| name | demographic-modeling |
| description | This skill should be used when the user asks to "design a demographic model", "model a person/organisation/role", "design party relationships", "plan identity structures", or "work with demographic archetypes". Covers designing openEHR demographic models using the PARTY hierarchy, roles, capabilities, relationships, and identity patterns. For clinical EHR archetypes (OBSERVATION/EVALUATION/etc.) use `archetype-authoring`; this skill owns the demographic PARTY model.
|
| argument-hint | <task: design|review> [entity type or use-case] |
| allowed-tools | ["Read","Glob","Grep","Write","Edit","mcp__openehr-assistant__ckm_archetype_search","mcp__openehr-assistant__ckm_archetype_get","mcp__openehr-assistant__guide_get","mcp__openehr-assistant__type_specification_get","mcp__openehr-assistant__terminology_resolve"] |
Demographic Modeling
The RM detail in the steps below is a working summary. The specs/rm-demographic guide loaded in Step 1 is authoritative — if they disagree, follow the guide (or confirm against type_specification_get).
Conflict Resolution
When guides conflict, apply this priority (highest first):
- Rules and structural constraints
- Privacy and separation principles
- Anti-patterns
- Principles and examples
- Convenience
Step 1: Load Guides (MANDATORY)
Before any demographic modeling work, load the authoritative guides:
guide_get("specs/rm-demographic")
guide_get("archetypes/principles")
Load additional guides as needed:
guide_get("specs/rm-ehr") — for EHR/demographic separation context and cross-referencing patterns
Step 2: Clarify Use Case
Before designing, gather requirements:
- Entity types: Which PARTY subtypes are needed — PERSON, ORGANISATION, GROUP, AGENT?
- Roles: What roles do parties play? What capabilities and time validity apply?
- Relationships: What relationships exist between parties? What is the directionality?
- Deployment context: Is this a standalone demographic service, a PMI wrapper, or embedded within an EHR system?
- Privacy requirements: What level of PARTY_SELF identification is appropriate for the deployment?
Step 3: Research Before Creating
Before designing new demographic archetypes, ALWAYS search CKM first:
ckm_archetype_search("person")
ckm_archetype_search("organisation")
ckm_archetype_search("party identity")
Reuse-first principle: If a suitable demographic archetype exists, use it. Only create new archetypes when no existing archetype covers the concept. If a close match exists, consider specialization instead.
Use ckm_archetype_get to retrieve and review candidate archetypes in full before deciding. For a deeper reuse survey across varied phrasings (demographic concepts are easy to phrase several ways), dispatch the ckm-scout agent — it runs parallel searches and returns a ranked reuse/specialize/new recommendation without filling the main context with raw hits.
Step 4: PARTY Hierarchy Design
ACTOR Subtype Selection
Choose the correct ACTOR subtype for each entity:
| ACTOR Subtype | Purpose | Examples |
|---|
| PERSON | Individual human beings | Patient, clinician, next of kin |
| ORGANISATION | Legal or administrative entities | Hospital, clinic, insurer |
| GROUP | Informal or functional collections | Care team, household |
| AGENT | Non-human actors | Software agent, device |
Use type_specification_get to verify the RM structure of ACTOR and its subtypes when uncertain.
ROLE Modeling
ROLE represents a party acting in a specific capacity:
- Each ROLE references its ACTOR via
performer
- Assign
time_validity to express when the role is active
- Use
capabilities to describe what the role is permitted to do
- A single ACTOR may hold multiple concurrent ROLEs (e.g., a person who is both a patient and a clinician)
GROUP vs ORGANISATION
- Use GROUP for informal or ad-hoc collections without a legal identity (e.g., care team, family unit)
- Use ORGANISATION for entities with a formal legal or administrative standing (e.g., registered company, government body)
Step 5: Identity and Contact Design
PARTY_IDENTITY
PARTY_IDENTITY holds names and designations for a party:
- Each identity has a
purpose (e.g., legal name, alias, trading name, maiden name)
- Apply
time_validity to capture historical names
- A party may hold multiple PARTY_IDENTITY instances simultaneously
Identifiers
State-issued and system-assigned identifiers (e.g., NHS number, passport number, employee ID) belong in PARTY.details, NOT in PARTY_IDENTITY. PARTY_IDENTITY is for names only.
Use type_specification_get("PARTY_IDENTITY") to confirm the structure before authoring.
CONTACT and ADDRESS
- CONTACT groups one or more ADDRESS instances under a shared
purpose (e.g., home, work, billing)
- Each ADDRESS carries its own
time_validity
- Prefer structured ADDRESS types over free-text where the deployment context supports it
Step 6: Relationship Design
PARTY_RELATIONSHIP Modeling
- PARTY_RELATIONSHIP is directional:
source → target
- The source party carries the relationship instance by value in
relationships
- The target party holds a reference back in
reverse_relationships — by reference only, not by value
- Apply
time_validity to express active periods for the relationship
- Assign a
details archetype to carry relationship-specific data (e.g., next-of-kin type, guardian authority)
Serialisation Safety
When producing EHR Extracts, relationships that reference parties outside the extract boundary must be serialised safely. Avoid assumptions that all referenced parties are included in the same extract.
Step 7: Privacy and Separation
Three Levels of PARTY_SELF Identification
openEHR supports three levels of identification in the EHR for privacy:
- Full identification: EHR contains explicit demographic references pointing to a Party in the demographic service
- Coded identification: EHR contains only a coded reference; mapping is held externally
- Anonymous: EHR contains no identifying links; identification is impossible from the EHR alone
Choose the level appropriate for the deployment context and applicable data-protection regulations.
EHR Index Service
Cross-referencing between the EHR and the demographic service is mediated by an EHR Index (or Master Patient Index). The EHR does not directly embed demographic records.
Clinical Demographic Data in the EHR
Certain demographic-adjacent data is legitimately recorded in the EHR as clinical observations:
- Age, date of birth (as OBSERVATION or ADMIN_ENTRY)
- Biological sex, gender identity (as OBSERVATION)
- Occupation, ethnicity (as ADMIN_ENTRY or EVALUATION)
This data lives in the EHR by clinical necessity and is distinct from the authoritative demographic record in the Party service.
Step 8: Versioning
- Demographic records use VERSIONED_PARTY, following the same change-control model as EHR content
- Every update creates a new Version; the version history is immutable
- Lifecycle states (draft, complete, deleted) apply to demographic versions
- All changes are associated with a Contribution carrying audit metadata (committer, timestamp, reason)
Ensure that any demographic archetype design accounts for which fields are expected to change over time and how version history will be navigated.
Step 9: Quality Review
Before finalizing the demographic model, verify:
