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.

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


Events

News & Announcements

AHRQ MEPS-HC Data Users’ Workshop September 19, 2017 - Rockville, MD

This workshop will provide a general overview of the Medical Expenditure Panel Survey (MEPS), with lectures on MEPS-HC survey design, health care utilization, expenditures, medical conditions; and statistical issues and challenges researchers face while analyzing MEPS-HC data.
- MEPS workshops & events
- Program information & registration
Healthcare Cost and Utilization Project (HCUP) Database Overview Webinar
- Wednesday, September 6 from 2:00-3:00 PM ET

Healthcare Cost and Utilization Project (HCUP) Overview of HCUP Products and Tools Webinar
- Wednesday, September 13 from 2:00-3:00 PM ET

HCUP Data Users' Workshop: Using HCUP's State Ambulatory Surgery and Services Databases (SASD)
- Tuesday, September 19 from 9:00 AM-4:00 PM ET
Location: U.S. Department of Health and Human Services (DHHS) Pavilion, Rockville, MD

Sponsored by AHRQ, the workshop is a one-day course for health services researchers on the use of HCUP databases and software tools. This year, there will be a specific focus on using the State Ambulatory Surgery and Services Databases (SASD) and how they differ from the State Inpatient Databases (SID) and State Emergency Department Databases (SEDD). Faculty will present instruction on working with the HCUP databases to conduct cross sectional analyses, with a specific hands-on comparison of the HCUP SASD and SID databases and how to use HCUP-US documentation to their advantage when developing analyses. Participants will use their own computers loaded with text editing software and will walk through SAS programs on the databases. It is highly recommended that attendees review the HCUP Online Overview Course prior to the workshop.

Learn more & register for these events
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.

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.

The Center for Large Data Research and Data Sharing in Rehabilitation (CLDR) has announced its 2017 Call for Pilot Project Applications in 3 categories:

Category 1: Large Data Pilot Studies - research examining questions using secondary analysis of large datasets. Funding provided up to $25,000. LOIs DUE FEB 15

Category 2: Data Sharing and Archiving Pilot Studies - archiving of existing data from a completed study. Funding is provided up to $10,000.

Category 3: Travel Award for Secondary Data Analysis of Archived Studies - early career researchers, postdoctoral fellows and graduate students will perform secondary analysis of data from studies in the Archive of Data on Disability to Enable Policy and research (ADDEP) repository. Award recipients will participate in the CLDR Symposium at the 2017 American Congress of Rehabilitation Medicine (ACRM) annual conference in Atlanta, GA. Funds, up to $2,500, will support conference registration, travel, and accommodations.

Visit the Pilot Projects pages for more information.
Small Grants for Secondary Analyses of Existing Data Sets and Stored Biospecimens (R03) (PA-17-299)

Eunice Kennedy Shriver National Institute of Child Health and Human Development

This Funding Opportunity Announcement (FOA) encourages applications that propose to conduct secondary analyses of publicly available NICHD-funded data sets or stored biospecimens. The goal of this program is to facilitate innovative yet cost-effective research utilizing data and biospecimens collected with NICHD resources.  

Posted Date - May 26, 2017
Open Date (Earliest Submission Date) - September 16, 2017

Standard dates apply, by 5:00 PM local time of applicant organization.

Recently the NIH, in collaboration with the U.S. Food and Drug Administration, announced new requirements for the sharing and dissemination of data resulting from clinical trials. Read Drs. Collins and Hudson's joint statement on the new policy and initiative: Clinical Trials: Sharing of Data and Living Up to Our End of the Bargain at the NIH Director's Blog.

Archiving and sharing data is one of the key focus areas of the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). Visit the Data Sharing & Archiving page for additional resources and information on our collaborative archival repository for disability- and rehabilitation-related datasets housed in the Inter-university Consortium for Political and Social research (ICPSR) at the University of Michigan. We also have pilot grant opportunities for archiving data from completed rehabilitation studies.

The National Center for Medical Rehabilitation Research (NCMRR), part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) at the NIH, led the development of this ambitious plan, aimed at energizing and advancing the research field.  The plan benefited from the support and partnership of 17 institutes and centers within the NIH, and extensive input from rehabilitation experts across the country.  It carries out many of the recommendations made by the Blue Ribbon Panel convened by NICHD in 2011. 

The comprehensive plan outlines six priority areas. It includes investigating new approaches to assistive technology in the home, expanding resources to recruit scientists and innovators to the field and analyzing the biology, chemistry and genetic components of recovery to better understand why some people are better able to recover after injury, while others require more rigorous rehabilitation.

For more details on the plan, visit:  https://www.nichd.nih.gov/publications/pubs/Documents/NIH_ResearchPlan_Rehabilitation.pdf
The Medical Expenditure Panel Survey, which began in 1996, is a set of large-scale surveys of families and individuals, their medical providers (doctors, hospitals, pharmacies, etc.), and employers across the United States. MEPS collects data on the specific health services that Americans use, how frequently they use them, the cost of these services, and how they are paid for, as well as data on the cost, scope, and breadth of health insurance held by and available to U.S. workers. More information is available at the AHRQ MEPS website.
The purpose of this funding opportunity announcement (FOA) is to invite R03 applications to support archiving and documenting existing data sets in order to enable secondary analysis of these data by the scientific community. The priority of this program is to archive data sets within the scientific mission of the NICHD; highest priority is to archive data collected with NICHD support. More information is available at the NIH website.

Researchers may now add data from NICHD-funded studies directly to the NICHD Data and Specimen Hub (DASH). Launched in August 2015, NICHD DASH is a centralized online resource that makes de-identified data available to researchers for secondary analyses, in accordance with the NIH Data Sharing Policy and the NIH Genomic Data Sharing Policy.

Read more: NICHD Invites Researchers to Share Their Data through Online Resource
These public data resources provide researchers and policymakers a better understanding of the burden of chronic conditions among beneficiaries and the implications for our health care system. This information can be used to improve care coordination and health outcomes for Medicare beneficiaries living with chronic conditions. The public data are available from the CMS website.
The Centers for Medicare & Medicaid Services (CMS) released a new dataset, the Home Health Agency Utilization and Payment Public Use File (Home Health Agency PUF). This data set, which is part of CMS's Medicare Provider Utilization and Payment Data set, details information on services provided to Medicare beneficiaries by home health agencies. These new data include information on 11,062 home health agencies, over 6 million claims, and over $18 billion in Medicare payments for 2013. Download Data | Fact Sheet | Press Release
The mission of the NIH Big Data to Knowledge (BD2K) initiative is to enable biomedical scientists to capitalize more fully on the Big Data being generated by those research communities. Read more at the BD2K website.
In response to growth of large biomedical datasets, the NIH formed the Working Group on Data and Informatics, charged with examining issues related to data. View the report at the NIH website.

An Interview with Dr. Ottenbacher

Big Data Collaboration Fuels Rehabilitation Research

Learn More