Study Instance UID (0020,000D)

Mirth Connect Example

// (0020,000D) Study Instance UID — globally unique per study
var studyUID = String(msg.dataset.attr.(@tag == '0020000D').value).trim();
var seen = $gc('seen_studies') || new java.util.HashMap();
var now = Date.now();
// Expire entries older than 7 days
var iter = seen.entrySet().iterator();
while (iter.hasNext()) { if (now - iter.next().getValue() > 7 * 86400 * 1000) iter.remove(); }
if (seen.containsKey(studyUID)) {
  logger.info('Duplicate study, skipping: ' + studyUID);
  destinationSet.removeAll();
  return;
}
seen.put(studyUID, now);
$gc('seen_studies', seen);

Reference only — validate before production. Snippets are starting points, not turnkey solutions. Always test against your channel's specific message structure and your facility's interface specification. See Mirth Connect User Guide + NEMA PS3.6 + your vendor conformance statement for authoritative specification.

Common Operational Errors

• high Same Study Instance UID re-used by mistake

  Diagnosis: Modality firmware bug or operator error generates the same (0020,000D) for two different studies. Second study overwrites the first in the PACS or fails QIDO-RS lookup with ambiguous result.

  Fix: Add a Mirth de-duplication filter: maintain `seen_studies` map in `globalChannelMap` keyed by StudyInstanceUID. On collision, route to a quarantine channel and notify the modality biomed team.

• high UID exceeds 64-character cap

  Diagnosis: DICOM UI VR caps at 64 chars. Some modalities concatenate vendor-specific suffixes that exceed the cap. PACS rejects with Status 0xC000.

  Fix: Validate UID length before forward in your DICOM Reader transformer: `if (uid.length > 64) { reject }`. Notify modality vendor — UID generators must respect the cap.

Reference only — validate before applying a fix. Scenarios are drawn from common DICOM/HL7 v2 integration patterns; reproduce against your environment before acting on any diagnosis. See NEMA PS3.6 + your vendor conformance statement for authoritative specification. Severity levels: high (data-loss / patient-safety), medium (workflow disruption), low (cosmetic).