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Clinical code set engineering for reusing EHR data for research: A review.

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Developing standardized methods for clinical code sets is crucial for reliable Electronic Health Record (EHR) data research. This study reviews best practices for managing these code sets to improve study credibility.

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Area of Science:

  • Health Informatics
  • Clinical Research Methodology
  • Data Management

Background:

  • Reliable clinical code sets are vital for reusing Electronic Health Record (EHR) data in research.
  • Current code set definitions lack transparency and sharing, hindering research reproducibility.
  • A need exists for methodological standards in clinical code set management.

Purpose of the Study:

  • To review the literature on managing clinical code sets for research using clinical databases.
  • To provide recommendations for best practices in future studies and software development.

Main Methods:

  • Conducted an exhaustive search of methodological papers on clinical code set engineering for EHR data reuse.
  • Supplemented literature search with snowball sampling.
  • Reviewed code set management processes in e-phenotyping systems.

Main Results:

  • Reviewed 30 methodological papers, identifying common approaches like synonym lists, hierarchical searching, clinician input, and code set reuse.
  • Found 3 open-source software tools for code set management.
  • Commonly used methods included creating synonym lists (n=20), utilizing terminology hierarchies (n=23), clinician review (n=20), and reusing/updating existing sets (n=20).

Conclusions:

  • Further development and routine reporting of clinical code selection methods are needed to enhance EHR data research.
  • Software tools are essential for efficient creation, revision, review, and sharing of code sets.
  • Recommendations for designing and implementing such tools are provided.