Exploring Semantics in Clinical Data Interoperability

AbstractClinical data interoperability requires shared specifications of meaning. This is the rationale for clinical data standards. Up until now, the adoption of such standards has been varied, although they are increasingly advocated in an area where proprietary specifications prevail, and semantic resources are geared to specific purposes and limited by boundaries of languages and jurisdictions. This chapter highlights the need of data standards in the context of the difficult and heterogeneous field of clinical data and the way how they are addressed by terminologies, ontologies and information models. It provides an overview of existing standards and discusses quality and implementation issues. Emphasis is also put on the eStandards methodology, which investigates needs for health data standards, supports the creation of standardised artefacts and defines actions for the implementation of standards.

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Healthcare Systems using Clinical Data

Cases on Healthcare Information Technology for Patient Care Management ◽

10.4018/978-1-4666-2671-3.ch013 ◽

2013 ◽

pp. 208-223

Author(s):

Biswadip Ghosh

Keyword(s):

Information Systems ◽

Clinical Data ◽

Multiple Sources ◽

Healthcare Organizations ◽

Data Interoperability ◽

Patient Health ◽

Care Systems ◽

Electronic Prescriptions ◽

Support Decision Making

The use of Information Systems (IS) in healthcare organizations is increasing. A variety of information systems have been implemented to support administrative activities such as scheduling systems, insurance and billing, electronic prescriptions, pharmaceutical dispensaries, and patient health records and portals. To make a fundamental difference in the delivery of patient care, systems that support important clinical healthcare decision processes are needed that leverage the clinical knowledge embedded in patient medical records. The aggregation of clinical data from multiple sources is difficult due to data interoperability issues. The VHA case study of the CICSP system illustrates a program that effectively leveraged clinical data from multiple surgical programs to build a system to support decision-making at many organizational levels. The technical and organizational practices from the VHA case provide important lessons to address interoperability issues when building other healthcare information systems.

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REDCap on FHIR: Clinical Data Interoperability Services

Journal of Biomedical Informatics ◽

10.1016/j.jbi.2021.103871 ◽

2021 ◽

pp. 103871

Author(s):

A.C. Cheng ◽

S.N. Duda ◽

R. Taylor ◽

F. Delacqua ◽

A.A. Lewis ◽

...

Keyword(s):

Clinical Data ◽

Data Interoperability

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Big Data for Nutrition Research in Pediatric Oncology: Current State and Framework for Advancement

JNCI Monographs ◽

10.1093/jncimonographs/lgz019 ◽

2019 ◽

Vol 2019 (54) ◽

pp. 127-131 ◽

Cited By ~ 3

Author(s):

Charles A Phillips ◽

Brad H Pollock

Keyword(s):

Big Data ◽

Clinical Data ◽

Pediatric Oncology ◽

Mobile Health ◽

Data Interoperability ◽

Current State ◽

Nutrition Research ◽

Mobile Health Applications ◽

Potential Use ◽

Health Applications

Abstract Recognition and treatment of malnutrition in pediatric oncology patients is crucial because it is associated with increased morbidity and mortality. Nutrition-relevant data collected from cancer clinical trials and nutrition-specific studies are insufficient to drive high-impact nutrition research without augmentation from additional data sources. To date, clinical big data resources are underused for nutrition research in pediatric oncology. Health-care big data can be broadly subclassified into three clinical data categories: administrative, electronic health record (including clinical data research networks and learning health systems), and mobile health. Along with -omics data, each has unique applications and limitations. We summarize the potential use of clinical big data to drive pediatric oncology nutrition research and identify key scientific gaps. A framework for advancement of big data utilization for pediatric oncology nutrition research is presented and focuses on transdisciplinary teams, data interoperability, validated cohort curation, data repurposing, and mobile health applications.

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