Look beyond
the number.
A lab result needs context. Bring the measurement, reference range, date, and source into the same view—and see exactly what your record says.
01 / ANATOMY
Every field
has a job.
Explore your results one observation at a time. No invented patient examples. No missing units quietly filled in.
- Measurement
- Read the value with the unit your source supplied.
- Reference range
- See the source’s range and interpretation, when provided.
- Time & origin
- Know when a result was collected and where it came from.
- Underlying record
- Open the normalized JSON when you want a closer look.
02 / PRINCIPLES
Clarity starts with
showing what’s there.
Missing means missing.
Unavailable fields stay clearly labeled.
Context travels with data.
Source information stays beside the result.
Your clinician interprets.
LabPrism organizes results; it does not diagnose.
Inside the observation
A lab result is more than a number
How LabPrism keeps units, dates, reference text and normalized fields beside a result without inventing an interpretation.
How to inspect a lab result’s fields in LabPrism
Find the value, unit, source reference text and status behind a lab entry, and inspect the normalized observation without inventing missing information.
Why LabPrism shows missing lab fields explicitly
How LabPrism handles absent units, reference text and interpretation when displaying normalized lab entries from an authorized record connection.
Why health AI needs lab context, not just result numbers
LabPrism explores why units, reference text, status and missing fields shape the usefulness of patient data for future AI-assisted lab experiences.
How to read your lab results: reference ranges, units and flags
A plain-language guide to lab reports: why reference ranges differ between labs, what H and L flags mean, and what to do when results arrive before your clinician calls.
Live record connections are awaiting activation. You can explore the site and guides now. Current availability.