Modelling principles

Priorities, from highest to lowest

1. Clinical safety

2. Clarity of information for data users (for example modellers and clinicians)

   1. Separation of information into appropriate RM classes

3. Ease of governance

4. Ease of templating

5. Ease of querying/implementation

Things to avoid

• Abstract archetypes (problem for clarity and ease of governance)

• Potential for mixing up data that isn’t comparable on retrieval (for example two different scores in one data element, separated only by a flag or by specialisation)

• Potential for mixing up negation with positive presence (for example separated only by a flag)

• Specialisation without a clear use case for governance or retrieval