Article

Data standards for clinical research data collection forms: current status and challenges

Department of Pediatrics, University of South Florida College of Medicine, Tampa, Florida, USA.
Journal of the American Medical Informatics Association (Impact Factor: 3.93). 05/2011; 18(3):341-6. DOI: 10.1136/amiajnl-2011-000107
Source: PubMed

ABSTRACT Case report forms (CRFs) are used for structured-data collection in clinical research studies. Existing CRF-related standards encompass structural features of forms and data items, content standards, and specifications for using terminologies. This paper reviews existing standards and discusses their current limitations. Because clinical research is highly protocol-specific, forms-development processes are more easily standardized than is CRF content. Tools that support retrieval and reuse of existing items will enable standards adoption in clinical research applications. Such tools will depend upon formal relationships between items and terminological standards. Future standards adoption will depend upon standardized approaches for bridging generic structural standards and domain-specific content standards. Clinical research informatics can help define tools requirements in terms of workflow support for research activities, reconcile the perspectives of varied clinical research stakeholders, and coordinate standards efforts toward interoperability across healthcare and research data collection.

0 Followers
 · 
131 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Achieving semantic interoperability is critical for biomedical data sharing between individuals, organizations and systems. The ISO/IEC 11179 MetaData Registry (MDR) standard has been recognized as one of the solutions for this purpose. The standard model, however, is limited. Representing concepts consist of two or more values, for instance, are not allowed including blood pressure with systolic and diastolic values. We addressed the structural limitations of ISO/IEC 11179 by an integrated metadata object model in our previous research. In the present study, we introduce semantic extensions for the model by defining three new types of semantic relationships; dependency, composite and variable relationships. To evaluate our extensions in a real world setting, we measured the efficiency of metadata reduction by means of mapping to existing others. We extracted metadata from the College of American Pathologist Cancer Protocols and then evaluated our extensions. With no semantic loss, one third of the extracted metadata could be successfully eliminated, suggesting better strategy for implementing clinical MDRs with improved efficiency and utility.
    Studies in health technology and informatics 01/2013; 192:618-21. DOI:10.3233/978-1-61499-289-9-618
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Clinical research informatics is the rapidly evolving sub-discipline within biomedical informatics that focuses on developing new informatics theories, tools, and solutions to accelerate the full translational continuum: basic research to clinical trials (T1), clinical trials to academic health center practice (T2), diffusion and implementation to community practice (T3), and 'real world' outcomes (T4). We present a conceptual model based on an informatics-enabled clinical research workflow, integration across heterogeneous data sources, and core informatics tools and platforms. We use this conceptual model to highlight 18 new articles in the JAMIA special issue on clinical research informatics.
    Journal of the American Medical Informatics Association 04/2012; 19(e1):e36-e42. DOI:10.1136/amiajnl-2012-000968 · 3.93 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Patient registries remove barriers to performing research by assembling patient cohorts and data in a systematic, efficient, and proactive manner. Consequently, registries are a valuable strategy for facilitating research and scientific discovery. Registries for rare diseases are arguably even more valuable since there is difficulty in assembling cohorts of adequate size for study. Recently, the NIH Office of Rare Diseases Research created a rare disease registry Standard to facilitate research across multiple registries. We implemented the Standard for the Oculopharyngeal Muscular Dystrophy patient registry created at the University of New Mexico Health Sciences Center. We performed a data element analysis for each Common Data Element defined in the Standard. Problems included the use of previous HL7 versions, non-structured data types, and a recent update to the Standard. Overall, the Standard is an excellent first step toward standardizing patient registries to facilitate work on broader questions and promote novel interdisciplinary collaborations.
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 01/2013; 2013:269-77.

Preview

Download
3 Downloads
Available from