Yearb Med Inform 2017; 26(01): 209-213
DOI: 10.15265/IY-2017-024
Section 9: Clinical Research Informatics
Georg Thieme Verlag KG Stuttgart

Clinical Research Informatics: Contributions from 2016

C. Daniel
1  AP-HP Direction of Information Systems, Paris, France
2  INSERM UMRS 1142, Paris, France
R. Choquet
2  INSERM UMRS 1142, Paris, France
Section Editors for the IMIA Yearbook Section on Clinical Research Informatics› Author Affiliations
Further Information

Publication History

18 August 2017

Publication Date:
11 September 2017 (online)



Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select the best papers published in 2016.

Methods: A bibliographic search using a combination of MeSH and free terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was organized to finally conclude on the selection of best papers.

Results: Among the 452 papers published in 2016 in the various areas of CRI and returned by the query, the full review process selected four best papers. The authors of the first paper utilized a comprehensive representation of the patient medical record and semi-automatically labeled training sets to create phenotype models via a machine learning process. The second selected paper describes an open source tool chain securely connecting ResearchKit compatible applications (Apps) to the widely-used clinical research infrastructure Informatics for Integrating Biology and the Bedside (i2b2). The third selected paper describes the FAIR Guiding Principles for scientific data management and stewardship. The fourth selected paper focuses on the evaluation of the risk of privacy breaches in releasing genomics datasets.

Conclusions: A major trend in the 2016 publications is the variety of research on “real-world data” – healthcare-generated data, person health data, and patient-reported outcomes - highlighting the opportunities provided by new machine learning techniques as well as new potential risks of privacy breaches.