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Clinical Research Informatics: Contributions from 2018.

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  • 1AP-HP Information Systems Direction, Paris, France.

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This summary is machine-generated.

This study highlights top Clinical Research Informatics (CRI) papers from 2018, focusing on electronic health records, data quality, and distributed research networks. These advancements aim to improve large-scale health data utilization for better patient care and research outcomes.

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Area of Science:

  • Clinical Research Informatics (CRI)
  • Health Data Science
  • Biomedical Informatics

Background:

  • Current research in Clinical Research Informatics (CRI) is rapidly evolving.
  • There is a growing need to identify and disseminate key advancements in the field.

Purpose of the Study:

  • To summarize key contributions to Clinical Research Informatics (CRI) research.
  • To identify and select the best papers published in 2018 within the CRI domain.

Main Methods:

  • A comprehensive bibliographic search was conducted using PubMed with specific CRI-related terms.
  • A rigorous double-blind review process, followed by external peer-review and an editorial consensus meeting, was employed to select the best papers.

Main Results:

  • Four outstanding papers from 2018 were selected from 1,469 retrieved articles.
  • Selected papers cover algorithms for co-morbidity detection in Electronic Healthcare Records (EHRs), federated learning for heart failure prediction, and data quality assessment tools for EHRs and Clinical Data Warehouses (CDWs).
  • A significant data quality program across 37 hospitals was also highlighted, addressing data quality throughout the research lifecycle.

Conclusions:

  • CRI research is increasingly focused on Distributed Research Networks to leverage large-scale, harmonized data from digital sources.
  • Data quality assessment, privacy-enhancing techniques, and the integration of big data and AI are critical areas of focus.
  • Ambitious European initiatives are emerging to develop big data and AI for population health research, with the role of real-world data in clinical research still under exploration.