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Review paper: coding systems in health care

J J Cimino1

  • 1Department of Medical Informatics, Columbia University College of Physicians and Surgeons, New York, NY, USA. James.Cimino@columbia.edu

Methods of Information in Medicine
|December 1, 1996
PubMed
Summary

Existing medical coding systems lack the detail needed for comprehensive patient data management. This review examines current coding schemes and efforts to establish unified medical language standards for better data utilization.

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Area of Science:

  • Health Informatics
  • Medical Terminology
  • Computer Science in Medicine

Background:

  • Computer-based patient data is crucial for healthcare functions like direct care, reporting, decision support, and research.
  • Current abstracting coding systems (e.g., ICD, CPT, DRGs, MeSH) lack sufficient detail for these diverse applications.
  • Application developers often create proprietary coding schemes, hindering interoperability and standardization.

Purpose of the Study:

  • To review existing coding schemes for abstracting, electronic records, and comprehensive medical data.
  • To discuss the barriers preventing the widespread acceptance of medical coding standards.
  • To highlight current initiatives aimed at developing unified medical language systems.

Main Methods:

  • Literature review of existing medical coding systems and standardization efforts.

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  • Analysis of the limitations of current abstracting and comprehensive coding schemes.
  • Discussion of emerging terminologies and their potential as standards.

    • Main Results:

    • No single standard adequately supports all functions of coded patient data.
    • Existing systems like ICD, CPT, and MeSH are insufficient for detailed data needs.
    • Several comprehensive coding initiatives (SNOMED, UMLS, Read Codes, etc.) are being developed to address these limitations.

    Conclusions:

    • A universally accepted standard for comprehensive medical coding is currently lacking.
    • Overcoming impediments to standardization requires collaborative efforts and robust terminology development.
    • Initiatives like the Unified Medical Language System (UMLS) show promise for future medical data integration.