Accessing complex patient data from Arden Syntax Medical Logic Modules

Area of Science:

• Medical Informatics
• Clinical Decision Support Systems

Background:

• Arden Syntax is a 25-year-old standard for medical knowledge representation.
• Current Arden Syntax struggles with mapping complex, nested patient data.
• Efficient data mapping is crucial for automated decision-making and timely alerts.

Purpose of the Study:

• To investigate methods for mapping complex patient data into Arden Syntax Medical Logic Modules.
• To address limitations in handling complex microbiology data and HL7 messages.
• To reduce the delay between critical lab events and alerting.

Main Methods:

• Analyzed Arden Syntax data mapping capabilities and three Arden Syntax environments.
• Developed and tested three distinct approaches for mapping complex microbiology data.
• Measured execution times and memory usage for each approach.

Main Results:

• Current Arden Syntax lacks support for complex data structures.
• Three approaches were successfully implemented for mapping complex data.
• XML deserialization demonstrated the fastest mean execution time (84ms) with 6MB peak memory usage.

Conclusions:

• XML deserialization is the most effective method for mapping complex patient data to Arden Syntax.
• This approach can generically transform patient data in XML format.
• Extending Arden Syntax with XML data format support is recommended for better clinical decision support integration.