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Embedding "Smart" Disease Coding Within Routine Electronic Medical Record Workflow: Prospective Single-Arm Trial.

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New electronic medical record (EMR) tools significantly improved disease coding volume and consistency in primary care. Clinician-designed, workflow-embedded solutions enhance data quality with minimal disruption.

Keywords:
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Area of Science:

  • Health Informatics
  • Primary Care Research
  • Clinical Data Management

Background:

  • Electronic medical records (EMRs) are crucial for chronic disease management and health service planning.
  • Incomplete and inconsistent disease coding in EMRs limits data utility for primary and secondary care.
  • The McMaster University Sentinel and Information Collaboration (MUSIC) PBRN faced challenges with EMR data quality.

Purpose of the Study:

  • To develop and evaluate new EMR interface tools.
  • To improve the quantity and consistency of disease codes in the MUSIC PBRN disease registry.
  • To enhance the usability and effectiveness of EMR data capture.

Main Methods:

  • A single-arm prospective trial design with pre- and post-intervention analysis.
  • Involved clinician champions in gap analysis and iterative design of interface tools.
  • Integrated new tools into routine clinical workflow during billing activities, leveraging terminology standards.

Main Results:

  • Disease recording volume increased by 48.67%, with a 11.2-fold rise in the monthly coding rate.
  • The proportion of preferred International Classification of Diseases, 9th Revision (ICD9) codes increased by 17.03%.
  • New screen prompt tools facilitated 45.03% of disease code entries, showing significant quarterly increases.

Conclusions:

  • Clinician co-designed, workflow-embedded tools effectively address poor EMR disease coding and quality issues.
  • The intervention demonstrated significant usability and effectiveness in a routine care setting.
  • Improvements in primary care EMR problem list coding are achievable with minimal workflow disruption.