Refreshing archetypes related to pathology reporting

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Style Guide for Diagnostic Archetype Design in openEHR

Introduction and Purpose:

This guide aims to provide a structured approach for designing diagnostic archetypes in openEHR. The purpose is to ensure that archetypes are consistently, accurately, and effectively modeled to represent diagnostic data, particularly in the field of pathology.

Requirements:

  • Completeness of data elements
  • Correct mapping of relations among data elements (semantic)
  • Standardization

Background:

Unlike clinical chemistry laboratory data, which primarily consists of name/value pairs, diagnostic pathology data is characterized by its rich semantics. For example, a malignant tumor requires detailed information such as morphological descriptions and specific tumor characteristics.

Structure of the Generic Archetype:

The generic archetype contains standardized core data elements applicable across various examinations. From these, more detailed and specific information is differentiated.

Checklist for Adding New Data Elements:

  1. Generic Element Check: Is the data element generic enough for various examinations?
  2. Multiplicity Check: Determine the occurrence of the data element (once or multiple times).
  3. Grouping/Nesting Check: Decide how to group or nest the data element.
  4. Data Type and Format Rule (Datentypen- und Formatregel): Confirm the data element’s conformity to established types and formats.

Example: Modeling “Malignant Tumor”

1. Generic Element Check:

  • Is the data element generic enough for various examinations?
  • Application: Yes, “malignant tumor” is a generic concept applicable across numerous types of pathological examinations, such as lung, breast, or colon biopsies.

2. Multiplicity Check:

  • Determine the occurrence of the data element (once or multiple times).
  • Application: “Malignant tumor” can occur multiple times within a single examination. For instance, in a lung biopsy, there could be multiple distinct tumors.

3. Grouping/Nesting Check:

  • Decide how to group or nest the data element.
  • Application: Each instance of a “malignant tumor” should be nested within the biopsy report. Further, specific information like tumor type, size, location and ICH results should be nested under each tumor instance.

4. Data Type and Format Rule:

  • Confirm the data element’s conformity to established types and formats.
  • Application: The “malignant tumor” data elements should conform to established medical terminologies and formats. For example, tumor size should be recorded in standardized units (like centimeters), and tumor type should use recognized classifications (like those from SNOMED CT).

I tried to keep it concise and hands-on using an example. The stage is open for feedback.

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