FHIR SDC form engines, terminology server infrastructure, and EMR development patterns for community healthcare IT.
Picking a FHIR platform without a storage estimate is a way to buy something you cannot afford to run. The purchase decision is usually driven by feature comparisons and vendor demos; the storage bill is what shows up in the second year....
FHIR resources compress well on paper. Field names repeat, canonical URLs repeat, resource structures share vocabulary, and JSON as a format is verbose. Every FHIR server ships with some form of compression enabled and every storage plan...
Retention policies own the long tail of a FHIR storage bill. A deployment that keeps everything forever writes a check every quarter for data nobody will read. A deployment that expires too aggressively loses audit surface when a regulator...
Storage tiering separates the FHIR data that clinicians touch every hour from the data that lives in the archive for compliance. The two workloads have different access patterns, different latency tolerances, and different cost per...
Every FHIR deployment eventually has a first attachment incident. A workflow ships that lets clinicians upload a scanned document as an Observation.valueAttachment, or that stores clinical PDFs inline in DocumentReference. The workflow...
FHIR servers preserve resource version history by default. Every update writes a new row to the history table without touching the current-state row that the read APIs return. The two tables grow independently, and if the plan only tracks...
FHIR resources are not equal on disk. A Patient in JSON is a couple of kilobytes; an Observation with a full CodeableConcept and a few extensions can be five; a Bundle carrying a hundred entries can be a megabyte. Sizing storage without...
FHIR storage budgets almost always underestimate the bill. The number you commit to on a slide deck is a projection of current-state resources at their compressed size, and the number you see on the invoice a year later includes history...