Enabling FAIR Clinical Data Standards with Linked Data

2020 ◽  
pp. 303-306
Author(s):  
Javier D. Fernández ◽  
Nelia Lasierra ◽  
Didier Clement ◽  
Huw Mason ◽  
Ivan Robinson
Keyword(s):  
Clinical Data ◽  
Linked Data ◽  
Data Standards

692-P: Development and Adoption of CDISC Clinical Data Standards for Type 1 Diabetes (T1D)

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 692-P
Author(s):  
JOHN M. OWEN
Keyword(s):  
Type 1 Diabetes ◽  
Clinical Data ◽  
Data Standards

scholarly journals Linking Spinal Cord Injury Data Sets to Describe the Patient Journey Following Injury: A Protocol

2020 ◽  
Vol 26 (4) ◽  
pp. 232-242
Author(s):  
Vanessa K. Noonan ◽  
Susan B. Jaglal ◽  
Suzanne Humphreys ◽  
Shawna Cronin ◽  
Zeina Waheed ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Administrative Data ◽  
Clinical Data ◽  
Linked Data ◽  
Population Data ◽  
Data Sets ◽  
Patient Journey ◽  
Cord Injury ◽  
Incident Cases

Background: To optimize traumatic spinal cord injury (tSCI) care, administrative and clinical linked data are required to describe the patient’s journey. Objectives: To describe the methods and progress to deterministically link SCI data from multiple databases across the SCI continuum in British Columbia (BC) and Ontario (ON) to answer epidemiological and health service research questions. Methods: Patients with tSCI will be identified from the administrative Hospital Discharge Abstract Database using International Classification of Diseases (ICD) codes from Population Data BC and ICES data repositories in BC and ON, respectively. Admissions for tSCI will range between 1995–2017 for BC and 2009-2017 for ON. Linkage will occur with multiple administrative data holdings from Population Data BC and ICES to create the “Admin SCI Cohorts.” Clinical data from the Rick Hansen SCI Registry (and VerteBase in BC) will be transferred to Population Data BC and ICES. Linkage of the clinical data with the incident cases and administrative data at Population Data BC and ICES will create subsets of patients referred to as the “Clinical SCI Cohorts” for BC and ON. Deidentified patient-level linked data sets will be uploaded to a secure research environment for analysis. Data validation will include several steps, and data analysis plans will be created for each research question. Discussion: The creation of provincially linked tSCI data sets is unique; both clinical and administrative data are included to inform the optimization of care across the SCI continuum. Methods and lessons learned will inform future data-linking projects and care initiatives.

The Challenges of Implementing the Clinical Data Standards

2020 ◽  
Vol 34 (11) ◽  
pp. 2881-2883
Author(s):  
Deepak K. Tempe ◽  
Praveen K. Neema
Keyword(s):  
Clinical Data ◽  
Data Standards

Clinical data standards and nursing

2007 ◽  
Vol 14 (2) ◽  
pp. 26-28
Author(s):  
Alison Wallis
Keyword(s):  
Clinical Data ◽  
Data Standards

scholarly journals Continuing Education in New Standards and Technologies for the Organization of Data and Information: A Report on the Cataloging and Metadata Professional Development Survey

2018 ◽  
Vol 62 (1) ◽  
pp. 4 ◽  
Author(s):  
Yuji Tosaka ◽  
Jung-ran Park
Keyword(s):  
Professional Development ◽  
Semantic Web ◽  
Continuing Education ◽  
Digital Libraries ◽  
Linked Data ◽  
Data Standards ◽  
Skill Sets ◽  
Web Standards ◽  
Exploratory Stage ◽  
Original Survey

This study uses data from a large original survey (nearly one thousand initial respondents) to present how the cataloging and metadata community is approaching new and emerging data standards and technologies. The data analysis demonstrates strong professional-development interest in Semantic Web and Linked Data applications. With respect to continuing education topics, Linked Data technology, BIBFRAME, and an overview of current and emerging data standards and technologies ranked high. The survey data illustrate that personal continuing education interests often varied from reported institutional needs. These results reflect the fact that library services and projects in these emerging areas have not yet progressed beyond the exploratory stage. They also suggest that cataloging and metadata professionals expect to be able to exercise a mixture of core professional skill sets including teamwork, communication, and subject analysis, and the ability to adapt and accommodate Semantic Web standards and technologies, digital libraries, and other innovations in cataloging and metadata services.

scholarly journals BRIDG: a domain information model for translational and clinical protocol-driven research

2017 ◽  
Vol 24 (5) ◽  
pp. 882-890 ◽  
Author(s):  
Lauren B Becnel ◽  
Smita Hastak ◽  
Wendy Ver Hoef ◽  
Robert P Milius ◽  
MaryAnn Slack ◽  
...  
Keyword(s):  
Clinical Data ◽  
Biomedical Research ◽  
Data Exchange ◽  
Information Model ◽  
International Standards ◽  
Data Standards ◽  
Health Level 7 ◽  
Health Level ◽  
Analysis Experiment ◽  
Domain Information

Abstract Background: It is critical to integrate and analyze data from biological, translational, and clinical studies with data from health systems; however, electronic artifacts are stored in thousands of disparate systems that are often unable to readily exchange data. Objective: To facilitate meaningful data exchange, a model that presents a common understanding of biomedical research concepts and their relationships with health care semantics is required. The Biomedical Research Integrated Domain Group (BRIDG) domain information model fulfills this need. Software systems created from BRIDG have shared meaning “baked in,” enabling interoperability among disparate systems. For nearly 10 years, the Clinical Data Standards Interchange Consortium, the National Cancer Institute, the US Food and Drug Administration, and Health Level 7 International have been key stakeholders in developing BRIDG. Methods: BRIDG is an open-source Unified Modeling Language–class model developed through use cases and harmonization with other models. Results: With its 4+ releases, BRIDG includes clinical and now translational research concepts in its Common, Protocol Representation, Study Conduct, Adverse Events, Regulatory, Statistical Analysis, Experiment, Biospecimen, and Molecular Biology subdomains. Interpretation: The model is a Clinical Data Standards Interchange Consortium, Health Level 7 International, and International Standards Organization standard that has been utilized in national and international standards-based software development projects. It will continue to mature and evolve in the areas of clinical imaging, pathology, ontology, and vocabulary support. BRIDG 4.1.1 and prior releases are freely available at https://bridgmodel.nci.nih.gov.

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