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J Am Med Inform Assoc 21:642-649 doi:10.1136/amiajnl-2013-001763
  • Research and applications

Sharing behavioral data through a grid infrastructure using data standards

  1. Eric A Ross2
  1. 1Department of Health Administration and Policy, College of Health and Human Services, George Mason University, Fairfax, Virginia, USA
  2. 2Fox Chase Cancer Center, Temple University Health, Philadelphia, Pennsylvania, USA
  3. 3Booz Allen Hamilton, Rockville, Maryland, USA
  4. 4University of Colorado Denver, Denver, Colorado, USA
  5. 5Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
  6. 6Dana-Farber Cancer Institute, Boston, Massachusetts, USA
  7. 7Behavioral Research Program, National Cancer Institute, Rockville, Maryland, USA
  8. 8PricewaterhouseCoopers LLP, McLean, Virginia, USA
  9. 9Science Applications International Corporation, McLean, Virginia, USA
  10. 10National Cancer Institute, Rockville, Maryland, USA
  11. 11Ireland Cancer Center, Case Western Reserve University, Cleveland, Ohio, USA
  12. 12Westat, Rockville, Maryland, USA
  1. Correspondence to Dr Hua Min, Department of Health Administration and Policy, College of Health and Human Services, 4400 University Drive – MS1J3, George Mason University, Fairfax, VA 22030, USA; gmu3{at}gmu.edu
  • Received 25 February 2013
  • Revised 21 August 2013
  • Accepted 9 September 2013
  • Published Online First 27 September 2013

Abstract

Objective In an effort to standardize behavioral measures and their data representation, the present study develops a methodology for incorporating measures found in the National Cancer Institute's (NCI) grid-enabled measures (GEM) portal, a repository for behavioral and social measures, into the cancer data standards registry and repository (caDSR).

Methods The methodology consists of four parts for curating GEM measures into the caDSR: (1) develop unified modeling language (UML) models for behavioral measures; (2) create common data elements (CDE) for UML components; (3) bind CDE with concepts from the NCI thesaurus; and (4) register CDE in the caDSR.

Results UML models have been developed for four GEM measures, which have been registered in the caDSR as CDE. New behavioral concepts related to these measures have been created and incorporated into the NCI thesaurus. Best practices for representing measures using UML models have been utilized in the practice (eg, caDSR). One dataset based on a GEM-curated measure is available for use by other systems and users connected to the grid.

Conclusions Behavioral and population science data can be standardized by using and extending current standards. A new branch of CDE for behavioral science was developed for the caDSR. It expands the caDSR domain coverage beyond the clinical and biological areas. In addition, missing terms and concepts specific to the behavioral measures addressed in this paper were added to the NCI thesaurus. A methodology was developed and refined for curation of behavioral and population science data.

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