Which rules apply when receiving HL7 messages and processing data values?

When processing HL7 messages, the rules emphasize that systems should be designed to handle variations in incoming messages. The correct approach is to ignore unexpected segments while treating any expected segments that are missing as null values. This practice ensures that the receiving system can continue to function appropriately even if it encounters unexpected or erroneous data structures.

By ignoring unexpected segments, the system can maintain its integrity and focus on the relevant information that it can process, thus reducing the risk of errors that arise from trying to handle unknown data. Treating missing expected segments as null helps maintain data consistency and makes it clear where information is absent, which is crucial for maintaining the quality of health data that systems rely on for patient care and reporting.

In contrast, including all unexpected fields in the response does not align with the necessity for clean and predictable data exchange, while identifying all fields as expected overlooks the dynamic nature of real-world data where variations can occur. Assuming that all received data values are correct fails to incorporate necessary validation and error checking, which is critical in healthcare settings where accuracy is paramount.