2024-05-06 Vocab and Standard WG Meeting

Raj Dash

College of American Pathologists (CAP)

Chair

Steering Committee member

Scott Campbell

UNMC

Steering Committee member

Dan Rutz

Epic

Steering Committee member

Muktha Natrajan

CDC

Sandy Jones (Secondary)

CDC Cancer Surveillance

Anne Peruski (Secondary)

CDC

Andrea Pitkus

University of Wisconsin-Madison

Steering Committee member

Xavier Gansel

bioMérieux

Steering Committee member

Stan Huff

Graphite Health

Steering Committee member

John Snyder

NLM

Steering Committee member

Rob Hausam

Hausam Consulting

Marjorie Rollins

Regenstrief

Steering Committee member

Amy McCormick (secondary)

Epic

Nanguneri Nirmala

Tufts Medical Center

Steering Committee member

Mehdi Nassiri

Indiana University/Indiana University Health/Association for Molecular Pathology

Steering Committee member

Eza Hafeza

Regenstrief

Steering Committee member

Jim Case

Snomed International

Steering Committee member

Kevin Schap

CAP

Review: Identify tangible activities for this working group

1. Find a co-chair for this group!

2. This workgroup is slated to comment on the roadmap’s approach to addressing educational / training gaps in the use of standards such as LOINC. Will address at next meeting!

   1. Concepts around Healthcare IT (HIT) standards needs to be conveyed earlier in training for healthcare providers as use and application of standards in vended applications is the major gap.

   2. IT folks are less susceptible because they have a script that is more rigidly followed through implementation guidance. A vendor may not support functionality for standards or only partially support.

   3. Regulatory requirements (such as CLIA) may pose a hurdle to implementation of data standards.

   4. Implementation guidance is often not well read. Training resources may not be well publicized or readily available. Perhaps conformance testing tools need to be made more widely available?

   5. What might be helpful is to look at standards implementation from a data lifecycle standpoint across all users (end to end across ecosystem), rather than just training on a single standard for a single use case.

   6. Last paragraph on page 4 of the road map final version could be augmented with these points.

3.  

Use case review

LRI

LRI review

Specimen Type - currently uses table 487 in HL7. Consensus recommendation of the WG is to use SNOMED CT Specimen Type hierarchy.

SCTID: 123038009

123038009 | Specimen (specimen) |
en Specimen (specimen)
en Specimen
en Material (structure, substance, device) removed from a source (patient, donor, physical location, product)

Specimen Reject Reason - WG consensus is to continue to use HL7 table 490. The rejection reasons represent local administrative terms that can be challenging to predict. The most common terms appear to already be listed in table 490. The value set is only 13 data rows in size and may require augmentation in certain implementations. It is unclear how an implementor might encode data in an interoperable way if the needed rejection reason is not listed. Should one more entry be added that indicates “Reason other than those listed?” (and then need a way to capture an additional comment).

Specimen Condition - WG consensus is to continue to use HL7 table 493. The specimen condition list represents terms that can be challenging to predict. The list appears to be incomplete and requires additional terms to support specimen condition interoperability more thoroughly.

Relevant Clinical Information - in LOINC this falls under “preconditions” but may not be exhaustive. In the current HL7 table 916, the valueset focuses only on fasting. Other relevant clinical information such as what might be needed for a COVID test order/result would require ask at order entry questions. Given the broad definition from HL7 below, it may not be scalable to have a single HL7 category list as the value set for this. A mechanism needs to exist to convey ask-at-order-entry questions and answers (potentially pre-populated from the electronic record and then reviewed by a provider) on the interface in an interoperable manner. Once the extension is completed, LOINC preconditions will be available for use within the LOINC extension to SCT. Thus the WG consensus is that use of the full list of preconditions in SCT will be a better solution than attempting to create an exhaustive value set in table 916.

Definition from HL7: This field contains additional clinical information about the patient or specimen. This field is used to report the supporting and/or suspected diagnosis and clinical findings on requests for interpreted diagnostic studies where a simple text string or code is sufficient. This field could use all appropriate code sets including SNOMED to message Relevant Clinical Information. If more information is needed, such as date/time of the observation, who observed it, abnormal ranges, etc., or must be provided in further structured format, e.g., structured numeric with units of measure encoded, the Observation/Result group following the OBR should be used. Examples include reporting the amount of inspired carbon dioxide for blood gasses, the point in the menstrual cycle for cervical pap tests, and other conditions that influence test interpretations. Refer to HL7 Table 0916  Relevant Clinical Information in Chapter 2C, Code Tables, for valid values.

Device Type - current HL7 references table 961, which is empty. The consensus of the WG is to use the UDI schema proposed by the FDA (UDI Basics | FDA).

LOINC

SNOMED CT

UCUM

Next steps