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.

Representation of Personal and Person-Generated Data with HL7 FHIR and HAPI Endpoint Security with TSD: Proof-of-Concept Study (Preprint)

2021 ◽  
Author(s):  
AYAN CHATTERJEE ◽  
Andreas Prinz
Keyword(s):  
Data Protection ◽  
Data Exchange ◽  
Service Providers ◽  
Application Programming Interface ◽  
Information Model ◽  
Behavioral Data ◽  
Health Records ◽  
Standard Format ◽  
General Data Protection Regulation ◽  
Health Level 7

BACKGROUND Interoperability is a challenge in healthcare information systems because of heterogeneity in semantic and technical levels of data. It creates a problem in exchanging data from different sources. Person-Generated Health Data (PGHD) is health-related data created, recorded, or collected by individuals or family members, or caregivers. PGHD can be captured passively and continuously to create a more accurate and comprehensive picture of the individual. PGHD is a category of Personal Health Records (PHR) that helps people to store and manage their health records. The rapid growth of PHRs and standards to exchange PHRs in a secure way have improved different aspects of health practices and personal care. OBJECTIVE This is a two-fold study. First, this study aims to investigate Health Level 7’s (HL7) new standard, Fast Healthcare Interoperable Resources (FHIR), as a standard format to explain information model (personal, physiological, and behavioral data from heterogeneous sources, such as activity sensor, questionnaire, and interview) and clinical terminologies together. Second, we explore the protocol’s advantages in some detail and critically analyze endpoint security of the HL7 application programming interface (HAPI). METHODS To address the interoperability problem, we combine FHIR and internationally acclaimed medical terminologies and use JavaScript object notion (JSON) to represent and exchange PGHD. We develop a secure digital infrastructure with TSD (services for sensitive data) as Infrastructure as a Service (IaaS), where we deploy the HAPI FHIR server as a docker image. We integrate the concepts such as authentication, authorization, and identity brokering to protect HAPI REST interfaces. PGHD inside TSD are protected following the Norwegian Data Protection Policies (NORMEN) and General Data Protection Regulation (GDPR). We use personal, physiological, and behavioral data involved in health monitoring and store them in the TSD database using the HAPI FHIR server. Storage and retrieval of PGHD from TSD are HL7 compliant. RESULTS First, we discuss storing PGHD in TSD and retrieving it from TSD following HL7 protocol using the HAPI FHIR server in JSON format, combining the information model and medical terminologies. Second, it describes how to secure HAPI REST APIs with the TSD platform. CONCLUSIONS FHIR resources can establish a coherent view of PGHD collected from heterogeneous sources by enabling flexible data exchange between stakeholders and service providers. Besides, the study reveals that TSD is a secure platform for the management of PGHD. CLINICALTRIAL NA

scholarly journals Section 1: Health and Clinical Management: Leveraging Information Technology to Improve Quality and Safety

2007 ◽  
Vol 16 (01) ◽  
pp. 22-29
Author(s):  
D. W. Bates ◽  
J. S. Einbinder
Keyword(s):  
Information Technology ◽  
Patient Safety ◽  
Clinical Data ◽  
Data Exchange ◽  
Personal Health Records ◽  
Personal Health ◽  
Health Records ◽  
Provider Behavior ◽  
Published Research ◽  
Improve Patient

SummaryTo examine five areas that we will be central to informatics research in the years to come: changing provider behavior and improving outcomes, secondary uses of clinical data, using health information technology to improve patient safety, personal health records, and clinical data exchange.Potential articles were identified through Medline and Internet searches and were selected for inclusion in this review by the authors.We review highlights from the literature in these areas over the past year, drawing attention to key points and opportunities for future work.Informatics may be a key tool for helping to improve patient care quality, safety, and efficiency. However, questions remain about how best to use existing technologies, deploy new ones, and to evaluate the effects. A great deal of research has been done on changing provider behavior, but most work to date has shown that process benefits are easier to achieve than outcomes benefits, especially for chronic diseases. Use of secondary data (data warehouses and disease registries) has enormous potential, though published research is scarce. It is now clear in most nations that one of the key tools for improving patient safety will be information technology— many more studies of different approaches are needed in this area. Finally, both personal health records and clinical data exchange appear to be potentially transformative developments, but much of the published research to date on these topics appears to be taking place in the U.S.— more research from other nations is needed.

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
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