Clinical Research Informatics for Big Data and Precision Medicine

C. Weng; M.G. Kahn

doi:10.15265/IY-2016-019

Yearbook of Medical Informatics, Inhaltsverzeichnis

Yearb Med Inform 2016; 25(01): 211-218
DOI: 10.15265/IY-2016-019

IMIA and Schattauer GmbH

Georg Thieme Verlag KG Stuttgart

Clinical Research Informatics for Big Data and Precision Medicine

C. Weng

¹Department of Biomedical Informatics, Columbia University, New York, NY 10032 USA

,

M.G. Kahn

²Department of Pediatrics, University of Colorado, Denver, CO 80045 USA

› Institutsangaben

Abstract

Summary

Objectives: To reflect on the notable events and significant developments in Clinical Research Informatics (CRI) in the year of 2015 and discuss near-term trends impacting CRI.

Methods: We selected key publications that highlight not only important recent advances in CRI but also notable events likely to have significant impact on CRI activities over the next few years or longer, and consulted the discussions in relevant scientific communities and an online living textbook for modern clinical trials. We also related the new concepts with old problems to improve the continuity of CRI research.

Results: The highlights in CRI in 2015 include the growing adoption of electronic health records (EHR), the rapid development of regional, national, and global clinical data research networks for using EHR data to integrate scalable clinical research with clinical care and generate robust medical evidence. Data quality, integration, and fusion, data access by researchers, study transparency, results reproducibility, and infrastructure sustainability are persistent challenges.

Conclusion: The advances in Big Data Analytics and Internet technologies together with the engagement of citizens in sciences are shaping the global clinical research enterprise, which is getting more open and increasingly stakeholder-centered, where stakeholders include patients, clinicians, researchers, and sponsors.

Keywords

Evidence-based medicine - learning health system - individualized medicine - patient selection - electronic health records - data bank; data quality

Volltext

Referenzen

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