Welcome to the CLDR

The Center for Large Data Research and Data Sharing in Rehabilitation (CLDR) is an extension of the previously funded, Center for Rehabilitation Research using Large Datasets. The Center continues to build scientific capacity in large data research by focusing on education and learning experiences designed to promote collaborative research. The CLDR has developed an innovative program that advances collaborative rehabilitation science research, information policy, and evidence-based rehabilitation practices.

The Center's mission is to build rehabilitation research capacity by increasing the number of investigators conducting rehabilitation and disability outcomes research using large administrative and research datasets. This mission has expended to include an important focus on data sharing and archiving information from completed rehabilitation research studies.

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Services Offered

  • Capacity Building in Large Data Research
  • Data Sharing and Archiving
  • Workshops, Webinars and Independent Training
  • Rehabilitation Data Directory and Variable Catalog
  • Pilot Project and Visiting Scholar Programs

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News and Announcements Archive

older african american couple  SCoA Press Release  11/11/18
For patients who need rehabilitation before they can leave the hospital, does the hospital make a difference in whether they go home at discharge?

That was the question Kenneth Ottenbacher, PhD, OTR and colleagues attempted to answer in their new paper published in JAMA Network Open on November 9th,  “Facility and Geographic Variation in Rates of SuccessfulCommunity Discharge after Inpatient Rehabilitation amongMedicare Fee-for-Service Beneficiaries."

The article looks at the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014. Dr. Addie Middleton, an assistant professor at the Medical University of South Carolina and a former faculty member at UTMB, is the lead author on the study. She is also a scholar in the Rehabilitation Sciences Career Development Program. Dr. Janet Bettger, another author on this study, is a former pilot project awardee of the Center for Large Data Research and Data Sharing in Rehabilitation.

Currently, more than 3 million of the approximately 9 million Veterans enrolled in VA care are over the age 65 and receive some care from the Veterans Health Administration (VHA). The VA Office of Geriatrics and Extended Care (GEC) offers a comprehensive array of programs and services with a unique responsibility for programs in all care settings. In addition, GEC has programs that support the transition of Veterans between each of these settings.

Join us on November 8 from 1:00 p.m. - 2:30 p.m. ET for a free webinar, Data and Analyses for VA Geriatrics & Extended Care and "Choose Home," to address the question of how the VA can better serve Veterans at home as they age and how data is used to guide the GEC in its development of a maintainable balance of services and needs?

The Stroke Dataset is a result of a study describing the cause/effect relationship between neural output and the biomechanical functions being executed in walking post-stroke patients. The dataset includes kinematic, kinetic, and electromyography (EMG) data collected from 27 post-stroke subjects and from 17 healthy control subjects.

Learn more about Medical University of South Carolina Stroke Data (ARRA).

Visit the Archive of Data on Disability to Enable Policy and research (ADDEP) to learn more on how to access these and other archived datasets.

The EI-CO study database was generated in collaboration with a large, urban EI program in Colorado, a community partner for an NIH/NCMRR R03 study. This academic-community research partnership provided researchers with access to an urban EI program's electronic administrative database. The dataset included as part of this collection includes 2045 cases for 44 variables; demographic variables include: race, ethnicity, language, sex, age, and developmental condition type.

Learn more about Early Intervention Colorado (EI-CO) Participant Characteristics, Service Use, and Outcomes, Colorado, 2014-2016.

Visit the Archive of Data on Disability to Enable Policy and research (ADDEP) to learn more on how to access these and other archived datasets.

NIH releases strategic plan for data science - June 4, 2018

Storing, managing, standardizing and publishing the vast amounts of data produced by biomedical research is a critical mission for the National Institutes of Health. In support of this effort, NIH today released its first Strategic Plan for Data Science that provides a roadmap for modernizing the NIH-funded biomedical data science ecosystem.  Over the course of the next year, NIH will begin implementing its strategy, with some elements of the plan already underway. NIH will continue to seek community input during the implementation phase. Learn more at the NIH website.

Health and Retirement Study: Biomarkers Data (Part 3 of 3) April 24, 2018

This webinar provides an overview of the data resources on physical measures and biomarkers in the Health and Retirement Study. The first part of the webinar provides information on the design of the physical measures and biomarkers data collection (through dried blood spot) and the measures collected. It also describes the Venous Blood Study with guidance on accessing these sensitive health data and relevant documentation.

Presented by Amanda Sonnega, associate research scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM), where she is responsible for integrating communication, outreach, and education efforts for the Health and Retirement Study; and Jessica Faul, associate research scientist in the Survey Research Center and a co–principal investigator of the Health and Retirement Study, and affiliated with the Michigan Center on the Demography of Aging, the Population Studies Center, and the University of Michigan BioSocial Methods Collaborative.

This webinar was developed and presented by the University of Michigan with funds from the National Institute on Aging and hosted by GSA.

GSA Webinars

Health and Retirement Study: Data on Cognition (Part 2 of 3) March 27, 2018

This webinar presents an overview of the data resources on cognition in the Health and Retirement Study (HRS). The first part of the webinar identifies and provides guidance on the measures that have been included in the core survey along with where to find them. It also describes the supplementary clinical study of dementia — the Aging, Demographics, and Memory Study (ADAMS) — and offers guidance on accessing these sensitive health data. The last part of the formal presentation provides an initial glimpse into a new data resource — the Healthy Cognitive Aging Project (HCAP) — that provided valid data on the presence of cognitive impairment and dementia in the U.S. population.

Presented by Amanda Sonnega, Associate Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM), where she is responsible for integrating communication, outreach, and education efforts for the Health and Retirement Study.

This webinar was developed and presented by the University of Michigan with funds from the National Institute on Aging and hosted by GSA.

GSA Webinars

photoFebruary, 2018
The UTMB Office of Biostatistics, Clinical & Translational Science Awards (CTSA) and CLDR sponsored this TRCC (Texas Regional CTSA Consortium) Quantitative Seminar: The Hope, Hype and Reality of EHR for Research, presented by Gulshan Sharma, MD, MPH, Vice President, Chief Medical & Clinical Innovation Officer.

photoFebruary, 2018

Dr. Sook-Lei Liew is the lead author of recent publication about ATLAS, "A large, open source dataset of stroke anatomical brain images and manual lesion segmentations." She is a pilot project recipient at CLDR and a phase 2 scholar at the Rehabilitation Research Career Development (RRCD) program.

brainThe Anatomical Tracings of Lesions after Stroke (ATLAS) dataset is now available for download through the Archive of Data on Disability to Enable Policy and research (ADDEP), supported by CLDR. Researchers globally are using the scans to develop and test algorithms that can automatically process MRI images from stroke patients. In the long run, scientists hope to identify biological markers that forecast which patients will respond to various rehabilitation therapies and personalize treatment plans.

Read More: MRI stroke data set released - Science Daily | USC releases MRI stroke dataset to spur AI research - Health Data Management | Researchers hope to use MRI for stroke treatment, recovery - HSC News
photoFebruary, 2018
Nancy Baker, ScD, OTR/L is lead author on a new publication, What Types of Treatment Are Provided for Patients With Carpal Tunnel Syndrome? A Retrospective Analysis of Commercial Insurance in the journal of the American Academy of Physical Medicine and Rehabilitation.Dr. Baker is a CLDR Visiting Scholar.

Introduction to the Health and Retirement Study (Part 1 of 3) January 9, 2018

This introduction familiarizes new users with the study including previewing available data, how to access it, and some tips on getting started with analysis. An overview of the study can be found in PubMed: Cohort Profile: the Health and Retirement Study (HRS).

This webinar was developed and presented by the University of Michigan with funds from the National Institute on Aging and hosted by GSA.

GSA Webinars

Approximately 53 million Americans live with a disability. For decades, the National Institutes of Health (NIH) has been conducting and supporting research to discover new ways to minimize disability and enhance the quality of life of people with disabilities. After the passage of the Americans With Disabilities Act, the NIH established the National Center for Medical Rehabilitation Research with the goal of developing and implementing a rehabilitation research agenda.

The NIH recently organized a conference under the title "Rehabilitation Research at NIH: Moving the Field Forward." This report is a summary of the discussions and proposals that will help guide rehabilitation research at NIH in the near future.

An Interview with Dr. Ottenbacher

Big Data Collaboration Fuels Rehabilitation Research

Learn More

Contact Us

CLDR is supported by:
 Division of Rehab Sciences
 (409) 747-1637
 CLDR.info@utmb.edu


MR3: Medical Rehabilitation Research Resource Network

CLDR is part of the Medical Rehabilitation Research Resource Network (MR3 Network), funded by The National Institute of Child Health and Human Development (NICHD), through the National Center for Medical Rehabilitation Research (NCMRR), the National Institute for Neurological Disorders and Stroke (NINDS), and the National Institute of Biomedical Imaging and Bioengineering (NIBIB).

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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