Vitals  /  Glossary

Glossary

Every term used across the site, one line each.

Architecture

TermMeaning
MedallionThree quality tiers — bronze (raw), silver (cleaned/conformed), gold (consumption-ready). A lifecycle, not a schema.
BronzeRaw ingested data, as-is; schema drift tolerated; PHI present & access-gated.
SilverDe-identified, type-clean, standardized. The PHI boundary — everything downstream reads only from here.
GoldConsumption-shaped outputs: analytics marts, feature store, vector index.
Delta / IcebergOpen table formats giving object storage ACID transactions, schema evolution, time travel.
Unity CatalogDatabricks governance layer: catalogs/schemas, table/column access, automatic lineage.
LineageThe dependency graph from sources → models → outputs (auto-generated from dbt here).

Healthcare data

TermMeaning
FHIRHL7's standard for clinical data as JSON Resources (Patient, Encounter, Condition, Observation…). Often exported as NDJSON.
OMOP CDMOHDSI's Common Data Model — one standard format + vocabulary so disparate sources analyze the same way.
Concept idOMOP's standard integer code for a clinical concept (e.g. gender 8507 = male); loaded from OHDSI Athena.
ICD-10 / LOINC / SNOMED / RxNormVocabularies for diagnoses / labs & observations / clinical findings / medications.
PHIProtected Health Information — names, SSN, address, full dates, etc.
Safe HarborHIPAA de-identification route: remove 18 specified identifier types.
Date-shiftShift each patient's dates by a fixed per-patient offset — preserves intervals while de-identifying.
patient_keySalted-hash surrogate replacing the real patient id.

Standards, organizations & acronyms

TermMeaning
HL7Health Level Seven International — publishes FHIR (and older HL7 v2 messaging).
HIPAAUS health-privacy law. Defines PHI and the two de-identification routes.
Expert DeterminationHIPAA de-id route #2: a qualified statistician certifies re-identification risk is "very small".
De-identificationRemoving PHI so data can be used for analytics/ML. In Vitals: done at the silver boundary.
OHDSI ("Odyssey")Observational Health Data Sciences and Informatics — the open community maintaining OMOP, its tools, and vocabularies.
AthenaOHDSI's vocabulary repository — where standard OMOP concept_ids are downloaded from.
InteroperabilityDifferent systems exchanging data they can both use — FHIR's purpose.
NDJSONNewline-delimited JSON — one object per line; the FHIR bulk-export format.
EHRElectronic Health Record — the clinical source system.
Claims (837 / 835)Billing data: 837 = claim submitted to the payer; 835 = the payer's remittance/payment.
CPTCurrent Procedural Terminology — procedure codes in claims (MRI, physical therapy, injection…).
PROPatient-Reported Outcome — a survey the patient fills in (e.g. pain, disability).
ODIOswestry Disability Index — the PRO instrument used here (0–100; higher = worse).
SyntheaOpen-source synthetic FHIR patient generator — PHI-free data the project can publish.
Value-based carePaying for outcomes, not volume — the cost mart reflects it.

Transformation & serving

TermMeaning
dbtSQL transformation framework: versioned models, tests, docs, lineage. Builds silver→gold here.
Dimensional modelKimball star schema: dim_ (entities) + fct_ (events/measurements).
Semantic layer / metricGoverned, reusable metric definitions analysts consume (e.g. surgery rate).
Feature storeServes ML features consistently for training (offline) and scoring (online). Here: Feast.
Vector indexEmbeddings of text for similarity search / RAG. Here: pgvector (TF-IDF fallback).
RAGRetrieval-Augmented Generation: fetch relevant text, feed it to an LLM.
MLflowExperiment tracking + model registry.

ML & reliability

TermMeaning
ROC-AUCRanking quality of a classifier (0.5 = random, 1.0 = perfect).
Label leakageA feature that encodes the outcome — inflates offline scores, fails in production. Avoided by using only conservative-care claims.
Feature selectionUsing a curated subset of available features in a model (store stays rich, model stays clean).
PSIPopulation Stability Index — drift metric per feature: <0.1 stable, 0.1–0.2 moderate, >0.2 significant.
Structured StreamingSpark's streaming engine; same API as batch. Uses trigger, checkpoint, watermark.
Window functionPer-partition ordered computation (e.g. 7-row rolling mean per patient).

Tooling

TermMeaning
DuckDBIn-process single-file analytical DB. Runs the MVP with no cloud (Databricks is the deploy target).
mise / uvPin tool versions / manage Python deps fast.