Sharing behavioral data through a grid infrastructure using data standards

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.

[1]  D. Blumenthal,et al.  The "meaningful use" regulation for electronic health records. , 2010, The New England journal of medicine.

[2]  Philip R. O. Payne,et al.  Adoption and Adaptation of caGrid for CTSA , 2009, Summit on translational bioinformatics.

[3]  Carol M Hamilton,et al.  PhenX: a toolkit for interdisciplinary genetics research , 2010, Current opinion in lipidology.

[4]  Rick S Zimmerman,et al.  Health Behavior Theory and cumulative knowledge regarding health behaviors: are we moving in the right direction? , 2005, Health education research.

[5]  J. Fries,et al.  The Patient-Reported Outcomes Measurement Information System (PROMIS): Progress of an NIH Roadmap Cooperative Group During its First Two Years , 2007, Medical care.

[6]  Huaqin Pan,et al.  The PhenX Toolkit: Get the Most From Your Measures , 2011, American journal of epidemiology.

[7]  Sarah M. Greene,et al.  Bioinformatics: Tools to accelerate population science and disease control research. , 2010, American journal of preventive medicine.

[8]  Mark S. Tuttle,et al.  NCI Thesaurus: Using Science-Based Terminology to Integrate Cancer Research Results , 2004, MedInfo.

[9]  Vincenzo Bonifati,et al.  Assessment of neurological and behavioural function: the NIH Toolbox , 2010 .

[10]  Julie Evans,et al.  Model Formulation: The BRIDG Project: A Technical Report , 2008, J. Am. Medical Informatics Assoc..

[11]  P. Ubel,et al.  Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[12]  D. Ballard,et al.  The Comparative Effectiveness and Safety Emerging Methods Symposium: A Tribute to Harry A. Guess , 2007 .

[13]  David Berrigan,et al.  The National Collaborative on Childhood Obesity Research catalogue of surveillance systems and measures registry: new tools to spur innovation and increase productivity in childhood obesity research. , 2012, American journal of preventive medicine.

[14]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[15]  Paul Courtney,et al.  Data Liquidity in Health Information Systems , 2011, Cancer journal.

[16]  T. Kamarck,et al.  A global measure of perceived stress. , 1983, Journal of health and social behavior.

[17]  Daniel J Buysse,et al.  The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005-2008. , 2010, Journal of clinical epidemiology.

[18]  Cynthia Helba,et al.  Grid-enabled measures: using Science 2.0 to standardize measures and share data. , 2011, American journal of preventive medicine.

[19]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[20]  Joel H. Saltz,et al.  Model Formulation: caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research , 2008, J. Am. Medical Informatics Assoc..

[21]  K. Buetow,et al.  Cancer Informatics Vision: caBIG™ , 2006, Cancer informatics.

[22]  Larry Wright,et al.  Overview and Utilization of the NCI Thesaurus , 2004, Comparative and functional genomics.

[23]  C. Abraham,et al.  A taxonomy of behavior change techniques used in interventions. , 2008, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[24]  Bonnie Spring,et al.  Translational Behavioral Medicine: a pathway to better health , 2011, Translational behavioral medicine.

[25]  A. Jha,et al.  Meaningful use of electronic health records: the road ahead. , 2010, JAMA.

[26]  David Cella,et al.  Meaningful change in cancer-specific quality-of-life scores: Differences between improvement and worsening , 2002 .

[27]  Amy P Abernethy,et al.  Supporting implementation of evidence-based behavioral interventions: the role of data liquidity in facilitating translational behavioral medicine , 2011, Translational behavioral medicine.

[28]  C. Abraham,et al.  Making psychological theory useful for implementing evidence based practice: a consensus approach , 2005, Quality and Safety in Health Care.

[29]  Deborah L. McGuinness,et al.  A Semantically-enabled Community Health Portal for Cancer Prevention and Control , 2011 .

[30]  L. Radloff The CES-D Scale , 1977 .

[31]  P. Ubel,et al.  Validation of the Subjective Numeracy Scale: Effects of Low Numeracy on Comprehension of Risk Communications and Utility Elicitations , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[32]  Huaqin Pan,et al.  Using the PhenX Toolkit to Add Standard Measures to a Study , 2011, Current protocols in human genetics.

[33]  C. DesRoches,et al.  A progress report on electronic health records in U.S. hospitals. , 2010, Health affairs.