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A HL7 transformer application for vaccination data report.

I-Chun Lin1, Hui-Mei Hsu, Chien-Tsai Liu

  • 1Department of Information Management, National Chung Cheng University, Min-Hsiung Chia-Yi, Taiwan, ROC. caviar_lin@mis.ccu.edu.tw

International Journal of Electronic Healthcare
|December 1, 2007
PubMed
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This study introduces a data transformer to convert Comma Separated Value (CSV) data into Health Level Seven (HL7) messages, ensuring data integrity. This flexible tool facilitates seamless data exchange between diverse hospital information systems, including vaccination reporting.

Area of Science:

  • Health Informatics
  • Data Interoperability
  • Computer Science

Background:

  • Healthcare systems generate vast amounts of data in various formats.
  • Interoperability between different hospital information systems remains a significant challenge.
  • Standardized data exchange is crucial for efficient healthcare management and public health initiatives.

Purpose of the Study:

  • To design and implement a data transformer capable of converting Comma Separated Value (CSV) data into Health Level Seven (HL7) messages.
  • To ensure the preservation of both syntax and semantics during data transformation.
  • To demonstrate the algorithm's flexibility and scalability for diverse healthcare data exchange scenarios.

Main Methods:

  • Development of a data transformer algorithm based on generic parsing principles for scheme-level mapping.

Related Experiment Videos

  • Application of the algorithm to transform non-uniform data formats for inter-hospital information system exchanges.
  • Utilizing the transformer for processing reported data within the Vaccination Reporting System (VRS).

    • Main Results:

    • Successful transformation of CSV data into HL7 messages without loss of information.
    • Demonstrated flexibility in handling non-uniform data formats.
    • Enabled direct reporting of diverse vaccination data formats to Taiwan's Center for Disease Control.

    Conclusions:

    • The developed data transformer effectively bridges data format gaps between different healthcare systems.
    • The algorithm's design supports scalability and adaptability for various data transformation needs.
    • Implementation in the VRS streamlines vaccination data reporting, enhancing public health surveillance capabilities.