Harmonization

This article describes what you can do in the Harmonization capability area, with example prompts for each action.

The underlying tool names and implementation details in this section are subject to change as the MCP server evolves. You do not need to know the tool names to use the MCP server — simply describe what you want to do in natural language and your AI assistant will handle the rest.

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Rhino's Harmonization tools allow you to map source datasets from participating sites to a target schema or standard medical vocabulary (e.g., OMOP, FHIR), and perform transformations in a federated manner. The raw and transformed data stay at each site — no data is centralised at any point.

If you do not have the required permissions, you will not be able to perform the following actions.

Managing harmonization schemas

Schemas define the structure that source and target data are mapped to. You can list, inspect, create, and delete schemas through conversation.

• "What data schemas are available in my workgroup?"

• "Show me the columns defined in the OMOP patient schema."

• "Create a new target schema called 'Standard Admissions' with columns for patient_id, admission_date, diagnosis_code, and los_days."

• "Delete the 'Draft Schema v1' schema."

Browsing medical vocabularies

Look up standard medical vocabulary concepts before constructing mappings. Supported vocabularies include OMOP CDM, SNOMED CT, ICD-10, LOINC, and RxNorm.

• "Find the SNOMED concept ID for 'type 2 diabetes mellitus'."

• "Look up ICD-10 codes related to heart failure."

• "What is the LOINC code for serum creatinine?"

• "Search the RxNorm vocabulary for metformin."

Creating semantic mappings

Use AI-assisted semantic mapping to generate suggested mappings from your source dataset column values to standard vocabulary concepts. Suggestions come with confidence scores for you to review before applying.

• "Generate an OMOP semantic mapping for the admissions dataset."

• "Suggest SNOMED mappings for the diagnosis codes in the trial dataset."

• "What standard concepts do the values in the 'procedure_type' column map to?"

Creating syntactic mappings

Syntactic mapping defines the structural field-level mapping between your source dataset's columns and the target schema's columns, independent of medical concept meaning.

• "Map the 'pt_id' column in my dataset to 'patient_id' in the standard admissions schema."

• "Create a field mapping from the trial dataset to the Standard Admissions schema."

Running the harmonization pipeline

Once your semantic and syntactic mappings are in place, run the full harmonization pipeline to transform the source dataset to the target schema across all sites.

• "Run the harmonization pipeline on the admissions dataset using the Standard Admissions schema."

• "Harmonize the trial data to OMOP CDM format and save the result as 'OMOP Trial Cohort'."

• "Transform the patient dataset to the standard schema across all three sites."