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Diagnostic Imaging

Tests that result in visual images requiring interpretation by a credentialed professional.

Data Element

Applicable Vocabulary Standard(s)

Diagnostic Imaging Report

Interpreted results of imaging test that includes the study performed, reason, findings, and impressions. Includes both structured and unstructured (narrative) components.

Diagnostic Imaging Test

The name of the test performed which generates visual images (radiographic, photographic, video, etc.) of anatomic structures; and requires interpretation by qualified professionals.

Logical Observation Identifiers Names and Codes (LOINC®) version 2.70

Comment

More than just radiology images

Should clarify that Diagnostic Imaging applies to colonoscopies, retinal images, cardiac ultrasounds, etc., all of which carry images and not just radiology images. Need more guidance about when to use the following code. Same issues as for  narrative pathology and laboratory reports. 18748-4 Diagnostic imaging study Diagnostic Imaging Report (DIR) contains a consulting specialist's interpretation of image data. It conveys the interpretation to the referring (ordering) physician and is for use in Radiology, Endoscopy, Cardiology, and other imaging specialties.

Common pattern needed for Diagnostic Imaging Data Elements

To present a more consistent way of putting forth testing for Diagnostic Imaging, (consistent with Laboratory and Pathology information too), we recommend creating a consistent set of data elements and a similar set of definitions and relationships.  The Order expresses the test when it is in an “ordered” state whereas the Test (same notion as "study/exam"), expresses the test when it is in a “completed” state.  The value/result is the measured value determined by the test as its “results”. The report contains information about the order, the test and the value/result along with other narrative explaining the assessment of the results.

Cerner Corporation USCDI Draft V2 Comments - Diagnostic Imaging

Provided below are Cerner's comments on the USCDI draft V2 proposals for the Diagnostic Imaging data class. Cerner's full public comments on the USCDI draft V2 have been posted on the USCDI general comments section.   Cerner appreciates and supports the proposal to add the new Diagnostic Imaging data class in the USCDI V2. The exchange of diagnostic imaging data is important to facilitate the best possible patient care and is mature enough within the industry for inclusion in the USCDI. However, we believe there are some important changes that must be made to the underlying data element proposals before adopting.   First and foremost, while we agree that the Diagnostic Imaging Narrative data element should be removed from the Clinical Notes data class as the content does not fit the intent of that data class, it represents a duplication of the newly proposed Diagnostic Imaging Report data element. As defined, the Diagnostic Imaging Report data element would actually encompass the Diagnostic Imaging Narrative (i.e., the narrative interpretation of the image). Furthermore, the standalone Diagnostic Imaging Narrative is limited in its value and usability without the additional supporting information from the full imaging report. Therefore, the Diagnostic Imaging Narrative data element should be eliminated from the Diagnostic Imaging data class in favor of the more complete Diagnostic Imaging Report data element.   Regarding the Diagnostic Imaging Report data element, there needs to be more clarity on the specific scope of a report. Most importantly, clarification is needed that the report does not include the diagnostic image itself. While in some cases the full report may contain replications or components of the diagnostic image (e.g., a .PDF report containing references to the image pointing out particular components for the interpretation), the diagnostic image itself is independent. Additionally, HL7 FHIR US Core does not currently provide a Profile supporting diagnostic images (only the reports), so it would be inconsistent with ONC’s stated intent with the USCDI V2 to include the actual diagnostic image in scope.   The proposal to adopt LOINC as the standard for the Diagnostic Imaging Report data element also appears problematic considering that the full report would consist of both structured and unstructured components. We would recommend that the standard be clarified as specific to distinct components of the full report to be clear that unstructured content is not expected to be codified by LOINC. Additionally, we note that if the re-classification and replacement of the Diagnostic Imaging Narrative data element is finalized in USCDI V2, ONC should include the same changes in USCDI V1 via an errata adoption. This is important for consistency as HIT developers and healthcare providers are currently working to align with USCDI V1. If changes other than additions are made for USCDI V2 it may create inconsistencies for exchange of the same data between those versions.   Finally, while we also support inclusion of the Diagnostic Imaging Order element to represent the service request from which the Diagnostic Imaging Report originated, there is a need to ensure that the definition sufficiently distinguishes the data element from a procedure that may also be associated with the Diagnostic Imaging Report.

Clinovations GovHealth USCDI Draft V2: Diagnostic Imaging

Consider future expansion to support automated adherence to clinical guidelines
  • In finalizing the forthcoming version of USCDI, please clarify the difference in Diagnostic Imaging Report and Diagnostic Imaging Narrative. Both appear to contain the radiologist’s interpretation of the data and use the same LOINC code. Please also clarify the difference between these categories and the Diagnostic Studies and Results class added in Level 2.
  • To support providers in following clinical guideline timelines, we raise the consideration of future expansion to include the date for orders and procedures and normal/abnormal value results. Knowing the study date, exam, date, and read date, for example, could facilitate automated tracking and follow-up to reduce provider burden. Knowing normal and abnormal value data could facilitate and prioritize follow-up.

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