Education & Training  Accessing Data

Activities Supported by the Center

Rehabilitation Dataset Directory

Rehabilitation Dataset Directory screen capture of websiteThe Rehabilitation Dataset Directory is designed to assist rehabilitation researchers identify potential secondary data sources.


Rehabilitation Cross-Dataset Variable Catalog

Rehabilitation Dataset Directory website screen captureBrowse or search the Rehabilitation Research Cross-Dataset Variable Catalog for detailed variable level rehabilitation relevant information.

ADDEP

Archive of Data on Disability to Enable Policy and research (ADDEP) screen capture of websiteThe Archive of Data on Disability to Enable Policy and research is an initiative to build a repository of data on disability and rehabilitation with the mission to improve and enable research.

Edu Training

webinar Finding Disability Related Data: Tools for locating, accessing, and analyzing survey and administrative data
A joint Cornell University and ADDEP Webinar November 13, 2017
Presented by William Erickson, Sarah von Schrader: K. Lisa Yang and Hock E. Tan Institute on Employment and Disability, Cornell University Alison Stroud: Archive of Data on Disability to Enable Policy and Research (ADDEP) Inter-university Consortium for Political and Social Research (ICPSR)
screen capture from webinar Tools for Finding Disability and Rehabilitation Related Data

Research tools for exploring national-survey and administrative data

Secondary datasets such as national surveys and administrative data are valuable resources for testing hypotheses and generating national-level statistics about disability and rehabilitation related-issues. Unfortunately, it can be difficult to identify what datasets are available and what data are most appropriate for addressing a specific research interest.

This presentation introduces two innovative web-based resources designed to help researchers learn:

- What datasets related to disability and rehabilitation are out there?
- What topics are covered in each dataset?
- What are the dataset strengths and limitations?
- How do I access the datasets?
- How to link to the University of Michigan’s Archive of Data on Disability to Enable Policy and Research (ADDEP)

The Rehabilitation Dataset Directory  is a browse-able/searchable database providing an overview, description, sample and other pertinent information for nearly 60 datasets. The Rehabilitation Research Cross-dataset Variable Catalog allows the exploration of variables organized by topics (including disability and health conditions, healthcare, health behaviors and more) simultaneously across 6 major datasets.

CLDR/Cornell Webinar, May 5, 2017 - Presenters: William Erickson and Sarah Von Schrader, K. Lisa Yang and Hock E. Tan Institute on Employment and Disability, Cornell University.

presented by Steven Cramer, MD

Big Data for Rehabilitation: Promises, Pitfalls and Future Potential

ASNR ANNUAL MEETING • NOVEMBER 10 – 11, 2016 • MARRIOTT MISSION VALLEY – SAN DIEGO, CA

Organized by Sook-Lei Liew, PhD, OTR/L & Steven Cramer, MD

A persistent challenge in rehabilitation research is the vast heterogeneity within clinical populations. This inter-individual variability makes it difficult to establish significance and reliably replicate findings of rehabilitation studies across smaller sample sizes. Large, diverse datasets (aka “big data”; e.g., n>1000) have the potential to drive rehabilitation research forward by providing the greater statistical power needed for robustly evaluating clinical hypotheses and validating findings from smaller studies. However, collecting, organizing, and analyzing such large amounts of data comes with a number of limitations and considerations. Here we present current applications of ‘big data’ approaches for rehabilitation research across both retrospective and prospective collections of behavioral, neuroimaging, and clinical outcomes data. In each talk, we provide a balanced approach to this topic, highlighting both the potential of ‘big data’ approaches for driving the rehabilitation field forward, as well as the challenges associated with properly implementing, analyzing and interpreting the results. In doing so, we aim to educate attendees about current methodologies and available tools for conducting big data analyses in rehabilitation. We also hope to provide a tempered, realistic view of the limitations of these approaches and ways to complement this approach with experimental approaches. While several of the applications presented here focus on stroke rehabilitation, we emphasize general methodologies and applications that can be related to many rehabilitation populations. Attendees will not only gain big picture insights into how large datasets can be used to further rehabilitation research, but they will also learn practical knowledge regarding what types of information are contained in various databases, how to access or contribute to them, and how to use these resources for their own questions and purposes.
Speakers: Steven Cramer, MD; Liam Johnson, PhD; Sook-Lei Liew, PhD, OTR/L; Keith Lohse, PhD; Kenneth Ottenbacher, PhD, OTR
Users Guide: TBI

Users Guide: Traumatic Brain Injury Model Systems National Database

May 2013 - Arun Karpur, Employment and Disability Institute , Cornell University

University at Texas-Medical Branch Project Team:
Ken Ottenbacher, Ph.D., OTR (Principal Investigator) James E. Graham, Ph.D. Amol Karmarkar, Ph.D.
Employment and Disability Institute (EDI) Project Team:
Susanne Bruyère, Ph.D., CRC, Director of EDI William Erickson, Research Specialist Arun Karpur, Extension Faculty

SDHI

Webinar: Secondary Datasets in Disability and Health: Tools for Researchers Using US Datasets

National survey and administrative datasets continue to be a rich resource for generating national-level statistics for people with disabilities in the United States. Heterogeneous definitions of identifying individuals with disabilities as well as the varying sampling framework limit the use of secondary datasets.

SDHI Webinar, December 13, 2012 - Presented by Arun Karpur, Research Faculty, School of Industrial & Labor Relations Employment & Disability Institute, Cornell University and William Erickson, Research Specialist Employment & Disability Institute, Cornell University

User Guide: Disability Statistics from the American Community Survey

Users Guide: Disability Statistics  from the American Community  Survey (2008 Forward)

June 2012 - University at Texas-Medical Branch Project Team:
Ken Ottenbacher, PhD, OTR (Principal Investigator) Amol Karmarkar, PhD
Employment and Disability Institute (EDI) Project Team:
Susanne Bruyère, PhD, CRC, Director of EDI William Erickson, Research Specialist Arun Karpur, Extension Faculty

screen capture of slide Slides: Security, Privacy, and Ethical Issues in Database Research

UTMB/CRRLD (r24) Presentation 2011 - Presented by Linda S. Elting, Dr.P.H, University of Texas MD Anderson Cancer Center


Additional Resources

Edu Training

graphic The Annual Disability Statistics Compendium is a web-based tool that pools disability statistics published by various federal agencies together in one place. When working on legislative and other matters relating to persons with disabilities, the Compendium will make finding and using disability statistics easier.
Public Health Information and Data Tutorial The Public Health Information and Data Tutorial provides instruction for members of the public health workforce on issues related to information access and management.
va-open-data New Department of Veteran Affairs Open Data Portal

Data, APIs, tools and resources that can be used to develop web and mobile applications, design data visualizations, and create stories directly from VA resources.


Websites

  • Health and Medical Care Archive (HMCA) The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States.
  • PCORnet, the National Patient-Centered Clinical Research Network An innovative initiative of the Patient-Centered Outcomes Research Institute (PCORI) designed to make it faster, easier, and less costly to conduct clinical research than is now possible by harnessing the power of large amounts of health data and patient partnerships.

The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Colorado State University, Cornell University, 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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