Normalize healthcare data
Normalization gives each fact one consistent home. Patient details belong to the patient; symptoms and treatment belong to an encounter; diagnoses and outcomes can then be connected with clear relationships. This structure makes it easier to follow change over time and reduces conflicting copies.
Check fields before the dashboard
Confirm which fields are required, inspect missingness by source and period, standardize codes against the agreed vocabulary, and identify duplicates with a defined key. Preserve an exception list so a clinical owner can resolve ambiguous records.
Clinical context in the model
A technically valid field can still be clinically misleading if its meaning is unclear. Document what an encounter represents, when a diagnosis is recorded and how follow-up is captured before translating those fields into measures.