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Clinical Research Informatics: Contributions from 2017.

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This study highlights five key papers from 2017 in Clinical Research Informatics (CRI), focusing on patient consent, natural language processing for mental illness, EHR platform utilization, patient safety tools, and bias reduction in health data research.

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Area of Science:

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

Background:

  • Clinical Research Informatics (CRI) is a rapidly evolving field.
  • The year 2017 saw significant advancements in tools and platforms for health data research.

Purpose of the Study:

  • To identify and summarize seminal contributions to Clinical Research Informatics (CRI) published in 2017.
  • To select the best papers that represent the cutting edge of CRI research.

Main Methods:

  • A comprehensive bibliographic search of CRI literature published in 2017 was conducted using PubMed.
  • A rigorous double-blind review process, followed by external peer review and editorial consensus, was employed to select the top papers.

Main Results:

  • Five outstanding papers were selected from 741 initial candidates.
  • Selected papers cover diverse CRI areas: patient consent for data use, natural language processing for mental illness symptom extraction, EHR platform implementation for clinical studies, case-crossover analysis for patient safety, and bias reduction methods for electronic health records data.

Conclusions:

  • CRI research is maturing, yielding scalable tools and platforms with promising outcomes.
  • Addressing biases in real-world health data is crucial for advancing learning health systems.
  • Continued innovation in CRI is essential for leveraging large-scale health data effectively and ethically.