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Related Experiment Videos

A natural language based search engine for ICD10 diagnosis encoding.

Robert Baud1

  • 1Service d'Informatique Médicale Hospitals of Geneva, Switzerland.

Medicinski Arhiv
|May 13, 2004
PubMed
Summary
This summary is machine-generated.

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Implementing an ICD10 search engine requires significant expertise and resources. Careful planning and adequate investment are crucial for a successful and beneficial outcome.

Area of Science:

  • Health Informatics
  • Medical Coding Systems

Background:

  • Implementing a robust ICD10 search engine presents considerable complexity.
  • Underestimating required expertise and data resources can lead to project failure.

Purpose of the Study:

  • To outline a multi-step process for developing an ICD10 search engine.
  • To highlight critical factors for successful implementation.

Main Methods:

  • Development of a systematic, multi-step implementation process.
  • Analysis of common pitfalls and success factors.

Main Results:

  • The complexity of ICD10 search engine implementation is significant.
  • Adequate expertise and data resources are essential prerequisites for success.

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Conclusions:

  • Successful ICD10 search engine development hinges on sufficient expert knowledge and resources.
  • A well-resourced and expertly guided project yields a responsive and valuable search tool.