FIND Disability Statistics
American Community Survey (ACS)
- Employment Rate
- Not Working but Actively Looking for Work
- Full-Time / Full-Year Employment
- Annual Earnings
- Annual Household Income
- Supplemental Security Income (SSI)
- Educational Attainment
- Veterans Service-Connected Disability
- Health Insurance Coverage (and Type)
Current Population Survey (CPS)
EEOC Charge Data
Rehabilitation Dataset Directory: Dataset Profile
Dataset: PEDSnet (PEDSnet)
|Dataset Full Name||PEDSnet|
The PEDSnet Data is comprised of health and healthcare information from over 6 million children and youth. The data come from eight of the nation's largest pediatric health systems and includes information from all types of encounters: outpatient (primary care and specialty care), emergency department, surgical centers, and hospitals. The dataset contains information from over 100 million visits and includes patients with every type of pediatric disorder, and every pediatric specialty that provides services to children. Sources of data include electronic health records, health insurance claims, and child and parent surveys.
Pediatric care, Child, Young adult, Conditions, Medications, Procedures, Lab results, Encounters, Electronic Health Record (EHR), Electronic Medical Record (EMR), PROMIS® (Patient-Reported Outcomes Measurement Information System), Longitudinal, Insurance
Patient-Centered Outcomes Research Institute
|Health Conditions/Disability Measures|
ICD-9/10 diagnostic codes, SNOMED-CT codes
|Measures/Outcomes of Interest|
Outpatient encounters (~75 specialist visit types), Inpatient admissions, Emergency department encounters, Anthropometrics, Vital signs, Providers, Diagnoses, Procedures, Prescribed medications, Dispensed medications, Laboratory test results, Visit payer, Drug exposure, Condition occurrence, Procedure occurrence
See Data Domains document for more details on topical coverage and potential research utility.
Patients ages 0 to 24 years old with inpatient, outpatient, lab test or emergency department (ED) admission at the 8 participating sites.
Over 6 million individuals, 2009 to present.
|Unit of Observation||
Participating Pediatric Health System Sites:
State & Zip code
|Data Collection Mode||
Primarily based on standardized/harmonized Electronic Health Records (EHR) from participating hospitals.
Parent/patient survey data may be included : PROMIS® (Patient-Reported Outcomes Measurement Information System)
2009 - present
|Data Collection Frequency||
Updated on a quarterly basis
|Strengths and Limitations|
Description, instructions and link to request forms:
PEDSnet Policies Handbook: Accessing PEDSnet resources:
|Data Access Requirements||
Data Use agreement, $ Cost:
Basic demographics and chronic conditions prevalence:
|Data Components||Selected Papers|
PEDSnet: a National Pediatric Learning Health System (basic background)
Common Data Model:
Ask Our Researchers
Have a question about disability data or datasets?
E-mail your question to our researchers at email@example.com
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:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
- Data Sharing & Archiving at CLDR
- Pilot Project Program
- Visiting Scholars Program
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 firstname.lastname@example.org