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 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.
- 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
- Large Data & Rehabilitation Research News -
Funding Opportunities - Pilot and Travel Awards
The Center for Large Data Research and Data Sharing in Rehabilitation (CLDR) has announced its 2017 Call for Pilot Project Applications. The Center funds pilot studies in two categories:
- Category 1 – includes research examining questions using secondary analysis of large datasets. Funding provided up to $25,000. LOIs Due Feb 15
- Category 2 – involves the 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 – is a new mechanism which will provide travel awards for 4 early career researchers, postdoctoral fellows and graduate students to participate in the CLDR Symposium at the ACRM 2017 Annual Conference in Atlanta, GA.
Awards up to $2,500 will support conference registration, travel, and accommodations. Applications are due 15 July 2017.
Learn More and Apply >>
ACRM 2017 Annual Conference >>
New NIH Initiative and Policy Regarding the Sharing of Clinical Trials Data
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.
National Institutes of Health Research Plan on Rehabilitation: Moving the Field Forward
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
- ICPSR Summer Program in Quantitative Methods of Social Research The ICPSR Summer Program in Quantitative Methods of Social Research is recognized throughout the world as a leading source of basic and advanced instruction in a wide range of methodologies and techniques for research across the social, behavioral, and medical sciences.
- Data Analysis Training Institute of Connecticut Professional development summer workshops in a variety of modern data analytic techniques geared toward researchers who wish to utilize these techniques in their own work.
- University of Texas at Austin Summer Statistics Institute The Department of Statistics and Data Sciences at The University of Texas at Austin was proud to host the 9th annual UT Summer Statistics Institute (SSI) May 23–26, 2016.
AHRQ Medical Expenditure Panel Survey
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.
Archiving and Documenting Child Health and Human Development Data Sets (R03)
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.
NICHD Data and Specimen Hub (DASH)
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.
Public data resources on chronic conditions among Medicare beneficiaries
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.
New Medicare utilization and payment data available for home health agencies
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 | Fast Sheet | Press Release
NIH Big Data to Knowledge (BD2K)
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.
Source: UTMB Academic Enterprise [online magazine]
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).