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Working Toward Automated Coding in General Practice
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Working Toward Automated Coding in General Practice



Stephen Lean

Stephen Lean
School of Engineering and Advanced Technology
Massey University
(P35, 16/10/08, Coding stream, 3.50pm)



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Working Toward Automated Coding in General Practice Working Toward Automated Coding in General Practice Presentation Transcript

  • Working Toward Automated Coding in General Practice A Work in Progress
  • Background
    • Electronic Medical Record (EMR) coding at PHC level in NZ.
      • What is coding and what is used?
      • Why is coding carried out?
      • How is coding carried out and by who?
  • Open Problems
    • Two main issues arising from coding.
      • It is a purely manual process requiring the GP to spend considerable time reviewing the record and selecting a code to apply.
      • Non-standardised approach to coding leads to inconsistencies in the way codes are applied e.g. the same patient visit may be coded differently by two different GP’s.
  • Open Problems - Consequences
    • Time spent coding by GP’s would be much better spent seeing patients.
    • Non-standardised coding leads to a loss in quality of medical records.
    • Only increasing requirements from the Ministry of Health for coding so issues, if left unattended, will only be magnified.
  • Project
    • Use an IT system to analyse the free text content of EMRs with the intention of using NLP techniques to automatically identify potential codes for the record.
    • The idea here is to:
      • Reduce the time GP’s spend coding.
      • Standardise the application of codes.
  • Main Concept for Development
    • Apply annotations to concepts from the free text.
    • Abstract away from the raw text where the proposed system would then operate over a set of annotated concepts.
    • Utilise these annotated concepts, or combination thereof.
  • Annotations - Example
  • Results
    • Prototype design only implemented to a rudimentary level of functionality.
    • Progress and knowledge gained was encouraging and shows promise.
    • Probably not feasible to create a set of rules that provide coverage of all potential coding outcomes.
  • Results
    • Implementation of a logical reaction to the firing of rules, based on pattern recognition within text and patterns from within the graph of annotations, is a very complex issue.
    • Issues encountered:
      • No direct access to vocabulary of codes.
      • Lack of access to actual medical records.
      • Time and resources i.e. one person over six months.
    • Design decisions were affected by these issues.
  • Conclusions and Future Work
    • Introduction of SNOMED CT will require a reassessment of the way codes can be implemented within the system.
    • Determine what language aspects of EMRs are most problematic.
    • Traceability, result representation and assurance.
  • Questions
    • ?