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Summary
An enhanced Soundex algorithm was developed for efficient phonetic name reduction in large patient record systems. This method improves name matching accuracy for better data retrieval in healthcare settings.
Area of Science:
- Medical Informatics
- Computer Science
- Data Management
Background:
- Accessing large patient record databases requires efficient name matching.
- Existing phonetic algorithms like Soundex have limitations in discrimination.
Purpose of the Study:
- To develop an improved phonetic name reduction algorithm for patient records.
- To enhance the Soundex methodology for greater accuracy and efficiency.
Main Methods:
- Enhanced the Soundex algorithm to equate beginning letters and improve discrimination.
- Developed a 16-bit representation for phonetic name encoding.
- Provided a specific algorithm for implementation.
Main Results:
- Achieved a potent 16-bit phonetic representation of names.
- The enhanced algorithm offers improved discrimination over standard Soundex.
- Demonstrated efficiency for accessing up to one million patient records.
Conclusions:
- The enhanced Soundex algorithm provides an efficient solution for phonetic name reduction in large-scale healthcare systems.
- This method can improve patient record accessibility and data retrieval accuracy.