A lab runs its own method on its own device, so the window a physician
evaluates a value against is the one printed next to it on that report,
not a catalog band averaged over every lab. Reading a report pulled the
value and dropped that range: the extraction asked for it, the commit
handed it to the biomarker resolver, and the resolver only uses it when
it mints a NEW marker. For every analyte the user already had — the
normal case after a first panel — the printed range was read and then
thrown away.
Add `sourceReferenceLow` / `sourceReferenceHigh` / `sourceReferenceText`
to `LabResult` and carry the range from the report to the reading. The
text is stored whether or not numbers can be read out of it, because
"bis 5,0" and "negativ" state a window too; a range that could not be
parsed is kept verbatim, never replaced with invented bounds.
`resolveEffectiveReferenceRange` is the one place the precedence lives:
the source window wins for that single reading, and the catalog stays
the net for readings without one. A printed string with no derivable
bound does not displace the catalog. Every surface that judges a
reading routes through it — the API verdict, the doctor report, the
insights blocks and per-marker assessment, the coach snapshot, the MCP
read and the FHIR `referenceRange` — so a value cannot read in range on
one surface and out on another.
The API keeps `referenceLow` / `referenceHigh` as the window in force,
so a client that reads only those two renders the right range and the
right verdict with no change of its own; the catalog band, the source
window, its origin and a divergence flag ride alongside for clients
that want to show both.
Read side: the chart draws the source window as a second, visually
distinct band with the reading it came from named beneath it, the
reading rows name the printed range and the catalog band where the two
disagree, and the doctor-report PDF prints the report's own string with
a footnote naming the saved range. Entry side: one optional field on
the lab form, folded away until asked for, and the printed range is
editable on the scan review screen.
The range parser covers the notations German and English reports
actually print — two-sided, one-sided, comma or dot decimals, thousands
separators, trailing units — reads units without ever converting them,
and refuses to guess on anything ambiguous.
Every staged fact carried a sourceText the model echoed back, stored verbatim
as 'the exact verbatim span of the document the fact came from'. Nothing
checked that the span existed. A paraphrase, a normalised rendering, or an
outright invention was persisted and shown to the reviewer as a transcription
of their own clinical record — an anchor pointing at nothing, or at a span the
document never contained.
Treat the echo as a lookup key instead. anchorSourceText resolves it against
the extracted text (exact, then whitespace-collapsed and case-folded to absorb
OCR reflow) and stores the span the document actually carries, with its offset.
A quote that matches nothing is dropped and the fact is flagged unanchored;
vision mode has no extracted text at all, so its facts are unanchored by
construction. Rows written before this resolve to unanchored on read — their
quote is preserved but never presented as checked.
The Coach SNAPSHOT was spliced into the prompt bare. Its JSON leaves are not
all server-computed: lab analyte, panel and unit names are transcribed by a
model out of an uploaded PDF and stored verbatim as the biomarker name, so a
hostile document chooses those strings. The about-me block has been fenced
since v1.16.1; extend the same pattern rather than adding per-field escapes.
- Move the fence markers and the wrapping primitive into a shared data-fence
module. Content is scrubbed against every known marker, not just its own
pair, so text in one block cannot forge another block's boundary.
- Fence the SNAPSHOT with an explicit data/instruction frame.
- Fence the OCR text handed to the document extractor; the previous
'OCR TEXT:' label was a label, not a boundary.
- Sanitise analyte, panel and unit at the labs source, which feeds both the
snapshot prompt and the labs_read tool result, and the medication label in
the adherence storyline.
- Capture a ---REMEMBER--- sentinel as proposed rather than active. It was
the only model-driven write with no confirm step, and the reminder recall
block fed it back into every later turn. Proposed reminders are already
excluded from that block and already carry a confirm control.
Ingest an uploaded doctor report / discharge letter through the existing
dedicated OCR/vision provider rails (the v1.22 document-scan provider/key,
reused — no new provider) and transcribe structured facts into staging.
The safety line is extract, never interpret: the prompt frames the document
as untrusted data to reproduce verbatim. Diagnoses map to Condition,
measured values to Observation, medications to MedicationStatement — with
STATED status only. A code survives only when the document writes it and its
system matches the resource (SNOMED/ICD-10 for a diagnosis, LOINC for a
value, RxNorm/ATC for a medication); nothing is inferred, no value is
range-flagged, no condition is linked to a medication. Every fact carries
per-field provenance and a confidence score; a fact below the confidence
floor fails closed — it cannot be approved until the user edits it.
Routes (apiHandler + Zod + session-narrowed userId, opt-in module-gated):
- POST/GET /api/documents/inbound — upload+extract (vision or local-OCR
text), and list. The raw document is stored encrypted at rest.
- GET/DELETE /api/documents/inbound/[id] — review detail; soft-delete.
- PATCH .../facts/[factId] — correct a staged fact before approval.
- POST .../confirm — the only write path: approved facts flow into the
labs / conditions / medications stores through their normal create paths;
rejected facts are discarded; low-confidence facts are refused.
Marc-André Bombeck