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A data mining approach to characterizing medical code usage patterns.

William E Spangler1, Jerrold H May, David P Strum

  • 1J. F. Donahue Graduate School of Business, Duquesne University, Pittsburgh, Pennsylvania 15282, USA. spangler@duq.edu

Journal of Medical Systems
|May 23, 2002
PubMed
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This study used data mining to analyze diagnostic (ICD-9) and procedure (CPT) code usage in hospitals, revealing areas where coding systems are effective and where improvements are needed for better patient classification.

Area of Science:

  • Health Informatics
  • Medical Data Analysis
  • Health Services Research

Background:

  • Current diagnostic (ICD-9) and procedure (CPT) coding systems are essential for healthcare management and billing.
  • Understanding physician code usage is crucial for evaluating the effectiveness of these classification systems.
  • Previous research has not fully explored the patterns and influencing factors of code utilization in clinical practice.

Purpose of the Study:

  • To evaluate the adequacy and effectiveness of current diagnostic (ICD-9) and procedure (CPT) coding systems.
  • To identify physician code usage patterns using a synthetic data mining approach.
  • To discover factors influencing the utilization of medical codes.

Main Methods:

  • Employed a synthetic data mining approach to analyze code usage in two US hospitals.

Related Experiment Videos

  • Combined relative frequency measurements with measures of industry concentration from economics.
  • Investigated the extent of physician utilization of available diagnostic and procedure codes.

    • Main Results:

    • Identified specific areas where the ICD-9 and CPT coding systems perform effectively.
    • Highlighted domains within the coding systems that exhibit relatively poor performance.
    • Revealed patterns in how physicians classify patients using the existing code sets.

    Conclusions:

    • The study provides insights into the practical application and limitations of current medical coding systems.
    • The findings can guide targeted improvements to enhance the accuracy and efficiency of ICD-9 and CPT codes.
    • This data mining methodology offers a framework for ongoing assessment of healthcare classification systems.