Mapping Generic extract to FHIR Patient: Field Reference
A simple flat CSV row with familiar column names mapped into a FHIR Patient resource.
Field-by-field mapping
Every rule in the Interoperall template is shown below: the source field, the FHIR target path it populates, and the transform applied. This table is generated from the live template, so it matches exactly what runs when you fork it.
| Source | FHIR path | Transform |
|---|---|---|
| column firstName | Patient.name[0].given[0] | Copied directly |
| column lastName | Patient.name[0].family | Copied directly |
| column dob | Patient.birthDate | Copied directly |
| column gender | Patient.gender | Value-set lookup (M→male, F→female, male→male, female→female; fallback "unknown") |
| column city | Patient.address[0].city | Copied directly |
| column state | Patient.address[0].state | Copied directly |
| column zip | Patient.address[0].postalCode | Copied directly |
| (literal "phone") | Patient.telecom[0].system | Copied directly |
| column phone | Patient.telecom[0].value | Copied directly |
Source extract (CSV row shown as JSON)
The sample input this template is designed to handle:
{
"firstName": "Alex",
"lastName": "Rivera",
"dob": "1990-03-22",
"gender": "M",
"city": "Austin",
"state": "TX",
"zip": "78701",
"phone": "555-555-0300"
}Common gotchas
- Vendor extract column names are not standardized, so verify the exact header in your export (Clarity vs. Caboodle, MAGIC vs. Expanse, CCL report vs. HealtheIntent) before trusting a template.
- This template looks up a numeric-coded column (Epic `_C` category columns, MEDITECH numeric flags). The lookup table is site-configurable, so confirm the codes against your own build.
Frequently asked questions
How do I convert a Generic CSV extract to a FHIR Patient?
Map each CSV column to a FHIR element. Coded columns need a value-set lookup, identifier columns need a real system URI/OID, and date columns must be normalized to ISO-8601. The field table on this page shows the exact column-to-path rules; fork the template to adapt the column names to your own export.
Is this Patient mapping US Core compliant?
It produces a base FHIR R4 Patient. Validate the output to confirm it meets whichever profile your downstream system requires.
Can I customize the Patient mapping?
Yes. Forking gives you an editable copy of all 9 rules, reading the source row columns. From there you can re-target a path, swap the value set behind a coded field, or add rules for anything this template leaves unmapped.