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

The use of Common Data Elements can facilitate cross-study comparisons, data aggregation, and meta-analyses; simplify training and operations; improve overall efficiency; promote interoperability between different systems; and improve the quality of data collection. A Common Data Element is a combination of a precisely defined question (variable) paired with a specified set of responses to the question that is common to multiple datasets or used across different studies. Common Data Elements, especially when they conform to accepted standards, are identified by research communities from variable sets currently in use or are newly developed to address a designated data need. There are no formal international specifications governing the construction or use of Common Data Elements. Consequently, Common Data Elements tend to be made available by research communities on an empiric basis. Some limitations of Common Data Elements are that there may still be differences across studies in the interpretation and implementation of the Common Data Elements, variable validity in different populations, and inhibition by some existing research practices and the use of legacy data systems. Current National Institutes of Health efforts to support Common Data Element use are linked to the strengthening of National Institutes of Health Data Sharing policies and the investments in data repositories. Initiatives include cross-domain and domain-specific resources, construction of a Common Data Element Portal, and establishment of trans-National Institutes of Health working groups to address technical and implementation topics. The National Institutes of Health is seeking to lower the barriers to Common Data Element use through greater awareness and encourage the culture change necessary for their uptake and use. As National Institutes of Health, other agencies, professional societies, patient registries, and advocacy groups continue efforts to develop and promote the responsible use of Common Data Elements, particularly if linked to accepted data standards and terminologies, continued engagement with and feedback from the research community will remain important.

[1]  John S. Silva,et al.  Role of clinical trials informatics in the NCI's cancer informatics infrastructure , 1999, AMIA.

[2]  Steven Hirschfeld,et al.  A Federated Model of IRB Review for Multisite Studies: A Report on the National Children's Study Federated IRB Initiative. , 2014, IRB.

[3]  Udi E. Ghitza,et al.  NIDA Clinical Trials Network Common Data Elements Initiative: Advancing Big-Data Addictive-Disorders Research , 2015, Front. Psychiatry.

[4]  Guido Ferrari,et al.  Results of an ELISPOT proficiency panel conducted in 11 laboratories participating in international human immunodeficiency virus type 1 vaccine trials. , 2005, AIDS research and human retroviruses.

[5]  Sylvia Janetzki,et al.  Results and harmonization guidelines from two large-scale international Elispot proficiency panels conducted by the Cancer Vaccine Consortium (CVC/SVI) , 2007, Cancer Immunology, Immunotherapy.

[6]  Isaac S Kohane,et al.  Federalist principles for healthcare data networks , 2015, Nature Biotechnology.

[7]  Kathryn E Flynn,et al.  Use of central institutional review boards for multicenter clinical trials in the United States: A review of the literature , 2013, Clinical trials.

[8]  Christopher G. Chute,et al.  Translating Cancer Research into Cancer Care: Final Report of the Long Range Planning Committee , 2002 .

[9]  Yaffa R Rubinstein,et al.  NIH/NCATS/GRDR® Common Data Elements: A leading force for standardized data collection. , 2015, Contemporary clinical trials.