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a3188cd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 | -- FHIR-SQL fine-tuning study: frozen core clinical schema.
--
-- This is the benchmark-facing schema shown to models in every prompt (benchmark
-- authoring, SFT prompt format, RL reward execution). It is a deliberately curated
-- subset of the full flattened data -- see METHODOLOGY_LOG.md for the two-layer
-- rationale (full fidelity in the database, curated scope in what models see) and
-- the token-cost/scope reasoning.
--
-- Generated from the actual column types DuckDB inferred when loading
-- data/train.duckdb, not hand-assumed -- see scripts/flatten_to_duckdb.py for
-- the extraction logic that produces this shape.
--
-- Version stamp:
-- Date frozen: 2026-08-02
-- Synthea build: v3.4.0-18-ga07a65555 (git-describe string embedded in
-- generated Patient resources; downloaded from the
-- GitHub v4.0.0 release page -- see methodology log)
-- Train population: 18,999 patients (target was ~15,000; see log for
-- per-batch seed/state/age-bracket design)
-- Held-out population: 6,383 patients (target was ~5,000)
-- Populations verified disjoint: 0 patient_id overlap between train and held-out
--
-- Every number produced downstream (benchmark accuracy, cost tables, etc.) is
-- relative to this artifact. Do not modify this file without a note on what
-- changed and why.
--
-- Provider attribution: Synthea generates exactly one participant per encounter,
-- typed "primary performer" only -- it does not distinguish admitting/attending/
-- consulting roles, so those remain unanswerable regardless of schema design.
-- Procedure.performer is never populated by this Synthea version (0/29,947 in a
-- full batch) -- procedure-level provider attribution is not available at all.
--
-- Naming convention: columns are named to match FHIR element names directly,
-- so a model's clinical-language understanding maps onto the schema with as
-- little translation as possible:
-- - Primary key: `id` (matches every FHIR resource's own `id` element).
-- - Foreign keys: `patient_id`, `encounter_id` (SQL join-key convention;
-- not itself a literal FHIR field name, since FHIR expresses this via
-- subject/patient/encounter *reference* elements, but resolving those
-- references to a flat join key needs a name, and `<type>_id` is the
-- clearest SQL-side compromise).
-- - Primary coding triple on each table: `code`, `system`, `display`
-- (matches FHIR Coding.code/.system/.display exactly).
-- - Where a resource's own field name differs from the generic "code"
-- (Encounter.type, Encounter.class, Immunization.vaccineCode,
-- CarePlan.category), the coding triple is prefixed with that field name
-- instead: `type_code/type_system/type_display`, `class_code`,
-- `vaccineCode/vaccineCode_system/vaccineCode_display`,
-- `category_code/category_system/category_display`.
-- - Status/descriptive fields: exact camelCase FHIR element names
-- (clinicalStatus, verificationStatus, intent, criticality).
-- - Dates: exact FHIR element names (birthDate, deceasedDateTime,
-- onsetDateTime, abatementDateTime, recordedDate, effectiveDateTime,
-- authoredOn, performedDateTime, occurrenceDateTime); Period-typed
-- start/end kept as `period_start`/`period_end` (Period.start/.end).
-- - value[x]: `valueQuantity`, `unit` (Quantity.unit), `valueCodeableConcept`
-- (+ `valueCodeableConcept_system`), `valueString`.
-- - Provider-reference columns match the FHIR field they were extracted
-- from: `requester_npi`/`requester_name` on medication_request (from
-- MedicationRequest.requester), `participant_npi`/`participant_name` on
-- encounter (from Encounter.participant).
-- - `race`/`ethnicity` on patient (US-Core extensions -- see
-- scripts/flatten_to_duckdb.py's us_core_ext_text macro).
-- - `imaging_study` (ImagingStudy resource) makes radiology-volume questions
-- answerable (department-level radiology questions remain unanswerable --
-- no department/service-line concept exists anywhere in Synthea's FHIR
-- output).
--
-- Indexes: secondary (ART) indexes are added directly to train.duckdb and
-- heldout.duckdb (not a change to this file -- no column/table/logical change,
-- only a physical one) on the coding-triple columns (condition.code,
-- observation.code, medication_request.code, encounter.class_code,
-- encounter.type_code, procedure.code, immunization.vaccineCode, allergy.code,
-- careplan.category_code, diagnostic_report.code, imaging_study.procedureCode,
-- imaging_study.modality), to support the RL execution-efficiency reward term.
-- patient_id/encounter_id deliberately NOT indexed -- DuckDB's ART index isn't
-- used by the optimizer to accelerate joins, only point/highly-selective
-- (<0.1% of rows) filters. See METHODOLOGY_LOG.md for the full verification
-- history of this schema and its indexes.
CREATE TABLE patient (
id VARCHAR PRIMARY KEY,
gender VARCHAR,
birthDate DATE,
deceasedDateTime TIMESTAMP,
maritalStatus VARCHAR,
state VARCHAR, -- address[0].state
city VARCHAR, -- address[0].city
postalCode VARCHAR, -- address[0].postalCode
race VARCHAR, -- US-Core race extension, ombCategory text
ethnicity VARCHAR -- US-Core ethnicity extension, ombCategory text
);
CREATE TABLE condition (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
code VARCHAR,
system VARCHAR, -- kept alongside code deliberately: code-system confusion (SNOMED vs ICD-10 vs LOINC) is a failure mode to observe
display VARCHAR,
clinicalStatus VARCHAR,
verificationStatus VARCHAR,
onsetDateTime TIMESTAMP,
abatementDateTime TIMESTAMP,
recordedDate TIMESTAMP
);
CREATE TABLE observation (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
code VARCHAR,
system VARCHAR,
display VARCHAR,
category VARCHAR,
status VARCHAR,
effectiveDateTime TIMESTAMP,
valueQuantity DOUBLE, -- value[x] flattened per plan design rule
unit VARCHAR,
valueCodeableConcept VARCHAR,
valueCodeableConcept_system VARCHAR, -- code-system pairing for the value itself, when value[x] is coded
valueString VARCHAR
);
CREATE TABLE medication_request (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
code VARCHAR,
system VARCHAR,
display VARCHAR,
status VARCHAR,
intent VARCHAR,
authoredOn TIMESTAMP,
requester_npi VARCHAR, -- prescribing physician's NPI (from MedicationRequest.requester)
requester_name VARCHAR
);
CREATE TABLE encounter (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
class_code VARCHAR, -- Encounter.class.code (AMB/EMER/IMP/HH/VR)
type_code VARCHAR, -- Encounter.type[0].coding[0]
type_system VARCHAR,
type_display VARCHAR,
status VARCHAR,
period_start TIMESTAMP,
period_end TIMESTAMP,
reasonCode VARCHAR,
participant_npi VARCHAR, -- primary-performer physician's NPI (Synthea models only one role per encounter, not admitting/attending/etc separately)
participant_name VARCHAR
);
CREATE TABLE procedure (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
code VARCHAR,
system VARCHAR,
display VARCHAR,
status VARCHAR,
performedDateTime TIMESTAMP
-- Note: Procedure.performer (physician who performed it) is never populated
-- by this Synthea version (confirmed 0/29,947) -- not available at all.
);
CREATE TABLE immunization (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
vaccineCode VARCHAR,
vaccineCode_system VARCHAR,
vaccineCode_display VARCHAR,
status VARCHAR,
occurrenceDateTime TIMESTAMP
);
CREATE TABLE allergy (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
code VARCHAR,
system VARCHAR,
display VARCHAR,
clinicalStatus VARCHAR,
verificationStatus VARCHAR,
category VARCHAR,
criticality VARCHAR,
recordedDate TIMESTAMP
);
CREATE TABLE careplan (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
category_code VARCHAR, -- CarePlan.category[0].coding[0]
category_system VARCHAR,
category_display VARCHAR,
status VARCHAR,
period_start TIMESTAMP,
period_end TIMESTAMP
);
CREATE TABLE diagnostic_report (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
code VARCHAR,
system VARCHAR,
display VARCHAR,
category VARCHAR,
status VARCHAR,
effectiveDateTime TIMESTAMP
);
CREATE TABLE imaging_study (
id VARCHAR PRIMARY KEY,
patient_id VARCHAR, -- join key -> patient.id
encounter_id VARCHAR, -- join key -> encounter.id
status VARCHAR,
started TIMESTAMP,
numberOfSeries INTEGER,
numberOfInstances INTEGER,
procedureCode VARCHAR, -- the imaging procedure performed, e.g. "Plain X-ray of ankle region"
procedureCode_system VARCHAR,
procedureCode_display VARCHAR,
modality VARCHAR, -- DICOM modality code, e.g. "DX" = Digital Radiography (from series[0])
modality_system VARCHAR,
modality_display VARCHAR,
bodySite VARCHAR, -- from series[0]
bodySite_display VARCHAR
);
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