Care Needs
Sample Size/Notes 40,586 detailed CSHCN interviews were collected during 2009-2010; with a minimum of 750 interviews conducted for EACH state, the District of Columbia, and the U.S. Virgin Islands.
Unit of Observation Individual
Continent(s) North America
Countries

United States
Geographic Coverage National
Geographic Specificity State
Special Population(s)

Children/Youth
Data Collection
Data Collection Mode Survey
Years Collected 2001, 2005-2006, 2009-2010, 2016-2017 (as part of the NSCH)
Data Collection Frequency

Prior to 2016-2017: Every 5 years

2016-2017 and beyond (as part of the NSCH): Annual
Strengths and Limitations
Strengths Large sample size -- adequate to perform state level analysis. Wide variety of health and disability measures including activity and functional limitations and participation restrictions as well as medical conditions and impairments. Comparisons can be made between the waves of surveys (2001, 2005-2006 2009-2010, and as part of the NSCH for 2016-2017 and beyond). Well documented measures and data.
Limitations A number of the survey’s questions were revised or reordered, and some of the indicators have been re-defined, so some of the indicators cannot be compared between survey waves. More information about survey revisions is available at: http://childhealthdata.org/learn/NS-CSHCN/resources/survey-revisions
Data Details
Primary Website http://www.childhealthdata.org/learn/NS-CSHCN
Data Access

Public Use dataset (original SAS version):

https://www.cdc.gov/nchs/slaits/cshcn.htm


Data Use agreement (SPSS, SAS, and STATA with formats and labels): http://childhealthdata.org/help/dataset

Data Access Requirements

Public Use Dataset (original SAS version) Data Use agreement, No cost

Data Use agreement, $ cost (fee may apply to certain for-profit organizations)
Summary Tables/Reports

Browse Data:

http://childhealthdata.org/learn/NS-CSHCN/data 


Data Briefs and Reports:

http://childhealthdata.org/action/databriefs

 

Chart Books:

http://childhealthdata.org/action/chartbooks 
Data Components
  • Household file: One observation per household (n=196,159 for the U.S. and D.C.; count unavailable for U.S. Virgin Islands)
  • Screener file: One observation for each child in the household (n=371,617 for the U.S. and D.C.; count unavailable for U.S. Virgin Islands)
  • Interview file: 1 CSHCN per household - Detailed CSHCN interview (n=40,242 for the U.S. and D.C.; n=344 for the U.S. Virgin Islands)
Similar/Related Dataset(s)

National Survey of Children’s Health (NSCH)
Selected Papers
Other Papers NA
Technical http://childhealthdata.org/action/publications
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).

Other CLDR supported resources and collaborative opportunities:

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.

For questions or comments please contact disabilitystatistics@cornell.edu



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