Literature DB >> 32308863

Unleashing the value of Common Data Elements through the CEDAR Workbench.

Martin J O'Connor1, Denise B Warzel2, Marcos Martínez-Romero1, Josef Hardi1, Debra Willrett1, Attila L Egyedi1, Aras Eftekhari3, John Graybeal1, Mark A Musen1.   

Abstract

Developing promising treatments in biomedicine often requires aggregation and analysis of data from disparate sources across the healthcare and research spectrum. To facilitate these approaches, there is a growing focus on supporting interoperation of datasets by standardizing data-capture and reporting requirements. Common Data Elements (CDEs)-precise specifications of questions and the set of allowable answers to each question-are increasingly being adopted to help meet these standardization goals. While CDEs can provide a strong conceptual foundation for interoperation, there are no widely recognized serialization or interchange formats to describe and exchange their definitions. As a result, CDEs defined in one system cannot be easily be reused by other systems. An additional problem is that current CDE-based systems tend to be rather heavyweight and cannot be easily adopted and used by third-parties. To address these problems, we developed extensions to a metadata management system called the CEDAR Workbench to provide a platform to simplify the creation, exchange, and use of CDEs. We show how the resulting system allows users to quickly define and share CDEs and to immediately use these CDEs to build and deploy Web-based forms to acquire conforming metadata. We also show how we incorporated a large CDE library from the National Cancer Institute's caDSR system and made these CDEs publicly available for general use. ©2019 AMIA - All rights reserved.

Entities:  

Year:  2020        PMID: 32308863      PMCID: PMC7153094     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  20 in total

1.  Standardizing the structure of stroke clinical and epidemiologic research data: the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Common Data Element (CDE) project.

Authors:  Jeffrey L Saver; Steven Warach; Scott Janis; Joanne Odenkirchen; Kyra Becker; Oscar Benavente; Joseph Broderick; Alexander W Dromerick; Pamela Duncan; Mitchell S V Elkind; Karen Johnston; Chelsea S Kidwell; James F Meschia; Lee Schwamm
Journal:  Stroke       Date:  2012-02-02       Impact factor: 7.914

2.  Health information technology data standards get down to business: maturation within domains and the emergence of interoperability.

Authors:  Rachel L Richesson; Christopher G Chute
Journal:  J Am Med Inform Assoc       Date:  2015-05-16       Impact factor: 4.497

3.  Analyzing Real-World Use of Research Common Data Elements.

Authors:  Vojtech Huser; Liz Amos
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

Review 4.  Clinical code set engineering for reusing EHR data for research: A review.

Authors:  Richard Williams; Evangelos Kontopantelis; Iain Buchan; Niels Peek
Journal:  J Biomed Inform       Date:  2017-04-22       Impact factor: 6.317

5.  Common Data Elements in Radiology.

Authors:  Daniel L Rubin; Charles E Kahn
Journal:  Radiology       Date:  2016-11-10       Impact factor: 11.105

6.  The Common Data Elements for cancer research: remarks on functions and structure.

Authors:  P M Nadkarni; C A Brandt
Journal:  Methods Inf Med       Date:  2006       Impact factor: 2.176

7.  Development of common data elements: the experience of and recommendations from the early detection research network.

Authors:  Marcy D Winget; John A Baron; Margaret R Spitz; Dean E Brenner; Denise Warzel; Heather Kincaid; Mark Thornquist; Ziding Feng
Journal:  Int J Med Inform       Date:  2003-04       Impact factor: 4.046

8.  The NLM value set authority center.

Authors:  Olivier Bodenreider; Duc Nguyen; Pishing Chiang; Philip Chuang; Maureen Madden; Rainer Winnenburg; Rob McClure; Steve Emrick; Ivor D'Souza
Journal:  Stud Health Technol Inform       Date:  2013

9.  Improving the value of clinical research through the use of Common Data Elements.

Authors:  Jerry Sheehan; Steven Hirschfeld; Erin Foster; Udi Ghitza; Kerry Goetz; Joanna Karpinski; Lisa Lang; Richard P Moser; Joanne Odenkirchen; Dianne Reeves; Yaffa Rubinstein; Ellen Werner; Michael Huerta
Journal:  Clin Trials       Date:  2016-06-15       Impact factor: 2.486

10.  Quality evaluation of value sets from cancer study common data elements using the UMLS semantic groups.

Authors:  Guoqian Jiang; Harold R Solbrig; Christopher G Chute
Journal:  J Am Med Inform Assoc       Date:  2012-04-17       Impact factor: 4.497

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  1 in total

Review 1.  Standardizing, harmonizing, and protecting data collection to broaden the impact of COVID-19 research: the rapid acceleration of diagnostics-underserved populations (RADx-UP) initiative.

Authors:  Gabriel A Carrillo; Michael Cohen-Wolkowiez; Emily M D'Agostino; Keith Marsolo; Lisa M Wruck; Laura Johnson; James Topping; Al Richmond; Giselle Corbie; Warren A Kibbe
Journal:  J Am Med Inform Assoc       Date:  2022-08-16       Impact factor: 7.942

  1 in total

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