my-ehi

Read, load, and make sense of an Epic "EHI Export" — the thousands-of-TSV-tables-plus-schema-HTML dump a patient receives from an Epic-based health system (folders named EHITables, EHITables Schema, Rich Text, Media). Use this whenever you are handed such an export, or any folder of Epic Clarity/ Chronicles-style tables (PAT_ENC, ORDER_MED, HNO_INFO, ZC_/CLARITY_ master files, *_HX history tables, CSN/PAT_ID identifiers), or when a task involves loading one into SQLite, mapping its schema, finding the clinical notes/messages, or interpreting Epic's data-modeling conventions (CSN contacts, *_DATE_REAL dates, _C_NAME categories, base+supplement tables, denormalized _NAME companions). The foundational skill of the tower: ehi-deep-dives builds on it, and import-ehi feeds it a redacted raw/.

Build a deep dive from an Epic EHI export — the whole loop: ideate the view, explore the record for what supports it, abstract the data into a clean view model (structured + narrative, in one JSON), then build a bespoke static bun/React/D3 web app on that view model. Use this whenever making a clinical or financial deep dive / analysis app from such an export (after reading-epic-ehi-export has the data understood and in SQLite). A deep dive is the tool a clinician would want to understand a condition's course, or a billing analyst a claims history — NOT an infographic, dashboard, or slide deck; designed around what that expert needs, narrative-led, with the data interrogable through clean evidence (never raw rows). The "abstraction to power a deep dive" is step 3 here, not a separate skill (see reference/abstracting-to-the-view-model.md). Trigger on "build a deep dive", "make the <condition>/<billing> analysis app", "turn this into a deep dive".

Import an Epic EHI Export (the "Requested Record" zip) into a working tree and produce a REDACTED, same-shape subset that is safe to commit and publish. Goes zip → raw.unredacted/ (full PHI, gitignored) → raw/ (redacted, committable) via: discover identifier values from the structured columns, fuzzy-redact them everywhere (notes included), use agents to catch free-text-only secrets, and PROVE the result clean. Use this whenever you want to publish or share more than a hand-picked artifact — closer to the full record — without leaking PHI.