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Build a Mapping Template

A mapping template translates one file shape into patients, visits and services. Build it once per source and every run from that source reads the same way.

  1. In the sidebar, select Data Mapping. It opens on the Import Mappings tab.
  2. Select Create.
  3. In the dialog, enter a Name and choose the Source Kind.
  4. Select Create. The builder opens.
  5. Attach the example file.
  6. Optional: For a CSV file, in the header, choose the file’s Delimiter.
  7. Select Suggest. Suggest is missing when the client is not licensed for the AI assist; map the fields by hand instead.
  8. Confirm at Suggest a Mapping With AI?. ClaimPod proposes a mapping from the file’s column names, and everything else waits until it finishes. Treat it as a first draft. If it fails, the toast reads “Couldn’t suggest a mapping” and the template is left as it was.
  9. Correct each target field the suggestion got wrong. Gender, marital status and diagnosis type accept only ClaimPod’s own values, such as Male and Female. A file that writes its own codes, such as M and F, needs a crosswalk onto them, or every row stops at import review as Value Not Allowed. An amount written with currency signs or thousands separators needs the Clean amount transform.
  10. Select Preview to see what a run would produce.
  11. Select Save & Activate. It stays greyed until at least one field is mapped. If someone else saved the template first, the toast reads “Couldn’t save template” and offers Reload (A Save Was Refused). On a practice with more than one location, a template with no visit location saves with “Saved, with a warning”; map Assigned Location Code on the Visit tab.

A mapping template with its example file attached: each file column runs to a ClaimPod field showing the example value, with one tab per table and Add table at the end of the rail

Import Mappings explains the builder’s rows, its per-record tabs and what each action needs.

Result: the template is available to connections, schedules and manual uploads.

Preview shows the records a run would create without creating them. This is the cheapest place to catch a wrong column, because after activation the same mistake becomes rows in an import review queue.

Related: Import Mappings · Re-run an Import · An Import or Queue Is Stuck